Che materia stai cercando?

# Human Development Report 2010

Materiale didattico per il corso di Differenziali Economici e Migrazioni della Prof.ssa Paola Giacomello e del Dott. Paolo Sellari. Trattasi del Rapporto sullo sviluppo umano 2010 redatto dall'Onu, all'interno del quale è analizzato il concetto di benessere e di sviluppo attraverso... Vedi di più

Esame di Differenziali Economici e Migrazioni docente Prof. P. Giacomello

Anteprima

### ESTRATTO DOCUMENTO

as the recent National HDRs. Given that the many Regional, National and Local HDRs

measures used are so often contested, we are have investigated inequality in income and

54 Per-

exploring new ways to develop a measure that other human development outcomes.

sistent inequalities, often structural, affect

highlights areas of consensus. For example, the the opportunities available to people. Gender

theory of partial orderings can be used to build inequality, and its impact on human develop-

comparisons across countries that are robust 55

to the weights used for each component­—thus Today, we know a lot more about the mul-

less vulnerable to disagreements on the relative tiple dimensions of inequality, but we still have

relevance of each of them.

Priorities for research only a limited understanding of their evolution

Participation is essential in defining the

include the overlapping 56 We need to know more about

and key drivers.

objectives of development and influencing

inequalities faced by how inequality interacts with structural forces,

decisions through engagement and dialogue. particularly with political economy factors and

But meaningful participatory processes are

specific groups and 57 Various social

inequality in empowerment.

complex. The national dialogue that fed into

how to overcome and economic policies have addressed inequali-

Bolivia’s Poverty Reduction Strategy Paper is

disadvantages ties, while other policies, though not specifi-

widely acknowledged to have tipped the bal-

52 cally aimed at equity effects, have nonetheless

ance of power towards disadvantaged groups.

However, other participation mechanisms, improved equity. We need a better sense of

such as government-led consultations on reli- when and how progressive policies have played

gious arbitration in Canada and on secular- out in practice.

ism in France, have been criticized for allow- Research on inequality could systemati-

53

ing participation only on predefined themes. cally address the multiple manifestations of

Fruitful areas for research include the effects inequality and its underlying drivers. Chap-

of national and local democratic structures on ter 5 gives us a snapshot of these differences

the forms of people’s engagement, national and and provides a fuller characterization of

international policies to protect civil liberties, inequalities than was previously available.

and community initiatives to monitor and hold Priorities for analysis include the overlapping

governments accountable. inequalities faced by specific groups—includ-

To move beyond mere formal consulta- ing women and girls, some ethnic groups and

tion, people need the capabilities, information indigenous peoples—and how disadvantages

and institutional structures to advance claims interact and reinforce each other. Economic

effectively (see chapter 4). Democratic struc- opportunities, legal guarantees, political par-

tures provide the preconditions for human ticipation and spatial inequalities should be

development, but governments need to be fully jointly explored. Innovations in mapping

accountable to their people in promoting the techniques could visually display the distri-

expansion of freedoms. A human development bution of human development nationally and

approach takes these antecedents very seriously regionally. Case studies of successful initia-

while also considering a broader range of soci- tives to address inequalities can suggest pos-

etal structures and institutions that are more sible entry points for change.

(or less) conducive to process freedoms and Policy recommendations to reduce inequal-

mechanisms that support individual and group ity have typically focused on redistributing

less extent, introducing progressive taxation.

## HDR

Inequality The research agenda builds on these

Inequality in a range of dimensions and across efforts to explore reforms aimed at address-

groups—including women and men and poor ing structural inequalities, which may relate

and affluent—is a growing challenge to prog- in turn to political empowerment of disadvan-

ress in human development. This Report has taged groups and institutional change. The role

documented how multidimensional and gen- of the state in eliminating barriers to empower-

der inequality erode human development. And ment and inclusion is a major theme.

116 human development report 2010

Vulnerability and sustainability measuring aggregates—be they health, educa-

tion, income or other quantifiable indictors of

achieving desirable outcomes—it is also about the risk of say, losing one’s job, falling into

securing these achievements against pres-

HDRs, recession or experiencing a natural disaster.

ent or future threats. Previous includ-

HDR This is partly because risk involves uncertainty.

ing the 1994 on human security and

HDR But it is also because we lack good measures of

the 2007/2008 on climate change, have the risks we have faced in the past.

studied vulnerability and security at multiple Risk raises concerns about sustainability.

levels—individual, national and global. This Report has made

Since we are never certain what will happen

The relationships between progress in the case that all good

in the future, all plans involve some degree

human development and risk warrant deeper things do not always

of risk and vulnerability. But the trade-offs

investigation. This Report has made the become different when we compare across

case that all good things do not always come come together

generations and have to evaluate the effect

together. Advances in some aspects of well- of today’s decisions on people who have not

being may be possible only at the cost of higher been born. Neoclassical economists would

individual and collective risk. This is illustrated define a discount rate to trade off well-being

by the former Soviet bloc countries, whose cen- across generations. But assigning weights

trally planned economies generated stable out- to different generations raises serious ethi-

comes for many of their citizens but were not cal dilemmas: discounting the well-being of

able to produce strong, sustained economic

58 Innovation and efficiency require future generations just because they are not

progress.

at least some degree of competition, although yet born seems unjustified, but sustainable

competition can also breed some uncertainty human development cannot be isolated from

59

and risk. concerns about poverty and inequality in

63

How does the human development Deeper conceptual

the current generation.

approach help us think about trade-offs thinking is necessary to work out alternative

between risk and progress? In a general sense principles.

the answer is obvious: we should search for Measuring sustainability also requires

solutions that mitigate risk without sacrificing considerably more work—many current mea-

not always possible, and when it is not, societies and conclusions. A sound measure of sustain-

need to confront hard choices. The pendulum able human development, for example, should

seems to have swung too far in the direction of reflect how societies use various resources over

ignoring insecurity and vulnerability. Perhaps time and judgements about which resources

this is why, despite the advances documented are substitutes or complements. This approach

in chapter 2, opinion surveys consistently show would differ from existing measures in consid-

widespread dissatisfaction with key aspects of ering not only the sustainability of consump-

60 A

life—including those linked with security. tion and production but also that of human

reassessment is in order. development more broadly—including health,

Consider again the dangers of catastrophic education, equity and empowerment.

climate change, the cumulative effect of con- Addressing sustainability increases ten-

centrating exclusively on economic growth and sions between intragenerational and inter-

callously disregarding the warning signs of the generational equity because not every policy

resulting damage to the planet. But there are will benefit poor people today as well as future

numerous other examples, as when liberaliza- generations. Key policy questions relate to

tion leads to both increased income and lower the transition to renewable energy, develop-

job stability or when financial deregulation leads ment links with the green economy and green

61

to higher growth but increased risk of crises. growth, and other market mechanisms, such as

Measuring risk and vulnerability is diffi- green taxes, cap and trade schemes for the envi-

62 Policy-makers have an array of data for

cult. ronment, and regulatory frameworks to prevent 117

chapter 6 The agenda beyond 2010

unsustainable use of resources—including major challenges to progress in human devel-

property rights and financial oversight. opment. The investigation of gender dispari-

The risks inherent in climate change ties revealed that some countries have achieved

demand decisive action. In recognition, the good outcomes in important areas but that

## HDR

2011 will focus on vulnerability and sus- gaps remain unacceptably large. A new measure

## HDR

tainability. A new global on sustainabil- of multidimensional poverty showed the inten-

ity can broaden the debate on what should be sity and reach of serious deprivation for more

sustained and what steps are needed to protect than 100 countries.

the world’s most vulnerable people. Releas- This final chapter proposed an agenda for

Putting people at the HDR

ing the sustainability in advance of the expanding human development. Drawing on

centre of development next Earth Summit in Rio de Janeiro in 2012 the rich legacy of thinking in this and related

means making progress HDR

can influence the debate as the 1992 did traditions, it focused on policies and research.

64 A frank and

before the first Earth Summit. On the policy front we identified the need for

equitable, enabling open discussion of links, conflicts and comple- a principle-based approach to policy guidance;

people to be active mentarities will also help clarify the concept of the importance of local context, particularly

participants in change sustainable human development. state capacity and the social contract within a

and ensuring that country; and the importance of global forces,

current achievements *    *    * notably global governance and aid and partner-

ships. On the research front we highlighted the

are not attained at the This Report has underlined the value and needs for collecting better data on the dimen-

expense of future robustness of the human development sions of human development, rethinking the

generations approach in thinking about and addressing the conceptual basis for the study of development

challenges of the 21st century. and investigating how the human development

The review of experience was broad, high- vision can better inform our understanding of

lighting new findings that deserve further the broader dimensions that are vital to our

attention. People around the world have expe- understanding of human development.

rienced dramatic improvements in some key “Human progress,” wrote Martin Luther

aspects of their lives. They are healthier, more King, Jr., “never rolls in on wheels of inevita-

educated and wealthier and have greater power bility. It comes through tireless efforts and

to select their leaders than at any other time in persistent work. . . . [W]ithout this hard work,

history. As a result, they have expanded their time itself becomes an ally of the forces of

65 The human development

capabilities to lead better lives. social stagnation.”

idea exemplifies these efforts, carried out by a

But we have also seen that the pace of prog- committed group of thinkers and practitio-

ress is highly variable and that people in some ners who wanted to change the way we think

countries and regions have experienced far about the progress of societies. But fully real-

slower improvements. Stark inequalities and izing the human development agenda requires

vulnerabilities remain and are increasing in going much further. Putting people at the cen-

many places, giving rise to—and reflecting— tre of development is more than an intellectual

acute power imbalances. And serious questions exercise—it means making progress equitable

are being raised about the sustainability of cur- and broad-based, enabling people to become

rent patterns of production and consumption. active participants in change and ensuring that

We cast new light on some perennial chal- achievements are not attained at the expense of

lenges, not least the many dimensions of pov- future generations. Meeting these challenges

erty and inequality. We identified persistent— is not only possible but necessary—and more

and in some areas growing—inequalities in a urgent than ever.

range of dimensions across various groups as

118 human development report 2010

Notes

Chapter 1 25 56

International Commission on Intervention and State Sovereignty, the Kahneman 1999. See also Diener and others (2009).

57

2003 Commission of Human Security, the 2004 High-Level Panel Sen (1985b) provides a thorough analysis of agency and its

1 Among recent efforts are the Stiglitz-­Sen-­Fitoussi Commis- on Threats, Challenges and Change. See Jolly, Emmerij, and Weiss importance.

sion (www.stiglitz-sen-fitoussi.fr), the Organisation for Eco- 58

(2009). Sen (1999: 157) argues that the significance of democracy lies

nomic Co-operation and Development project on measuring 26 Including Canada, Japan, Norway and Switzerland. “in three distinct virtues: (i) its intrinsic importance, (ii) its instru-

well-being (www.oecd.org/progress) and the European Union 27 African Union, European Union, Association of Southeast Asian mental contributions and (iii) its constructive role in the creation

framework for multi­dimensional indicators (www.ec.europa. Nations, Organization of American States and League of Arab of values and norms [emphasis in original].”

eu/social/). 59

States. See UN (2010a). Harding and Wantchekon 2010. See also Barbone and others

2 UNDP–HDRO 1990–2009; see inside back cover for a list of 28 UN 2010a. (2007).

HDRs. 29 Anand and Sen 2000b; Osmani 2005; Sen 2004, 2005.

3 The literature and experience are vast; see Alkire (2010) for a Chapter 2

30 Vizard 2006.

review. 31 Edwards and Gaventa 2001: 277.

4 Sen 2002: 585. 1 Gertner 2010.

5 Sen 2009a. 2 See Raworth and Stewart (2002) for a survey.

global warming whether they perceived it to be a serious threat.

6 Crocker 2007; Narayan and Petesch 2007; Richardson 2006. 3 For country-level values of the HDI and its components, see sta-

On average, more than three-quarters of respondents in 126

7 The Economist 1990. tistical table 1.

countries described it as serious.

8 The Economist 1991. The World Bank subsequently dropped 4 There are no major differences in the results when the new HDI

33 Neumayer 2010a.

the income-based ranking in 1998 and now presents countries indicators are used; see Gidwitz and others (2010).

34 Kant 1785; HDR 1994 (UNDP–HDRO 1994: 13; see inside back

alphabetically. 5 The analysis in this chapter and chapter 3 covers the 40-year

cover for a list of HDRs); Anand and Sen 2000a: 2030.

9 Anand and Sen 2000c. period since 1970. In many cases comparisons over such a long

35 WCED 1987: 43.

10 Gertner 2010. period require restricting the sample to countries for which data

36 HDR 1994 (UNDP–HDRO 1994; see inside back cover for a list of

11 Kaletsky 1990. are available. For this reason, some of the aggregates presented

HDRs); Anand and Sen 2000a.

12 Gittings 1990. in these chapters differ from those presented in the statistical

37 Jolly, Emmerij, and Weiss 2009.

13 Seneviratne 1999. tables.

38 World Bank 2000; Fukuda-Parr 2007.

14 Chahine 2005. 6 Sixty countries are not covered by our sample. On aver-

39 F. Stewart 2010.

15 The Straits Times 1990. age, they are somewhat less developed than countries in

40 For a useful review see Nayyar (2008).

16 John Williamson (1989) coined the term “Washington Consen- the sample: life expectancy is three years shorter, literacy

41 Lindauer and Pritchett 2002.

sus” to describe the policy prescriptions that the International is similar but gross enrolment is 6 percentage points lower,

42 Alkire 2007; OECD 2008b.

Monetary Fund, World Bank and US Department of the Treasury and per capita income is $2,785 lower. This does not mean 43 Bourguignon 2004. promoted for developing countries hit by the economic crises of that all countries excluded from the hybrid HDI sample are 44 Stern 2006. the 1980s. Key prescriptions were cutting government spend- poor: eight (including Germany and Singapore) are classified 45 Rodrik 2006. ing, reducing inflation, selling state enterprises, opening to today as developed according to the new HDI reported in sta- 46 Narayan and others 1999. trade and liberalizing exchange and interest rates. tistical table 1. Their annual economic growth and changes 47 Acemoglu, Johnson, and Robinson 2001; Bardhan 2006; Pritch- 17 See Nayyar (2008) for a review of the evolution of development in health were slightly higher than in the rest of the sample, ett, Woolcock, and Andrews 2010. thinking. On basic needs, see Ghai and others (1980). while changes in gross enrolment and literacy were similar. 48 Polanyi 2002. See also Veblen (2007) and Myrdal (1957). Dis- 18 The 1990 HDR (UNDP–HDRO 1990: 67; see inside back cover for Obviously, this evidence is only partial because the data are cussions about participatory development and management of a list of HDRs) included a chapter on development strategies that incomplete, but it suggests that the omission of these coun- common resources also go back several decades; see Agarwal argued for “more realistic and operational” targets. The 1991 tries does not systematically bias the picture of progress that (2001) for a useful review of participation, and Baland and Plat- HDR developed these points, as did the 1994 HDR, which carried emerges from our analysis. teau (1996) on property rights. the global compact idea forward. Key conferences and summits 7 We start with 1970 because that is the first year for which we 49 Rodrik (2006) provides an excellent review of the report. over the period related to education (Jomtien 1990), children can calculate the HDI for a sufficiently large number of countries. 50 Commission on Growth and Development 2008: 2. (New York 1990), environment (Rio de Janeiro 1992), popula- 8 Unless otherwise noted, all dollar figures in this Report refer to 51 The indicator set is updated over time, most recently in 2009, tion (Cairo 1994), social development (Copenhagen 1995) and purchasing power parity–adjusted 2008 dollars. when material deprivation and housing were added; see www. women (Beijing 1995). 9 Since the HDI is about people, we use averages weighted by peer-review-social-inclusion.eu/. 19 UN 2000. population, unless otherwise noted. The main exception relates 52 Duflo, Hanna, and Ryan 2009. 20 Hulme and Fukuda-Parr 2009: 4. to policy indicators such as those discussed in chapter 3, where 53 Mookherjee 2005; see also Deaton (2009) and Cartwright 21 UNDP 2010. the country is the relevant unit of observation. Unweighted (2009). 22 New indicators have been added over time to address some of averages give a better sense of average country performance 54 Seminal work is associated with Kahneman, Diener, and these dimensions, as in 2005 when a target on access to repro- and show an increase in the HDI from 0.53 in 1970, to 0.62 in Schwarz (1999) and Kahneman and Krueger (2006). ductive health was added. 1990 and to 0.69 in 2010. 55 The well known paradox noted by Easterlin (1995) points out 23 This is clearly indicated in a box authored by Sen as co-chair 10 Similarly, Easterly (2009) shows that choices about how to mea- that while richer people are happier than poorer people within of the Commission on Human Security (2003). See also Alkire sure and set Millennium Development Goal targets significantly countries, there is no systemic relationship between income and (2003), Gasper (2005), ul Haq (1995) and Tajbakhsh and Che- affect which countries and regions are progressing most and happiness above a certain income threshold either between noy (2007). which are failing. countries or over time (see Graham 2010). This paradox has been 24 Journal of Human Development and Capabilities 2003; Gasper 11 Specifically, the deviation from fit is the residual from a regres- challenged of late (see Stevenson and Wolfers 2008 and Deaton 2005. sion of changes in the HDI on the initial HDI level. 2008) but not yet fully repudiated (see Krueger 2008). 119 Notes 12 59 Common alternatives to the deviation from fit are the absolute these values differ from those presented in figure 2.5, as the See Tanzi and Schuknecht (2000), which covers a sample of change in the HDI, the HDI growth rate and the percentage figure uses decade averages from 1970s and 2000s. now-developed countries. There are no systematic data on 26 reduction of the shortfall from the maximum level. The four Rajaratnam and others 2010. spending on schooling in developing countries at the turn of 27 methods applied coincide broadly in identifying the bottom UNICEF 2008. the 19th century, but the existing evidence indicates that it was 28 movers, which include such countries as the Democratic Republic Hogan and others 2010. These results have already sparked likely even less (Gargarella 2002). 60 of the Congo, Moldova, Zambia and Zimbabwe. But the shortfall some controversy, however; see Graham, Braunholtz, and The pupil–teacher ratio fell from 37 in 1990 to 35 in 2007 (in reduction method comes out with different top performers: 9 of Campbell (2010). 1970, it stood at 36) in all regions except Sub-Saharan Africa. 29 the top 10 are developed countries, in contrast to at most 1 in the UNICEF 2008. Teachers are also typically better educated now than they were 30 other three methods. China, Lao PDR, Nepal, Oman, Saudi Ara- For this as well as several other comparisons presented below, in the past—the ratio of teachers with training now stands at bia and South Korea are consistently among the top performers we use decadal averages rather than specific years in order to 80 percent for developing countries. 61 regardless of method. See also Gray and Purser (2010) and Ranis increase the size of the sample over which the comparison is The average for 2005–2009 for countries with available data. 62 and Stewart (2010) for a comparison of alternative methods. carried out. Nielson 2009. 13 31 63 The Spence Commission on Growth and Development examined Background research prepared for this Report suggests that Hanlon, Barrientos, and Hulme 2010. 64 13 success stories of countries that experienced high growth these phenomena may have contributed to a dual convergence, Hanushek 1995; Glewwe 1999. 65 over sustained periods since 1950. Of these, only four (China, with different sets of countries converging to different levels of The test is the Trends in International Mathematics and Science Indonesia, Oman and South Korea) coincide with our group of life expectancy. Countries whose life expectancy exceeded 55 Study—see Glewwe and Kremer (2006). 66 top movers. years in 1965 continued converging to low mortality. However, Comparison based on the latest available year of data from 14 Pritchett 1997; UNDESA 2006; Ocampo, Vos, and Sundaram only a few countries with initial life expectancy below 55 years Trends in International Mathematics and Science Study for the 2007. made the transition. See Canning (2010). test scores and World Bank (2010g) for spending. 15 32 67 Pritchett 1997. UNAIDS 2008: 39. Bessell 2009a, b. 16 33 68 The HDI upper bound is the result of a normalization that has For alternative views see Treisman (2010); Brainerd and Cutler Greaney, Khandker, and Alam 1999. 69 no effect on rates of change (see Technical note 1); thus, it is not (2005); and World Bank (2010g). World Bank 2009d. 34 70 true in general that the functional form imposes a constraint on Brainerd 2010. Pritchett and Murgai 2007; Walton 2010. 35 71 progress at the top. On convergence caused by natural upper Zaridze and others 2009. Pritchett, Woolcock, and Andrews 2010; De and Drèze 1999. 36 72 bounds, see endnote 18. Watson 1995. The most recent Trends in International Mathematics and Sci- 17 37 Take, for example, the case of life expectancy. Although one Yates 2006. ence Study found that higher levels of parents’ education (and 38 might expect that there is an upper limit, this is not generally Ridde and Diarra 2009; Yates 2006. assets and services at home, such as computers and access 39 accepted by longevity researchers. Oeppen and Vaupel (2002) Daponte and Garfield 2000. to the Internet) were associated with higher average math 40 show that female life expectancy in the top-ranked country has Brown, Langer, and Stewart 2008. achievement in almost all countries. Similar patterns exist 41 advanced at a steady annual pace of three more months a year UNDP 2010. in developing countries (see Ishida, Muller, and Ridge 1995; 42 over the past 160 years, with no deceleration over time. Sen 1983. Maundu 1988). This gap often remains large even after adjust- 18 43 To evaluate whether this generates the convergence, we An interesting potential research question, which could be ing for student and family characteristics such as gender, age, unbounded the variables through a logit transformation explored in future reports, is whether the correlation of hun- number of parents and siblings (see Ma 2001; Caldas 1993; ger is greater with multidimensional poverty than with income Schultz 1993). x lx = ln( ), x–x 73 poverty. Time series data for four developing countries show a decline of 44 where x is the variable in question and x denotes its upper Shiva Kumar 2007. 9 percent in test scores from 1995 to 2007, even though these 45 bound and confirmed the convergence results. Beta conver- Kasirye 2010. countries also greatly increased gross enrolment (by an average of 46 gence tests (see Barro and Sala-i-Martin 2003) associated with Barrett and Maxwell 2005. 14 percent) over the same period. See also UNESCO (2004). 47 74 the logit transform of literacy, gross enrolment and mean years Drèze and Sen 1989. The assessment depends on whether the income figures are 48 of schooling reject the hypothesis of no convergence with p-val- FAO 2010b. Data on undernourishment and food deprivation are weighted by population or unweighted—that is, whether ues of less than 1 percent for all three variables. A statistically also in statistical table 8. one thinks of the income of the average person or the average 49 significant decline in the relationship between initial levels and Olshansky and others 2005. country. Because of China’s size and rapid growth, the income 50 log changes was found for all variables except income, both in Strauss and Thomas 1998. of the average person in East Asia and the Pacific has grown 51 levels and in the logit transform. Alternative indicators (among Nussbaum 2000. 1,000 percent since 1970—but that of the average country in 52 them years of tertiary schooling and undernourishment) con- Education is a consistent correlate of empowerment: in Bangla- the region rose 344 percent. Likewise, the income of the average firm the convergence—albeit for shorter time spans and fewer desh, see Kamal and Zunaid (2006); in Ethiopia, Legovini (2006); person in Sub-Saharan Africa increased only 17 percent, but that countries. For all nonincome variables except life expectancy, in India, Gupta and Yesudian (2006); in Nepal, Allendorf (2007); of the average African country, 93 percent. This reflects the weak the beta convergence effect weakens after 1990. and in the Russian Federation, Lokshin and Ravallion (2005). overall growth records of the Democratic Republic of the Congo, 19 53 Proposals have been put forward to create a separate index for The positive effect of education on longevity has been found for Ethiopia and Nigeria, where 311 million people live. 75 developed countries to better distinguish among them; see Her- many countries, including Bangladesh (see Hurt, Ronsmans, and This comparison refers to unweighted averages, which are typi- rero, Martínez, and Villar (2010). Saha 2004), South Korea (see Khang, Lynch, and Kaplan 2004) cally used to evaluate convergence across countries. As shown in 20 China’s gross enrolment ratio fell from 69 percent in 1976 to 50 and the United States (see Cutler and Lleras-Muney 2006). table 2.1, the conclusion is reversed if we use weighted averages 54 percent in 1990 and has recovered to 68 percent today. The gross enrolment ratio captures a country’s enrolment as a because of the influence of China and India on the weighted fig- 21 We created an indicator of quality-adjusted years of schooling share of the corresponding school-age population. Gross enrol- ures. We return to this issue in our discussion of global inequal- for 13 countries for which the dispersion fell from 1995 to 2007, ment ratios can exceed 100 percent when students are enrolled ity in chapter 4. 76 a suggestive but not conclusive result given the small sample who are not in the school-age population—due to grade rep- That is, than of any country in the top quarter of the world size. etition or late school entry. The net enrolment ratio covers only income distribution in 1970. 22 77 Namely, the Congo, the Democratic Republic of the Congo, children who are in the age subgroup corresponding to a par- While from 1990 to 2010 differences in per capita income growth Georgia, Kyrgyzstan, Moldova, Swaziland, Tajikistan, Ukraine, ticular level of education—but such data are more limited and rates narrowed—­developed countries grew 1.9 percent a year on Zambia and Zimbabwe. ignore the benefits of education for those outside the “appropri- average, compared with 1.8 percent in developing countries­— 23 Note, however, that the clustering does not occur at the top of ate” age group. the gap between the two continued to grow, although much 55 the scale in either figure 2.4 or figure 2.7, suggesting that it is not World Bank 2010g. more slowly than in the previous two decades. During 2005–2010 56 due to countries hitting an upper bound. We say that the female gross enrolment ratio is close to or developing countries grew much faster than developed countries 24 WHO 2008: 2. greater than the male ratio when it exceeds 98 percent; see UN (an average of 3 percent a year, compared with 1.2 percent). 25 78 This is consistent with a faster increase in longevity in develop- (2009). This comparison excludes oil-producing countries. For countries 57 ing countries as the higher absolute reductions in infant mortal- UNESCO 2010, tables 5 and 8. that are monoexporters and subject to high price fluctuations, 58 ity have a significant effect on life expectancy. Also note that World Bank 2010g. per capita GDP at constant prices may not be the best indicator 120 human development report 2010 23 48 See Kenny (forthcoming) and Boone and Zhan (2006). Causality in the relation between aid and development has been for assessing long-run performance; see Rodríguez (2006) for 24 Bryce and others 2003; Gauri 2002; Jones and others 2003. explored by, among others, Rajan and Subramanian (2008) and a discussion. 25 79 Drèze and Sen 1989; McGuire 2010. Minoiu and Reddy (2007). Namely Burundi, Central African Republic, the Democratic 26 49 Miguel and Kremer 2004. Ranis and Stewart 2010. Republic of the Congo, Côte d’Ivoire, Djibouti, Haiti, Liberia, 27 50 Cross-country studies examining aggregate measures of expen- Olavarria-Gambi 2003. Madagascar, Niger, Somalia, Togo, Zambia and Zimbabwe. 51 80 ditures (such as public health spending as a share of GDP) or Durlauf, Johnson, and Temple 2005. See also Barro and Sala-i- Equatorial Guinea’s growth was similar to that of China, fuelled inputs (hospital beds or nurses per capita) tend to blur the Martin (2003) and Rodríguez (2007). by oil. However, the use of base year prices to value growth in 52 distinctions between diverse programmes and inputs of vary- Rodrik 2007; Hausmann, Rodrik, and Velasco 2008. oil-abundant economies tends to distort the results from pur- 53 ing quality and effectiveness and reach mixed conclusions: see Rodrik 2007; Hausmann and Rodríguez forthcoming; Denison chasing power parity–adjusted GDP series over long periods; Filmer and Prichett (1999); McGuire (2010); Gupta, Verhoeven, 1967; Bhagwati and Desai 1970; Little, Scitovsky, and Scott 1970. see endnote 78. 54 81 and Tiongson (2003); Kruk and others (2007); and Gauri and Binder and Georgiadis 2010; Gray and Purser 2010; Mayer- della Paolera and Taylor 2003: 5. Khaleghian (2002). Foulkes 2010. Chapter 3 28 55 For more statistics on health, see statistical table 14. Mayer-Foulkes 2010. 29 56 Deaton 2002. McGuire 2010. 1 Improvements in human development are measured using the 30 57 Kenny forthcoming: chapters 6 and 7. Klasen 2000. deviation from fit criterion presented in chapter 2. 31 58 Lake and Baum 2001. Kudamatsu (2007) used individual-level Behrman and others 2009. 2 The nonincome HDI comprises the health and education indices, 59 data from 28 African countries and found that children were Duflo 2003. equally weighted. The correlation between changes in the non- 60 more likely to survive after democratization. This analysis exam- Chen and Li 2009. income HDI and economic growth is negative (–0.30) and sta- 61 ined children born to the same mother before and after democ- Binder and Georgiadis 2010. tistically significant at the 1 percent level. However, this measure 62 ratization to control for familial differences. Mayer-Foulkes 2010. may be biased by the fact that less developed countries tend to 32 63 On mortality and risk of dying in childbirth, see Przeworski Moreno-Lopez and others 2009. have faster rates of improvement in the HDI. Thus in figure 3.1 64 (2004); on life expectancy, see Lake and Baum (2001); Franco, Brun, Chambas, and Mourji 2009; Diaw, Guérineau, and Jean- we use the deviation from fit measure to account for different Alvarez-Dardet, and Ruiz (2004); and Vollmer and Ziegler (2009). neney 2009. HDI starting points (see box 2.1 in chapter 2). The corresponding 33 65 Harding and Wantchekon 2010. Moreno and Rodríguez 2009. correlation is 0.13 and is not statistically significant. This robust 34 66 This expansion involved an increase in the public provision of OECD 2008b. finding does not depend on the specific indicators used to calcu- 67 education, often while private education was marginalized; Cubero and Hollar 2010. late nonincome human development. 68 UNESCO (2006). See Pritchett (2002). Nattrass and Seekings 2001. 3 Preston (1975), however, also showed that a snapshot relation- 35 69 Tansel 2002; Edmonds 2005; Clemens 2004. OECD 2008b. ship between levels of income and life expectancy did yield a 36 70 The increase over 1970–2007 was 22 and 23 percentage points, Fiszbein and others 2009. significant relationship, a fact to which we return. 71 and the difference was not statistically significant. For more Prasad 2008; HDR 1990 (UNDP–HDRO 1990; see inside back 4 Easterly 1999. See also Cutler, Deaton, and Lleras-Muney (2006) information about levels and trends in education enrolment, see cover for a list of HDRs); OECD 2008b; Nattrass and Seekings and Kenny (2009). statistical table 13. 2001; Johannes, Akwi, and Anzah 2006; Cubero and Hollar 2010. 5 Bourguignon and others 2008. 37 72 For a sample of 48 countries the correlation between skill premi- World Bank 2005b. 6 Kenny 2009. 73 ums and rate of growth of schooling over 1970–2010 is 0.14 and This section draws heavily on Walton (2010). 7 On average, countries with negative economic growth over 74 is not statistically significant. The Glass-Steagall Act was repealed in 1999. On the compara- 1970–2010 experienced an increase of 11 years in life expec- 38 Pritchett 2002. tive evolution of financial systems regulation in Japan and Ger- tancy, 22 percentage points in gross enrolment and 40 percent- 39 Many governments came under intense international pressure many, see Vitols (2003) and Bebenroth, Dietrich, and Vollmer age points in literacy. to require universal primary education. The United Nations Edu- (2009). 8 See, for example, the discussion in Wooldridge (2002). 75 cational, Scientific and Cultural Organization convened regional Charumilind, Kali, and Wiwattanakantang 2006. 9 Easterly 1999. 76 conferences on free and compulsory education (Bombay 1952; Hulme and Moore 2008; Nath, Sylva, and Grimes 1997; Born- 10 Anand and Sen 2000c. People in high-income economies, how- Cairo 1955; Lima 1956). stein 2005. ever, may not use higher incomes to attain higher functioning. 40 77 Elson 2001. Studies of the programme have shown significant Marglin 2008. Examples are the high rates of obesity and the decline of leisure 78 effects on schooling and later on wages compared with people ITOPF 2010. time in the United States (see Schor 1992; Cook and Daponte 79 who did not participate; see Duflo (2001). NOIA 2006; EEA 2008. 2008) and more recently in Qatar. Within five years, Qatar’s obe- 41 80 On years of education, see Tavares and Wacziarg (2001); on Amnesty International 2009a. sity rate is projected to be 70 percent (see WHO 2010). 81 enrolment and literacy, see Lake and Baum (2001); Tsai (2006); The Economist 2007; Davies and others 2008. 11 Srinivasan 1994; Wolfers 2009. 82 and Vollmer and Ziegler (2009). However, in recent years, China has erected more barriers to 12 HDR 1997 and HDR 2003 (UNDP–HDRO 1997, 2003; see inside 42 Expanding enrolment at higher levels requires meeting at least entry and competition; see Bradsher (2010). back cover for a list of HDRs); Casabonne and Kenny 2009; Kenny 83 some basic efficiency and quality thresholds. Decentralization of Li and Meng 2005. 2008; Pritchett 2006; Glewwe and Kremer 2006; Strauss and 84 school management at the local level has been found to be posi- Di John 2009. Thomas 2008; Riley 2001; Benavot and Resnik 2006. 85 tively and significantly associated with efficiency and educa- For South Korea and Taiwan Province of China, Wade (1992: 314) 13 Hobbes 1651. tion quality; see Gallego (2010); Fuchs and Woessmann (2007); noted that “whereas the governments of most other developing 14 Wrigley and Schofield 1989: 230; Riley 2001: 33. Stasavage (2005); and Tsai (2006). countries know that they can fail economically and not risk inva- 15 Some countries in northwestern Europe passed through an 43 See Walton (2010). sion, the governments and elites of these countries knew that earlier health transition by reducing health crises caused by epi- 44 Drèze and Sen 1989. On typologies of human development, see without fast economic growth and social stability this could well demics, wars and harvest failures. See Riley (2001): 20. Ranis and Stewart (2000, 2010). happen. This led them to make an unusually close coupling of 16 Soares 2007; Cutler and Miller 2005; Fogel 2004; Cutler, Deaton, 45 Walton 2010. national security and economic strength.” and Lleras-Muney 2006. 46 86 Pineda and Rodríguez 2010. Walton 2010. 17 Latin America and the Caribbean and Europe and Central Asia 47 87 Data on conflict from UCDP and PRIO (2009). We define as Friedman 2006. had life expectancies of 51 years and 60 years, still lower than conflicts those that involve two parties, of which one is the the 65 years in developed countries. Chapter 4 government of a state, and that result in at least 1,000 battle- 18 Cutler, Deaton, and Lleras-Muney 2006; Cutler and Miller 2005. related deaths in one year, and exclude interstate armed con- 19 1 Kenny forthcoming; Cutler, Deaton, and Lleras-Muney 2006: Fuentes-Nieva and Pereira 2010. flicts between two or more states, so that our variable covers 2 108. In figure 4.1 the measure of political freedom we use is Polity IV only “civil” conflicts. Some countries experiencing conflict in 20 de Quadros and others 1998. because it varies across a greater range and thus can be more this database are Afghanistan (1990–2001, 2003–2008), India 21 Soares 2007. easily graphed; the results are similar if we use the democracy (1990–2006), Rwanda (1990–1993, 1997–1998, 2001–2002) 22 Jolly 2010. measure described later in this chapter; see also statistical and Turkey (1992–1998). 121 Notes 33 65 table 6. For the measure of inequality loss in HDI, see chapter 5. Trends are assessed using an annual measure (created by Gib- Considering the 2003 HDI ranking as presented in the 2005 HDR The measure of sustainability is adjusted net savings from the ney, Cornett, and Wood 2010) based on human rights viola- (UNDP–HDRO 2005; see inside back cover for a list of HDRs) World Bank. tions, as reported by Amnesty International. The measure uses since the Demographic and Health Survey for Burkina Faso used 3 Harding and Wantchekon 2010; World Bank 2005b; Przeworski a broad notion of the state, including agents that are not offi- in the example is for 2003. 66 and others 2000; Cornia and Court 2001; Eicher and Turnovsky cially recognized as agents of the government and areas where See Stewart, Brown, and Mancini (2005), Roemer (1998), and 2003. quasi-state or extra-state entities are acting in place of a weak Barros and others (2008). 4 67 Kabeer 1999: 447. or fragmented central government. Countries are coded from Stewart 2009. 5 68 HDR 1990 (UNDP–HDRO 1990; see inside back cover for a list 1 (secure rule of law prevails) to 5 (widespread political fear) UNDP 2003. 69 of HDRs). based on expert assessment of the scope (type of violence), UNESCO 2009: 64, 65. 6 70 HDR 1993, 2000, 2002 and 2004 (UNDP–HDRO 1993, 2000, intensity (frequency) and range (share of the population tar- See the 2009 HDR (UNDP–HDRO 2009; see inside back cover for 2002, 2004; see inside back cover for a list of HDRs). geted or selectivity) of violations. For 101 countries the median a list of HDRs). 7 71 Gaye and Jha 2010. level of abuses was 3. K. Stewart 2010; Wood and others 2009. 8 34 72 Hamel 2010. Harding and Wantchekon 2010. Burd-Sharps and others 2010. 9 35 73 See discussion in Donner (2008). See the 2000 HDR on human rights (UNDP–HDRO 2000; see Sen 2003; The Economist 2010. 10 74 IEA 2009. inside back cover for a list of HDRs). We follow the more recent practice in these estimates of treat- 11 36 UIA 2010. Data from Amnesty International (2009b). ing sex-selective abortions as female deaths. This differs from 12 37 Walton 2010: 22. Data from Gallup World Poll (2010). the practice of demographers who distinguish foetal deaths 13 38 The World Values Survey asks respondents how much freedom Ottoson 2009: 5. from mortality (for example, Shryock and Siegel 1980). An 39 they have over their lives. For 87 countries the average was 7 Amnesty International 2010. alternative approach would consider the ramifications of gender 40 on a 10-point scale, with a range of 5−8. The Gallup World Poll HDR 1997, 1998 and 2005 (UNDP–HDRO 1997, 1998, 2005; see discrimination for mortality across genders and age groups. To asks respondents whether they are satisfied with their freedom inside back cover for a list of HDRs). the best of our knowledge the implications of such an approach 41 to choose. This freedom at the individual level does not appear World Bank 2005b. have yet to be worked out. See also Coale (1991). 42 75 to be connected with democracy at the national level. This calculation uses the loss from the Inequality-adjusted HDI This calculation assumes that in the absence of sex-selective 14 Since 1990 Kuwait and Samoa have extended the right to vote to presented in chapter 5. abortions a woman would have an equal probability of giving 43 women, and South Africa to Blacks. Paul Krugman has often referred to this fact as evidence of birth to a girl or a boy. See also Klasen and Wink (2009). 15 76 We present a measure that defines democracy on a minimalist increasing inequality in the United States (see, for example, Nussbaum 2005. . 77 basis (see Cheibub 2010, building on Alvarez and others 1996). Krugman 2007); United States Census Bureau 2008. WHO 2005 78 44 Desai 2010. Countries are classified as democratic if the chief executive and World Bank 2005b. 79 45 Agarwal and Panda 2007. legislature are elected, more than one political party competes Results using data from World Bank (2010g) showed a similar 80 UNIFEM 2010. in elections and a party has transferred power in the event of pattern with a smaller sample. 81 46 UNIFEM 2010. a loss; otherwise, countries are identified as dictatorships. Milanovic 1998. 82 47 UNDESA-DAW-CSW 2010. Democracies with no alternation of parties are countries that Atkinson and Micklewright 1992. 83 48 Cuno and Desai 2009. formally meet the conditions for democracy but where the rul- ADB 2007; Liu 2010; The broad picture is consistent with the 84 UN 2009. ing party has yet to lose an election and thus relinquish power. Kuznets (1955) hypothesis that inequality would increase at the 85 World Bank 2010f. This simple measure has gained broad endorsement in the com- initial stages of economic development and then decline, but 86 LIS 2009. parative political literature (see Munck and Verkuilen 2002). the empirical evidence is mixed. 87 16 49 OECD 2009. This category consists of countries that have not met the alter- Pinkovskiy and Sala-i-Martin 2010. 88 50 UNDESA 2009a. nation rule; see the previous endnote. López-Calva and Lustig 2010; Cornia 2010. 89 17 51 Fuentes-Nieva and Seck 2010. Coups took place in Honduras (1972), Chile and Uruguay (1973), Jayadev and Rodríguez 2010. These results are robust to adjust- 90 Skoufias 2003. Argentina (1976), Bolivia (1980) and Guatemala (1982). ing for the contribution of self-employment to capital income. 91 18 52 WCED 1987. See UNDP (2009: 71), which describes political movements Commander 2010. The exceptions are the Scandinavian coun- 92 Information about global employment trends is weak outside using this tactic. tries and Belgium. 19 53 developed countries because of differences in definition and The Mutahidda Majlis-i-Amal (United Action Council), a coali- There is considerable debate in the literature on ethics and jus- data collection methods and lags. Official estimates of unem- tion of religious parties, won 19 percent of national assembly tice on whether the fairness of distributive arrangements should ployment are especially problematic in countries with extensive seats and made greater inroads in Khyber Pakhutunkhwa and be evaluated at the global or national level. If the justice of insti- informal sectors and no formal safety nets. See ILO (2009b). Balochistan. tutions is to be judged at the level at which the social contract 93 20 See IMF (2009) for a comparison between the crises. Whitehead 2002. is conceptualized, the national level is appropriate, while a cos- 94 21 Reinhart and Rogoff 2009. Calculated from Database of Political Institutions (updated mopolitan position would suggest that the global level is the 95 ILO 2010b; World Bank 2010b. 2010) as described in Beck and others (2001). relevant one for assessment. See Risse (2009) for a discussion 96 22 World Bank 2009c. Bardhan and Mookherjee 2000; Abraham and Platteau 2004. of these issues for international migration. 97 23 54 One example of how policy intervention and good initial condi- See, for example, Besley, Pande, and Rao (2005) and Dasgupta Pinkovskiy and Sala-i-Martin 2009; Milanovic 2009; Anand and tions enabled some countries to overcome the negative impacts and Beard (2007). Segal 2008. See the 2009 HDR (UNDP–HDRO 2009; see inside 24 of the crisis is China, whose growth is high (8.7 percent for 2009 Mansuri and Rao (2010), which synthesizes the results of back cover for a list of HDRs). 55 and an expected 10 percent for 2010), driven mostly by infra- research on the conceptual foundations and the efficacy of ini- Pineda and Rodríguez 2006; Bénabou 2000; Alesina and others structure lending. See IMF (2010b). tiatives to foster citizen participation. 1996. 98 25 56 This was a common pattern in past crises: Thailand reduced its See the 2004 HDR (UNDP–HDRO 2004; see inside back cover for Deaton 2007; Sen, Iyer, and Mukherjee 2009. 57 health spending 9 percent and education spending 6 percent in a list of HDRs). Narayana 2008; Minujina and Delamonica 2003; see also Cornia, 26 response to the East Asian crisis in 1998; health expenditures in On the limits of consultation and the problems of refugee status, Rosignoli, and Tiberti (2007). 58 Mexico fell 15 percent during the Tequila crisis (see Calvo 2010). see Bassel (2010). K. Stewart 2010. 99 27 59 ILO 2009. See Elson (2006) and O’Brien (2010). For example, Elson (2006) Joe, Mishra, and Navaneetham 2009. 100 60 IMF 2009; Horváth, Ivanov, and Peleah 2010. cites gender budget initiatives in Australia, France, Mexico, Gwatkin and others 2007. 101 61 Cord and others 2009; Marone, Thelen, and Gulasan 2009. South Africa and Uganda. Houweling and others 2007. 102 28 62 Rodrik 1998. Council of Europe CDEG 2009: 41, 43; ECLAC 2010. Measure DHS 2010. 103 29 63 Commander 2010. Chattopadhyay and Duflo 2004. Thomas, Wang, and Fan (2001), and personal communication 104 30 Commander 2010; Freeman 1998. Gibney, Cornett, and Wood 2010. with Robert Barro and Jong-Wha Lee. 105 31 64 See www.doingbusiness.org/. UNDP 2009: 6. Harttgen and Klasen 2010. 106 32 Salehi-Isfahani 2010. ACHR 2008. 122 human development report 2010 14 29 107 Seth 2009. This terminology follows government categories, which are Blanchard 2008; Commander 2010. 15 108 While indicators in other dimensions are compared between defined officially and vary by state. Sirimanne 2009: 4. 30 109 men and women, indicators of reproductive health are com- Some experts have argued that inequality among poor people ILO 2009. 110 pared to thresholds of no maternal death and no teenage should be reflected in a measure of poverty, but this requires Ablett and Slengesol 2000. 111 pregnancy. using cardinal measures, and the MPI would be sensitive to the Walker and others 2007. 16 112 The risk of maternal death is five times higher in teen births, in scale in which these measures are defined. See Alkire and Foster Ferreira and Schady 2008; FAO 2010a. 113 part because girls’ bodies are not yet fully developed (see Row- (2009) for a discussion. Harper and others 2009. 114 bottom 2007). We use the adolescent fertility rate for girls ages Heyzer and Khor 1999; Knowles, Pernia, and Racelis 1999. Chapter 6 115 15–19. Fertility for girls below age 18 would be preferable, but van der Hoeven 2010. 116 these data are not available. Baird, Friedman, and Schady 2007: 26. 1 Asher and Daponte 2010. 17 117 ILO 2010c. This figure differs from the global female labour force Calvo 2010. 2 An alternative approach using the projections for component 118 participation rate of 56.8 percent presented in statistical table UNICEF 2010a. variables produced by international organizations and inde- 119 4 because of different schema used to weight country-specific UNICEF 2010b. pendent forecasters yielded similar projections. See Asher and 120 female labour force participation rates. Walton 2010; Lustig 2000. Daponte (2010). 18 121 Desai 2010. UN 2010b. 3 Maddison 2007. 19 122 The GDI relied on the gender ratio of nonagricultural wages, Fuentes-Nieva and Pereira 2010. 4 Nelson and others 2009. but the nonagricultural formal sector is limited in size in many 5 Cline 2008. Chapter 5 developing countries and the gap may not have been represen- 6 Rodríguez 2007. tative of the overall picture. 1 7 See for example, Narayan and others (2000) and UNDESA Deaton 2010; Ravallion 1996. 20 This is not driven solely by the fact that both measures of 8 (2009b). Rodrik and Hausmann 2003; Rodrik 2007. See also box 3.1 in inequality are (negatively) correlated with HDI: the correlation 2 Because the aspects of well-being and inequality measured by chapter 3. between the residuals of both inequality measures on the HDI is 9 the GII differ from those measured by the IHDI, the associated Easterly 2002. 0.48, which is significant at 1 percent. 10 loss in achievement can be higher than the loss in human devel- Ostrom 1996; Parks and others 1999; Pestoff 2009. 21 Compared with HDR 2009 (UNDP–HDRO 2009; see inside back 11 opment captured by the IHDI. Drèze and Sen 2002; Sen 1985b. cover for a list of HDRs), the total coverage is lower than that for 3 12 Foster, López-Calva, and Szekely 2005. See also Alkire and Fos- UNDP 2010. the GDI (155) but well above that for the GEM (109). As noted 13 ter (2010). Walton 2010. earlier, the previous approach relied heavily on imputations, 4 14 The measure is the general mean of general means, a class of Rodrik 2003. which is not the case for the GII. The countries lacking sufficient 15 measures derived from Atkinson’s (1983) seminal work on the Evans 2010. data to adjust for the GII have HDI ranks from 6 (Lichtenstein) to 16 measurement of inequality. Its basic desirable properties are path Pritchett, Woolcock, and Andrews 2010. 164 (Guinea-Bissau). 17 independence (the order of aggregation across populations and Pritchett, Woolcock, and Andrews 2010. 22 This is echoed in Pogge (2009: 21): “A credible index of develop- 18 dimensions can be altered without affecting the value of the IHDI) Panagariya 2008; Damodaran 2008. ment must be sensitive to whether an increase in literacy goes 19 and subgroup consistency. See Technical note 2 for further details. Vaughan 2003. to landowners or the landless, an improvement in medical care 5 20 Calculating the IHDI requires setting a parameter that captures Watson and Yohannes 2005. goes to children or to aged, an increase in enrolment to privi- 21 how much people dislike inequality. The parameter can range Iglehart 2010. leged university students or to children in slums, an increase 22 from 0 to infinity; we use a value of 1. This fairly mild adjustment The White House 2010. in life expectancy to the elite or to the marginalized, enhanced 23 for inequality moderately penalizes inequality in each dimen- Di Tella and Dubra 2009. physical security to males or to females.” 24 sion; see Technical note 2 for more details. The choice of param- See Rajan and Zingales (2003) on the threat of oligarchic capital- 23 Alkire and Foster 2009; Alkire and Santos 2010; Bourguignon eter involves a normative judgement analogous to that for other ism, and Walton (2010) for an overview. and Chakravarty 2003; Brandolini and D’Alessio 2009. 25 policy-relevant norms—for example, in establishing a threshold These principles are associated with the work of Sen (1999), 24 Anand and Sen 1997. for relative and absolute poverty. It also reflects judgement about Unger (1998), and Jayadev (2010). 25 See for example, Kanbur and Squire (2001) and Micklewright 26 how much inequality matters. The academic literature addresses Birdsall 2008. and Stewart (2001). 27 both theoretical and empirical issues (see Atkinson 1983 and World Bank 2010e. The size of the carbon market ($144 bil-

26 Population figures refer to 2010. This assumes that the poverty

Pirttilä and Uusitalo 2010). Another strand of the literature lion) exceeds total official development assistance for 2009

rates in the year of the most recent survey (which goes back as

attempts to distinguish between inequality that is justified and ($136 billion). far as 2000) adequately reflect poverty today. Because none of 28 inequality that is not (see Roemer 1998). Social preferences for See www.oslocfc2010.no. these surveys post-dates the more recent economic crisis, these 29 redistribution have been examined based on the tax and transfer Ethiopia’s figure is for 2002, the latest year available. may well be underestimates. 30 systems in place (see Bourguinon and Spadaro 2005). UNAIDS 2008; The Global Fund 2009. 27 The average HDI of countries where the MPI headcount 6 31 Because of the multiplicative form of the HDI and the IHDI, the Wolf 2007; Asiedu and Nandwa 2007; d’Aiglepierre and Wag- exceeded$1.25 a day poverty rate was 0.49; the average for

loss in HDI due to inequality (1 – IHDI/HDI) falls between the ner 2010.

countries where income poverty exceeded the MPI headcount 32

minimum and the maximum loss in dimensions. Levine 2004.

was 0.60.

7 33

Narayana 2008. OECD/DAC 2010b.

28 Income poverty estimates of less than $1.25 a day exclude the 8 34 That is, the implicit welfare function is separable for the various Sachs and others 2004. In particular, aid provided for military following countries because of lack of data: Belize, Czech Repub- dimensions of the IHDI (Atkinson and Bourguignon 2000). and political considerations or other geopolitically motivated lic, Guyana, Iraq, Mauritius, Myanmar, Occupied Palestinian Ter- 9 Anand and Sen 1995. reasons tends to be negatively associated with growth (Minoiu ritories, Somalia, Suriname, Syrian Arab Republic, Trinidad and 10 See Charmes and Wieringa (2003), who review the GDI and GEM and Reddy 2010). Tobago, United Arab Emirates and Zimbabwe. Excluding these 35 to construct the African Gender and Development index for the Easterly 2006; Moyo 2009. countries, the total number of multidimensionally poor people 36 Economic Commission for Africa, and Klasen (2006) on the GDI World Bank 2010d. is 1,719 million, which is still between the two income poverty 37 and GEM. See OECD (2008a), which is based on a survey of 33 OECD part- estimates. For the income poverty estimates of less than$2 a

11 Hawken and Munck (2009) and Klasen and Schüler (2010) pro- ner countries.

day the countries excluded because of lack of data are Guinea, 38

vide useful reviews. For example, see www.aidtransparency.net.

Guyana, Haiti, Iraq, Lao PDR, Mauritania, Mauritius, Myanmar,

12 39

Various other gender indices have adopted this approach— This is shown by the burgeoning literature in the field, published

Namibia, Somalia, Syrian Arab Republic, Trinidad and Tobago,

including Social Watch’s Gender Equity Index and the World in such scholarly journals as the Journal of Human Develop-

United Arab Emirates and Zimbabwe. Excluding these coun-

Economic Forum’s Global Gender Gap Index. ment and Capabilities or presented at the annual meetings of

tries, the total number of multidimensionally poor people is

13 See Technical note 3. The aversion towards gender inequality the Human Development and Capabilities Association. For an

1,699.5 million, which again is between the two income poverty

parameter is set at 2 while the aversion towards overlapping anthology of some key contributions, see Fukuda-Parr and Shiva

estimates.

deprivation is set at 1. Kumar (2003). 123

Notes

40 55

Living Standards Measurement Study surveys have been con- is based on variants of the Ramsey-Cass-Koopmans model in Nussbaum 2000; Osmani and Sen 2003; Klasen 2002; Robeyns

ducted in 40 countries since 1980 (www.surveynetwork.org); which a representative agent maximizes a discounted sum of 2003.

56

Demographic and Health Surveys are available for 82 countries the utility of consumption. Stuckler, Basu, and McKee 2010; Mejía and St-Pierre 2008;

45

(www.measuredhs.com/countries); and Multiple Indicator See, for example, Diener and Seligman (2004) and Gough and Piketty 2000.

57

Cluster Surveys are available for more than 70 countries (www. McGregor (2007). Bourguignon and Verdier 2000; Acemoglu and Robinson 2002.

46 58

childinfo.org/mics_available.html). Neumayer 2010b. Ivanov and Peleah 2010.

41 47 59

The Missing Dimensions programme of the Oxford Poverty and Southgate 1990; Mink 1993. The relationship between competition and growth is complex

48

Human Development Initiative is seeking to rectify this gap for Comin, Hobjin, and Rovito 2008; Córdoba and Ripoll 2008; and potentially nonlinear. See Aghion and Griffith (2005).

60

empowerment, work quality, physical safety, dignity and other Duarte and Restuccia 2006. According to results from the Gallup World Poll, less than

49

areas (www.ophi.org). Barro 1991; Barro and Lee 1994. half of people around the world feel that the area where

42 50

OECD 2010. Ibrahim and Alkire 2007; Alsop and Heinsohn 2005; Narayan they live is becoming more liveable, only 4 in 10 feel that

43 Naturally, this should build on the existing literature (such 2005. economic conditions in their country are getting better,

51

as Ranis, Stewart, and Ramirez 2000; Bourguignon and oth- The sample was drawn from civil society organizations that have and just half are satisfied with environmental preservation

ers 2008; and Kenny 2008). Various global and National HDRs consultative status with the United Nations. The survey, pre- efforts.

61

describe the causal chains through which economic growth pared in three languages, had 644 respondents and a response Stiglitz and Members of the UN Commission of Financial Experts

addresses core human priorities—for example, by creating jobs rate of 29 percent. The best represented region was Western 2010.

62

for poor people, empowering women within the household and Europe (30 percent of respondents), followed by North America Hoddinott and Quisumbing 2010.

63

contributing revenue for social investment, social protection (26 percent) and Africa (17 percent). Anand and Sen 2000a; Sen 2009b.

52 64

and redistribution. Eyben 2004 See www.earthsummit2012.org/.

44 53 65

For basic expositions, see Jones (2002) and Barro and Sala-i- Bassel 2008a, 2008b. King 1964.

54

Martin (2003). Most theoretical and empirical growth analysis Gaye and Jha 2010; PNUD México 2003; PNUD Argentina 2002.

124 human development report 2010

References

Ablett, J., and I. Slengesol. 2000. ———. 2010.

Education in Crisis: The Impact and “Conceptual Overview of Human Development: Defi- Working Paper. Harvard Kennedy School of Government, Cam-

Lessons of the East Asia Financial Shock 1997–1999. Paris: United nitions, Critiques, and Related Concepts.” Human Development bridge, MA, and Center for Global Development, Washington, DC.

Nations Educational, Scientific and Cultural Organization. Research Paper 1. UNDP–HDRO, New York. Asher, J., and B. Daponte. 2010. “A Hypothetical Cohort Model of

Abraham, A., and J. P. Platteau. 2004. Alkire, S., and J. Foster. 2009.

“Participatory Development: “Counting and Multidimensional Pov- Human Development.” Human Development Research Paper 40.

When Culture Creeps In.” In Culture and Public Action, eds. V. Rao erty Measurement.” OPHI Working Paper 7. Oxford Poverty and UNDP–HDRO, New York.

and M. Walton. Stanford, CA: Stanford University Press. Human Development Initiative, Oxford, UK. Asiedu, E., and B. Nandwa. 2007. “On the Impact of Foreign Aid in

Acemoglu, D., S. Johnson, and J. Robinson. 2001. ———. 2010.

“The Colonial “Designing the Inequality-Adjusted Human Devel- Education on Growth: How Relevant Is the Heterogeneity of Aid

Origins of Comparative Development: An Empirical Investigation.” opment Index (HDI).” Human Development Research Paper 28. Flows and the Heterogeneity of Aid Recipients?” Review of World

American Economic Review 91(5): 1369–1401. UNDP–HDRO, New York. Economics 143(4): 631–49.

———. 2003. Alkire, S., and M. Santos. 2010. Aslund, A. 2001.

“An African Success Story: Botswana.” In In Search of “Acute Multidimensional Poverty: “The Myth of Output Collapse after Commu-

Prosperity: Analytical Narratives on Economic Growth, ed. D. Rodrik. A New Index for Developing Countries.” Human Development nism.” Carnegie Endowment for International Peace, Washing-

Princeton, NJ: Princeton University Press. Research Paper 11. UNDP–HDRO, New York. ton, DC. www.carnegieendowment.org/publications/index.

cfm?fa=view&id=611. Accessed 25 June 2010.

Acemoglu, D., and J. Robinson. 2002. Allendorf, K. 2007.

“The Political Economy of the “Do Women’s Land Rights Promote Empowerment Atkinson, A. 1970.

Kuznets Curve.” Review of Development Economics 6(2): 183–203. and Child Health in Nepal?” World Development 35(11): 1975–88. “On the Measurement of Inequality.” Journal of Eco-

nomic Theory 2(3): 244–63.

ACHR (Asian Centre for Human Rights). 2008. Alsop, R., and N. Heinsohn. 2005.

South Asia: Human “Measuring Empowerment in ———. 1983.

Rights Index 2008. New Delhi: Asian Centre for Human Rights. Practice: Structuring Analysis and Framing Indicators.” Policy The Economics of Inequality, 2nd edition. Oxford, UK:

Research Working Paper 3510. World Bank, Washington, DC. Clarendon Press.

Adamolekun, L., G. Lusignan, and A. Atomate (Eds.). 1997. Civil Alvarez, M., J. A. Cheibub, F. Limongi, and A. Przeworski. 1996. Atkinson, A., and F. Bourguignon (Eds.). 2000.

Service Reform in Francophone Africa: Proceedings of a Workshop, Handbook of Income

Abidjan, January 23–26, 1996. World Bank Technical Paper 357, “Classifying Political Regimes.” Studies in Comparative International Distribution, 1st edition. Amsterdam: Elsevier.

Africa Region Series. Washington, DC: World Bank. Development 31(2): 3–36. Atkinson, A., and J. Micklewright. 1992. Economic Transformation in

ADB (Asian Development Bank). 2007. Amnesty International. 2009a.

Key Indicators for Asia and the Nigeria: Petroleum, Pollution and Pov- Eastern Europe and the Distribution of Income. Cambridge, UK: Cam-

Pacific 2007: Inequality in Asia. Manila. erty in the Niger Delta. London. bridge University Press.

Agarwal, B. 2001. ———. 2009b. Baird, S., J. Friedman, and N. Schady. 2007.

“Participatory Exclusions, Community Forestry, and “The Dealth Penalty in 2009.” London. www. “Aggregate Income

Gender: An Analysis for South Asia and a Conceptual Framework.” amnesty.org/en/death-penalty/death-sentences-and-executions Shocks and Infant Mortality in the Developing World.” Policy

World Development 29(10): 1623–48. -in-2009. Accessed 7 June 2010. Research Working Paper 4346. World Bank, Washington, DC.

———. 2003. ———. 2010. Baland, J. M., and J. P. Platteau. 1996.

“Gender and Land Rights Revisited: Exploring New Uganda: Antihomosexuality Bill is Inherently Discrimi- Halting Degradation of Natural

Prospects via the State, Family and Market.” In Agrarian Change, natory and Threatens Broader Human Rights. London. Resources: Is There a Role for Rural Communities? Rome: Food and

Gender and Land Rights, ed. S. Razavi. Oxford, UK: Blackwell Pub- Agriculture Organization.

Anand, S., and P. Segal. 2008. “What Do We Know about Global

lishing Ltd. Barbone, L., L. Cord, K. Hull, and J. Sandefur. 2007.

Income Inequality?” Journal of Economic Literature 46(1): 57–94. “Democracy and

Agarwal, B., and P. Panda. 2007. “Toward Freedom from Domestic Poverty Reduction: Explorations on the Sen Conjecture.” In Politi-

Anand, S., and A. Sen. 1995. “Gender Inequality in Human Develop-

Violence: The Neglected Obvious.” Journal of Human Development cal Institutions and Development: Failed Expectations and Renewed

ment: Theories and Measurement.” Human Development Report

and Capabilities 8(3): 359–88. Hopes, eds. N. Dinello and V. Popov. Cheltenham, UK: Edward Elgar

Office Occasional Paper 19. United Nations Development Pro- Publishing Ltd.

Aghion, P., and R. Griffith. 2005. Competition and Growth: Reconciling gramme, New York. Bardhan, P. 2006.

Theory and Evidence. Cambridge, MA: MIT Press. “Globalization and Rural Poverty.” World Develop-

———. 1997. “Concepts of Human Development and Poverty: A ment 34(8): 1393–1404.

Akram, T. 2004. “Ranking Countries and Other Essays.” Columbia Uni- Multidimensional Perspective.” Human Development Report 1997 Bardhan, P., and D. Mookherjee. 2000.

versity, New York. Papers: Poverty and Human Development. United Nations Devel- “Capture and Governance

opment Programme, New York. at Local and National Levels.” American Economic Review 90(2):

Alderman, H., P. F. Orazem, and E. M. Paterno. 2001. “School Qual- 135–39.

———. 2000a.

ity, School Cost, and the Public/Private School Choices of Low- “Human Development and Economic Sustainability.” Barrett, C. B., and D. G. Maxwell. 2005.

Income Households in Pakistan.” Journal of Human Resources 36(2): World Development 28(12): 2029–49. Food Aid After Fifty Years:

304–26. Recasting Its Role. London: Routledge.

———. 2000b. Human Development and Human Rights. Oxford, UK:

Alesina, A., S. Özler, N. Roubini, and P. Swagel. 1996. Barro, R. J. 1991.

“Political Oxford University Press. “Economic Growth in a Cross Section of Countries.”

Instability and Economic Growth.” Journal of Economic Growth 1(2): Quarterly Journal of Economics 106(2): 407–43.

———. 2000c. “The Income Component of the Human Development

189–211. Barro, R. J., and J. W. Lee. 1994.

Index.” Journal of Human Development and Capabilities 1(1): 83–106. “Sources of Economic Growth.”

Alkire, S. 2003. “A Conceptual Framework for Human Security.” CRISE Carnegie-Rochester Conference Series on Public Policy 40(1): 1–46.

Andrews, M. 2008. “The Good Governance Agenda: Beyond Indica-

Working Paper 2. Centre for Research on Inequality, Human Secu- ———. 2010.

tors without Theory.” Oxford Development Studies 36(4): 379–407. A New Data Set of Educational Attainment in the World,

rity and Ethnicity, Oxford, UK. 1950–2010. NBER Working Paper 15902. Cambridge, MA: National

Andrews, M., A. Grinsted, A. Nucifora, and R. Seligmann. 2010.

———. 2007. “The Missing Dimensions of Poverty Data: Introduction Bureau of Economic Research.

“Public Institutional Reform in Mozambique: But with Limits.”

to the Special Issue.” Oxford Development Studies 35(4): 347–59. 125

References

Barro, R. J., and X. Sala-i-Martin. 2003. Boone, P., and Z. Zhan. 2006. Caldas, S. J. 1993.

Economic Growth, 2nd edi- “Lowering Child Mortality in Poor “Reexamination of Input and Process Factor Effects

tion. Cambridge, MA: MIT Press. Countries: The Power of Knowledgeable Parents.” CEP Discussion on Public School Achievement.” Journal of Educational Research

Papers 751. Centre for Economic Performance, London. 86(4): 206–14.

Barros, R. P., F. Ferreira, J. R. Molinas Vega, and J. Saavedra Chan-

duvi. 2008. Bornstein, D. 2005. Calvo, S. G. 2010.

Measuring Inequality of Opportunities in Latin America The Price of a Dream: The Story of the Grameen “The Global Financial Crisis of 2008–10: A View

and the Caribbean. Basingstroke, UK, and Washington, DC: Palgrave Bank. Oxford, UK: Oxford University Press. from the Social Sectors.” Human Development Research Paper 18.

MacMillan and World Bank. UNDP–HDRO, New York.

Bourguignon, F. 2004. The Poverty-Growth-Inequality Triangle.

Bassel, L. 2008a. Canning, D. 2010.

“Citizenship as Interpellation: Refugee Women and New Delhi: Indian Council for Research on International Economic “Progress in Health Around the World.” Human

the State.” Government and Opposition 43(2): 293–314. Relations. Development Research Paper 43. UNDP–HDRO, New York.

———. 2008b. Bourguignon, F., A. Bénassy-Quéré, S. Dercon, A. Estache, J. W. Cartwright, N. 2009.

“Silencing to Protect: The Debate Over Women’s “What Are Randomised Controlled Trials Good

Gunning, R. Kanbur, S. Klasen, S. Maxwell, J. P. Platteau, and

Rights in France and Canada.” In Silencing Human Rights: Critical For?” Philosophical Studies 147(1): 59–70.

Engagements with a Contested Project, eds. G. K. Bhambra and R. “Millennium Development Goals at Midpoint: Casabonne, U., and C. Kenny. 2009. The Best Things in Life are (Nearly)

Shilliam. Basingstoke, UK: Palgrave Macmillan. Where Do We Stand and Where Do We Need to Go?” Background Free: Technology, Knowledge and Global Health. Washington, DC:

paper for the 2009 European Report on Development. European

———. 2010. “Intersectional Politics at the Boundaries of the Nation World Bank.

Commission, Brussels.

State.” Ethnicities 10(2): 155–80. Chahine, J. 2005. “Lebanon Slips in Human Development Index—UN

Bourguignon, F., and S. Chakravarty. 2003. “The Measurement of

Bebenroth, R., D. Dietrich, and U. Vollmer. 2009. “Bank Regulation Report Identifies Three Pillars of Cooperation in Urgent Need of

Multidimensional Poverty.” Journal of Economic Inequality 1(1):

and Supervision in Bank-Dominated Financial Systems: A Compari- Committment.” The Daily Star. 9 September.

25–49.

son Between Japan and Germany.” European Journal of Law and Charmes, J., and S. Wieringa. 2003. “Measuring Women’s Empow-

Bourguinon, F., and A. Spadaro. 2005.

Economics 27(2): 177–209. “Tax-Benefit Revealed Social erment: An Assessment of the Gender-Related Development Index

Preferences: Are Tax Authorities Non-Paretian?” Paris-Jourdan

Beck, T., G. Clarke, A. Groff, P. Keefer, and P. Walsh. 2001. “New and the Gender Empowerment Measure.” Journal of Human Devel-

Sciences Economiques Working Paper 22. Paris-Jourdan Sciences

Tools in Comparative Political Economy: The Database of Political opment and Capabilities 4(3): 419–35.

Economiques, Paris.

Institutions.” World Bank Economic Review 15(1): 165–76. Charumilind, C., R. Kali, and Y. Wiwattanakantang. 2006. “Con-

Bourguignon, F., and T. Verdier. 2000. “Oligarchy, Democracy,

Behrman, J., A. Murphy, A. Quisumbing, and K. Yount. 2009. “Are nected Lending: Thailand Before the Financial Crisis.” Journal of

Inequality and Growth.” Journal of Development Economics 62(2):

Returns to Mothers’ Human Capital Realized in the Next Genera- Business 79(1): 181–218.

285–313.

tion? The Impact of Mothers’ Intellectual Capital and Long-Run Chattopadhyay, R., and E. Duflo. 2004. “Women as Policy Makers:

Nutritional Status on Children’s Human Capital in Guatemala.” IFPRI “Foreign Companies Chafe at China’s Restrictions.” Evidence from a Randomized Policy Experiment in India.” Econo-

Discussion Paper 850. International Food Policy Research Institute, The New York Times. May 16. metrica 72(5): 1409–43.

Washington, DC. Brainerd, E. 2010. “Human Development in Eastern Europe and the Cheibub, J. A., J. Gandhi, and J. R. Vreeland. 2009. “Democracy and

Bénabou, R. 2000. “Unequal Societies: Income Distribution and the CIS since 1990.” Human Development Research Paper 16. UNDP– Dictatorship Revisited Dataset.” University of Illinois at Urbana-

Social Contract.” The American Economic Review 90(1): 96–129. HDRO, New York. Champaign. netfiles.uiuc.edu/cheibub/www/DD_page.html.

Benavot, A., and J. Resnik. 2006. Brainerd, E., and D. Cutler. 2005.

“Lessons from the Past: A Com- “Autopsy on an Empire: Under- Accessed 15 April 2010.

parative Socio-Historical Analysis of Primary and Secondary Educa- standing Mortality in Russia and the Former Soviet Union.” Journal Chen, Y., and H. Li. 2009. “Mother’s Education and Child Health:

tion.” In Educating all Children: A Global Agenda, eds. J. E. Cohen, D. of Economic Perspectives 19(1): 107–30. Is There a Nurturing Effect.” Journal of Health Economics 28(2):

E. Bloom, and M. B. Malin. Cambridge, MA: American Academy of Brandolini, A., and G. D’Alessio. 2009. “Measuring Well-Being in the 413–26.

Arts and Sciences. Functioning Space.” In Debating Global Society: Reach and Limits of Chen, S., and M. Ravallion. 2008. “The Developing World is Poorer

Besley, T., R. Pande, and V. Rao. 2005. “Political Selection and the the Capability Approach, ed. E. Chiappero-Martinetti. Milan, Italy: Than We Thought, But No Less Successful in the Fight Against Pov-

Quality of Government: Evidence from South India.” CEPR Discus- Feltrinelli Foundation. erty.” Policy Research Working Paper 4703. Washington, DC: Devel-

sion Paper 5201. Center for Economic and Policy Research, Wash- Brown, G., A. Langer, and F. Stewart. 2008. “A Typology of Post- opment Research Group, World Bank.

ington, DC. Conflict Environments: An Overview.” CRISE Working Paper 53. China NDRC (National Development and Reform Commission).

Bessell, S. 2009a. “Indonesian Children’s Views and Experiences of Centre for Research on Inequality, Human Security and Ethnicity, 2006. “The Outline of the 11th Five-year Plan for National Economic

Work and Poverty.” Social Policy and Society 8(4): 527–40. Oxford, UK. and Social Development of the People’s Republic of China.” en.ndrc.

———. 2009b. Brun, J. F., G. Chambas, and F. Mourji. 2009.

“Strengthening Fiji’s Education System: A View from “Guaranteeing Fiscal gov.cn/hot/t20060529_71334.htm. Accessed 15 July 2010.

Key Stakeholders.” Pacific Economic Bulletin 24(3): 58–70. Space for Human Development in Morocco.” In Fiscal Space: Policy Clemens, M. A. 2004. “The Long Walk to School: International Educa-

Options for Financing Human Development, eds. R. Roy and A.

Bhagwati, J., and P. Desai. 1970. India: Planning for Industrialization. tion Goals in Historical Perspective.” Working Paper 37. Center for

Heuty. London: Earthscan.

Oxford, UK: Oxford University Press. Global Development, Washington, DC.

Bryce, J., S. Arifeen, G. Pariyo, C. Lanata, D. Gwatkin, and J. P. Hab-

Binder, M., and G. Georgiadis. 2010. Cline, W. 2008.

“Determinants of Human Devel- Global Warming and Agriculture: Impact Estimates

icht. 2003. “Reducing Child Mortality: Can Public Health Deliver?”

opment: Insights from State-Dependent Panel Models.” Human by Country. Washington, DC: Center for Global Development and

The Lancet 362 (9378): 159–64.

Development Research Paper 24. UNDP–HDRO, New York. Peterson Institute for International Economics.

Budlender, D. 2008. The Statistical Evidence on Care and Non-Care

Birdsall, N. 2008. Coale, A. 1991.

Put Double Majority Voting Back on the Table at the “Excess Female Mortality and the Balance of the Sexes

Work across Six Countries. Gender and Development Programme

IMF. Washington, DC: Center for Global Development. in the Population: An Estimate of ‘Missing Females.’” Population

Paper 4. Geneva: United Nations Research Institute for Social and Development Review 17(3): 517–23.

Blanchard, O. 2008. “Reforming Labor Market Institutions: Unem- Development. Collier, P., and A. Hoeffler. 2007.

ployment Insurance and Employment Protection.” In Washington “Civil War.” In Handbook of Defense

Burd-Sharps, S., K. Lewis, P. Guyer, and T. Lechterman. 2010.

Consensus Reconsidered: Towards a New Global Governance, eds. N. Economics: Defense in a Globalized World, eds. T. Sandler and K.

“Twenty Years of Human Development in Six Affluent Countries:

Serra and J. E. Stiglitz. New York: Oxford University Press. Hartley. Amsterdam: Elsevier.

Australia, Canada, Japan, New Zealand, United Kingdom, and

Boden, T. A., G. Marland, and R. J. Andres. 2009. Comin, D., B. Hobijn, and E. Rovito. 2008.

“Global, Regional, United States.” Human Development Research Paper 27. UNDP– “Technology Usage Lags.”

and National Fossil-Fuel CO Emissions.” Carbon Dioxide Informa- HDRO, New York. Journal of Economic Growth 13(4): 237–56.

2

tion Analysis Center, Oak Ridge National Laboratory, TN. http:// Burd-Sharps, S., K. Lewis, and E. B. Martins (Eds.). 2008. Commander, S. 2010.

The Mea- “Employment Risk and Policy.” Human Devel-

cdiac.ornl.gov/trends/emis/tre_coun.html. Accessed 15 May sure of America: American Human Development Report 2008–2009. opment Research Paper 30. UNDP–HDRO, New York.

2010. New York: Columbia University Press.

126 human development report 2010

Commission on Growth and Development. 2008. d’Aiglepierre, R., and L. Wagner. 2010.

The Growth “Aid and Universal Primary Space: Policy Options for Financing Human Development, eds. R. Roy

Report: Strategies for Sustained Growth and Inclusive Development. Education.” Working Paper 201022. National Center for Scientific and A. Heuty. London: Earthscan.

Washington, DC: World Bank. Research, Universite d’Auvergne, France. Diener, E., and R. Biswas-Diener. 2000. “New Directions in Subjec-

Commission on Human Security. 2003. Damodaran, H. 2008.

Human Security Now. New India’s New Capitalists: Caste, Business, and tive Well-Being Research: The Cutting Edge.” Indian Journal of Clini-

York: Commission on Human Security. Industry in a Modern Nation. New York: Palgrave Macmillan. cal Psychology 27: 21–33.

Cook, A., and B. Daponte. 2008. Daponte, B., and R. Garfield. 2000. Diener, E., R. Lucas, U. Schimmack, and J. Helliwell. 2009.

“A Demographic Analysis of the Rise “The Effect of Economic Sanc- Well-

in the Prevalence of the US Population Overweight and/or Obese.” tions on the Mortality of Iraqi Children Prior to the 1991 Persian Gulf Being for Public Policy. Oxford, UK: Oxford University Press.

Population Research and Policy Review 27(4): 403–26. War.” American Journal of Public Health 90(4): 546–52. Diener, E., and M. Seligman. 2004. “Beyond Money: Toward an

Cooke, M., F. Mitrou, D. Lawrence, E. Guimond, and D. Beavon. Dasgupta, A., and V. A. Beard. 2007. “Community Driven Develop- Economy of Well-Being.” Psychological Science in the Public Inter-

2007. “Indigenous Well-Being in Four Countries: An Application ment, Collective Action and Elite Capture in Indonesia.” Develop- est 5(1): 1–31.

of the UNDP’s Human Development Index to Indigenous Peoples ment and Change 38(2): 229–49. Donner, J. 2008. “Research Approaches to Mobile Use in the Devel-

in Australia, Canada, New Zealand, and the United States.” BioMed Davies, V. 2007. “Capital Flight and War.” Post-Conflict Transitions oping World: A Review of the Literature.” The Information Society

Central International Health and Human Rights 7(9): 1–11. Working Paper 13. University of Oxford, Centre for the Study of Afri- 24(3): 140–59.

Cord, L., M. Verhoeven, C. Blomquist, and B. Rijkers. 2009. “The can Economies and Department of Economics, Oxford, UK. Drèze, J., and R. Khera. 2010. “India’s National Rural Employment

Global Economic Crisis: Assessing Vulnerability with a Poverty Davies, R., M. Brumm, M. Manga, R. Rubiandini, R. Swarbrick, and Guarantee Act.” UNDP–HDRO, New York.

Lens.” Policy Note. World Bank, Washington, DC. M. Tingay. 2008. “The East Java Mud Volcano (2006 to Present): Drèze, J., and A. Sen. 1989. Hunger and Public Action. Oxford, UK:

Córdoba, J., and M. Ripoll. 2008. “Endogenous TFP and Cross- An Earthquake or Drilling Trigger?” Earth and Planetary Science Let- Clarendon Press.

country Income Differences.” Journal of Monetary Economics 55(6): ters 272(3–4): 627–38. ———. 2002.

1158–70. India: Development and Participation. New Delhi:

de Quadros, C. A., J. M. Olivé, C. Nogueira, P. Carrasco, and C. Sil- Oxford University Press.

Cornia, G. 2010. veira. 1998.

“Income Distribution under Latin America’s New Left “Expanded Program on Immunization.” In Maternal Duarte, M., and D. Restuccia. 2006.

Regimes.” Journal of Human Development and Capabilities 11(1): Health and Child Health Activities at the Local Level: Toward the “The Productivity of Nations.” Fed-

85–114. Goals of the World Summit for Children, eds. Y. Benguigui, S. Land, eral Reserve Bank of Richmond Economic Quarterly 92(3): 195–223.

J. M. Paganini, and J. Yunes. Washington, DC: Pan American Health

Cornia, G., and J. Court. 2001. Duflo, E. 2001.

Inequality, Growth, and Poverty in an “Schooling and Labor Market Consequences of School

Organization.

Era of Liberalization and Globalization. Helsinki: United Nations Uni- Construction in Indonesia: Evidence from an Unusual Policy Experi-

De, A., and J. Drèze. 1999.

versity, World Institute for Development Economics Research. Public Report on Basic Education in India. ment.” American Economic Review 91(4): 795–813.

New Delhi: Oxford University Press.

Cornia, G. A., S. Rosignoli, and L. Tiberti. 2007. ———. 2003.

Globalisation and “Grandmothers and Granddaughters: Old-Age Pen-

Deaton, A. 2002.

Health: Impact Pathways and Recent Evidence. Santa Cruz, CA: Uni- “Policy Implications of the Gradient of Health and sions and Intrahousehold Allocation in South Africa.” World Bank

versity of California Santa Cruz, Center for Global, International and Wealth.” Health Affairs 21(2): 13–30. Economic Review 17(1): 1–25.

Regional Studies. ———. 2007. Duflo, E., R. Hanna, and S. Ryan. 2009.

“Global Patterns of Income and Health: Facts, Inter- “Incentives Work: Getting

Council of Europe, CDEG (Steering Committee for Equality pretations, and Policies.” WIDER Annual Lecture 10. United Nations Teachers to Come to School.” Applied Economics Workshop. Uni-

between Women and Men). 2009. “Sex-Disaggregated Statis- University, World Institute for Development Economics Research, versity of Chicago Booth School of Business, Chicago, IL.

tics on the Participation of Women and Men in Political and Public Helsinki. Durlauf, S., P. A. Johnson, and J. Temple. 2005. “Growth Economet-

Decision-Making in Council of Europe Member States: Situation as ———. 2008. “Income, Health, and Well-Being Around the World: rics.” In Handbook of Economic Growth, eds. P. Aghion and S. Dur-

at 1 September 2008.” Council of Europe, Strasbourg, France. Evidence from the Gallup World Poll.” Journal of Economic Perspec- lauf. Amsterdam: Elsevier.

CPJ (Committee to Protect Journalists). 2009. “Attacks on the Press tives 22(2): 53–72. Easterlin, R. A. 1995. “Will Raising the Incomes of All Increase the

Report 2009.” New York. www.cpj.org/attacks/. Accessed 15 May ———. 2009. Instruments of Development: Randomization in the Happiness of All?” Journal of Economic Behavior and Organization

2010. Tropics, and the Search for the Elusive Keys to Economic Development. 27(1): 35–47.

CRED (Centre for Research on the Epidemiology of Disasters). NBER Working Paper 14690. Cambridge, MA: National Bureau of Easterly, W. 1999. “Life During Growth.” Journal of Economic Growth

2010. “EM-DAT: The International Disaster Database.” Univer- Economic Research. 4(3): 239–76.

sité catholique de Louvain, Belgium. www.emdat.be/advanced ———. 2010. “Instruments, Randomization, and Learning about ———. 2002.

-search-details. Accessed 15 April 2010. The Elusive Quest for Growth: Economists’ Adventures

Development.” Journal of Economic Literature 48(2): 424–55. and Misadventures in the Tropics. Cambridge, MA: MIT Press.

Crocker, D. A. 2007. “Deliberative Participation in Local Development.” della Paolera, G., and A. M. Taylor (Eds.). 2003. A New Economic His- ———. 2006.

Journal of Human Development and Capabilities 8(3): 431–55. White Man’s Burden: Why the West’s Efforts to Aid the

tory of Argentina. New York: Cambridge University Press. Rest Have Done so Much Ill and So Little Good. New York: The Pen-

Cubero, R., and I. V. Hollar. 2010. “Equity and Fiscal Policy: The Denison, E. 1967. Why Growth Rates Differ: Postwar Experience in Nine guin Press.

Income Distribution Effects of Taxation and Social Spending in Western Countries. Washington, DC: The Brookings Institution ———. 2009.

Central America.” IMF Working Paper 112. International Monetary “How the Millennium Development Goals are Unfair to

Press.

Fund, Washington, DC. Africa.” World Development 37(1): 26–35.

Desai, M. 2010. “Hope in Hard Times: Women’s Empowerment and

Cuno, K., and M. Desai. 2009. ECLAC (Economic Commission for Latin America and the Carib-

Family, Gender, and Law in a Globalizing Human Development.” Human Development Research Paper 14. bean). 2010.

Middle East and South Asia. Syracuse, NY: Syracuse University Press. “Gender Equality Observatory for Latin Amer-

UNDP–HDRO, New York. ica and the Caribbean.” Santiago. www.eclac.cl/oig/default.

Cutler, D., A. Deaton, and A. Lleras-Muney. 2006. “The Determi- Di John, J. 2009. From Windfall to Curse? Oil and Industrialization in asp?idioma=IN. Accessed 12 August 2010.

nants of Mortality.” Journal of Economic Perspectives 20(3): 97–120. Venezuela, 1920 to the Present. University Park, PA: Penn State Uni- 1990.

The Economist. “United Nations Development Programme

Cutler, D., and A. Lleras-Muney. 2006. “Education and Health: Evalu- versity Press. Includes Human Development Index in 1990 Report.” The Econo-

ating Theories and Evidence.” In Making Americans Healthier: Social Di Tella, R., and J. Dubra. 2009. The Interruption of a Policy for Less mist. 26 May.

and Economic Policy as Health Policy, eds. R. F. Schoeni, J. S. House, Corruption in the Health Sector, and Better Health Care in Argentina. ———. 1991.

G. A. Kaplan, and H. Pollack. New York: Russell Sage Foundation. “Measuring Human Development.” The Economist.

Cambridge, MA: Harvard Business School. 25 May.

Cutler, D., and G. Miller. 2005. “The Role of Public Health Improve- Diaw, A., S. Guérineau, and S. G. Jeanneney. 2009. “Securing Fiscal ———. 2007.

ments in Health Advances: The Twentieth-Century United States.” “Slimy Business: The Mud Does Not Stick.” The Econo-

Space for the Millennium Development Goals in Senegal.” In Fiscal

Demography 42(1): 1–22. mist. 29 November. 127

References

———. 2010. Frankel, J. 2010. Gibney, M., L. Cornett, and R. Wood. 2010.

“The Worldwide War on Baby Girls.” The Economist. “Mauritius: A Success Story.” Presentation at Harvard “Political Terror Scale

4 March. Kennedy School MPA/ID 10th Anniversary. 15 May, Cambridge, MA. 1976–2008.” Political Terror Scale. www.politicalterrorscale.org/.

Accessed 7 June 2010.

Edmonds, E. 2005. Freeman, R. 1998.

“Does Child Labor Decline with Improving Eco- “War of the Models: Which Labour Market Institu- Gidwitz, Z., M. Heger, J. Pineda, and F. Rodríguez. 2010.

nomic Status?” Journal of Human Resources 40(1): 77–99. tions for the 21st Century?” Labour Economics 5(1): 1–24. “Under-

standing Performance in Human Development: A Cross-National

Edwards, M., and J. Gaventa. 2001. Friedman, S. 2006.

Global Citizen Action. Boulder, CO: “Participatory Governance and Citizen Action in Study.” Human Development Research Paper 42. UNDP–HDRO,

Lynne Rienner Publishers. Post-Apartheid South Africa.” International Institute for Labour Stud- New York.

ies Discussion Paper 164. International Labour Organization, Geneva.

EEA (European Environment Agency). 2008. “EN15 Accidental Gittings, J. 1990. “New Economic Indicator Puts Rich Countries under

Fuchs, T., and L. Woessmann. 2007.

Oil Spills from Marine Shipping.” Copenhagen. http://themes. “What Accounts for International Microscope.” The Guardian. 25 May.

eea.europa.eu/Sectors_and_activities/energy/indicators/ Differences in Student Performance: A Re-Examination Using PISA Glewwe, P. 1999.

EN15%2C2008.11. Accessed 18 June 2010. Data.” Empirical Economics 32(2–3): 433–64. The Economics of School Quality Investments in Devel-

oping Countries. New York: Palgrave Macmillan.

Eicher, T., and S. Turnovsky (Eds.). 2003. Fuentes-Nieva, R., and I. Pereira. 2010.

Inequality and Growth: The- “The Disconnect Between Glewwe, P., and M. Kremer. 2006.

ory and Policy Implications. Cambridge, MA: MIT Press. Indicators of Sustainability and Human Development.” Human “Schools, Teachers, and Educa-

Development Research Paper 34. UNDP–HDRO, New York. tion Outcomes in Developing Countries.” In Handbook of the Eco-

Elson, D. 2006. “The Changing Economic and Political Participation of nomics of Education, eds. E. A. Hanushek and F. Welch. Amsterdam:

Fuentes-Nieva, R., and P. Seck (Eds.). 2010.

Women: Hybridization, Reversals and Contradictions in the Con- Risk, Shocks and Human Elsevier.

text of Globalization.” GEM-IWG Working Paper 8. Salt Lake City, Development: On the Brink. Basingstoke, UK: Palgrave Macmillan. The Global Fund (The Global Fund to Fight AIDS, Tuberculosis and

UT: International Working Group on Gender, Macroeconomics, and Fukuda-Parr, S. 2003. “The Human Development Paradigm: Opera- Malaria). 2009.

International Economics. “Global Fund ARV Fact Sheet.” Geneva.

tionalizing Sen’s Ideas on Capabilities.” Feminist Economics 9(2–3):

Elson, R. E. 2001. Gough, I., and J. A. McGregor (Eds.). 2007.

Suharto: A Political Biography. Cambridge, MA: Cam- 301–17. Wellbeing in Developing

bridge University Press. Countries: New Approaches and Research Strategies. Cambridge, UK:

———. 2007. “Has the Human Development Approach Influenced Cambridge University Press.

Eurostat. 2010. “European Union Statistics on Income and Living Condi- Policy? The Case of World Bank Flagship Reports.” Indian Journal of Graham, C. 2010.

tions.” European Commission, Brussels. http://epp.eurostat.ec.europa. Human Development 1(1): 153–60. “The Challenges of Incorporating Empowerment

eu/portal/page/portal/microdata/eu_silc. Accessed 15 April 2010. into the HDI: Some Lessons from Happiness Economics and Quality

Fukuda-Parr, S., and A. K. Shiva Kumar. 2003. Readings in Human of Life Research.” Human Development Research Paper 13. UNDP–

Evans, P. 2010. “The Challenge of 21st Century Development: Building Development. New York: Oxford University Press. HDRO, New York.

Capability-Enhancing States.” Global Event Working Paper. United Gallego, F. 2010. “Historical Origins of Schooling: The Role of Democ- Graham, W., D. Braunholtz, and O. Campbell. 2010.

Nations Development Programme, New York. “New Modelled

racy and Political Decentralization.” Review of Economics and Sta- Estimates of Maternal Mortality.” The Lancet 375(9730): 1963.

Eyben, R. 2004. “Who Owns a Poverty Reduction Strategy? A Case tistics 92(2): 228–43. Gray, G., and M. Purser. 2010.

Study of Power, Instruments and Relationships in Bolivia.” In Inclu- “Human Development Trends since

Gallup World Poll. 2010. “Gallup.” Washington, DC. www.gallup.

sive Aid: Changing Power and Relationships in International Develop- 1970: A Social Convergence Story.” Human Development Research

com/home.aspx. Accessed 7 June 2010.

ment, eds. L. Groves and R. Hinton. London: Earthscan. Paper 2. UNDP–HDRO, New York.

Faguet, J. P. 2002. Greaney, V., S. R. Khandker, and M. Alam. 1999.

“Does Decentralization Increase Government Bangladesh: Assess-

Sex Ratio Imbalances in Asia.” Reproductive Health Matters 16(31):

Responsiveness to Local Needs? Evidence from Bolivia.” Policy ing Basic Learning Skills. Dhaka: University Press.

90–98.

Research Working Paper 2516. World Bank, Washington, DC. Grimm, M., and I. Günther. 2004. How to Achieve Pro-Poor Growth

Gargarella, R. 2002. “‘Too Far Removed from the People’: Access to Jus-

Fallon, P., S. Aiyar, L. Cui, M. Hussain, L. Redifer, N. Staines, and in a Poor Economy: The Case of Burkina Faso. Göttingen, Germany:

tice for the Poor: The Case of Latin America.” Universidad Torcuato Di

R. Stern. 2004. “Review of Recent IMF Experience in Post-Conflict University of Göttingen.

Tella, Buenos Aires.

Economies.” International Monetary Fund, Washington, DC. Gupta, K., and P. P. Yesudian. 2006. “Evidence of Women’s Empow-

Gasper, D. 2005. “Securing Humanity: Situating ‘Human Security’ as

FAO (Food and Agriculture Organization). 2010a. “FAO Stat.” Rome. erment in India: A Study of Socio-Spatial Disparities.” GeoJournal

Concept and Discourse.” Journal of Human Development and Capa-

http://faostat.fao.org/. Accessed 19 May 2010. 65(4): 365–80.

bilities 6(2): 221–45.

———. 2010b. Gupta, S., M. Verhoeven, and E. Tiongson. 2003.

“Food Security Statistics.” Rome. www.fao.org/ “Public Spending

Gauri, V. 2002. “Brazil: Maternal and Child Health.” Report 23811.

economic/ess/food-security-statistics/en/. Accessed 30 June 2010. on Health Care and the Poor.” Health Economics 12(8): 685–96.

World Bank, Washington, DC.

Ferreira, F., and N. Schady. 2008. Gwatkin, D., S. Rutstein, K. Johnson, E. Suliman, A. Wagstaff, and

“Aggregate Economic Shocks, Child Gauri, V., and P. Khaleghian. 2002. “Immunization in Developing A. Amouzou. 2007.

Schooling and Child Health.” Policy Research Working Paper 4701. “Socio-Economic Differences in Health, Nutri-

Countries: Its Organizational and Political Determinants.” World

World Bank, Washington, DC. tion, and Population within Developing Countries: An Overview.”

Development 30(12): 2109–32. Country Reports on HNP (Health, Nutrition and Population) and

Filmer, D., and L. Prichett. 1999. “The Impact of Public Spending on Gaye, A., and S. Jha. 2010. “A Review of Conceptual and Measure- Poverty. World Bank, Washington, DC.

Health: Does Money Matter?” Social Science and Medicine 49(10): ment Innovations in National and Regional Human Development Hall, G., and H. A. Patrinos (Eds.). 2010.

1309–23. Indigenous Peoples, Poverty

Reports, 1998–2009.” Human Development Research Paper 21. and Development. Washington, DC: World Bank.

Fiszbein, A., N. Schady, F. Ferreira, M. Grosh, N. Keleher, P. Olinto, UNDP–HDRO, New York.

and E. Skoufias. 2009. Hamel, J. Y. 2010.

Conditional Cash Transfers: Reducing Present “ICT4D and the Human Development and Capability

Georgiadis, G., J. Pineda, and F. Rodríguez. 2010. “Has the Preston

and Future Poverty. Washington, DC: World Bank. Approach.” Human Development Research Paper 37. UNDP–HDRO,

Curve Broken Down?” Human Development Research Paper 32. New York.

Fogel, R. W. 2004. The Escape from Hunger and Premature Death, UNDP–HDRO, New York. Hanlon, J., A. Barrientos, and D. Hulme. 2010.

1700–2100: Europe, America, and the Third World. Cambridge, UK: Just Give Money to the

Gertner, J. 2010. “The Rise and Fall of the G.D.P.” The New York Times.

Cambridge University Press. Poor: The Development Revolution from the Global South. Sterling,

May 16. VA: Kumarian Press.

Foster, J., L. López-Calva, and M. Szekely. 2005. “Measuring the GFN (Global Footprint Network). 2009. “The Ecological Footprint Hanushek, E. A. 1995.

Distribution of Human Development: Methodology and an Appli- “Interpreting Recent Research on Schooling in

Atlas.” Oakland, CA. www.footprintnetwork.org/atlas. Accessed

cation to Mexico.” Journal of Human Development 6(1): 5–25. Developing Countries.” World Bank Research Observer 10(2): 227–46.

15 June 2010.

Franco, A., C. Alvarez-Dardet, and M. Ruiz. 2004. Haq, K., and R. Ponzio (Eds.). 2008.

“Effect of Democ- Pioneering the Human Develop-

Ghai, D. P., A. R. Khan, E. L. H. Lee, and T. Alfthan. 1980. The Basic-

racy on Health: Ecological Study.” British Medical Journal 329(7480): ment Revolution: An Intellectual Biography of Mahbub ul Haq. New

Needs Approach to Development: Some Issues Regarding Concepts

1421–23. York: Oxford University Press.

and Methodology. Geneva: International Labour Office.

128 human development report 2010

Harding, R., and L. Wantchekon. 2010. “The Political Economy of Comparative Study of Maternity and Child Care in Developing Coun- information-services/data-and-statistics/index.html. Accessed

Human Development.” Human Development Research Paper 29. tries.” Bulletin of the World Health Organization 85(10): 733–820. 17 June 2010.

UNDP–HDRO, New York. Hulme, D., and S. Fukuda-Parr. 2009. ITU (International Telecommunication Union). 2009.

“International Norm Dynamics “ICT Indica-

Harper, C., N. Jones, A. McKay, and J. Espey. 2009. “Children in and ‘the End of Poverty’: Understanding the Millennium Develop- tors Database 2009.” International Telecommunication Union. www.

Times of Economic Crisis: Past Lessons, Future Policies.” ODI Back- ment Goals (MDGs).” Brooks World Poverty Institute Working Paper itu.int/ITU-D/ict/publications/world/world.html. Accessed 20 July

ground Note. Overseas Development Institute, London. 96. University of Manchester, UK. 2010.

Harttgen, K., and S. Klasen. 2010. Hulme, D., and K. Moore. 2008. Ivanov, A., and M. Peleah. 2010.

“A Household-Based Human “Assisting the Poorest in Bangla- “From Centrally Planned to Human

Development Index.” Human Development Research Paper 22. desh: Learning from BRAC’s ‘Targeting the Ultra Poor‘ Programme.” Development.” Human Development Research Paper 38. UNDP–

UNDP–HDRO, New York. In Social Protection for the Poor and Poorest: Concepts, Policies HDRO, New York.

and Politics, eds. A. Barrientos and D. Hulme. New York: Palgrave

Hausmann, R., and F. Rodríguez. Forthcoming. Jayadev, A. 2010.

Venezuela: Anat- “Global Governance and Human Development: Pro-

Macmillan.

omy of a Collapse. Cambridge, MA: Harvard Kennedy School of moting Democratic Accountability and Institutional Experimenta-

Huntington, S. 1991.

Government. The Third Wave: Democratization in the Late tion.” Human Development Research Paper 6. UNDP–HDRO, New

Twentieth Century. Norman, OK: University of Oklahoma Press. York.

Hausmann, R., F. Rodríguez, and R. Wagner. 2008. “Growth Col- Hurt, L. S., C. Ronsmans, and S. Saha. 2004. Jayadev, A., and F. Rodríguez. 2010.

lapses.” In Money, Crises and Transition: Essays in Honor of Guillermo “Effects of Education “The Declining Labor Share of

A. Calvo, eds. C. M. Reinhart, C. Végh, and A. Velasco. Cambridge, and Other Socioeconomic Factors in Middle Age Mortality in Rural Income.” Human Development Research Paper 36. UNDP–HDRO,

MA: MIT Press. Bangladesh.” Journal of Epidemiology and Community Health 58(4): New York.

315–20.

Hausmann, R., D. Rodrik, and A. Velasco. 2008. Joe, W., U.S. Mishra, and K. Navaneetham. 2009.

“Growth Diagnos- “Inequalities in

Ibrahim, S., and S. Alkire. 2007.

tics.” In The Washington Consensus Reconsidered: Towards a New “Agency and Empowerment: A Pro- Childhood Malnutrition in India: Some Evidence on Group Dispari-

Global Governance, eds. N. Serra and J. E. Stiglitz. Oxford, UK: Oxford prosal for Internationally Comparable Indicators.” Oxford Develop- ties.” Journal of Human Development and Capabilities 10(3): 417–39.

University Press. ment Studies 35(4): 379–403. Johannes, T. A., T. Akwi, and P. E. Anzah. 2006. “The Distributive

Hawken, A., and G. Munck. 2009. IDMC (Internal Displacement Monitoring Centre). 2010.

“Cross-National Indices with “Inter- Impact of Fiscal Policy in Cameroon: Tax and Benefit Incidence.”

Gender-Differentiated Data: What Do They Measure? How Valid nal Displacement Monitoring Centre.” Geneva. www.internal PMMA Working Paper 16. Ottawa: International Research Centre.

Are They?” Technical Background Paper for the forthcoming UNDP -displacement.org. Accessed 15 April 2010. Jolly, R. 2010. “The UN and Development Policies.” UN Intellectual His-

Asia Pacific Human Development Report on Gender. United Nations IEA (International Energy Agency). 2009. World Energy Outlook tory Project Briefing Note 7. United Nations, New York.

Development Programme, New York. 2009. Paris: Organisation for Economic Co-operation and Develop- Jolly, R., L. Emmerij, and T. G. Weiss. 2009. UN Ideas That Changed

Helpman, E. 1998. General Purpose Technologies and Economic Growth. ment and IEA. the World. Bloomington, IN: Indiana University Press.

Cambridge, MA: MIT Press. Iglehart, J. 2010. “Historic Passage—Reform at Last.” The New Eng- Jones, C. 2002. Introduction to Economic Growth. New York: W.W.

Herrero, C., R. Martínez, and A. Villar. 2010. “Improving the Mea- land Journal of Medicine 362(14): 48. Norton.

surement of Human Development.” Human Development Research ILO (International Labour Organization). 2009. World of Work Jones, G., R. Steketee, R. Black, Z. Bhutta, and S. Morris. 2003.

Paper 12. UNDP–HDRO, New York. Report: The Global Jobs Crisis. Geneva: International Labour Office. “How Many Child Deaths Can We Prevent This Year?” The Lancet

Heston, A., R. Summers, and B. Aten. 2009. “Penn World Table ———. 2010a. “Accelerating a Job-Rich Recovery in G20 Countries: 362(9377): 65–71.

Version 6.3.” University of Pennsylvania, Center for International Building on Experience.” Report to G20 Labour and Employment Journal of Human Development and Capabilities. 2003.

Comparisons of Production, Income and Prices, Philadelphia, PA. “Special

Ministers. International Labour Office, Washington, DC.

http://pwt.econ.upenn.edu/php_site/pwt_index.php. Accessed Issue on New Insecurities.” Journal of Human Development and

———. 2010b.

15 July 2010. Global Employment Trends. Geneva: International Capabilities 4(2).

Labour Office.

Heyzer, N., and M. Khor. 1999. Kabeer, N. 1999.

“Globalization and the Way Forward.” “Resources, Agency, Achievement: Reflections on the

———. 2010c.

Development Outreach, Summer 1999. www.devoutreach.com/ Key Indicators on the Labour Market, 6th edition. Measurement of Women’s Empowerment.” Development as Change

summer99/GlobalizationandtheWayForward/tabid/819/Default. Geneva: International Labour Office. 30(3): 435–64.

aspx. Accessed 1 February 2009. ———. 2010d. Kahneman, D. 1999.

“LABORSTA Database.” Employment by Occupation “Objective Happiness.” In Well-Being: The Foun-

Hidalgo, C. 2010. “Graphical Statistical Methods for the Represen- Data. International Labour Office, Geneva. http://laborsta.ilo.org/. dations of Hedonic Psychology, eds. D. Kahneman, E. Diener, and N.

tation of the Human Development Index and its Components.” Accessed 15 January 2010. Schwarz. New York: Russell Sage Foundation.

Human Development Research Paper 39. UNDP–HDRO, New York. Imai, K., and J. Weinstein. 2000. Kahneman, D., E. Diener, and N. Schwarz (Eds.). 1999.

“Measuring the Economic Impact Well-Being:

Hobbes, T. 1651. Leviathan, or, the Matter, Forme, and Power of a Com- of Civil War.” CID Working Paper 51. Harvard University, Center for The Foundations of Hedonic Psychology. New York: Russell Sage

monwealth Ecclesiastical and Civil. Oxford, UK: Oxford University International Development, Cambridge, MA. Foundation.

Press (Printed in 1996). IMF (International Monetary Fund). 2009. Kahneman, D., and A. B. Krueger. 2006.

World Economic Outlook: “Developments in the Mea-

Hoddinott, J., and A. Quisumbing. 2010. “Methods for Microecono- Sustaining the Recovery. Washington, DC. surement of Subjective Well-Being.” Journal of Economic Perspec-

metric Risk and Vulnerability Assessment.” In Risk, Shocks and tives 20(1): 3–24.

———. 2010a. Government Finance Statstics. Washington, DC.

Human Development: On the Brink, eds. R. Fuentes-Nieva and P. Kaletsky, A. 1990. “UN Adds a Human Element to Economics: Con-

———. 2010b.

Seck. Basingstoke, UK: Palgrave Macmillan. World Economic Outlook Update: An Update of the Key troversial New Way to Measure Development.” The Financial Times.

WEO Projections. Washington, DC.

Hogan, M., K. Foreman, M. Naghavi, S. Ahn, M. Wang, S. Makela, A. 25 May.

Lopez, R. Lozano, and C. Murray. 2010. IPU (Inter-Parliamentary Union). 2010.

“Maternal Mortality for 181 “Women in Parliaments: Kamal, N., and K. M. Zunaid. 2006. “Education and Women’s

Countries, 1980–2008: A Systematic Analysis of Progress Towards World and Regional Averages.” Geneva. www.ipu.org/wmn-e/ Empowerment in Bangladesh.” Working Paper 11. Centre for

Millennium Development Goal 5.” The Lancet 375(9726): 1609–23. world.htm. Accessed 7 June 2010. Health, Population and Development at Independent University

Horváth, B., A. Ivanov, and M. Peleah. 2010. Ishida, H., W. Muller, and J. M. Ridge. 1995.

“The Human Develop- “Class Origin, Class Des- Bangladesh, Dhaka.

ment Impact of the Global Crisis in Central, Eastern and Southern tination, and Education: A Cross-National Study of Ten Industrial Kanbur, R., and L. Squire. 2001. “The Evolution of Thinking about

Europe and the CIS.” Working Paper. United Nations Development Nations.” American Journal of Sociology 101(1): 145–93. Poverty: Exploring the Interactions.” In Frontiers of Development

Programme Bratislava Regional Center, Bratislava. ITOPF (International Tank Owners Pollution Federation Limited). Economics: The Future in Perspective, eds. G. Meier and J. E. Stiglitz.

Houweling, T., C. Ronsmans, O. Campbell, and A. Kunst. 2007. 2010. “ITOPF-Data and Statistics.” London. www.itopf.com/ New York: Oxford University Press.

“Huge Poor—Rich Inequalities in Maternity Care: An International 129

References

Kant, I. 1785. Marshall, M., and K. Jaggers. 2010.

Grundlegung zur Metaphysik der Sitten. Hamburg, Ger- Paper 685. Institute of Social and Economic Research, Osaka Uni- “Polity IV Project, Political

many: Felix Meiner Verlag (Printed in 1952). versity, Japan. Regime Characteristics and Transitions, 1800–2008.” Integrated

Network for Societal Conflict Research Program. University of

Kasirye, I. 2010. Kumar, A. 2010.

“What Are the Successful Strategies for Reducing “A Review of Human Development Trends in South Maryland, Center for International Development and Conflict Man-

Malnutrition among Young Children in East Africa?” Human Devel- Asia 1990–2009.” Human Development Research Paper 44. agement, College Park, MD.

opment Research Paper 15. UNDP–HDRO, New York. UNDP–HDRO, New York. Maundu, J. 1988. “Family Background and Student Achievement.”

Kenny, C. 2008. Kuznets, S. 1955.

“The Global Expansion of Primary Education.” http:// “Economic Growth and Income Inequality.” Ameri- Kenyan Journal of Education 4(1): 53–87.

charleskenny.blogs.com/weblog/files/the_global_expansion. can Economic Review 45(1): 1–28. Mayer-Foulkes, D. 2010.

pdf. Accessed 7 June 2010. “Divergences and Convergences in Human

Lacina, B., and N. P. Gleditsch. 2005. “Monitoring Trends in Global Development.” Human Development Research Paper 20. UNDP–

———. 2009. “There’s More to Life than Money: Exploring the Lev- Combat: A New Dataset of Battle Deaths.” European Journal of Pop- HDRO, New York.

els/Growth Paradox in Health and Education.” Journal of Interna- ulation 21(2–3): 145–66. McGuire, J. 2010.

tional Development 21(1): 24–41. “Political Factors and Health Outcomes: Insights

Lake, D. A., and M. Baum. 2001. “The Invisible Hand of Democracy: from Argentina’s Provinces.” Human Development Research Paper

———. Forthcoming. Getting Better: Why Global Development is Political Control and the Provision of Public Services.” Comparative 25. UNDP–HDRO, New York.

Succeeding—And How We Can Improve the World Even More. New Political Studies 34(6): 587–621. McLeod, D., and M. Dávalos. 2008.

York: Basic Books. “Sustainable Post-Conflict

Legovini, A. 2006. “Measuring Women’s Empowerment in Ethiopia: Employment Creation: From Stabilization to Poverty Reduction.”

Khang, Y., J. W. Lynch, and G. A. Kaplan. 2004. “Health Inequali- The Women’s Development Initiatives Project.” In Empowerment UNDP Poverty Group Paper. United Nations Development Pro-

ties in Korea: Age- and Sex-Specific Educational Differences in the in Practice: From Analysis to Implementation, eds. R. Alsop, M. Ber- gramme, New York.

10 Leading Causes of Death.” International Journal of Epidemiology telsen, and J. Holland. Washington, DC: World Bank. Measure DHS. 2010.

33(2): 299–308. “Demographic and Health Surveys.” www.

Leith, J. C. 2005. Why Botswana Prospered. Québec, Canada: McGill’s- measuredhs.com/. Accessed 10 May 2010.

King Jr., M. L. 1964. Why Can’t We Wait. New York: Signet Classics. Queens University Press. Mejía, D., and M. St-Pierre. 2008. “Unequal Opportunities and

Klasen, S. 2000. Levine, R. 2004.

“Does Gender Inequality Reduce Growth and Devel- Millions Saved: Proven Successes in Global Health. Human Capital Formation.” Journal of Development Economics

opment? Evidence from Cross-Country Regressions.” Collaborative Washington, DC: Center for Global Development. 86(2): 395–413.

Research Center 386, Discussion Paper 212. Institute for Statistics, Li, H., and L. Meng. 2005. The Human Cost of China’s Industrial Micklewright, J., and K. Stewart. 2001.

Munich, Germany. “Poverty and Social Exclu-

Growth. College Park, MD: University of Maryland, Department of sion in Europe: European Comparisons and Impact of Enlargement.”

———. 2002. “Low Schooling for Girls, Slower Growth for All? Cross- Economics. New Economy 8(2): 104–09.

Country Evidence on the Effect of Gender Inequality in Education on Lindauer, D., and L. Pritchett. 2002. “What’s the Big Idea? The Third Miguel, E., and M. Kremer. 2004.

Economic Development.” World Bank Economic Review 16(3): 345–73. “Worms: Identifying Impacts on

Generation of Policies for Economic Growth.” Economica 3(1): 1–39. Education and Health in the Presence of Treatment Externalities.”

———. 2006. “Special Issue: Revisiting the Gender-Related Devel- LIS (Luxembourg Income Study). 2009. “Luxembourg Income Study Econometrica 72(1): 159–217.

opment Index and Gender Empowerment Measure.” Journal of Project.” www.lisproject.org/techdoc.htm. Accessed 7 June 2010. Milanovic, B. 1998.

Human Development and Capabilities 7(2). Income, Inequality, and Poverty During the Transi-

Little, I., T. Scitovsky, and M. Scott. 1970. Industry and Trade in Some tion from Planned to Market Economy. Washington, DC: World Bank.

Klasen, S., and D. Schüler. 2010. “Reforming the Gender-Related Developing Countries. Oxford, UK: Oxford University Press. ———. 2009.

Development Index (GDI) and the Gender Empowerment Measure “Global Inequality Recalculated: The Effect of New

Liu, M. 2010.

(GEM): Implementing Some Specific Proposals.” IAI Discussion “Human Development in East and Southeast Asian 2005 PPP Estimates on Global Inequality.” Policy Research Working

Paper 186. Ibero America Institute for Economic Research, Göt- Economies: (1990–2010).” Human Development Research Paper Paper 5061. World Bank, Washington, DC.

tingen, Germany. 17. UNDP–HDRO, New York. Miller, C. 2008. “Evaluation of Mchinji Cash Transfer.” Research

Klasen, S., and C. Wink. 2009. Lokshin, M., and M. Ravallion. 2005.

“A Turning-Point in Gender Bias in “Self-Rated Power and Welfare and Policy to Promote Child and Health Development. http://

Mortality? An Update on the Number of Missing Women.” In Gender in Russia.” In Empowerment: Cross-Disciplinary Perspectives Measur- childresearchpolicy.org/mchinjicashtransfer.html. Accessed 18

and Discrimination: Health, Nutritional Status and the Role of Women ing, ed. D. Narayan. Washington, DC: World Bank. May 2010.

in India, eds. M. Pal, P. Bharati, B. Ghosh, and T. S. Vasulu. New Delhi: López-Calva, L., and N. Lustig (Eds.). 2010. Mink, S. D. 1993.

Declining Inequality “Poverty, Population and the Environment.” Discus-

Oxford University Press. in Latin America: A Decade of Progress? New York: United Nations sion Paper 189. World Bank, Washington, DC.

Knowles, C., E. Pernia, and M. Racelis. 1999. “Social Consequences Development Programme. Minoiu, C., and S. Reddy. 2007. “Aid Does Matter, After All: Revisit-

of the Financial Crisis in Asia: The Deeper Crisis.” Economic and Lustig, N. 2000. “Crises and the Poor: Socially Responsible Macroeco- ing the Relationship Between Aid and Growth.” Challenge 50(2):

Development Resource Center Briefing Note 16. Asian Develop- nomics.” Economía 1(1): 1–19. 39–58.

ment Bank, Manila. Ma, X. 2001. ———. 2010.

“Stability of Socio-Economic Gaps in Mathematics and “Development Aid and Economic Growth: A Positive

Kovacevic, M. 2010a. “Measurement of Inequality in Human Devel- Science Achievement among Canadian Schools.” Canadian Journal Long-Run Relation.” Quarterly Review of Economics and Finance

opment—A Review.” Human Development Research Paper 35. of Education 26(1): 97–118. 50(1): 27–39.

UNDP–HDRO, New York. Maddison, A. 2007. Minujina, A., and E. Delamonica. 2003.

Contours of the World Economy, 1–2030 AD. Paris: “Mind the Gap! Widening

———. 2010b. “Review of Critiques to HDI and Potential Improve- Organisation for Economic Co-operation and Development. Child Mortality Disparities.” Journal of Human Development and

ments.” Human Development Research Paper 33. UNDP–HDRO, Capabilities 4(3): 397–418.

———. 2010.

New York. Historical Statistics of the World Economy: 1–2008 AD. Mody, A. 2010.

Paris: Organisation for Economic Co-operation and Development. “Who Fell in 2009: Those with Current Account Defi-

Krueger, A. 2008. “Comments on Economic Growth and Subjective cits or with Extra Froth?” Vox, London. http://voxeu.org/index.

Mansuri, G., and V. Rao. 2010.

Well-Being: Reassessing the Easterlin Paradox.” Brookings Papers Localizing Development: Has the Partici- php?q=node/4507. Accessed 7 June 2010.

on Economic Activity 1: 95–100. patory Approach Worked? Washington, DC: World Bank. Mookherjee, D. 2005. “Is There Too Little Theory in Development

Krugman, P. 2007. Marglin, S. 2008.

The Conscience of a Liberal. New York: W.W. Norton. The Dismal Science: How Thinking Like an Economist Economics Today?” Economic and Political Weekly 40(40): 4328–33.

Undermines Community. New York: Faber and Faber Ltd.

Kruk, M., S. Galea, M. Prescott, and L. Freedman. 2007. “Health Moreno, M., and F. Rodríguez. 2009. “Plenty of Room? Fiscal Space

Marone, H., N. Thelen, and N. Gulasan. 2009.

Care Financing and Utilization of Maternal Health Services in Devel- “The Economic Cri- in a Resource-Abundant Economy: The Case of Venezuela.” In Fiscal

oping Countries.” Health Policy and Planning 22(5): 303–10. sis: Assessing Vulnerability in Human Development.” UNDP/ODS Space: Policy Options for Financing Human Development, eds. R. Roy

Working Paper. United Nations Development Programme, Office of

Kudamatsu, M. 2007. “Has Democratization Reduced Infant Mortal- and A. Heuty. London: Earthscan.

Development Studies, New York.

ity in Sub-Saharan Africa? Evidence from Micro Data.” Discussion

130 human development report 2010

Moreno-Lopez, P., L. Bandiera, M. Prasad, S. Zeikate, B. Mukho- ———. 2005. Parks, R., P. Baker, L. Kiser, R. Oakerson, E. Ostrom, V. Ostrom,

“Women’s Bodies: Violence, Security, Capabilities.”

padhyay, K. Kalonji, F. Painchaud, A. Unigovskaya, J. De, and S. S. Percy, M. Vandivort, G. Whitaker, and R. Wilson. 1999.

Journal of Human Development and Capabilities 6(2): 167–83.

Mockler. 2009. Heavily Indebted Poor Countries (HIPC) Initiative and “Consumers as Coproducers of Public Services: Some Economic

O’Brien, D. 2010. When Women Matter: Linking Women’s Descriptive

Multilateral Debt Relief Initiative (MDRI)—Status of Implementation. and Institutional Considerations.” In Polycentricity and Local Pub-

and Substantive Representation. St. Louis, MO: Center for New Insti-

Washington, DC: International Development Association and Inter- lic Economies: Readings from the Workshop in Political Theory and

tutional Social Sciences.

national Monetary Fund. Policy Analysis, ed. M. D. McGinnes. Ann Arbor, MI: University of

Ocampo, J. A., R. Vos, and J. K. Sundaram. 2007. Growth Diver- Michigan Press.

Moyo, D. 2009. Dead Aid: Why Aid is Not Working and How There is a gences: Explaining Differences in Economic Performance. New York: Pestoff, V. 2009.

Better Way for Africa. New York: Farrar, Straus and Giroux. “Towards a Paradigm of Democratic Participation:

Zed Books for the United Nations. Citizen Participation and Co-Production of Personal Social Ser-

Munck, G., and J. Verkuilen. 2002. “Conceptualizing and Measuring OECD (Organisation for Economic Co-operation and Develop- vices in Sweden.” Annals of Public and Cooperative Economics 80(2):

Democracy.” Comparative Political Studies 35(1): 5–34. ment). 2008a. 2008 Survey on Monitoring the Paris Declaration: 197–224.

Mwabu, G., and A. Fosu. 2010. “Human Development in Africa.” Making Aid More Effective by 2010. Paris. Piketty, T. 2000. “Theories of Persistent Inequality and Intergenera-

Human Development Research Paper 8. UNDP–HDRO, New York. ———. 2008b. Growing Unequal? Income Distribution and Poverty in tional Mobility.” In Handbook of Income Distribution, 1st edition,

Myrdal, G. 1957. Economic Theory and Underdeveloped Regions. Lon- OECD Countries. Paris. eds. A. Atkinson and F. Bourguignon. Amsterdam: Elsevier.

don: Duckworth. ———. 2009. Pineda, J., and F. Rodríguez. 2006.

“LMF5: Gender Pay Gaps for Full-Time Workers and “The Political Economy of Invest-

Narayan, D. 2005. Measuring Empowerment: Cross-Disciplinary Per- Earnings Differentials by Educational Attainment.” Paris. www. ment in Human Capital.” Economics of Governance 7(2): 167–93.

spectives. Washington, DC: World Bank. oecd.org/dataoecd/29/63/38752746.pdf. Accessed 25 April 2010. ———. 2010. “Curse or Blessing? Natural Resources and Human

Narayan, D., R. Chambers, M. Kaul Shah, and P. Petesch. 1999. ———. 2010. “Measuring the Progress of Societies.” Paris. www. Development.” Human Development Research Paper 4. UNDP–

Voices of the Poor: Global Synthesis. Washington, DC: World Bank. o e c d .o r g /p a g e s / 0, 3 417, e n _4 0 033 426 _4 0 033 82 8 _ HDRO, New York.

1_1_1_1_1,00.html. Accessed 15 August 2010.

Narayan, D., R. Patel, K. Schafft, A. Rademacher, and S. Koch- Pinkovskiy, M., and X. Sala-i-Martin. 2009. Parametric Estimations

Schulte. 2000. OECD/DAC (Organisation for Economic Co-operation and Develop-

Voices of the Poor: Can Anyone Hear Us? Oxford, UK: of the World Distribution of Income. NBER Working Paper 15433.

ment Development Assistance Committee). 2010a.

Oxford University Press. “Creditor Cambridge, MA: National Bureau of Economic Research.

Reporting System Database.” www.oecd.org/dac/stats/idsonline.

Narayan, D., and P. Petesch. 2007. ———. 2010.

Moving Out of Poverty: Cross- African Poverty is Falling­…Much Faster Than You

Accessed 15 May 2010.

Disciplinary Perspectives on Mobility. Washington, DC: World Bank. Think! NBER Working Paper 15775. Cambridge, MA: National

———. 2010b. “Development Aid Rose in 2009 and Most Donors Bureau of Economic Research.

Narayana, D. 2008. “Intensifying Infant Mortality Inequality in India Will Meet 2010 Aid Targets.” Newsroom. 14 April. www.oecd.org/ Pirttilä, J., and R. Uusitalo. 2010.

and a Reversal by Policy Intervention.” Journal of Human Develop- “A ‘Leaky Bucket’ in the Real World:

document/11/0,3343,en_21571361_44315115_44981579

ment and Capabilities 9(2): 265–81. Estimating Inequality Aversion Using Survey Data.” Economica

_1_1_1_1,00.html. Accessed 24 June 2010. 77(305): 60–76.

Nath, S., K. Sylva, and J. Grimes. 1997. “Raising Basic Education Oeppen, J., and J.W. Vaupel. 2002. “Broken Limits to Life Expec- PNUD Argentina (Programa de las Naciones Unidas para el Desar-

Levels for the Children of Rural Bangladesh: The Impact of a Non- tancy.” Science 296(5570): 1029–32. rollo). 2002.

Formal Education Programme.” International Review of Education Aportes para el Desarrollo Humano de la Argentina

Olavarria-Gambi, M. 2003.

45(1): 5–26. “Poverty Reduction in Chile: Has Eco- 2002: Un Enfoque Integral. Buenos Aires.

nomic Growth Been Enough?” Journal of Human Development and

Nattrass, N., and J. Seekings. 2001. PNUD Mexico (Programa de las Naciones Unidas para el Desar-

“Democracy and Distribution in Capabilities 4(1): 103–23. rollo). 2003.

Highly Unequal Economies: The Case of South Africa.” Journal of Informe Sobre Desarrollo Humano México 2002. Mex-

Olshansky, S., D. Passaro, R. Hershow, J. Layden, B. Carnes, J.

Modern African Studies 39(3): 471–98. ico City: Mundi-Prensa México.

Brody, L. Hayfick, R. Butler, D. Allison, and D. Ludwig. 2005.

Nayyar, D. 2008. PNUD Tunisie (Le Programme des Nations Unies pour le dével-

“Learning to Unlearn from Development.” Oxford “A Potential Decline in Life Expectancy in the United States in the oppement). 2001.

Development Studies 36(3): 259–80. Rapport sur le Developpement Humain en

21st Century.” New England Journal of Medicine 352(11): 1138–45. Tunisie. Tunis.

Nelson, G., M. Rosegrant, J. Koo, R. Robertson, T. Sulser, T. Zhu, Oman Ministry of National Economy. 2003. Oman Human Develop-

C. Ringler, S. Msangi, A. Palazzo, M. Batka, M. Magalhaes, R. Pogge, T. 2009. Developing Morally Plausible Indices of Poverty and

ment Report 2003. Muscat.

Valmonte-Santos, M. Ewing, and D. Lee. 2009. Climate Change: Gender Equity: A Research Program. New York: New York University

Osmani, S. R. 2005.

Impact on Agriculture and Costs of Adaptation. Washington, DC: “Poverty and Human Rights: Building on the Institute for Public Knowledge.

International Food Policy Research Institute. Capability Approach.” Journal of Human Development and Capabili- Polanyi, K. 2002. “The Great Transformation.” In Readings in Economic

ties 6(2): 205–19.

Nelson, J., and D. Prescott. 2008. Business and the Millennium Devel- Sociology, ed. N. W. Biggart. Oxford, UK: Blackwell Publishers Ltd.

Osmani, S. R., and A. Sen. 2003.

opment Goals: A Framework for Action, 2nd edition. New York: “The Hidden Penalties of Gender Prahalad, C. K. 2004. The Fortune at the Bottom of the Pyramid. Upper

United Nations Development Programme and International Busi- Inequality: Fetal Origins of Ill-Health.” Economics and Human Biol- Saddle River, NJ: Wharton School Publishing.

ness Leaders Forum. ogy 1(1): 105–21. Prasad, N. 2008. “Policies for Redistribution: The Use of Taxes and

Neumayer, E. 2010a. Ostrom, E. 1996.

“Human Development and Sustainability.” “Crossing the Great Divide: Coproduction, Synergy, Social Transfers.” ILO Discussion Paper DP/194/2008. International

Human Development Research Paper 5. UNDP–HDRO, New York. and Development.” World Development 24(6): 1073–87. Labour Office, Geneva.

———. 2010b. Ottoson, D. 2009.

Weak Versus Strong Sustainability. Exploring the State-Sponsored Homophobia: A World Survey of Preston, S. H. 1975. “The Changing Relation Between Mortality

Limits of Two Opposing Paradigms, 3rd edition. Northampton, UK: Laws Prohibiting Same Sex Activity Bewteen Consenting Adults. and Level of Economic Development.” Population Studies 29(2):

Edward Elgar Publishing Ltd. Brussels: International Lesbian, Gay, Bisexual, Trans and Intersex 231–48.

Association.

Nielson, H. D. 2009. Moving Towards Free Primary Education: Policy Pritchett, L. 1997. “Divergence, Big Time.” The Journal of Economic

Oxfam International. 2007.

Issues and Implementation Challenges. New York: United Nations “Africa’s Missing Billions: International Perspectives 11(3): 3–17.

Children’s Fund and World Bank. Arms Flows and the Cost of Conflict.” Briefing Paper 107. Oxford, UK. ———. 2002. When Will They Ever Learn? Why All Governments Pro-

NOIA (National Ocean Industries Association). 2006. Pagliani, P. 2010.

“Oil in the “Influence of Regional, National, and Sub-national duce Schooling. Cambridge, MA: Harvard Kennedy School of Gov-

Sea III: Inputs, Fates and Effects.” Washington, DC. www.noia.org/ HDRs.” Human Development Research Paper 19. UNDP–HDRO, ernment and Center for Global Development.

website/article.asp?id=129. Accessed 18 June 2010. New York. ———. 2006. “Does Learning to Add up Add up? The Returns to

Nussbaum, M. 2000. Panagariya, A. 2008.

Women and Human Development: The Capabili- India: the Emerging Giant. Oxford, UK: Oxford Schooling in Aggregate Data.” In Handbook of the Economics of

ties Approach. Cambridge, UK: Cambridge University Press. University Press. Education, eds. E. A. Hanushek and F. Welch. Amsterdam: Elsevier. 131

References

———. 2010. Reinhart, C. M., and K. Rogoff. 2009. Schor, J. B. 1992.

“Birth Satisfaction Units (BSU): Measuring Cross- This Time is Different. Eight Hun- The Overworked American: The Unexpected Decline of

National Differences in Human Well-Being.” Human Development dred Years of Financial Folly. Princeton, NJ: Princeton University Press. Leisure. New York: Basic Books.

Research Paper 3. UNDP–HDRO, New York. Reporters Without Borders. 2009. Schultz, G. F. 1993.

“Press Freedom Index.” http:// “Socioeconomic Advantage and Achievement

Pritchett, L., and R. Murgai. 2007. “Teacher Compensation: Can en.rsf.org/press-freedom-index-2009,1001.html. Accessed 15 Motivation: Important Mediators of Academic Performance in

Decentralization to Local Bodies Take India from Perfect Storm April 2010. Minority Children in Urban Schools.” The Urban Review 25(3):

Through Troubled Waters to Clear Sailing?” In India Policy Forum 221–32.

Richardson, H. S. 2006. Democratic Autonomy: Public Reasoning about

2006–07, eds. S. Bery, B. P. Bosworth, and A. Panagariya. New Sen, A. 1983.

the Ends of Policy. Oxford, UK: Oxford University Press. Poverty and Famines: An Essay on Entitlement and Depri-

Dehli and Washington, DC: National Council of Applied Economic vation. New York: Oxford University Press.

Ridde, V., and A. Diarra. 2009.

Research and Brookings Institution. “A Process Evaluation of User Fees ———. 1985a.

Abolition for Pregnant Women and Children under Five in Two Commodities and Capabilities. Amsterdam: Elsevier.

Pritchett, L., and L. Summers. 1996. “Wealthier is Healthier.” Journal Districts in Niger (West Africa).” BioMed Central Health Services ———. 1985b.

of Human Resources 31(4): 841–68. “Well-Being, Agency and Freedom: The Dewey Lec-

Research 9(89). tures 1984.” The Journal of Philosophy 82(4): 169–221.

Pritchett, L., and M. Viarengo. 2010. “Explaining the Cross-National Riley, J. C. 2001. Rising Life Expectancy: A Global History. Cambridge, ———. 1999.

and Time Series Variation in Life Expectancy: Income, Women’s Development as Freedom. Oxford, UK: Oxford Univer-

UK: Cambridge University Press.

Education, Shifts, and What Else?” Human Development Research sity Press.

———. 2005.

Paper 31. UNDP–HDRO, New York. Poverty and Life Expectancy. Cambridge, UK: Cam- ———. 2002. Rationality and Freedom. Cambridge, MA: Harvard

bridge University Press.

Pritchett, L., M. Woolcock, and M. Andrews. 2010. “Capability University Press.

Risse, M. 2009.

Traps? The Mechanisms of Persistent Implementation Failure.” “Immigration, Ethics and the Capabilities Approach.” ———. 2003. “Missing Women Revisited.” British Medical Journal

World Development Report Working Paper 11. World Bank, Wash- Human Development Research Paper 2009/34. UNDP–HDRO, New 327(7427): 1297–98.

ington, DC. York. ———. 2004. “Elements of a Theory of Human Rights.” Philosophy

Przeworski, A. 2004. Robalino, D., M. Vodopivec, and A. Bodor. 2009.

“Democracy and Economic Development.” In “Savings for Unem- and Public Affairs 32(4): 315–56.

The Evolution of Political Knowledge, eds. E. Mansfield and R. Sisson. ployment in Good and Bad Times: Options for Developing Coun- ———. 2005.

Columbus, OH: Ohio State University Press. tries.” IZA Discussion Paper 4516. World Bank and Institute for the “Human Rights and Capabilities.” Journal of Human

Study of Law, Washington, DC. Development and Capabilities 6(2): 151–166.

Przeworski, A., M. Alvarez, J. A. Cheibub, and F. Limongi. 2000. Robeyns, I. 2003. ———. 2009a.

Democracy and Development: Political Institutions and Well-Being in “Sen’s Capability Approach and Gender Inequality: “Foreword.” In Handbook of Human Development,

the World, 1950–1990. Cambridge, UK: Cambridge University Press. Selecting Relevant Capabilities.” Feminist Economics 9(2–3): 61–92. eds. S. Fukuda-Parr and A. K. Shiva Kumar. New Delhi: Oxford Uni-

versity Press.

Qian, Y. 2003. Rodríguez, F. 2006.

“How Reform Worked in China.” In In Search of Prosper- “The Anarchy of Numbers: Understanding the ———. 2009b.

ity, ed. D. Rodrik. Princeton, NJ: Princeton University Press. Evidence on Venezuelan Economic Growth.” Canadian Journal of The Idea of Justice. London: Penguin.

Development Studies 27(4): 503–29.

Rajan, R., and A. Subramanian. 2008. Sen, G., A. Iyer, and C. Mukherjee. 2009.

“Aid and Growth: What Does “A Methodology to Analyse

———. 2007.

the Cross-Country Evidence Really Show?” The Review of Economics “Cleaning Up the Kitchen Sink: Growth Empirics When the Intersections of Social Inequalities in Health.” Journal of Human

and Statistics 90(4): 643–65. the World is Not Simple.” Working Paper. Wesleyan University, Development and Capabilities 10(3): 397–415.

Middletown, CT.

Rajan, R., and L. Zingales. 2003. Seneviratne, K. 1999.

Saving Capitalism from the Capital- “Has Asia Succumbed to Western Agenda?” The

Rodrik, D. 1998.

ists: Unleashing the Power of Financial Markets to Create Wealth and “Why Do More Open Economies have Bigger Govern- Straits Times. October 26.

Spread Opportunity. Princeton, NJ: Princeton University Press. ments?” Journal of Political Economy 106(5): 997–1032. Seth, S. 2009. “Inequality, Interactions, and Human Development.”

Rajaratnam, J., J. Marcus, A. Fraxman, H. Wang, A. Levin-Rector, ———. (Ed.) 2003. In Search of Prosperity: Analytic Narratives on Eco- Journal of Human Development and Capabilities 10(3): 375–96.

L. Dwyer, M. Costa, A. Lopez, and C. Murray. 2010. “Neonatal, nomic Growth. Princeton, NJ: Princeton University Press. Shiva Kumar, A. K. 2007. “Why Are Levels of Child Malnutrition High?”

Postneonatal, Childhood, and Under-5 Mortality for 187 Countries, ———. 2006. “Goodbye Washington Consensus, Hello Washington The Hindu. June 22.

1970–2010: A Systematic Analysis of Progress Towards Millennium Confusion? A Review of the World Bank’s Economic Growth in the Shryock, H., and J. Siegel. 1980.

Development Goal 4.” The Lancet 375(9730): 1988–2008. The Methods and Materials of

1990s: Learning from a Decade of Reform.” Journal of Economic Lit- Demography. Washington, DC: U.S. Government Printing Office.

Ranis, G., and F. Stewart. 2000. “Strategies for Success in Human erature 44(4): 973–87. SIPRI (Stockholm International Peace Research Institute). 2010a.

Development.” Journal of Human Development 1(1): 49–70. ———. 2007. One Economics, Many Recipes: Globalizations, Institu- Correspondence on Arms Transfers. Stockholm.

———. 2010. “Success and Failure in Human Development, 1970– tions, and Economic Growth. Princeton, NJ: Princeton University ———. 2010b.

2007.” Human Development Research Paper 10. UNDP–HDRO, New Press. Correspondence on Military Expenditure. Stockholm.

York. Rodrik, D., and R. Hausmann. 2003. Sirimanne, S. 2009.

“Economic Development as Self- Emerging Issue: The Gender Perspectives of the

Ranis, G., F. Stewart, and A. Ramirez. 2000. “Economic Growth and Discovery.” Journal of Development Economics 72(2): 603–33. Financial Crisis. New York: Commission on the Status of Women.

Human Development.” World Development 28(2): 197–220. Roemer, J. E. 1998. Skoufias, E. 2003.

Equality of Opportunity. Cambridge, MA: Harvard “Economic Crisis and Natural Disasters: Coping

Ranis, G., F. Stewart, and E. Samman. 2006. “Human Development: University Press. Strategies and Policy Implications.” World Development 31(7):

Beyond the Human Development Index.” Journal of Human Devel- 1087–1102.

Rowbottom, S. 2007. Giving Girls Today and Tomorrow: Breaking the

opment 7(3): 323–58. Soares, R. R. 2007.

Cycle of Adolescent Pregnancy. New York: United Nations Popula- “On the Determinants of Mortality Reductions in

Ravallion, M. 1996. “How Well Can Method Substitute for Data? tion Fund. the Developing World.” Population and Development Review 33(2):

Five Experiments in Poverty Analysis.” The World Bank Research 247–87.

Royston, P., and D. G. Altman. 1994. “Regression Using Fractional

Observer 11(2): 199–221. Southgate, D. 1990.

Polynomials of Continuous Covariates: Parsimonious Parametric “The Causes of Land Degradation along Sponta-

Rawls, J. 1971. A Theory of Justice. Cambridge, MA: Harvard University Modelling.” Applied Statistics 43(3): 429–67. neously Expanding Agricultural Frontiers in the Third World.” Land

Press. Economics 66(1): 93–101.

Sachs, J. D., J. W. McArthur, G. Schmidt-Traub, M. Kruk, C. Baha-

Raworth, K., and D. Stewart. 2002. dur, M. Faye, and G. McCord. 2004. Srinivasan, T. N. 1994.

“Critiques of the Human Devel- “Ending Africa’s Poverty “Human Development: A New Paradigm or

opment Index: A Review.” In Readings in Human Development, Trap.” Brookings Papers on Economic Activity 35(1): 217–30. Reinvention of the Wheel?” The American Economic Review 84(2):

Concepts, Measures and Policies for a Development Paradigm, eds. 238–43.

Salehi-Isfahani, D. 2010. “Human Development in the Middle East

S. Fukuda-Parr and A. K. Shiva Kumar. New York: Oxford Univer- Staines, N. 2004.

and North Africa.” Human Development Research Paper 26. UNDP– “Economic Performance Over the Conflict Cycle.” IMF

sity Press. HDRO, New York. Working Paper 95. International Monetary Fund, Washington, DC.

132 human development report 2010

Stasavage, D. 2005. Tsai, M. 2006.

“Democracy and Education Spending in Africa.” “Does Political Democracy Enhance Human Develop- New York. www.un.org/womenwatch/daw/beijing15/. Accessed

American Journal of Political Science 49(2): 343–58. ment in Developing Countries? A Cross-National Analysis.” Ameri- 7 June 2010.

can Journal of Economics and Sociology 65(2): 233–68.

Stern, N. 2006. UNDP (United Nations Development Programme). 1998.

The Economics of Climate Change: The Stern Review. Human

Twaweza. 2010.

Cambridge, MA: Cambridge University Press. “Twaweza: Ni Sisi [We Can Make It Happen: It’s Us].” Development Report Zimbabwe. New York.

Dar es Salaam. twaweza.org/. Accessed 7 June 2010.

Stevenson, B., and J. Wolfers. 2008. ———. 2003.

“Economic Growth and Sub- Avoiding the Dependency Trap. New York.

UCDP and PRIO (Uppsala Conflict Data Program and International

jective Well-Being: Reassessing the Easterlin Paradox.” Brookings ———. 2008. “Post-Conflict Economic Recovery: Enabling Local

Peace Research Institute). 2009.

Papers on Economic Activity 1: 1–87. “UCDP/PRIO Armed Conflict Ingenuity.” Crisis Prevention and Recovery Report 2008. New York:

Dataset.” Centre for the Study of Civil War, Oslo. www.prio.no/

Stewart, F. 2009. “Horizontal Inequality: Two Types of Trap.” Journal of Bureau of Crisis Prevention and Recovery.

CSCW/Datasets/Armed-Conflict/UCDP-PRIO/. Accessed 7 June

Human Development and Capabilities 10(3): 315–40. ———. 2009.

2010. Arab Human Development Report 2009: Challenges to

———. 2010. “Power and Progress: The Swing of the Pendulum.” Human Security in Arab Countries. New York: Regional Bureau for

UIA (Union of International Associations). 2010. “UIA Databases.”

Journal of Human Development and Capabilities 11(3): 371–95. Arab States.

www.uia.be/. Accessed 7 June 2010.

Stewart, F., G. Brown, and L. Mancini. 2005. ———. 2010.

“Why Horizontal What Will It Take to Achieve the Millennium Develop-

ul Haq, M. 1973. “System is to Blame for the 22 Wealthy Families.” The

Inequalities Matter: Some Implications for Measurement.” CRISE ment Goals?–An International Assessment. New York.

London Times. March 22.

Working Paper 19. Centre for Research on Inequality, Human Secu- UNDP (United Nations Development Programme) Armenia. 2007.

———. 1995.

rity and Ethnicity, Oxford, UK. Reflections on Human Development. New York: Oxford National Human Development Report 2006: Educational Transfor-

University Press.

Stewart, K. 2010. “Human Development in Europe.” Human Develop- mations in Armenia. Yerevan.

UN (United Nations). 2000.

ment Research Paper 7. UNDP–HDRO, New York. “We Can End Poverty 2015: Millennium UNDP (United Nations Development Programme) China and

Development Goals.” New York. www.un.org/millenniumgoals/.

Stiglitz, J. E. and Members of the UN Commission of Financial China Institute for Reform and Development. 2008. Human

Accessed 20 November 2009.

Experts. 2010. The Stiglitz Report: Reforming the International Development Report China 2007/08: Access for All: Basic Public Ser-

———. 2009.

Monetary and Financial Systems in the Wake of the Global Crisis. New The Millennium Development Goals Report 2009. New vices for 1.3 Billion People. Beijing: China Translation and Publishing

York: The New Press. York: United Nations. Corporation.

Stiglitz, J. E., A. Sen, and J. Fitoussi. 2009. ———. 2010a. UNDP (United Nations Development Programme) China and

“Report by the Commis- “Human Security Report of the Secretary-General.” Renmin University of China. 2010.

sion on the Measurement of Economic Performance and Social Sixty-fourth Session, Agenda Items 48 and 114, A/64/701. UN Gen- China Human Development

Progress.” Commission on the Measurement of Economic Perfor- eral Assembly, New York. Report 2009/10: China and a Sustainable Future: Towards a Low Car-

mance and Social Progress, Paris. bon Economy and Society. Beijing: China Translation & Publishing

———. 2010b. “Progress to Date and Remaining Gaps in the Imple- Corporation.

1990.

The Straits Times. “S’pore trails Hong Kong and Seoul in Human mentation of the Outcomes of the Major Summits in the Area of UNDP (United Nations Development Programme) Evaluation

Resources Development.” The Straits Times. May 29. Sustainable Development and Analysis of the Themes for the Con- Office. 2009.

ference.” Item of the Provisional Agenda, A/CONF.216/PC/2. UN Assessment of Development Results: Evaluation of

Strauss, J., and D. Thomas. 1998. “Health, Nutrition, and Economic General Assembly, New York. UNDP Contribution—Peru. New York.

Development.” Journal of Economic Literature 36(2): 766–817. UN Statistics Division (United Nations Statistics Division). 2010. UNDP (United Nations Development Programme) Nepal. 2002.

———. 2008. “Health Over the Life Course.” In Handbook of Develop- United Nations Commodity Trade Statistics Database—UN Nepal Human Development Report 2001: Poverty Reducation and

ment Economics, 4th edition, eds. T. Schultz and J. Strauss. Amster- Comtrade. New York. comtrade.un.org/db/dqBasicQuery.aspx. Goverance. Kathmandu.

dam: Elsevier. Accessed 3 August 2010. ———. 2004. Nepal Human Development Report 2004: Empower-

Stuckler, D., S. Basu, and M. McKee. 2010. “Drivers of Inequality in UNAIDS (Joint United Nations Programme on HIV/AIDS). 2008. ment and Poverty Reduction. Kathmandu.

Millennium Development Goal Progress: A Statistical Analysis.” Report on the Global AIDS Epidemic. Geneva. ———. 2009.

PLoS Medicine 7(3). Nepal Human Development Report 2009: State Trans-

UNDESA (United Nations Department of Economic and Social formation and Human Development. Kathmandu.

Subramanian, A., and R. Devesh. 2003. “Who Can Explain the Mau- Affairs). 2004. World Youth Report 2003: The Global Situation of UNDP (United Nations Development Programme) Zambia. 1997.

ritian Miracle: Meade, Romer, Sachs, or Rodrik?” In In Search of Young People. New York.

Prosperity: Analytic Narratives on Economic Growth, ed. D. Rodrik. Zambia Human Development Report 1997: Poverty. Lusaka.

———. 2006.

Princeton, NJ: Princeton University Press. World Economic and Social Survey 2006: Diverging UNDP (United Nations Development Programme)–Human Devel-

Growth and Development. New York.

Tajbakhsh, S., and A. M. Chenoy. 2007. opment Report Office. 1990–2009.

Human Security: Concepts and Human Development Reports

———. 2009a.

Implications. New York: Routledge. “Population Ageing and Development 2009.” 1990–2009. New York: Oxford University Press through 2005; and

New York. www.un.org/esa/population/publications/ageing/ Palgrave Macmillan since 2006.

Tansel, A. 2002. “Determinants of School Attainment of Boys and Girls ageing2009.htm. Accessed 19 May 2010. UNEP-WCMC (United Nations Environment Programme–World

in Turkey: Individual, Household and Community Factors.” Econom- ———. 2009b. Conservation Monitoring Centre). 2006.

ics of Education Review 21(5): 455–70. “Rethinking Poverty.” Report on the World Social World Database on

Situation. New York. Protected Areas. Cambridge, UK: United Nations Environmental

Tanzi, V., and L. Schuknecht. 2000. Public Spending in the 20th Century: Programme.

———. 2009c.

A Global Perspective. Cambridge, UK: Cambridge University Press. “World Fertility Patterns 2009.” New York. www. UNESCO (United Nations Educational, Scientific and Cultural

un.org/esa/population/publications/worldfertility2009/

Tavares, J., and R. Wacziarg. 2001. “How Democracy Affects Organization). 2004.

worldfertility2009.htm. Accessed 7 June 2010. EFA Global Monitoring Report 2005: Educa-

Growth.” European Economic Review 45(8): 1341–78. tion For All: The Quality Imperative. Paris.

———. 2009d. World Population Prospects: The 2008 Revision. New

Thede, N. 2009. “Decentralization, Democracy and Human Rights: A ———. 2006.

York. Teachers and Education Quality: Monitoring Global

Human Rights-Based Analysis of the Impact of Local Democratic Needs for 2015. Montreal, Canada: Institute for Statistics.

———. 2010.

Reforms on Development.” Journal of Human Development and “World Urbanization Prospects: The 2009 Revision ———. 2009.

Capabilities 10(1): 103–23. Population Database.” New York. esa.un.org/wup2009/unup/. EFA Global Monitoring Report 2009: Overcoming

Accessed 25 June 2010. Inequality: Why Governance Matters. Paris.

Thomas, V., Y. Wang, and X. Fan. 2001. “Measuring Education UNDESA-DAW-CSW (United Nations Department of Economic ———. 2010.

Inequality: Gini Coefficients of Education.” Policy Research Working EFA Global Monitoring Report 2010: Reaching the Mar-

and Social Affairs, Division for the Advancement of Women,

Paper 2525. World Bank, Washington, DC. ginalized. Paris.

Commission on the Status of Women. 2010. “Review of the

Treisman, D. 2010. UNESCO (United Nations Educational, Scientific and Cul-

“Death and Prices: The Political Economy of Rus- Implementation of the Beijing Declaration and Plan for Action.” tural Organization) Institute for Statistics. 2009.

sia’s Alcohol Crisis.” Economics of Transition 18(2): 281–331. “Global 133

References

Vollmer, S., and M. Ziegler. 2009. Wolf, S. 2007.

Education Digest 2008.” New York. www.uis.unesco.org/ev_ “Political Insitutions and Human “Does Aid Improve Public Service Delivery?” Review of

en.php?ID=7660_201&ID2=DO_TOPIC. Accessed 7 June 2010. Development: Does Democracy Fulfill its ‘Constructive’ and ‘Instru- World Economics 143(4): 650–72.

mental’ Role?” Policy Research Working Paper 4818. World Bank,

———. 2010a. Wolfers, J. 2009.

Correspondence on Education Indicators. Montreal, “What Does the Human Development Index Mea-

Washington, DC.

Canada. sure?.” The New York Times. 22 May.

von Braun, J., and U. Grote. 2000. “Does Decentralization Serve the

———. 2010b. Wood, M., J. Hales, S. Purdon, T. Sejersen, and O. Hayllar. 2009.

“UNESCO Institute for Statistics Data Site.” New York. Poor?” International Monetary Fund Conference on Fiscal Decen-

http://stats.uis.unesco.org/unesco. Accessed May 2010. “A Test for Racial Discrimination in Recruitment Practices in British

tralization, Washington, DC. Cities.” DWP Research Report 607. Government of the United King-

Unger, R. M. 1998. Democracy Realized: The Progressive Alternative. Vroman, W., and V. Brsusentsev. 2009. “Unemployment Compensa- dom, Department of Work and Pensions, London.

London: Verso. tion in a Worldwide Recession.” Urban Institute and University of Wooldridge, J. 2002. Econometric Analysis of Cross Section and Panel

UNHCR (United Nations High Commissioner for Refugees). 1997. Delaware, Washington, DC, and Dover, DE. Data. Cambridge, MA: MIT Press.

The State of the World’s Refugees 1997: A Humanitarian Agenda. Wade, R. 1992. “East Asia’s Economic Success: Conflicting Perspec- World Bank. 2000.

Geneva. World Development Report 2000/2001: Attacking

tives, Partial Insights, Shaky Evidence.” World Politics 44(2): Poverty. New York: Oxford University Press.

———. 2010. Correspondence on Refugees. Geneva. 270–320. ———. 2005a. Economic Growth in the 1990s: Learning from a

UNICEF (United Nations Children’s Fund). 2000–2008. Walker, S., S. Chang, C. Powell, E. Simonoff, and S. Grantham-

Multiple Decade of Reform. Washington, DC.

McGregor. 2007.

Indicators Cluster Surveys. New York. “Early Childhood Stunting is Associated with ———. 2005b.

Poor Psychological Functioning in Late Adolescence and Effects are World Development Report: Equity and Development.

———. 2008. Progress for Children: A Report Card on Maternal Mor- Reduced by Psychosocial Stimulation.” Journal of Nutrition 137(2): Washington, DC.

tality. New York. 2464–69. ———. 2009a. Burkina Faso Population Growth, Competitiveness and

———. 2010a. “Protecting Salaries of Frontline Teachers and Health Walton, M. 2010. “Capitalism, the State, and the Underlying Drivers Diversification: Country Economic Memorandum. Washington, DC.

Workers.” Social and Economic Policy Working Briefs. New York. of Human Development.” Human Development Research Paper 9. ———. 2009b. “Financial Crisis Highlights Need for More Social

———. 2010b. Recovery with a Human Face: A Coordinated Strategy UNDP–HDRO, New York. Safety Nets, Including Conditional Cash Transfers.” Press release, 10

of Policy Advocacy and Partnerships for Children in Response to the Watson, D., and L. Yohannes. 2005. “Capacity Building for Decentral- February. World Bank. Washington, DC.

Global Financial Crisis and Economic Slowdown. New York. ised Education Service Delivery in Ethiopia: A Case Study Prepared ———. 2009c. Global Monitoring Report 2009: A Development Emer-

———. 2010c. The State of the World’s Children. New York. for the Project ‘Capacity, Change and Performance.’” Discussion gency. Washington, DC.

Paper 57H. European Centre for Development Policy Management,

UNIFEM (United Nations Development Fund for Women). 2010. ———. 2009d.

“Who Answers to Women? Gender and Accountability.” Progress of Acquisition. Timor-Leste.

Watson, P. 1995.

the World’s Women 2008/2009. New York. “Explaining Rising Mortality Among Men in Eastern ———. 2010a.

Europe.” Social Science and Medicine 41(7): 923–34. Environmental Economics and Indicators: Green

United States Census Bureau. 2008. “U.S. Income Statistics.” www. Accounting. Washington, DC.

WCED (World Commission on Environment and Development).

census.gov/hhes/www/income/data/statistics/index.html. 1987. ———. 2010b.

Accessed 27 July 2010. Our Common Future. WCED Report. Oxford, UK: Oxford Uni- “Global Economic Prospects—Summer 2010.”

versity Press. Washington, DC. www.worldbank.org. Accessed 15 July 2010.

UNODC (United Nations Office on Drugs and Crime). 2010. “UNODC Whitehead, L. 2002. ———. 2010c.

Homicide Statistics.” Vienna. www.unodc.org/unodc/en/data Democratization: Theory and Experience. Oxford, International Income Distribution Database. Wash-

-and-analysis/homicide.html. Accessed 15 May 2010. UK: Oxford University Press. ington, DC.

UNRISD (United Nations Research Institute for Social Devel- The White House. 2010. ———. 2010d.

“Health Care.” Washington, DC. www. “Poverty Reduction Supports Credits: An Evaluation

opment). 2010. “Why Care Matters for Social Development.” whitehouse.gov/issues/health-care. Accessed 12 May 2010. of World Bank Support.” IEG Study Series. Washington, DC: Inde-

Research and Policy Brief 9. Geneva. pendent Evaluation Group.

WHO (World Health Organization). 2000–2008. World Health Sur-

UNU-WIDER (United Nations University, World Institute for ———. 2010e.

veys. Geneva. State and Trends of the Carbon Market 2010. Wash-

Development Economics Research). 2008. World Income ington, DC.

———. 2005. WHO Multi-Country Study on Women’s Health and

Inequality Database, Version 2.0c, May 2008. Helsinki. www.wider. ———. 2010f.

Domestic Violence Against Women: Summary Report of Initial Results Women, Business and the Law Report: Measuring

unu.edu/research/Database/en_GB/database/. on Prevalence, Health Outcomes and Women’s Responses. Geneva. Legal Gender Parity for Entrepreneurs and Workers in 128 Economies.

van der Hoeven, R. 2010. “Employment, Inequality and Globalization: Washington, DC.

———. 2008. “Global Burden of Disease Series: 2004 Update.”

A Continuous Concern.” Journal of Human Development and Capa- ———. 2010g.

Geneva. www.who.int/healthinfo/global_burden_disease. World Development Indicators 2010. Washington, DC.

bilities 11(1): 1–9. Accessed 15 July 2010. Wrigley, E. and R. Schofield. 1989. The Population History of England,

Vaughan, S. 2003. Ethnicity and Power in Ethiopia. Edinburgh, UK: Uni- ———. 2010. “World Health Statistics 2010.” World Health Organi- 1541–1871: A Reconstruction. Cambridge, UK: Cambridge University

versity of Edinburgh. zation Statistical Information System. Geneva. www.who.int/who- Press.

Veblen, T. 2007. Theory of the Leisure Class. Oxford, UK: Oxford Uni- sis/whostat/2010/en/index.html. Accessed 29 June 2010. Yates, R. 2006. International Experiences in Removing User Fees for

versity Press. WHO and UNICEF (World Health Organization and United Nations Health Services—Implications for Mozambique. London: UK

Vitols, S. 2003. Children’s Fund). 2010.

“From Banks to Markets: The Political Economy of Lib- “Joint Monitoring Programme for Water Department for International Development, Health Resource

eralization of the German and Japanese Financial Systems.” In The Supply and Sanitation.” Geneva. www.wssinfo.org/. Accessed 15 Centre.

End of Diversity? Prospects for German and Japanese Capitalism, eds. July 2010. Zaridze, D., D. Maximovitch, A. Lazarev, V. Igitov, A. Boroda, J.

K. Yamamura and W. Streeck. Ithaca, NY: Cornell University Press. Williamson, J. 1989. Boreham, P. Boyle, R. Peto, and P. Boffetta. 2009.

“What Washington Means by Policy Reform.” “Alcohol Poi-

Vizard, P. 2006. Poverty and Human Rights: Sen’s ‘Capability Perspec- In Latin American Adjustment: How Much has Happened, ed. J. soning is a Main Determinant of Recent Mortality Trends in Russia:

tive’ Explored. Oxford, UK: Oxford University Press. Williamson. Washington, DC: Peterson Institute for International Evidence from a Detailed Analysis of Mortality Statistics and Autop-

Economics. sies.” International Journal of Epidemiology 38(1): 143–53.

134 human development report 2010 Statistical Annex

Sources and definitions

The 17 statistical tables provide an assessment

of country achievements in key aspects of The HDRO is primarily a user, not a producer,

human development, including several com- of statistics. It relies on international data agen-

posite indices estimated by the Human Devel- cies with the mandate, resources and expertise

opment Report Office (HDRO) and a series to collect and compile international data on

of new indicators related to sustainability and specific indicators. Where specific data are not

empowerment. The methods underlying the

Technical available from our traditional data suppliers,

composite indices are detailed in

notes 1–4; data from other credible sources are used.

key aspects of other indicators are Sources for all data used in compiling the

detailed below. statistical tables are given at the end of each

The tables include data for as many of the References.

table with full references in the The

192 UN member states as possible, as well as source notes show the original data components

Hong Kong Special Administrative Region of used in calculations by the HDRO. Definitions

China and the Occupied Palestinian Territo- Definitions of

of key indicators are included in

ries. Countries and areas are ranked by their statistical terms. Other relevant information

2010 Human Development Index (HDI) value.

Key to countries appears in the notes at the end of each table. For

on the inside back cover of the more detailed technical information about the

Report lists countries alphabetically with their indicators, the relevant websites of the source

HDI ranks. Data in the tables are those avail- agencies should be consulted, links to which can

able to the HDRO as of 15 May 2010, unless be found at http://hdr.undp.org/en/statistics.

otherwise specified.

Six new statistical tables cover broad themes

of empowerment, sustainability and vulnerabil- Coverage of the Human

ity, human security, perceptions of individual Development Index

well-being, measures of civic and community

well-being, and decent work. Two tables reflect Data availability determines HDI country cov-

the enabling environment for improved human erage. To enable cross-country comparisons, the

well-being in terms of financial flows and in HDI is, to the extent possible, calculated based

terms of economy and infrastructure. on data from leading international data agencies

All the indicators are available online in sev- and other credible data sources available at the

eral formats: individually, in predefined tables time of writing. However, for a number of coun-

and via a query tool that allows users to design tries data are missing from these agencies for

their own tables. Interactive media, including one or more of the four HDI component indi-

maps of all the human development indices and cators. Where reliable data are unavailable and

selected animations, are available. There are also there is significant uncertainty about the valid-

more descriptive materials such as country fact- ity of data estimates, countries are excluded to

sheets as well as further technical details on HDR

ensure the credibility of the HDI and the

how to calculate the indices. These materials family of indices (see box 1).

are available in English (http://hdr.undp.org/ The HDI in 2010 can be calculated for 169

en/statistics), French (http://hdr.undp.org/fr/ countries (168 UN member countries plus Hong

statistiques) and Spanish (http://hdr.undp.org/ Kong Special Administrative Region of China).

## STATISTICAL ANNEX

Micronesia has entered the HDI table for the International data agencies continually

first time this year, and Zimbabwe has reentered. improve their data series, including periodi-

Dropping from the table this year are Antigua cally updating historical data. The year-to-year

and Barbuda, Bhutan, Cuba, Dominica, Eritrea, changes in the HDI values and rankings across

Grenada, Lebanon, Oman, Saint Kitts and editions of the Report often reflect these revi-

Nevis, Saint Lucia, Saint Vincent and the Gren- sions to data rather than real changes in a coun-

adines, Samoa, Seychelles and Vanuatu. try. In addition, occasional changes in country

coverage can affect the HDI ranking of a coun-

try. Thus, for example, a country’s HDI rank

Comparisons over time and across could drop considerably between two consecu-

editions of the Report tive Reports, but when comparable revised data

are used to reconstruct the HDI, the HDI rank

The HDI is an important tool for monitoring and value may actually show an improvement.

long-term trends in human development. To For this reason, statistical table 2 should be used

facilitate trend analyses across countries, the to see trends.

HDI is calculated at five-year intervals for the The HDI values and ranks presented in this

period 1980–2010. Presented in table 2, these Report are not comparable to estimates pub-

estimates are based on a consistent methodol- lished in earlier editions of the Report—to look

Technical note 1)

ogy (described in using the at trends over time, readers must refer to table 2.

data available at the time of writing. The HDI

values and ranks presented in this Report are Inconsistencies between national

not comparable to those published in earlier edi- and international estimates

tions. An alternative HDI measure, the hybrid

HDI, based on indicators that are available over When compiling data series, international

a longer time span, is used in chapters 2 and 3 to agencies apply international standards and

analyse long-term trends.

1

BOX Purchasing power parity conversions and the HDI: an illustration with the case of Cuba

The HDI uses internationally comparable data on gross national income (GNI) per capita from the World Bank (2010g). These data are expressed using

a conversion factor that allows comparisons of prices across countries. This conversion, known as purchasing power parity (PPP), is necessary to take

into account differences in the value of a dollar across countries.

Four countries have data on all HDI components except for GNI: Cuba, Iraq, Marshall Islands and Palau. For three of these countries (Cuba, Marshall

Islands and Palau) this is due to the fact that they do not participate in the International Comparisons Program. Iraq lacks information about GNI for

the last 10 years.

To illustrate the options and problems that arise in attempting to reliably estimate GNI per capita in PPP terms, Cuba is used as an example. One

well known approach to estimating GNI—used by the Center for International Comparisons of Production, Income and Prices at the University of

Pennsylvania (Heston, Summers and Aten 2009)—is a regression that relies on data from the salaries of international civil servants converted at the

official exchange rate. However, because the markets in which foreigners purchase goods and services tend to be separated from the rest of the

economy, these data can be a weak guide to the prices citizens face in practice. The Center for International Comparisons of Production, Income

and Prices recognizes this problem, rating its own estimate of Cuba’s GDP as a “D” (the lowest grade). An alternative estimate applies the exchange

rate used in Cuba and the PPP conversion of an economy with similar attributes, but this method goes against the principle of using a country’s

legally recognized exchange rate and prices to convert its national aggregates to an international currency. Another option is to not apply any PPP

correction factor to the official exchange rate for convertible pesos. Both of these options yield far lower estimated income than the PPP correction

does. The wide variation in income estimates arising from these different techniques indicates that no single robust method exists in the absence

of reliable data.

With the support of the United Nations, Cuba is currently revising and updating its international statistics in order to establish internationally

comparable data. We can thus be optimistic that in due time comparable GNI data will become available that will allow calculation of Cuba’s HDI.

The country’s achievements in the other dimensions of the HDI (education and health) are extensively discussed in this Report.

Source: Heston, Summers, and Aten 2009.

138 human development report 2010 Regional groupings

harmonization procedures to make national

data comparable across countries. When data This edition divides countries into two main

for a country are missing, an international groups, developed and developing, based

agency may produce an estimate if other rel- on HDI classification, and shows other key

evant information is available. In some cases groupings, such as Least Developed Coun-

international data series may not incorporate tries, as defined by the United Nations.

the most recent national data. All these fac- Countries in the top quartile of the distri-

tors can lead to substantial differences between bution, those with very high HDI, are clas-

national and international estimates. sified as developed, and the rest as developing.

When data inconsistencies have arisen, the The developed group is further classified into

HDRO has helped bring national and interna- Organisation for Economic Co-operation and

tional data authorities together to address them. Development (OECD) members and non-

In many cases this has led to better statistics OECD members (which includes Monaco

becoming available. The HDRO continues to and San Marino, even though an HDI value

advocate for improving international data and is not available), while the developing group is

actively supports efforts to enhance data qual- further classified into Arab States, East Asia

ity. And it works with national agencies and and the Pacific, Europe and Central Asia,

international bodies to improve data consis- Latin America and the Caribbean, South Asia

tency through more systematic reporting and and Sub-Saharan Africa, following UNDP

Country

monitoring of data quality. Regional Bureau classifications (see

groupings).

Country groupings and aggregates Country notes

In addition to country-level data, several aggre-

gates are shown in the tables. These are gener- Data for China do not include Hong Kong Spe-

ally weighted averages that are calculated for the cial Administrative Region of China, Macao

country groupings described below. In general, Special Administrative Region of China or Tai-

an aggregate is shown for a country grouping wan Province of China, unless otherwise noted.

only when data are available for at least half the Data for Sudan are often based on information

countries and represent at least two-thirds of collected from the northern part of the country

the available weight in that classification. The only.

HDRO does not impute missing data for the

purpose of aggregation. Therefore, unless oth- Symbols

erwise specified, aggregates for each classifica-

tion represent only the countries for which data A dash between two years, as in 2005–2010,

are available. Occasionally aggregates are those indicates that the data presented are the most

from the original source rather than weighted recent year available in the period specified,

averages; these values are indicated with a super- unless otherwise noted. Growth rates are usu-

script “T.” ally average annual rates of growth between the

Human development classification first and last years of the period shown.

A slash between years such as 2005/2010

In the past, HDI classification was based on indicates average for the years shown, unless

preset cut-off points of HDI values. This year otherwise noted.

the classifications are based on quartiles and The following symbols are used in the tables:

denoted very high, high, medium and low .. Not available

HDI. Because there are 169 countries, one 0 or 0.0 Nil or negligible

group must have one more country than oth- — Not applicable

ers; the high HDI group was assigned the extra < Less than

country. 139

## STATISTICAL ANNEX

Primary data sources for the Mean years of schooling

Human Development Index In the absence of mean years of schooling data

from the UNESCO Institute for Statistics,

Life expectancy at birth the Report uses estimates from Barro and Lee

The life expectancy at birth estimates are from (2010) that are based on population censuses and

World Population Prospects 1950–2050: The household survey data compiled by UNESCO,

2008 Revision (UNDESA 2009d), the official Eurostat and other sources to provide bench-

source of UN population estimates and pro- marks for school attainment by gender and age

jections. They are prepared biennially by the group. They are presented in six categories: no

United Nations Department of Economic and formal education, incomplete primary, complete

Social Affairs Population Division using data primary, first cycle of secondary, second cycle

from national vital registration systems, popu- of secondary, and tertiary. Barro and Lee use

lation censuses and surveys. country-specific information about duration of

UNDESA (2009d) classifies countries schooling at each level to calculate the estimates.

where HIV prevalence among people ages Gross national income per capita

15–49 was 1 percent or higher during 1980– Data on gross national income (GNI) per capita

2007 as affected by the HIV epidemic, and their are from the World Bank’s (2010g) World Devel-

mortality is projected by modelling the course opment Indicators database. To better compare

of the epidemic and projecting the yearly inci- standards of living across countries, data must

dence of HIV infection. Also considered among be converted into purchasing power parity (PPP)

the affected countries are those where HIV terms to eliminate differences in national price

prevalence has always been lower than 1 percent levels. The GNI estimates are based on price data

and where more than 500,000 people were liv- from the latest round of the International Com-

ing with HIV in 2007 (Brazil, China, India, the parison Program (ICP), which was conducted

Russian Federation and the United States). This in 2005 and covered 146 countries and areas.

brings the number of countries considered to be For more than 20 countries not included in the

affected by HIV to 58. ICP surveys, the World Bank derives estimates

Expected years of schooling through econometric regressions, and we rely on

The Report uses data on expected years of those here where available.

schooling from the United Nations Educa-

tional, Scientific and Cultural Organization Underlying data for measures of

(UNESCO) Institute for Statistics. The esti- inequality

mates are based on enrolment by age at all levels

of education and population of official school Inequality in the underlying distributions of

age for all levels of education by age. mean years of schooling and income are esti-

Cross-country comparison of expected mated from the most recent national house-

years of schooling should be made with caution hold surveys available from international data-

because the length of the school year and the bases: Luxembourg Income Study; EU Statistics

quality of education are not the same in every on Income and Living Conditions; United

country and because the indicator does not Nations Children’s Fund Multiple Indicator

directly take into account the effects of repeti- Cluster Surveys; Measure DHS; the UN Uni-

tion (some countries have automatic promotion versity’s World Income Inequality Database;

while others do not). The coverage of different and, the World Bank’s International Income

types of continuing education and training also Distribution Database. Inequality in the distri-

varies across countries. Thus, where possible, the bution of life expectancy is estimated from life

indicator should be interpreted in the context tables produced by the United Nations Popula-

of complementary indicators, such as repetition tion Division.

rates, as well as indicators of quality.

140 human development report 2010

Human development

statistical tables

Composite measures

1 Human Development Index and its components

2 Human Development Index trends, 1980–2010

4 Gender Inequality Index

5 Multidimensional Poverty Index

Dimensions of human development

6 Empowerment

7 Sustainability and vulnerability

8 Human security

9 Perceptions of individual well-being and happiness

10 Civic and community well-being

11 Demographic trends

12 Decent work

13 Education

14 Health

Cross-cutting themes

15 Enabling environment: financial flows and commitments

16 Enabling environment: economy and infrastructure

Key to HDI countries and ranks, 2010

Afghanistan 155 Georgia 74 Nigeria 142

Albania 64 Germany 10 Norway 1

Algeria 84 Ghana 130 Pakistan 125

Andorra 30 Greece 22 Panama 54

Angola 146 Guatemala 116 Papua New Guinea 137

Argentina 46 Guinea 156 Paraguay 96

Armenia 76 Guinea-Bissau 164 Peru 63

Australia 2 Guyana 104 Philippines 97

Austria 25 Haiti 145 Poland 41

Azerbaijan 67 Honduras 106 Portugal 40

Bahamas 43 Hong Kong, China (SAR) 21 Qatar 38

Bahrain 39 Hungary 36 Romania 50

Bangladesh 129 Iceland 17 Russian Federation 65

Barbados 42 India 119 Rwanda 152

Belarus 61 Indonesia 108 São Tomé and Príncipe 127

Belgium 18 Iran, Islamic Republic of 70 Saudi Arabia 55

Belize 78 Ireland 5 Senegal 144

Benin 134 Israel 15 Serbia 60

Bolivia, Plurinational State of 95 Italy 23 Sierra Leone 158

Bosnia and Herzegovina 68 Jamaica 80 Singapore 27

Botswana 98 Japan 11 Slovakia 31

Brazil 73 Jordan 82 Slovenia 29

Brunei Darussalam 37 Kazakhstan 66 Solomon Islands 123

Bulgaria 58 Kenya 128 South Africa 110

Burkina Faso 161 Korea, Republic of 12 Spain 20

Burundi 166 Kuwait 47 Sri Lanka 91

Cambodia 124 Kyrgyzstan 109 Sudan 154

Cameroon 131 Lao People's Democratic Republic 122 Suriname 94

Canada 8 Latvia 48 Swaziland 121

Cape Verde 118 Lesotho 141 Sweden 9

Central African Republic 159 Liberia 162 Switzerland 13

Chad 163 Libyan Arab Jamahiriya 53 Syrian Arab Republic 111

Chile 45 Liechtenstein 6 Tajikistan 112

China 89 Lithuania 44 Tanzania, United Republic of 148

Colombia 79 Luxembourg 24 Thailand 92

Comoros 140 Madagascar 135 The former Yugoslav Republic of Macedonia 71

Congo 126 Malawi 153 Timor-Leste 120

Congo, Democratic Republic of the 168 Malaysia 57 Togo 139

Costa Rica 62 Maldives 107 Tonga 85

Côte d'Ivoire 149 Mali 160 Trinidad and Tobago 59

Croatia 51 Malta 33 Tunisia 81

Cyprus 35 Mauritania 136 Turkey 83

Czech Republic 28 Mauritius 72 Turkmenistan 87

Denmark 19 Mexico 56 Uganda 143

Djibouti 147 Micronesia, Federated States of 103 Ukraine 69

Dominican Republic 88 Moldova, Republic of 99 United Arab Emirates 32

Ecuador 77 Mongolia 100 United Kingdom 26

Egypt 101 Montenegro 49 United States 4

El Salvador 90 Morocco 114 Uruguay 52

Equatorial Guinea 117 Mozambique 165 Uzbekistan 102

Estonia 34 Myanmar 132 Venezuela, Bolivarian Republic of 75

Ethiopia 157 Namibia 105 Viet Nam 113

Fiji 86 Nepal 138 Yemen 133

Finland 16 Netherlands 7 Zambia 150

France 14 New Zealand 3 Zimbabwe 169

Gabon 93 Nicaragua 115

Gambia 151 Niger 167

1 Human Development Index

e

l and its components

b

ta Human Development Life expectancy Mean years Expected years Gross national income GNI per capita rank Nonincome

a

Index (HDI) value at birth of schooling of schooling (GNI) per capita minus HDI rank HDI value

HDI rank (years) (years) (years) (PPP 2008 $) b 2010 2010 2010 2010 2010 2010 2010 ## VERY HIGH HUMAN DEVELOPMENT 0.938 1 Norway 81.0 12.6 17.3 58,810 2 0.954 0.937 2 Australia 81.9 12.0 20.5 38,692 11 0.989 0.907 3 New Zealand 80.6 12.5 19.7 25,438 30 0.979 0.902 4 United States 79.6 12.4 15.7 47,094 5 0.917 0.895 5 Ireland 80.3 11.6 17.9 33,078 20 0.936 c d e,f 0.891 10.3 14.8 81,011 –5 0.861 6 Liechtenstein 79.6 0.890 7 Netherlands 80.3 11.2 16.7 40,658 4 0.911 0.888 8 Canada 81.0 11.5 16.0 38,668 6 0.913 0.885 9 Sweden 81.3 11.6 15.6 36,936 8 0.911 0.885 10 Germany 80.2 12.2 15.6 35,308 9 0.915 0.884 11 Japan 83.2 11.5 15.1 34,692 11 0.915 g 0.877 79.8 11.6 16.8 29,518 16 0.918 12 Korea, Republic of 0.874 13 Switzerland 82.2 10.3 15.5 39,849 –1 0.889 0.872 14 France 81.6 10.4 16.1 34,341 9 0.898 0.872 15 Israel 81.2 11.9 15.6 27,831 14 0.916 0.871 16 Finland 80.1 10.3 17.1 33,872 8 0.897 0.869 17 Iceland 82.1 10.4 18.2 22,917 20 0.928 0.867 18 Belgium 80.3 10.6 15.9 34,873 3 0.888 0.866 19 Denmark 78.7 10.3 16.9 36,404 –1 0.883 0.863 20 Spain 81.3 10.4 16.4 29,661 6 0.897 0.862 21 Hong Kong, China (SAR) 82.5 10.0 13.8 45,090 –11 0.860 0.855 22 Greece 79.7 10.5 16.5 27,580 8 0.890 0.854 23 Italy 81.4 9.7 16.3 29,619 4 0.882 0.852 24 Luxembourg 79.9 10.1 13.3 51,109 –18 0.836 0.851 25 Austria 80.4 9.8 15.0 37,056 –9 0.859 0.849 26 United Kingdom 79.8 9.5 15.9 35,087 –6 0.860 h 0.846 48,893 –19 0.831 27 Singapore 80.7 8.8 14.4 0.841 28 Czech Republic 76.9 12.3 15.2 22,678 10 0.886 0.828 29 Slovenia 78.8 9.0 16.7 25,857 3 0.853 c i j,k 0.824 10.4 11.5 38,056 –15 0.817 30 Andorra 80.8 0.818 31 Slovakia 75.1 11.6 14.9 21,658 12 0.854 0.815 32 United Arab Emirates 77.7 9.2 11.5 58,006 –28 0.774 l 0.815 11 0.850 33 Malta 80.0 9.9 14.4 21,004 0.812 34 Estonia 73.7 12.0 15.8 17,168 13 0.864 0.810 35 Cyprus 80.0 9.9 13.8 21,962 6 0.840 0.805 36 Hungary 73.9 11.7 15.3 17,472 10 0.851 0.805 37 Brunei Darussalam 77.4 7.5 14.0 49,915 –30 0.769 m 0.803 –36 0.737 38 Qatar 76.0 7.3 12.7 79,426 0.801 39 Bahrain 76.0 9.4 14.3 26,664 –8 0.809 0.795 15.5 22,105 0 0.815 40 Portugal 79.1 8.0 0.795 41 Poland 76.0 10.0 15.2 17,803 4 0.834 n 0.788 21,673 0 0.806 42 Barbados 77.7 9.3 13.4 HIGH HUMAN DEVELOPMENT b,o p 0.784 43 Bahamas 74.4 11.1 11.6 25,201 –9 0.788 0.783 44 Lithuania 72.1 10.9 16.0 14,824 7 0.832 0.783 45 Chile 78.8 9.7 14.5 13,561 11 0.840 0.775 46 Argentina 75.7 9.3 15.5 14,603 6 0.821 143 ## STATISTICAL ANNEX Human Development Index and its components Human Development Life expectancy Mean years Expected years Gross national income GNI per capita rank Nonincome table a Index (HDI) value at birth of schooling of schooling (GNI) per capita minus HDI rank HDI value 1 HDI rank (years) (years) (years) (PPP 2008$)

b

2010 2010 2010 2010 2010 2010 2010

0.771

47 Kuwait 77.9 6.1 12.5 55,719 –42 0.714

0.769

48 Latvia 73.0 10.4 15.4 12,944 13 0.822

b,q h

0.769 14.4 12,491 16 0.825

49 Montenegro 74.6 10.6

0.767

50 Romania 73.2 10.6 14.8 12,844 13 0.820

0.767

51 Croatia 76.7 9.0 13.8 16,389 –2 0.798

0.765

52 Uruguay 76.7 8.4 15.7 13,808 3 0.810

0.755

53 Libyan Arab Jamahiriya 74.5 7.3 16.5 17,068 –5 0.775

0.755

54 Panama 76.0 9.4 13.5 13,347 4 0.796

0.752

55 Saudi Arabia 73.3 7.8 13.5 24,726 –20 0.742

0.750

56 Mexico 76.7 8.7 13.4 13,971 –3 0.785

0.744

57 Malaysia 74.7 9.5 12.5 13,927 –3 0.775

0.743

58 Bulgaria 73.7 9.9 13.7 11,139 10 0.795

0.736

59 Trinidad and Tobago 69.9 9.2 11.4 24,233 –23 0.719

0.735

60 Serbia 74.4 9.5 13.5 10,449 11 0.788

b,q

0.732 14.6 12,926 1 0.763

61 Belarus 69.6 9.3

0.725

62 Costa Rica 79.1 8.3 11.7 10,870 7 0.768

0.723

63 Peru 73.7 9.6 13.8 8,424 14 0.788

0.719

64 Albania 76.9 10.4 11.3 7,976 19 0.787

0.719

65 Russian Federation 67.2 8.8 14.1 15,258 –15 0.729

0.714

66 Kazakhstan 65.4 10.3 15.1 10,234 6 0.756

b,o

0.713 13.0 8,747 8 0.769

67 Azerbaijan 70.8 10.2 b,q

0.710 13.0 8,222 12 0.771

68 Bosnia and Herzegovina 75.5 8.7

0.710

69 Ukraine 68.6 11.3 14.6 6,535 20 0.794

0.702

70 Iran, Islamic Republic of 71.9 7.2 14.0 11,764 –3 0.725

0.701

71 The former Yugoslav Republic of Macedonia 74.5 8.2 12.3 9,487 3 0.742

0.701

72 Mauritius 72.1 7.2 13.0 13,344 –13 0.712

0.699

73 Brazil 72.9 7.2 13.8 10,607 –3 0.728

b,q

0.698 12.6 4,902 26 0.805

74 Georgia 72.0 12.1

0.696

75 Venezuela, Bolivarian Republic of 74.2 6.2 14.2 11,846 –9 0.716

0.695

76 Armenia 74.2 10.8 11.9 5,495 19 0.787

0.695

77 Ecuador 75.4 7.6 13.3 7,931 7 0.749

0.694

78 Belize 76.9 9.2 12.4 5,693 16 0.782

0.689

79 Colombia 73.4 7.4 13.3 8,589 –3 0.732

0.688

80 Jamaica 72.3 9.6 11.7 7,207 6 0.748

0.683

81 Tunisia 74.3 6.5 14.5 7,979 1 0.729

0.681

82 Jordan 73.1 8.6 13.1 5,956 10 0.755

0.679

83 Turkey 72.2 6.5 11.8 13,359 –26 0.679

0.677

84 Algeria 72.9 7.2 12.8 8,320 –6 0.716

0.677

85 Tonga 72.1 10.4 13.7 4,038 23 0.792

MEDIUM HUMAN DEVELOPMENT 0.669

86 Fiji 69.2 11.0 13.0 4,315 21 0.771

b,o h

0.669

87 Turkmenistan 65.3 9.9 13.0 7,052 1 0.719

0.663

88 Dominican Republic 72.8 6.9 11.9 8,273 –9 0.695

0.663

89 China 73.5 7.5 11.4 7,258 –4 0.707

0.659

90 El Salvador 72.0 7.7 12.1 6,498 0 0.711

0.658

91 Sri Lanka 74.4 8.2 12.0 4,886 10 0.738

n

0.654 8,001 –11 0.683

92 Thailand 69.3 6.6 13.5

0.648

93 Gabon 61.3 7.5 12.7 12,747 –29 0.637

b,q

0.646 12.0 7,093 –7 0.681

94 Suriname 69.4 7.2

0.643

95 Bolivia, Plurinational State of 66.3 9.2 13.7 4,357 11 0.724

0.640

96 Paraguay 72.3 7.8 12.0 4,585 9 0.714

0.638

97 Philippines 72.3 8.7 11.5 4,002 12 0.726

0.633

98 Botswana 55.5 8.9 12.4 13,204 –38 0.613

0.623

99 Moldova, Republic of 68.9 9.7 12.0 3,149 19 0.729

0.622

100 Mongolia 67.3 8.3 13.5 3,619 12 0.710

0.620

101 Egypt 70.5 6.5 11.0 5,889 –8 0.657

b,q

0.617 11.5 3,085 17 0.721

102 Uzbekistan 68.2 10.0 b,o r s

0.614 11.7 3,266 13 0.709

103 Micronesia, Federated States of 69.0 8.8

17 0.611

104 Guyana 67.9 8.5 12.2 3,302 11 0.702

144 human development report 2010 Human Development Index and its components

Human Development Life expectancy Mean years Expected years Gross national income GNI per capita rank Nonincome table

a

Index (HDI) value at birth of schooling of schooling (GNI) per capita minus HDI rank HDI value 1

HDI rank (years) (years) (years) (PPP 2008 $) b 2010 2010 2010 2010 2010 2010 2010 0.606 105 Namibia 62.1 7.4 11.8 6,323 –14 0.629 0.604 106 Honduras 72.6 6.5 11.4 3,750 5 0.676 0.602 107 Maldives 72.3 4.7 12.4 5,408 –11 0.636 0.600 108 Indonesia 71.5 5.7 12.7 3,957 2 0.663 0.598 109 Kyrgyzstan 68.4 9.3 12.6 2,291 17 0.726 0.597 110 South Africa 52.0 8.2 13.4 9,812 –37 0.581 r 0.589 4,760 –9 0.627 111 Syrian Arab Republic 74.6 4.9 10.5 0.580 112 Tajikistan 67.3 9.8 11.4 2,020 22 0.709 0.572 113 Viet Nam 74.9 5.5 10.4 2,995 7 0.646 0.567 114 Morocco 71.8 4.4 10.5 4,628 –10 0.594 0.565 115 Nicaragua 73.8 5.7 10.8 2,567 7 0.652 0.560 116 Guatemala 70.8 4.1 10.6 4,694 –13 0.583 b,q 0.538 8.1 22,218 –78 0.454 117 Equatorial Guinea 51.0 5.4 b,o 0.534 11.2 3,306 –4 0.573 118 Cape Verde 71.9 3.5 0.519 119 India 64.4 4.4 10.3 3,337 –6 0.549 b,o 0.502 11.2 5,303 –23 0.485 120 Timor-Leste 62.1 2.8 0.498 121 Swaziland 47.0 7.1 10.3 5,132 –23 0.482 0.497 122 Lao People’s Democratic Republic 65.9 4.6 9.2 2,321 3 0.548 b,o 0.494 9.1 2,172 6 0.550 123 Solomon Islands 67.0 4.5 0.494 124 Cambodia 62.2 5.8 9.8 1,868 12 0.566 0.490 125 Pakistan 67.2 4.9 6.8 2,678 –4 0.523 0.489 126 Congo 53.9 5.9 9.3 3,258 –9 0.503 b,o 0.488 10.2 1,918 8 0.553 127 São Tomé and Príncipe 66.1 4.2 LOW HUMAN DEVELOPMENT 0.470 128 Kenya 55.6 7.0 9.6 1,628 10 0.541 0.469 129 Bangladesh 66.9 4.8 8.1 1,587 12 0.543 0.467 130 Ghana 57.1 7.1 9.7 1,385 14 0.556 0.460 131 Cameroon 51.7 5.9 9.8 2,197 –3 0.493 0.451 132 Myanmar 62.7 4.0 9.2 1,596 8 0.511 0.439 133 Yemen 63.9 2.5 8.6 2,387 –9 0.453 0.435 134 Benin 62.3 3.5 9.2 1,499 8 0.491 b,o 0.435 10.2 953 22 0.550 135 Madagascar 61.2 5.2 0.433 136 Mauritania 57.3 3.7 8.1 2,118 –5 0.454 0.431 137 Papua New Guinea 61.6 4.3 5.2 2,227 –10 0.447 0.428 138 Nepal 67.5 3.2 8.8 1,201 12 0.506 0.428 139 Togo 63.3 5.3 9.6 844 22 0.557 b,o 0.428 10.7 1,176 12 0.507 140 Comoros 66.2 2.8 0.427 141 Lesotho 45.9 5.8 10.3 2,021 –8 0.448 b,q 0.423 8.9 2,156 –12 0.436 142 Nigeria 48.4 5.0 0.422 143 Uganda 54.1 4.7 10.4 1,224 5 0.491 0.411 1,816 –7 0.433 144 Senegal 56.2 3.5 7.5 n 0.404 949 13 0.493 145 Haiti 61.7 4.9 6.8 b,o 0.403 4.4 4,941 –47 0.353 146 Angola 48.1 4.4 b,q 0.402 4.7 2,471 –24 0.394 147 Djibouti 56.1 3.8 0.398 148 Tanzania, United Republic of 56.9 5.1 5.3 1,344 –1 0.441 0.397 149 Côte d’Ivoire 58.4 3.3 6.3 1,625 –10 0.420 0.395 150 Zambia 47.3 6.5 7.2 1,359 –5 0.434 0.390 151 Gambia 56.6 2.8 8.6 1,358 –5 0.426 0.385 152 Rwanda 51.1 3.3 10.6 1,190 –1 0.432 0.385 153 Malawi 54.6 4.3 8.9 911 6 0.463 0.379 154 Sudan 58.9 2.9 4.4 2,051 –22 0.373 0.349 155 Afghanistan 44.6 3.3 8.0 1,419 –12 0.358 b,t 0.340 8.6 953 0 0.380 156 Guinea 58.9 1.6 b,o 0.328 8.3 992 –2 0.357 157 Ethiopia 56.1 1.5 0.317 158 Sierra Leone 48.2 2.9 7.2 809 4 0.360 0.315 159 Central African Republic 47.7 3.5 6.3 758 4 0.363 0.309 160 Mali 49.2 1.4 8.0 1,171 –7 0.312 b,q 0.305 5.8 1,215 –12 0.303 161 Burkina Faso 53.7 1.3 0.300 162 Liberia 59.1 3.9 11.0 320 5 0.509 145 ## STATISTICAL ANNEX Human Development Index and its components Human Development Life expectancy Mean years Expected years Gross national income GNI per capita rank Nonincome table a Index (HDI) value at birth of schooling of schooling (GNI) per capita minus HDI rank HDI value 1 HDI rank (years) (years) (years) (PPP 2008$)

b

2010 2010 2010 2010 2010 2010 2010

b,o

0.295

163 Chad 49.2 1.5 6.0 1,067 –9 0.298

b,q

0.289 9.1 538 1 0.362

164 Guinea-Bissau 48.6 2.3

0.284

165 Mozambique 48.4 1.2 8.2 854 –5 0.300

0.282

166 Burundi 51.4 2.7 9.6 402 0 0.400

0.261

167 Niger 52.5 1.4 4.3 675 –3 0.285

0.239

168 Congo, Democratic Republic of the 48.0 3.8 7.8 291 0 0.390

0.140

169 Zimbabwe 47.0 7.2 9.2 176 0 0.472

## OTHER COUNTRIES OR TERRITORIES ..

Antigua and Barbuda .. .. .. 17,924 .. ..

..

Bhutan 66.8 .. 11.3 5,607 .. ..

..

Cuba 79.0 10.2 17.7 .. .. 0.892

..

Dominica .. .. 12.5 8,549 .. ..

..

Eritrea 60.4 .. 5.5 643 .. ..

..

Grenada 75.8 .. 13.4 7,998 .. ..

..

Iraq 68.5 5.6 9.7 .. .. 0.600

..

Kiribati .. .. 12.3 3,715 .. ..

..

Korea, Democratic People’s Rep. of 67.7 .. .. .. .. ..

..

Lebanon 72.4 .. 13.5 13,475 .. ..

b,o

.. 13.0 .. .. 0.766

Marshall Islands .. 9.8

..

Monaco .. .. .. .. .. ..

..

Nauru .. .. 8.5 .. .. ..

..

Occupied Palestinian Territories 73.9 .. 13.1 .. .. ..

..

Oman 76.1 .. 11.1 25,653 .. ..

b,o

.. 14.9 .. 0.836

Palau .. 12.1

..

Saint Kitts and Nevis .. .. 12.3 14,196 .. ..

..

Saint Lucia 74.2 .. 13.0 8,652 .. ..

..

Saint Vincent and the Grenadines 72.0 .. 13.5 8,535 .. ..

..

Samoa 72.2 .. 12.2 4,126 .. ..

..

San Marino .. .. .. .. .. ..

..

Seychelles .. .. 14.7 19,128 .. ..

r

.. .. .. ..

Somalia 50.4 .. 1.8

..

Tuvalu .. .. 11.2 .. .. ..

..

Vanuatu 70.8 .. 10.4 3,908 .. ..

Developed 0.879

OECD 80.3 11.4 15.9 37,077 — 0.904

0.844

Non-OECD 80.0 10.0 13.9 42,370 — 0.845

Developing 0.588

Arab States 69.1 5.7 10.8 7,861 — 0.610

0.643

East Asia and the Pacific 72.6 7.2 11.5 6,403 — 0.692

0.702

Europe and Central Asia 69.5 9.2 13.6 11,462 — 0.740

0.704

Latin America and the Caribbean 74.0 7.9 13.7 10,642 — 0.746

0.516

South Asia 65.1 4.6 10.0 3,417 — 0.551

0.389

Sub-Saharan Africa 52.7 4.5 9.0 2,050 — 0.436

0.878

Very high human development 80.3 11.3 15.9 37,225 — 0.902

0.717

High human development 72.6 8.3 13.8 12,286 — 0.749

0.592

Medium human development 69.3 6.3 11.0 5,134 — 0.634

0.393

Low human development 56.0 4.1 8.2 1,490 — 0.445

0.386 57.7 3.7 8.0 1,393 — 0.441

Least developed countries 0.624

World 69.3 7.4 12.3 10,631 — 0.663

17

146 human development report 2010 Human Development Index and its components

Notes

a h o

See Technical note 1 for details on how the HDI is calculated. Based on cross-country regression. Based on data on years of schooling of adults from household surveys in the World table

1

b i

Refers to an earlier year than that specified. Assumes the same adult mean years of schooling as Spain. Bank’s International Income Distribution Database.

c j p

To calculate the HDI, unpublished estimates from UNDESA (2009d) were used. The Based on the growth rate of GDP per capita in PPP US dollars for Spain from IMF Based on implied PPP conversion factors from IMF (2010a), data on GDP per capita

data are not published because the population is below 100,000. (2010a). in local currency unit and the ratio between GNI and GDP in US dollars from World

d k

Assumes the same adult mean years of schooling as Switzerland. Based on data on GDP from the United Nations Statistics Division’s National Bank (2010g).

e q

Based on the growth rate of GDP per capita in purchasing power parity (PPP) Accounts: Main Aggregates Database, data on population from UNDESA (2009d) Based on data from United Nations Children’s Fund Multiple Indicator Cluster

US dollars for Switzerland from IMF (2010a). and the PPP exchange rate for Spain from World Bank (2010g). Surveys.

f l r

Based on data on GDP from the United Nations Statistics Division’s National 2007 prices. Refers to primary and secondary education only from UNESCO Institute for Statistics

m

Accounts: Main Aggregates Database, data on population from UNDESA (2009d) Based on the ratio of GNI in US dollars to GDP in US dollars from World Bank (2010a).

s

and the PPP exchange rate for Switzerland from World Bank (2010g). (2010g). Based on the growth rate of GDP per capita in PPP US dollars for Fiji from IMF (2010a).

g n t

In keeping with common usage, the Republic of Korea is referred to as South Korea UNESCO Institute for Statistics (2009). Based on data from Measure DHS Demographic and Health Surveys.

in the body of this Report.

Sources

Column 1: Calculated based on data from UNDESA (2009d), Barro and Lee (2010),

UNESCO Institute for Statistics (2010a), World Bank (2010g) and IMF (2010a).

Column 2: UNDESA (2009d).

Column 3: Barro and Lee (2010).

Column 4: UNESCO Institute for Statistics (2010a).

Column 5: Based on data on GNI per capita and GDP per capita in PPP US dollars

(current and constant prices) from World Bank (2010g) and implied growth rates of GDP

per capita from IMF (2010a).

Column 6: Calculated based on GNI per capita rank and HDI rank.

Column 7: Calculated based on data in columns 2–4. 147

## STATISTICAL ANNEX

2 Human Development Index

e

l trends, 1980–2010

b

ta Human Development Index (HDI) HDI rank Average annual HDI growth rate HDI improvement

a

HDI rank rank

Value Change (%)

1980 1990 1995 2000 2005 2009 2010 2005–2010 2009–2010 1980–2010 1990–2010 2000–2010 1980–2010

## VERY HIGH HUMAN DEVELOPMENT

1 Norway 0.788 0.838 0.869 0.906 0.932 0.937 0.938 0 0 0.58 0.56 0.34 34

2 Australia 0.791 0.819 0.887 0.914 0.925 0.935 0.937 0 0 0.57 0.67 0.25 35

3 New Zealand 0.786 0.813 0.846 0.865 0.896 0.904 0.907 0 0 0.48 0.55 0.47 47

4 United States 0.810 0.857 0.873 0.893 0.895 0.899 0.902 0 0 0.36 0.25 0.10 65

5 Ireland 0.720 0.768 0.799 0.855 0.886 0.894 0.895 0 0 0.72 0.76 0.45 26

6 Liechtenstein .. .. .. .. 0.875 0.889 0.891 5 0 .. .. .. ..

7 Netherlands 0.779 0.822 0.853 0.868 0.877 0.888 0.890 3 0 0.44 0.40 0.25 59

8 Canada 0.789 0.845 0.857 0.867 0.880 0.886 0.888 0 0 0.39 0.25 0.24 64

9 Sweden 0.773 0.804 0.843 0.889 0.883 0.884 0.885 –3 0 0.45 0.48 –0.04 61

10 Germany .. 0.782 0.820 .. 0.878 0.883 0.885 –1 0 .. 0.62 .. ..

11 Japan 0.768 0.814 0.837 0.855 0.873 0.881 0.884 1 0 0.47 0.41 0.33 56

12 Korea, Republic of 0.616 0.725 0.776 0.815 0.851 0.872 0.877 8 0 1.18 0.95 0.74 11

13 Switzerland 0.800 0.824 0.836 0.859 0.870 0.872 0.874 0 0 0.30 0.30 0.18 76

14 France 0.711 0.766 0.807 0.834 0.856 0.869 0.872 5 2 0.68 0.65 0.45 37

15 Israel 0.748 0.788 0.809 0.842 0.861 0.871 0.872 0 –1 0.51 0.51 0.35 50

16 Finland 0.745 0.782 0.810 0.825 0.863 0.869 0.871 –2 –1 0.52 0.54 0.54 49

17 Iceland 0.747 0.792 0.815 0.849 0.881 0.869 0.869 –10 0 0.50 0.46 0.23 55

18 Belgium 0.743 0.797 0.840 0.863 0.858 0.865 0.867 –1 0 0.51 0.42 0.05 52

19 Denmark 0.770 0.797 0.821 0.842 0.860 0.864 0.866 –3 0 0.39 0.41 0.27 69

20 Spain 0.680 0.729 0.789 0.828 0.848 0.861 0.863 1 0 0.79 0.84 0.42 24

21 Hong Kong, China (SAR) 0.693 0.774 0.797 0.800 0.842 0.857 0.862 2 0 0.73 0.53 0.75 31

22 Greece 0.707 0.753 0.761 0.784 0.839 0.853 0.855 3 0 0.63 0.64 0.86 43

23 Italy 0.703 0.764 0.795 0.825 0.838 0.851 0.854 4 0 0.65 0.56 0.35 42

24 Luxembourg 0.719 0.784 0.812 0.845 0.856 0.850 0.852 –6 0 0.57 0.42 0.08 48

25 Austria 0.727 0.777 0.801 0.826 0.841 0.849 0.851 –1 0 0.52 0.45 0.30 58

0.770 0.824 0.823 0.845 0.847 0.849 –4 0 0.47 0.49 0.31 63

26 United Kingdom 0.737

27 Singapore .. .. .. .. 0.826 0.841 0.846 1 0 .. .. .. ..

28 Czech Republic .. .. 0.774 0.801 0.838 0.841 0.841 –2 0 .. .. 0.50 ..

29 Slovenia .. .. 0.743 0.780 0.813 0.826 0.828 0 0 .. .. 0.59 ..

30 Andorra .. .. .. .. 0.803 0.822 0.824 2 0 .. .. .. ..

31 Slovakia .. .. 0.738 0.764 0.796 0.815 0.818 5 0 .. .. 0.69 ..

32 United Arab Emirates 0.627 0.693 0.732 0.756 0.794 0.812 0.815 5 1 0.87 0.81 0.76 23

33 Malta 0.683 0.735 0.754 0.783 0.806 0.813 0.815 –3 –1 0.59 0.51 0.39 57

34 Estonia .. .. 0.700 0.762 0.805 0.809 0.812 –3 0 .. .. 0.63 ..

35 Cyprus 0.662 0.723 0.766 0.768 0.793 0.809 0.810 4 0 0.67 0.57 0.54 44

36 Hungary 0.689 0.692 0.723 0.767 0.798 0.803 0.805 –1 1 0.52 0.76 0.48 66

37 Brunei Darussalam .. 0.773 0.787 0.792 0.801 0.804 0.805 –5 –1 .. 0.20 0.16 ..

38 Qatar .. .. .. 0.764 0.799 0.798 0.803 –5 0 .. .. 0.49 ..

39 Bahrain 0.615 0.694 0.738 0.765 0.793 0.798 0.801 –1 0 0.88 0.72 0.46 25

40 Portugal 0.625 0.694 0.745 0.774 0.775 0.791 0.795 3 1 0.80 0.68 0.27 36

41 Poland .. 0.683 0.710 0.753 0.775 0.791 0.795 3 –1 .. 0.76 0.54 ..

42 Barbados .. .. .. .. 0.775 0.787 0.788 –1 0 .. .. .. ..

## HIGH HUMAN DEVELOPMENT

43 Bahamas .. .. .. .. 0.776 0.783 0.784 –3 0 .. .. .. ..

44 Lithuania .. 0.709 0.677 0.730 0.775 0.782 0.783 –2 0 .. 0.50 0.71 ..

45 Chile 0.607 0.675 0.707 0.734 0.762 0.779 0.783 2 0 0.85 0.74 0.65 30

46 Argentina 0.656 0.682 0.709 0.734 0.749 0.772 0.775 4 0 0.56 0.64 0.55 70

47 Kuwait 0.675 .. 0.760 0.763 0.764 0.769 0.771 –2 0 0.44 .. 0.10 80

148 human development report 2010 Human Development Index trends, 1980–2010

Human Development Index (HDI) HDI rank Average annual HDI growth rate HDI improvement

a

HDI rank rank

Value Change (%)

1980 1990 1995 2000 2005 2009 2010 2005–2010 2009–2010 1980–2010 1990–2010 2000–2010 1980–2010

48 Latvia 0.651 0.679 0.652 0.709 0.763 0.769 0.769 –2 0 0.55 0.63 0.81 71

49 Montenegro .. .. .. .. 0.755 0.768 0.769 –1 0 .. .. .. .. table

2

50 Romania .. 0.688 0.674 0.690 0.733 0.764 0.767 1 1 .. 0.54 1.06 ..

51 Croatia .. .. 0.690 0.720 0.752 0.765 0.767 –2 –1 .. .. 0.63 ..

52 Uruguay .. 0.670 0.691 0.716 0.733 0.760 0.765 0 0 .. 0.67 0.67 ..

53 Libyan Arab Jamahiriya .. .. .. .. 0.726 0.749 0.755 3 1 .. .. .. ..

54 Panama 0.613 0.644 0.672 0.703 0.724 0.751 0.755 4 –1 0.69 0.79 0.70 54

55 Saudi Arabia 0.556 0.620 0.649 0.690 0.732 0.748 0.752 –2 0 1.01 0.96 0.85 21

56 Mexico 0.581 0.635 0.660 0.698 0.727 0.745 0.750 –2 0 0.85 0.83 0.73 38

57 Malaysia 0.541 0.616 0.659 0.691 0.726 0.739 0.744 –2 1 1.06 0.94 0.73 19

58 Bulgaria 0.649 0.678 0.678 0.693 0.724 0.741 0.743 –1 –1 0.45 0.46 0.69 82

59 Trinidad and Tobago 0.656 0.660 0.662 0.685 0.713 0.732 0.736 1 1 0.38 0.54 0.71 84

60 Serbia .. .. .. .. 0.719 0.733 0.735 –1 –1 .. .. .. ..

61 Belarus .. .. .. .. 0.706 0.729 0.732 1 0 .. .. .. ..

62 Costa Rica 0.599 0.639 0.668 0.684 0.708 0.723 0.725 –1 0 0.63 0.63 0.59 68

63 Peru 0.560 0.608 0.644 0.675 0.695 0.718 0.723 4 0 0.85 0.87 0.69 41

64 Albania .. 0.647 0.633 0.670 0.700 0.716 0.719 –1 0 .. 0.52 0.70 ..

65 Russian Federation .. 0.692 0.644 0.662 0.693 0.714 0.719 3 0 .. 0.19 0.82 ..

66 Kazakhstan .. 0.650 0.620 0.614 0.696 0.711 0.714 –1 0 .. 0.47 1.51 ..

67 Azerbaijan .. .. 0.563 0.597 0.655 0.710 0.713 16 0 .. .. 1.77 ..

68 Bosnia and Herzegovina .. .. .. .. 0.698 0.709 0.710 –4 0 .. .. .. ..

69 Ukraine .. 0.690 0.644 0.649 0.696 0.706 0.710 –3 0 .. 0.14 0.89 ..

70 Iran, Islamic Republic of .. 0.536 0.576 0.619 0.660 0.697 0.702 10 2 .. 1.35 1.27 ..

71 The former Yugoslav Republic of Macedonia .. .. 0.634 0.660 0.678 0.697 0.701 1 –1 .. .. 0.61 ..

72 Mauritius 0.525 0.602 0.631 0.657 0.685 0.697 0.701 –2 –1 0.96 0.76 0.64 28

.. 0.649 0.678 0.693 0.699 0 4 .. .. 0.73 ..

73 Brazil .. ..

74 Georgia .. .. .. .. 0.679 0.695 0.698 –3 0 .. .. .. ..

75 Venezuela, Bolivarian Republic of 0.611 0.620 0.633 0.637 0.666 0.696 0.696 3 –2 0.44 0.58 0.90 85

76 Armenia .. .. 0.571 0.620 0.669 0.693 0.695 0 0 .. .. 1.15 ..

77 Ecuador 0.576 0.612 0.630 0.642 0.676 0.692 0.695 –2 1 0.62 0.64 0.79 72

78 Belize .. .. .. .. 0.690 0.694 0.694 –9 –3 .. .. .. ..

79 Colombia 0.537 0.579 0.612 0.637 0.658 0.685 0.689 2 1 0.83 0.87 0.79 46

80 Jamaica 0.589 0.620 0.648 0.665 0.676 0.686 0.688 –6 –1 0.52 0.52 0.35 83

81 Tunisia 0.436 0.526 0.568 0.613 0.650 0.677 0.683 5 0 1.49 1.30 1.07 7

82 Jordan 0.509 0.564 0.595 0.621 0.652 0.677 0.681 2 0 0.97 0.94 0.92 32

83 Turkey 0.467 0.552 0.583 0.629 0.656 0.674 0.679 –1 1 1.24 1.03 0.76 14

84 Algeria 0.443 0.537 0.564 0.602 0.651 0.671 0.677 1 1 1.42 1.16 1.18 9

85 Tonga .. 0.619 0.641 0.651 0.663 0.675 0.677 –6 –2 .. 0.45 0.39 ..

## MEDIUM HUMAN DEVELOPMENT

86 Fiji 0.551 0.612 0.636 0.651 0.667 0.667 0.669 –9 0 0.65 0.45 0.28 75

87 Turkmenistan .. .. .. .. 0.642 0.662 0.669 0 0 .. .. .. ..

88 Dominican Republic .. 0.560 0.591 0.624 0.638 0.660 0.663 0 0 .. 0.85 0.61 ..

89 China 0.368 0.460 0.518 0.567 0.616 0.655 0.663 8 0 1.96 1.83 1.57 2

90 El Salvador 0.456 0.511 0.562 0.606 0.635 0.655 0.659 0 0 1.23 1.27 0.85 16

91 Sri Lanka 0.513 0.558 0.584 .. 0.635 0.653 0.658 0 0 0.83 0.82 .. 51

92 Thailand 0.483 0.546 0.581 0.600 0.631 0.648 0.654 1 0 1.01 0.90 0.86 29

93 Gabon 0.510 0.593 0.610 0.616 0.628 0.642 0.648 1 1 0.80 0.45 0.50 62

94 Suriname .. .. .. .. 0.636 0.643 0.646 –5 –1 .. .. .. ..

95 Bolivia, Plurinational State of .. .. .. 0.593 0.631 0.637 0.643 –3 0 .. .. 0.80 ..

96 Paraguay 0.528 0.557 0.580 0.593 0.619 0.634 0.640 0 1 0.64 0.69 0.75 79

97 Philippines 0.523 0.552 0.569 0.597 0.619 0.635 0.638 –2 –1 0.66 0.72 0.67 78

98 Botswana 0.431 0.576 0.589 0.572 0.593 0.627 0.633 2 0 1.28 0.47 1.01 15

1.21 ..

99 Moldova, Republic of .. 0.616 0.547 0.552 0.606 0.620 0.623 0 0 .. 0.06

100 Mongolia .. 0.520 0.502 0.539 0.588 0.616 0.622 2 0 .. 0.90 1.43 ..

101 Egypt 0.393 0.484 0.523 0.566 0.587 0.614 0.620 2 0 1.52 1.23 0.90 8

102 Uzbekistan .. .. .. .. 0.588 0.612 0.617 –1 1 .. .. .. ..

103 Micronesia, Federated States of .. .. .. .. 0.614 0.612 0.614 –5 –1 .. .. .. ..

104 Guyana 0.500 0.472 0.522 0.552 0.585 0.605 0.611 1 0 0.67 1.29 1.02 81

105 Namibia .. 0.553 0.582 0.568 0.577 0.603 0.606 2 0 .. 0.46 0.64 ..

106 Honduras 0.436 0.495 0.523 0.552 0.579 0.601 0.604 0 0 1.09 0.99 0.91 27 149

## STATISTICAL ANNEX

Human Development Index trends, 1980–2010

Human Development Index (HDI) HDI rank Average annual HDI growth rate HDI improvement

a

HDI rank rank

Value Change (%)

1980 1990 1995 2000 2005 2009 2010 2005–2010 2009–2010 1980–2010 1990–2010 2000–2010 1980–2010

107 Maldives .. .. .. 0.513 0.560 0.595 0.602 4 0 .. .. 1.60 ..

108 Indonesia 0.390 0.458 0.508 0.500 0.561 0.593 0.600 2 2 1.43 1.35 1.82 12

table

2 109 Kyrgyzstan .. 0.577 0.515 0.550 0.572 0.594 0.598 0 –1 .. 0.18 0.84 ..

110 South Africa .. 0.601 0.634 .. 0.587 0.594 0.597 –6 –1 .. –0.03 .. ..

111 Syrian Arab Republic 0.470 0.519 0.546 .. 0.576 0.586 0.589 –3 0 0.75 0.63 .. 74

112 Tajikistan .. 0.592 0.501 0.493 0.550 0.576 0.580 0 0 .. –0.10 1.61 ..

113 Viet Nam .. 0.407 0.457 0.505 0.540 0.566 0.572 1 0 .. 1.70 1.24 ..

114 Morocco 0.351 0.421 0.450 0.491 0.536 0.562 0.567 1 0 1.59 1.49 1.44 5

115 Nicaragua 0.440 0.454 0.473 0.512 0.545 0.562 0.565 –2 0 0.84 1.10 1.00 67

116 Guatemala 0.408 0.451 0.479 0.514 0.533 0.556 0.560 0 0 1.05 1.08 0.85 39

117 Equatorial Guinea .. .. .. 0.477 0.510 0.536 0.538 1 0 .. .. 1.21 ..

118 Cape Verde .. .. .. 0.500 0.519 0.531 0.534 –1 0 .. .. 0.64 ..

119 India 0.320 0.389 0.415 0.440 0.482 0.512 0.519 1 0 1.61 1.44 1.66 6

120 Timor-Leste .. .. .. .. 0.428 0.497 0.502 11 0 .. .. .. ..

121 Swaziland .. 0.511 0.523 0.490 0.474 0.492 0.498 0 0 .. –0.13 0.17 ..

122 Lao People’s Democratic Republic .. 0.354 0.388 0.425 0.460 0.490 0.497 4 1 .. 1.69 1.56 ..

123 Solomon Islands .. .. .. 0.459 0.483 0.492 0.494 –4 –1 .. .. 0.73 ..

124 Cambodia .. .. 0.385 0.412 0.466 0.489 0.494 1 0 .. .. 1.81 ..

125 Pakistan 0.311 0.359 0.389 0.416 0.468 0.487 0.490 –2 0 1.52 1.55 1.64 10

126 Congo 0.462 0.499 0.469 0.458 0.470 0.483 0.489 –4 1 0.19 –0.10 0.65 90

127 São Tomé and Príncipe .. .. .. .. 0.466 0.485 0.488 –3 –1 .. .. .. ..

## LOW HUMAN DEVELOPMENT

128 Kenya 0.404 0.437 0.435 0.424 0.443 0.464 0.470 –1 0 0.50 0.37 1.03 87

129 Bangladesh 0.259 0.313 0.350 0.390 0.432 0.463 0.469 1 0 1.99 2.03 1.86 3

130 Ghana 0.363 0.399 0.421 0.431 0.443 0.463 0.467 –2 0 0.84 0.79 0.82 77

131 Cameroon 0.354 0.418 0.408 0.415 0.437 0.456 0.460 –2 0 0.87 0.48 1.02 73

.. .. .. 0.406 0.444 0.451 6 0 .. .. .. ..

132 Myanmar ..

133 Yemen .. .. .. 0.358 0.403 0.431 0.439 8 2 .. .. 2.04 ..

134 Benin 0.264 0.305 0.347 0.386 0.418 0.432 0.435 0 0 1.67 1.78 1.19 4

135 Madagascar .. .. .. 0.399 0.420 0.436 0.435 –2 –2 .. .. 0.86 ..

136 Mauritania .. 0.337 0.368 0.390 0.411 0.429 0.433 0 0 .. 1.25 1.05 ..

137 Papua New Guinea 0.295 0.349 0.386 .. 0.408 0.426 0.431 0 1 1.27 1.07 .. 22

138 Nepal 0.210 0.316 0.344 0.375 0.400 0.423 0.428 5 2 2.37 1.52 1.34 1

139 Togo 0.347 0.361 0.374 0.399 0.414 0.425 0.428 –4 0 0.70 0.85 0.72 86

140 Comoros .. .. .. .. 0.423 0.426 0.428 –8 –3 .. .. .. ..

141 Lesotho 0.397 0.451 0.452 0.423 0.404 0.423 0.427 –1 0 0.24 –0.27 0.10 91

142 Nigeria .. .. .. .. 0.402 0.419 0.423 0 0 .. .. .. ..

143 Uganda .. 0.281 0.312 0.350 0.380 0.416 0.422 4 0 .. 2.03 1.87 ..

144 Senegal 0.291 0.331 0.338 0.360 0.388 0.408 0.411 0 1 1.15 1.08 1.34 40

145 Haiti .. .. .. .. 0.406 0.410 0.404 –6 –1 .. .. .. ..

146 Angola .. .. .. 0.349 0.376 0.399 0.403 2 1 .. .. 1.45 ..

147 Djibouti .. .. .. .. 0.382 0.399 0.402 –1 –1 .. .. .. ..

148 Tanzania, United Republic of .. 0.329 0.330 0.332 0.370 0.392 0.398 1 1 .. 0.95 1.81 ..

149 Côte d’Ivoire 0.350 0.360 0.369 0.379 0.383 0.394 0.397 –4 –1 0.42 0.48 0.47 89

150 Zambia 0.382 0.423 0.371 0.345 0.360 0.387 0.395 1 0 0.11 –0.34 1.35 92

151 Gambia .. .. 0.312 0.343 0.362 0.385 0.390 –1 0 .. .. 1.29 ..

152 Rwanda 0.249 0.215 0.192 0.277 0.334 0.379 0.385 2 0 1.45 2.92 3.31 13

153 Malawi 0.258 0.289 0.344 0.344 0.336 0.376 0.385 0 0 1.33 1.44 1.13 20

154 Sudan 0.250 0.282 0.310 0.336 0.360 0.375 0.379 –2 0 1.39 1.47 1.19 18

155 Afghanistan .. .. .. .. 0.307 0.342 0.349 1 0 .. .. .. ..

156 Guinea .. .. .. .. 0.323 0.338 0.340 –1 0 .. .. .. ..

157 Ethiopia .. .. .. 0.250 0.287 0.324 0.328 3 0 .. .. 2.73 ..

2.95 53

158 Sierra Leone 0.229 0.230 0.226 0.236 0.292 0.313 0.317 1 0 1.09 1.62

159 Central African Republic 0.265 0.293 0.294 0.299 0.299 0.311 0.315 –1 0 0.58 0.37 0.52 88

160 Mali 0.165 0.187 0.212 0.245 0.279 0.305 0.309 2 0 2.10 2.53 2.34 60

161 Burkina Faso .. .. .. .. 0.285 0.303 0.305 0 0 .. .. .. ..

162 Liberia 0.295 .. .. 0.294 0.264 0.294 0.300 2 0 0.05 .. 0.20 93

163 Chad .. .. .. 0.269 0.299 0.293 0.295 –6 0 .. .. 0.90 ..

164 Guinea-Bissau .. .. .. .. 0.278 0.286 0.289 –1 0 .. .. .. ..

165 Mozambique 0.195 0.178 0.186 0.224 0.263 0.280 0.284 0 0 1.25 2.34 2.37 33

150 human development report 2010 Human Development Index trends, 1980–2010

Human Development Index (HDI) HDI rank Average annual HDI growth rate HDI improvement

a

HDI rank rank

Value Change (%)

1980 1990 1995 2000 2005 2009 2010 2005–2010 2009–2010 1980–2010 1990–2010 2000–2010 1980–2010

166 Burundi 0.181 0.236 0.216 0.223 0.239 0.276 0.282 1 0 1.47 0.87 2.33 17

167 Niger 0.166 0.180 0.192 0.212 0.241 0.258 0.261 –1 0 1.51 1.87 2.09 45 table

2

168 Congo, Democratic Republic of the 0.267 0.261 0.226 0.201 0.223 0.233 0.239 0 0 –0.37 –0.44 1.75 94

169 Zimbabwe 0.241 0.284 0.262 0.232 0.159 0.118 0.140 0 0 –1.81 –3.53 –5.05 95

Developed

OECD 0.754 0.798 0.827 0.852 0.868 0.876 0.879 — — 0.51 0.48 0.31 —

Non-OECD 0.701 0.761 0.779 0.799 0.829 0.840 0.844 — — 0.62 0.51 0.54 —

Developing

Arab States 0.396 0.470 0.505 0.525 0.562 0.583 0.588 — — 1.32 1.12 1.14 —

East Asia and the Pacific 0.383 0.466 0.519 0.559 0.600 0.636 0.643 — — 1.73 1.61 1.40 —

Europe and Central Asia 0.503 0.660 0.628 0.648 0.679 0.698 0.702 — — 1.11 0.31 0.80 —

Latin America and the Caribbean 0.573 0.614 0.640 0.660 0.681 0.699 0.704 — — 0.68 0.68 0.64 —

South Asia 0.315 0.387 0.415 0.440 0.481 0.510 0.516 — — 1.65 1.44 1.61 —

Sub-Saharan Africa 0.293 0.354 0.358 0.315 0.366 0.384 0.389 — — 0.94 0.46 2.10 —

Very high human development 0.753 0.797 0.827 0.851 0.867 0.875 0.878 — — 0.51 0.48 0.31 —

High human development 0.556 0.633 0.634 0.659 0.692 0.712 0.717 — — 0.85 0.62 0.84 —

Medium human development 0.361 0.440 0.480 0.510 0.555 0.586 0.592 — — 1.65 1.49 1.49 —

Low human development 0.271 0.310 0.324 0.332 0.366 0.388 0.393 — — 1.24 1.19 1.68 —

Least developed countries 0.251 0.292 0.311 0.325 0.357 0.382 0.386 — — 1.44 1.40 1.72 —

World 0.455 0.526 0.554 0.570 0.598 0.619 0.624 — — 1.05 0.85 0.89 —

Note

a Measured using deviation from fit (see chapter 2). Lower numbers indicate faster

improvement.

Sources

Columns 1–7: Calculated based on data from UNDESA (2009d), Barro and Lee (2010),

UNESCO Institute for Statistics (2010a), World Bank (2010g) and IMF (2010a).

Columns 8–13: Calculated based on Human Development Index values in the

relevant years. 151

## STATISTICAL ANNEX

e

l Human Development Index

b

c d e

a

Index (HDI) expectancy at birth index education index income index coefficient

HDI rank Value Value Overall loss (%) Change in rank Value Loss (%) Value Loss (%) Value Loss (%)

2010 2010 2010 2010 2010 2010 2010 2010 2010 2010 2000–2010

## VERY HIGH HUMAN DEVELOPMENT f

0.876 6.6

1 Norway 0.938 0 0.927 4.0 0.919 2.4 0.788 13.1 25.8

f

0.864 7.9 35.2

2 Australia 0.937 0 0.934 4.7 0.982 1.7 0.702 16.6

.. ..

3 New Zealand 0.907 .. 0.912 5.0 .. .. .. .. 36.2

f

0.799 11.4 40.8

4 United States 0.902 –9 0.886 6.0 0.863 3.2 0.667 23.5 f

0.813 9.2 34.3

5 Ireland 0.895 –3 0.911 4.6 0.888 3.2 0.664 18.8

.. ..

6 Liechtenstein 0.891 .. .. .. .. .. .. .. ..

f

0.818 8.1 30.9

7 Netherlands 0.890 1 0.911 4.6 0.834 4.0 0.720 15.3 f

0.812 8.6 32.6

8 Canada 0.888 –2 0.918 5.0 0.834 3.2 0.698 17.1 f

0.824 6.9 25.0

9 Sweden 0.885 4 0.934 3.7 0.825 3.6 0.726 13.0 f

0.814 8.0 28.3

10 Germany 0.885 3 0.911 4.4 0.858 2.3 0.689 16.7

.. ..

11 Japan 0.884 .. 0.961 3.9 .. .. .. .. 24.9

f

0.731 16.7 31.6

12 Korea, Republic of 0.877 –18 0.902 4.8 0.663 25.5 0.653 18.4 f

0.813 7.1 33.7

13 Switzerland 0.874 4 0.941 4.4 0.786 2.0 0.725 14.3 f

0.792 9.2 32.7

14 France 0.872 –3 0.932 4.5 0.751 9.1 0.709 13.9 f

0.763 12.5 39.2

15 Israel 0.872 –11 0.922 4.8 0.799 7.9 0.603 23.7 f

0.806 7.5 26.9

16 Finland 0.871 2 0.913 4.0 0.805 4.7 0.711 13.4 f

0.811 6.6 ..

17 Iceland 0.869 5 0.948 3.5 0.854 2.6 0.659 13.4 f

0.794 8.4 33.0

18 Belgium 0.867 2 0.911 4.6 0.784 5.2 0.701 15.1 f

0.810 6.5 24.7

19 Denmark 0.866 6 0.884 4.8 0.813 3.0 0.738 11.3 f

0.779 9.7 34.7

20 Spain 0.863 0 0.928 4.4 0.781 5.7 0.653 18.5

.. ..

21 Hong Kong, China (SAR) 0.862 .. 0.950 4.1 .. .. .. .. 43.4

f

0.768 10.2 34.3

22 Greece 0.855 –2 0.907 4.0 0.788 5.8 0.633 19.9 f

0.752 12.0 36.0

23 Italy 0.854 –5 0.931 4.3 0.706 11.8 0.645 19.4 f

0.775 9.0 ..

24 Luxembourg 0.852 2 0.903 4.8 0.692 6.2 0.746 15.7 f

0.787 7.5 29.1

25 Austria 0.851 5 0.913 4.5 0.753 2.4 0.709 15.1 f

0.766 9.7 36.0

26 United Kingdom 0.849 1 0.900 4.9 0.766 2.1 0.653 21.0

.. .. .. 42.5

27 Singapore 0.846 .. 0.925 3.8 .. .. .. f

0.790 6.1 25.8

28 Czech Republic 0.841 8 0.862 4.3 0.859 1.3 0.667 12.2 f

0.771 6.9 31.2

29 Slovenia 0.828 5 0.891 4.3 0.750 4.0 0.685 12.2

.. ..

30 Andorra 0.824 .. .. .. .. .. .. .. ..

f

0.764 6.7 25.8

31 Slovakia 0.818 3 0.816 6.5 0.821 1.7 0.664 11.7

.. ..

32 United Arab Emirates 0.815 .. 0.846 7.4 .. .. .. .. ..

.. ..

33 Malta 0.815 .. 0.897 5.6 .. .. .. .. ..

f

0.733 9.8 36.0

34 Estonia 0.812 0 0.784 7.9 0.851 3.1 0.590 17.7 f

0.716 11.7 ..

35 Cyprus 0.810 –1 0.901 5.1 0.626 15.7 0.650 13.8 g

0.736 8.6 30.0

36 Hungary 0.805 3 0.796 6.6 0.815 4.1 0.614 14.7

.. ..

37 Brunei Darussalam 0.805 .. 0.860 5.4 .. .. .. .. ..

.. ..

38 Qatar 0.803 .. 0.820 7.4 .. .. .. .. 41.1

.. ..

39 Bahrain 0.801 .. 0.816 8.1 .. .. .. .. ..

f

0.700 11.9 38.5

40 Portugal 0.795 –1 0.891 4.8 0.670 5.7 0.575 23.9 f

0.709 10.8 34.9

41 Poland 0.795 1 0.829 6.4 0.728 7.1 0.590 18.4 g

.. .. ..

42 Barbados 0.788 .. 0.841 7.9 .. .. 0.631 16.1

HIGH HUMAN DEVELOPMENT g

0.671 14.4

43 Bahamas 0.784 –4 0.777 9.7 0.665 7.9 0.586 24.5 ..

f

0.693 11.5 35.8

44 Lithuania 0.783 1 0.752 8.8 0.804 4.3 0.551 20.6 f

0.634 19.0 52.0

45 Chile 0.783 –10 0.867 6.9 0.656 13.3 0.448 34.1 f

0.622 19.7 48.8

46 Argentina 0.775 –11 0.790 10.4 0.672 12.1 0.460 34.4

152 human development report 2010 Inequality-adjusted Human Development Index

c d e

a

Index (HDI) expectancy at birth index education index income index coefficient

HDI rank Value Value Overall loss (%) Change in rank Value Loss (%) Value Loss (%) Value Loss (%)

2010 2010 2010 2010 2010 2010 2010 2010 2010 2010 2000–2010

.. ..

47 Kuwait 0.771 .. 0.850 7.3 .. .. .. .. ..

f

0.684 11.0 36.3

48 Latvia 0.769 2 0.768 8.5 0.778 3.3 0.536 20.5 h

0.693 9.9 36.9

49 Montenegro 0.769 4 0.801 7.3 0.711 9.6 0.584 12.6 g

0.675 12.1 32.1

50 Romania 0.767 3 0.751 10.9 0.693 13.1 0.590 12.2 g

0.650 15.3 29.0

51 Croatia 0.767 –2 0.844 6.0 0.636 10.4 0.512 27.8 table

3

f

0.642 16.1 47.1

52 Uruguay 0.765 –2 0.806 10.1 0.653 10.8 0.504 26.3

.. ..

53 Libyan Arab Jamahiriya 0.755 .. 0.759 12.1 .. .. .. .. ..

f

0.541 28.3 54.9

54 Panama 0.755 –20 0.766 13.6 0.644 9.9 0.321 52.6

.. ..

55 Saudi Arabia 0.752 .. 0.737 12.7 .. .. .. .. ..

f

0.593 21.0 51.6

56 Mexico 0.750 –8 0.787 12.3 0.564 17.9 0.469 31.6 f

.. .. 37.9

57 Malaysia 0.744 .. 0.797 8.0 .. .. 0.488 28.7 g

0.659 11.3 29.2

58 Bulgaria 0.743 5 0.771 9.4 0.682 8.1 0.545 16.1 h

0.621 15.5 40.3

59 Trinidad and Tobago 0.736 –2 0.653 17.4 0.611 6.6 0.601 21.9 h

0.656 10.8 28.2

60 Serbia 0.735 6 0.783 9.0 0.640 11.1 0.562 12.2 g

0.664 9.3 28.8

61 Belarus 0.732 9 0.716 8.8 0.683 8.0 0.599 11.1 f

0.576 20.6 48.9

62 Costa Rica 0.725 –6 0.858 8.3 0.519 17.7 0.428 33.7 g

0.501 30.7 50.5

63 Peru 0.723 –26 0.709 16.5 0.510 30.2 0.348 42.7 g

0.627 12.7 33.0

64 Albania 0.719 4 0.802 10.9 0.601 12.7 0.512 14.4 g

0.636 11.5 43.7

65 Russian Federation 0.719 7 0.661 11.5 0.631 11.2 0.616 11.9 h

0.617 13.6 30.9

66 Kazakhstan 0.714 3 0.595 17.2 0.753 5.3 0.525 17.6 g

0.614 13.8 16.8

67 Azerbaijan 0.713 3 0.613 23.8 0.646 12.0 0.586 4.4 g

0.565 20.4 36.3

68 Bosnia and Herzegovina 0.710 –2 0.798 9.2 0.545 19.4 0.416 31.1 f

0.652 8.1 27.6

69 Ukraine 0.710 14 0.685 11.0 0.795 2.8 0.509 10.4

.. ..

70 Iran, Islamic Republic of 0.702 .. 0.680 17.3 .. .. .. .. 38.3

h

0.584 16.7 42.8

71 The former Yugoslav Republic of Macedonia 0.701 4 0.773 10.4 0.527 17.5 0.489 21.8

.. ..

72 Mauritius 0.701 .. 0.731 11.4 .. .. .. .. ..

f

0.509 27.2 55.0

73 Brazil 0.699 –15 0.698 16.6 0.470 25.7 0.401 37.6 h

0.579 17.0 40.8

74 Georgia 0.698 5 0.667 19.0 0.749 4.9 0.388 25.9 f

0.549 21.2 43.4

75 Venezuela, Bolivarian Republic of 0.696 –1 0.745 13.3 0.495 17.0 0.449 32.0 g

0.619 11.0 30.2

76 Armenia 0.695 12 0.727 15.3 0.675 6.5 0.483 10.8 f

0.554 20.2 54.4

77 Ecuador 0.695 3 0.745 15.2 0.501 21.8 0.458 23.4 g

0.495 28.7 59.6

78 Belize 0.694 –16 0.788 12.4 0.545 19.8 0.282 48.5 f

0.492 28.6 58.5

79 Colombia 0.689 –18 0.718 15.1 0.482 23.9 0.344 43.6 g

0.574 16.6 45.5

80 Jamaica 0.688 9 0.690 16.7 0.619 8.3 0.442 24.1 i

0.511 25.2 40.8

81 Tunisia 0.683 –6 0.751 12.7 0.378 38.7 0.469 21.8 g

0.550 19.2 37.7

82 Jordan 0.681 7 0.729 13.3 0.508 25.1 0.450 18.7 h

0.518 23.6 41.2

83 Turkey 0.679 1 0.690 16.5 0.405 27.4 0.498 26.5

.. ..

84 Algeria 0.677 .. 0.688 17.9 .. .. .. .. 35.3

.. ..

85 Tonga 0.677 .. 0.705 14.5 0.721 5.1 .. .. ..

MEDIUM HUMAN DEVELOPMENT .. ..

86 Fiji 0.669 .. 0.671 13.9 0.679 11.0 .. .. ..

g

0.493 26.4 40.8

87 Turkmenistan 0.669 –12 0.520 27.5 0.647 10.2 0.355 38.7 f

0.499 24.8 48.4

88 Dominican Republic 0.663 –7 0.678 18.9 0.450 22.2 0.407 32.6 i

0.511 23.0 41.5

89 China 0.663 0 0.714 15.6 0.453 23.2 0.412 29.5 f

0.477 27.6 46.9

90 El Salvador 0.659 –14 0.687 16.5 0.415 32.5 0.382 32.7 g

0.546 17.1 41.1

91 Sri Lanka 0.658 11 0.756 12.3 0.519 17.9 0.414 20.8 g

0.516 21.2 42.5

92 Thailand 0.654 5 0.706 9.5 0.491 18.0 0.396 34.0 g

0.512 21.0 41.5

93 Gabon 0.648 5 0.446 31.9 0.575 7.3 0.523 22.1 g

0.489 24.3 52.8

94 Suriname 0.646 –7 0.651 16.7 0.475 20.1 0.378 34.9 f

0.398 38.0 57.2

95 Bolivia, Plurinational State of 0.643 –17 0.534 27.2 0.510 28.7 0.232 54.2 f

0.482 24.7 53.2

96 Paraguay 0.640 –6 0.663 19.9 0.494 19.8 0.342 33.4 g

0.518 18.9 44.0

97 Philippines 0.638 11 0.705 15.0 0.554 12.9 0.355 28.0

.. ..

98 Botswana 0.633 .. 0.417 25.9 .. .. .. .. 61.0

g

0.539 13.5 37.4

99 Moldova, Republic of 0.623 16 0.673 13.1 0.635 7.5 0.367 19.4 g

0.527 15.2 36.6

100 Mongolia 0.622 16 0.579 22.6 0.635 5.8 0.399 16.4 g

0.449 27.5 32.1

101 Egypt 0.620 –7 0.641 19.8 0.304 43.6 0.465 15.9 h

0.521 15.7 0.372 17.9 36.7

102 Uzbekistan 0.617 17 0.565 25.9 0.672 1.4 f

0.375 39.0 ..

103 Micronesia, Federated States of 0.614 –11 0.616 20.5 0.503 22.4 0.170 63.1 f

0.497 18.6 43.2

104 Guyana 0.611 7 0.567 25.2 0.588 9.6 0.369 20.3 153

## STATISTICAL ANNEX

c d e

a

Index (HDI) expectancy at birth index education index income index coefficient

HDI rank Value Value Overall loss (%) Change in rank Value Loss (%) Value Loss (%) Value Loss (%)

2010 2010 2010 2010 2010 2010 2010 2010 2010 2010 2000–2010

h

0.338 44.3

105 Namibia 0.606 –15 0.503 24.5 0.429 27.8 0.178 68.3 74.3

f

0.419 30.6 55.3

106 Honduras 0.604 –4 0.669 19.7 0.379 31.0 0.291 39.7 g

0.508 15.6 37.4

107 Maldives 0.602 14 0.700 15.5 0.433 11.5 0.434 19.5 g

0.494 17.7 37.6

108 Indonesia 0.600 9 0.678 16.8 0.424 21.4 0.418 14.8 g

0.508 15.1 33.5

109 Kyrgyzstan 0.598 15 0.601 21.6 0.611 11.1 0.357 12.2

table

3 h

0.411 31.2 57.8

110 South Africa 0.597 –1 0.353 30.2 0.529 20.8 0.373 40.9 g

0.467 20.8 ..

111 Syrian Arab Republic 0.589 4 0.769 11.1 0.312 31.5 0.424 18.3 g

0.469 19.1 33.6

112 Tajikistan 0.580 6 0.517 31.0 0.608 9.4 0.328 15.3 g

0.478 16.4 37.8

113 Viet Nam 0.572 9 0.750 13.8 0.398 17.1 0.367 18.2 g

0.407 28.1 40.9

114 Morocco 0.567 2 0.671 18.3 0.246 42.7 0.409 20.7 g

0.426 24.6 52.3

115 Nicaragua 0.565 6 0.718 15.6 0.333 33.3 0.324 23.8 f

0.372 33.6 53.7

116 Guatemala 0.560 0 0.640 20.4 0.270 36.1 0.297 42.5

.. ..

117 Equatorial Guinea 0.538 .. 0.255 48.2 0.297 29.2 .. .. ..

.. ..

118 Cape Verde 0.534 .. 0.688 16.4 0.277 30.7 .. .. 50.4

g

0.365 29.6 36.8

119 India 0.519 0 0.483 31.3 0.255 40.6 0.397 14.7 g

0.334 33.3 31.9

120 Timor-Leste 0.502 –4 0.438 34.3 0.197 44.3 0.433 19.2 g

0.320 35.7 50.7

121 Swaziland 0.498 –7 0.272 36.4 0.336 38.3 0.359 32.3 g

0.374 24.8 32.6

122 Lao People’s Democratic Republic 0.497 5 0.526 27.6 0.287 30.5 0.345 15.5

.. ..

123 Solomon Islands 0.494 .. 0.557 25.2 0.284 30.2 .. .. ..

g

0.351 28.8 44.2

124 Cambodia 0.494 3 0.445 33.4 0.331 31.1 0.295 21.4 g

0.336 31.5 31.2

125 Pakistan 0.490 1 0.501 32.9 0.196 46.4 0.385 10.6 g

0.334 31.8 47.3

126 Congo 0.489 0 0.312 41.9 0.330 30.0 0.360 22.0

.. ..

127 São Tomé and Príncipe 0.488 .. 0.479 34.4 0.324 22.7 .. .. 50.6

LOW HUMAN DEVELOPMENT g

0.320 31.9

128 Kenya 0.470 –1 0.354 37.2 0.369 29.2 0.252 28.8 47.7

g

0.331 29.4 31.0

129 Bangladesh 0.469 1 0.555 25.3 0.219 44.8 0.299 14.8 g

0.349 25.4 42.8

130 Ghana 0.467 7 0.354 39.7 0.487 7.5 0.246 25.4 g

0.304 33.9 19.9 44.6

131 Cameroon 0.460 –1 0.279 44.4 0.312 35.3 0.321

.. ..

132 Myanmar 0.451 .. 0.418 38.2 .. .. .. .. ..

g

0.289 34.2 37.7

133 Yemen 0.439 –2 0.477 31.2 0.149 49.8 0.341 17.6 g

0.282 35.2 38.6

134 Benin 0.435 –5 0.404 39.7 0.202 44.1 0.276 19.2 g

0.308 29.2 47.2

135 Madagascar 0.435 3 0.415 36.4 0.320 30.8 0.220 19.3 g

0.281 35.1 39.0

136 Mauritania 0.433 –5 0.361 38.9 0.199 43.2 0.310 21.5

.. ..

137 Papua New Guinea 0.431 .. 0.470 28.5 .. .. .. .. 50.9

g

0.292 31.9 47.3

138 Nepal 0.428 3 0.569 24.3 0.193 43.3 0.226 26.4 g

0.287 32.9 34.4

139 Togo 0.428 2 0.443 35.4 0.264 41.5 0.203 20.0 h

0.240 43.9 64.3

140 Comoros 0.428 –11 0.534 27.0 0.185 47.4 0.140 54.0 h

0.282 34.0 52.5

141 Lesotho 0.427 0 0.260 36.6 0.368 24.9 0.234 39.5 g

0.246 41.7 42.9

142 Nigeria 0.423 –6 0.220 51.1 0.228 46.0 0.298 25.1 g

0.286 32.1 42.6

143 Uganda 0.422 5 0.321 40.7 0.321 28.2 0.229 26.4 g

0.262 36.2 39.2

144 Senegal 0.411 0 0.359 37.4 0.172 47.3 0.293 21.1 h

0.239 40.8 59.5

145 Haiti 0.404 –7 0.443 32.9 0.219 40.7 0.141 47.9 g

0.242 39.9 58.6

146 Angola 0.403 –4 0.206 53.7 0.207 26.2 0.334 36.4 g

0.252 37.3 39.9

147 Djibouti 0.402 0 0.338 41.0 0.144 47.0 0.329 21.3 g

0.285 28.4 34.6

148 Tanzania, United Republic of 0.398 9 0.365 37.5 0.237 28.7 0.268 17.6 g

0.254 36.1 48.4

149 Côte d’Ivoire 0.397 3 0.361 40.5 0.160 44.8 0.281 20.5 g

0.270 31.5 50.7

150 Zambia 0.395 7 0.231 46.5 0.330 24.2 0.259 20.8 g

0.238 39.0 47.3

151 Gambia 0.390 –2 0.356 38.5 0.174 44.7 0.218 33.3 g

0.243 37.0 46.7

152 Rwanda 0.385 3 0.259 47.4 0.263 30.7 0.210 31.5 g

0.261 32.1 39.0

153 Malawi 0.385 8 0.327 40.3 0.256 34.7 0.213 19.7

.. ..

154 Sudan 0.379 .. 0.379 38.5 .. .. .. .. ..

.. ..

155 Afghanistan 0.349 .. 0.161 58.8 0.199 39.3 .. .. ..

g

0.209 38.4 43.3

156 Guinea 0.340 –1 0.341 44.5 0.135 42.6 0.199 26.8 g

0.216 34.3 29.8

157 Ethiopia 0.328 1 0.331 42.1 0.137 38.2 0.220 20.8 g

0.193 39.3 42.5

158 Sierra Leone 0.317 –1 0.248 44.5 0.150 48.2 0.192 22.2 g

0.183 42.0 43.6

159 Central African Republic 0.315 –3 0.220 49.8 0.163 45.9 0.170 28.1 g

0.191 38.3 36.9 0.227 25.4 39.0

160 Mali 0.309 0 0.231 50.1 0.133 g

0.195 36.2 39.6

161 Burkina Faso 0.305 3 0.296 44.5 0.108 37.3 0.231 25.3 g

0.188 37.3 52.6

162 Liberia 0.300 1 0.351 43.3 0.225 46.4 0.084 19.0

154 human development report 2010 Inequality-adjusted Human Development Index

c d e

a

Index (HDI) expectancy at birth index education index income index coefficient

HDI rank Value Value Overall loss (%) Change in rank Value Loss (%) Value Loss (%) Value Loss (%)

2010 2010 2010 2010 2010 2010 2010 2010 2010 2010 2000–2010

g

0.179 39.3

163 Chad 0.295 0 0.210 54.5 0.119 37.8 0.229 20.8 39.8

h

0.166 42.4 35.5

164 Guinea-Bissau 0.289 –2 0.215 52.5 0.172 40.3 0.124 32.5 g

0.155 45.3 47.1

165 Mozambique 0.284 –2 0.244 45.7 0.144 28.2 0.107 58.1 g

0.177 37.0 33.3

166 Burundi 0.282 2 0.259 47.8 0.206 36.3 0.104 24.9 h

0.173 33.9 43.9

167 Niger 0.261 2 0.274 46.8 0.109 31.3 0.173 21.1 table

3

g

0.153 36.2 44.4

168 Congo, Democratic Republic of the 0.239 0 0.209 52.9 0.244 29.1 0.070 22.1 h

0.098 29.9 50.1

169 Zimbabwe 0.140 0 0.281 34.2 0.416 20.1 0.008 34.5

Developed 0.789 10.2

OECD 0.879 .. 0.907 5.0 0.810 5.6 0.669 19.5 ..

j j j j

10.5

0.756 .. 0.900 5.3 0.790 4.3 0.607 21.8 ..

Non-OECD 0.844

Developing j j j j

0.426 27.6

Arab States 0.588 .. 0.619 21.6 0.289 43.4 0.432 17.7 ..

j j j j

21.5

0.505 .. 0.699 16.3 0.452 21.2 0.407 27.1 ..

East Asia and the Pacific 0.643 0.607 13.6

Europe and Central Asia 0.702 .. 0.672 14.3 0.623 11.9 0.535 16.1 ..

0.527 25.1

Latin America and the Caribbean 0.704 .. 0.728 15.1 0.510 22.1 0.395 37.6 ..

0.361 30.2

South Asia 0.516 .. 0.499 30.4 0.246 41.3 0.383 18.2 ..

0.261 32.8

Sub-Saharan Africa 0.389 .. 0.294 43.8 0.254 34.1 0.238 26.0 ..

0.789 10.2

Very high human development 0.878 .. 0.907 5.0 0.810 5.7 0.668 19.5 ..

0.575 19.8

High human development 0.717 .. 0.718 13.8 0.561 17.6 0.472 28.1 ..

0.449 24.3

Medium human development 0.592 .. 0.611 22.4 0.369 29.3 0.401 21.9 ..

0.267 32.0

Low human development 0.393 .. 0.348 40.8 0.227 38.2 0.242 23.2 ..

0.263 31.9

Least developed countries 0.386 .. 0.375 39.0 0.209 38.0 0.232 22.3 ..

0.489 21.7

World 0.624 .. 0.630 21.3 0.436 28.2 0.425 22.7 ..

Notes

a e i

See Technical note 2 for details on how the Inequality-adjusted HDI (IHDI) is Inequality adjustment is based on data from household surveys, including the Inequality is estimated from household consumption per capita.

j

calculated. Luxembourg Income Study, Eurostat’s European Union Survey of Income and Living Based on less than half the countries.

b Change in rank is based on countries for which IHDI is calculated. Conditions, the World Bank’s International Income Distribution Database, UNICEF’s

c Inequality adjustment is based on life tables produced by the United Nations Multiple Indicators Cluster Survey, Measure DHS Demographic and Health Surveys

Department of Economic and Social Affairs. and the United Nations University World Institute for Development Economics

d Inequality adjustment is based on data from household surveys, including the Research’s (UNU-WIDER) World Income Inequality Database.

f

Luxembourg Income Study, Eurostat’s European Union Survey of Income and Inequality is estimated from household disposable income per capita.

g

Living Conditions, the World Bank’s International Income Distribution Database, Inequality is estimated from imputed income using the assets index matching

the United Nations Children’s Fund’s (UNICEF) Multiple Indicator Cluster methodology in Harttgen and Klasen (2010).

h

Survey, Measure DHS Demographic and Health Surveys and the World Health Inequality is estimated from income deciles available from UNU-WIDER.

Organization’s (WHO) World Health Survey.

Sources

Column 1: Calculated based on data from UNDESA (2009d), Barro and Lee (2010),

UNESCO Institute for Statistics (2010a), World Bank (2010g) and IMF (2010a).

Column 2: Calculated as the geometric mean of the values in columns 5, 7 and 9

using the methodology in Technical note 2.

Columns 3, 6, 8 and 10: Calculated based on data from UN life tables, the

Luxembourg Income Study, Eurostat’s European Union Survey of Income and Living

Conditions, the World Bank’s International Income Distribution Database, UNICEF’s

Multiple Indicator Cluster Survey, Measure DHS Demographic and Health Surveys, the

WHO’s World Health Survey and UNU-WIDER’s World Income Inequality Database using

the methodology in Technical note 2.

Column 4: Calculated based on data in columns 1 and 2.

Column 5: Calculated based on data in column 6 and the unadjusted life

expectancy index.

Column 7: Calculated based on data in column 10 and the unadjusted education index.

Column 9: Calculated based on data in column 9 and the unadjusted income index.

Column 11: World Bank (2010c). 155

## STATISTICAL ANNEX

4

e

l Gender Inequality Index

b

ta Population

with at least

secondary Labour force Births attended

Antenatal

Contraceptive

education participation

Gender Maternal Adolescent Seats in by skilled health

coverage of at

prevalence rate,

rate

Inequality mortality fertility parliament (% ages 25

a b c personnel

least one visit

any method

Index ratio rate (%)

and older)

(%) (% of married

HDI rank Rank Value Female Female Male Female Male women ages 15–49) (%) (%)

d d d d d

2008 2008 2003–2008 1990–2008 2008 2010 2010 2008 2008 1990–2008 1990–2008 2000–2008

VERY HIGH HUMAN DEVELOPMENT 5 0.234

1 Norway 7 8.6 36.1 99.3 99.1 77.3 82.6 88.4 .. .. e

18 0.296

2 Australia 4 14.9 29.7 95.1 97.2 69.9 83.0 70.8 .. 99 e

25 0.320

3 New Zealand 9 22.6 33.6 71.6 73.5 72.1 84.5 .. .. 94

f

37 0.400

4 United States 11 35.9 17.0 95.3 94.5 68.7 80.6 72.8 .. 99

29 0.344

5 Ireland 1 15.9 15.5 82.3 81.5 62.8 80.7 89.0 .. 100

.. ..

6 Liechtenstein .. .. 24.0 .. .. .. .. .. .. ..

1 0.174

7 Netherlands 6 3.8 39.1 86.3 89.2 73.4 85.4 67.0 .. 100

16 0.289

8 Canada 7 12.8 24.9 92.3 92.7 74.3 82.7 74.0 .. 100

3 0.212

9 Sweden 3 7.7 47.0 87.9 87.1 77.1 81.8 .. .. .. g

7 0.240

10 Germany 4 7.7 31.1 91.3 92.8 70.8 82.3 .. .. 100

12 0.273

11 Japan 6 4.7 12.3 80.0 82.3 62.1 85.2 54.3 .. 100

20 0.310

12 Korea, Republic of 14 5.5 13.7 79.4 91.7 54.5 75.6 80.2 .. 100 g

4 0.228

13 Switzerland 5 5.5 27.2 62.9 74.5 76.6 87.8 .. .. 100

11 0.260

14 France 8 6.9 19.6 79.6 84.6 65.8 74.9 71.0 .. ..

28 0.332

15 Israel 4 14.3 14.2 78.9 77.2 61.1 70.1 .. .. ..

8 0.248

16 Finland 7 11.4 41.5 70.1 70.1 73.9 77.7 .. .. 100

13 0.279

17 Iceland 4 15.1 33.3 66.3 57.7 81.7 89.9 .. .. ..

6 0.236

18 Belgium 8 7.7 36.2 75.7 79.8 60.9 73.5 74.6 .. ..

2 0.209

19 Denmark 3 6.0 38.0 59.0 65.6 77.2 84.3 .. .. ..

14 0.280

20 Spain 4 12.1 33.6 70.9 75.7 63.2 81.7 65.7 .. ..

.. ..

21 Hong Kong, China (SAR) .. 5.7 .. 67.3 71.0 60.5 79.2 84.0 .. ..

23 0.317

22 Greece 3 8.9 14.7 64.4 72.0 55.4 79.0 76.2 .. .. e

9 0.251

23 Italy 3 4.9 20.2 76.5 84.1 51.6 74.5 .. .. 99

24 0.318

24 Luxembourg 12 12.3 23.3 66.4 73.9 58.1 73.9 .. .. 100

19 0.300 ..

25 Austria 4 12.8 26.6 67.3 85.9 68.3 81.0 .. ..

32 0.355

26 United Kingdom 8 24.1 19.6 68.8 67.8 69.2 82.2 82.0 .. .. e

10 0.255

27 Singapore 14 4.5 24.5 57.3 64.8 60.6 81.8 .. .. 100

27 0.330

28 Czech Republic 4 10.6 16.0 85.5 87.6 61.1 78.1 .. .. 100

17 0.293

29 Slovenia 6 4.9 10.0 45.9 63.7 67.5 75.4 .. .. 100

h

.. .. .. .. .. .. ..

30 Andorra .. .. 25.0 50.8 50.9

31 0.352

31 Slovakia 6 20.7 19.3 80.8 87.1 61.3 76.5 .. .. 100

45 0.464

32 United Arab Emirates 37 16.0 22.5 76.9 77.3 42.5 92.6 .. .. 100 g

35 0.395

33 Malta 8 11.5 8.7 64.4 73.5 41.3 77.7 .. .. 100

39 0.409

34 Estonia 25 21.4 20.8 94.4 94.6 70.2 78.6 .. .. 100

15 0.284

35 Cyprus 10 6.1 14.3 64.0 75.2 64.5 78.5 .. .. 100

34 0.382

36 Hungary 6 20.2 11.1 93.2 96.7 54.8 68.0 .. .. 100

.. ..

37 Brunei Darussalam 13 25.0 .. 66.6 23.5 62.6 77.8 .. .. 100

94 0.671

38 Qatar 12 15.9 0.0 62.1 54.7 49.3 93.1 .. .. 100

h h

55 0.512 74.7 33.5 86.5 .. .. 99

39 Bahrain 32 16.7 13.8 57.0

21 0.310

40 Portugal 11 16.5 28.3 44.6 43.8 69.0 79.6 67.1 .. 100

26 0.325

41 Poland 8 13.9 18.0 79.7 83.9 56.9 71.0 .. .. 100

42 0.448

42 Barbados 16 42.7 13.7 89.5 87.6 76.5 84.9 .. 100 100

156 human development report 2010 Gender Inequality Index

Population

with at least

secondary Labour force Births attended

Antenatal

Contraceptive

education participation

Gender Maternal Adolescent Seats in by skilled health

coverage of at

prevalence rate,

rate

Inequality mortality fertility parliament (% ages 25

a b c personnel

least one visit

any method

Index ratio rate (%)

and older)

(%) (% of married

HDI rank Rank Value Female Female Male Female Male women ages 15–49) (%) (%)

d d d d d

2008 2008 2003–2008 1990–2008 2008 2010 2010 2008 2008 1990–2008 1990–2008 2000–2008

HIGH HUMAN DEVELOPMENT .. ..

43 Bahamas 16 53.0 25.0 .. .. 74.3 82.8 .. 98 99

33 0.359

44 Lithuania 11 21.9 17.7 91.9 95.7 65.5 71.6 .. .. 100 table

53 0.505

45 Chile 16 59.6 12.7 67.3 69.8 48.1 78.9 64.2 .. 100 4

60 0.534

46 Argentina 77 56.9 39.8 57.0 54.9 57.0 81.6 65.3 99 99

i

43 0.451 52.2 43.9 45.6 84.5 .. .. 100

47 Kuwait 4 13.2 3.1

22 0.316

48 Latvia 10 15.2 20.0 94.8 96.2 70.6 78.8 .. .. 100

h h j

.. .. 98.8 .. .. 39.4 97 99

49 Montenegro 14 14.7 11.1 97.5

49 0.478

50 Romania 24 31.2 9.8 83.8 90.5 55.3 70.7 70.0 94 99

30 0.345

51 Croatia 7 14.1 20.9 57.4 72.3 58.9 71.7 .. .. 100

54 0.508

52 Uruguay 20 61.1 12.3 56.6 51.7 64.4 84.6 77.0 97 99 j

52 0.504

53 Libyan Arab Jamahiriya 97 3.2 7.7 55.6 44.0 25.1 81.1 .. .. 100

81 0.634

54 Panama 130 82.6 16.7 63.5 60.7 52.6 87.0 .. .. 91

128 0.760

55 Saudi Arabia 18 26.1 0.0 50.3 57.9 21.8 81.8 23.8 .. 96

68 0.576

56 Mexico 60 64.8 22.1 57.7 63.6 46.3 84.6 70.9 94 94

50 0.493

57 Malaysia 62 12.8 14.6 66.0 72.8 46.7 82.1 .. 79 100

36 0.399

58 Bulgaria 11 42.2 21.7 69.1 70.6 63.4 73.8 .. .. 99

48 0.473

59 Trinidad and Tobago 45 34.6 33.3 67.6 66.6 59.4 81.9 42.5 96 98 j

.. ..

60 Serbia 14 22.1 21.6 61.7 70.7 .. .. 41.2 98 99 j

.. ..

61 Belarus 18 21.3 32.5 .. .. 68.1 74.1 72.6 99 100

51 0.501

62 Costa Rica 30 67.0 36.8 54.4 52.8 48.8 84.2 .. 90 94 j

74 0.614

63 Peru 240 54.7 29.2 64.1 78.6 61.3 77.6 71.3 91 73

61 0.545

64 Albania 92 14.2 7.1 83.2 89.2 55.5 76.4 60.1 97 100

41 0.442

65 Russian Federation 28 25.1 11.5 90.6 71.3 68.7 76.3 .. .. 100 j

67 0.575

66 Kazakhstan 140 30.7 12.3 92.2 95.1 73.9 80.4 50.7 100 100

h h j

62 0.553

67 Azerbaijan 82 33.8 11.4 90.0 96.0 66.3 71.1 51.1 77 89 j

.. ..

68 Bosnia and Herzegovina 3 15.9 12.3 .. .. 65.4 78.1 35.7 99 100

44 0.463

69 Ukraine 18 28.3 8.2 91.5 96.1 62.3 72.6 66.7 99 99

98 0.674

70 Iran, Islamic Republic of 140 18.3 2.8 39.0 57.2 32.5 73.1 73.3 98 97 j

.. ..

71 The former Yugoslav Republic of Macedonia 10 21.7 31.7 .. .. 50.4 74.8 13.5 94 98 e

46 0.466

72 Mauritius 15 39.3 17.1 45.2 52.9 46.3 80.3 75.8 .. 99

80 0.631

73 Brazil 110 75.6 9.4 48.8 46.3 64.0 85.2 .. 98 97

h h

71 0.597 92.7 59.8 77.4 47.3 94 98

74 Georgia 66 44.7 6.0 89.7

64 0.561

75 Venezuela, Bolivarian Republic of 57 89.9 18.6 33.4 29.6 54.0 82.7 .. 94 95

66 0.570

76 Armenia 76 35.7 8.4 94.1 94.8 68.6 81.8 53.1 93 98 j

86 0.645

77 Ecuador 210 82.8 25.0 44.2 45.8 48.1 79.2 72.7 84 99 j

73 0.600

78 Belize 52 78.7 11.1 35.2 32.8 49.0 83.7 34.3 94 96 j

90 0.658

79 Colombia 130 74.3 9.7 49.5 48.5 43.3 79.8 78.2 94 96 j

84 0.638

80 Jamaica 170 77.3 13.6 74.0 71.1 62.2 78.4 69.0 91 97

56 0.515

81 Tunisia 100 6.9 19.9 33.5 48.0 27.7 74.2 60.2 96 90

76 0.616

82 Jordan 62 24.5 8.5 57.6 73.8 24.7 78.3 57.1 99 99

77 0.621

83 Turkey 44 38.8 9.1 27.1 46.8 26.9 74.6 71.0 92 83

70 0.594

84 Algeria 180 7.3 6.5 36.3 49.3 38.2 83.1 61.4 89 95

k

.. .. 84.0 87.9 56.0 76.7 .. .. 99

85 Tonga .. 22.8 3.1

MEDIUM HUMAN DEVELOPMENT .. ..

86 Fiji 210 31.5 .. 86.6 88.6 40.2 80.4 .. .. 99

.. ..

87 Turkmenistan 130 19.5 .. .. .. 65.3 76.6 61.8 99 100

87 0.646

88 Dominican Republic 150 108.7 17.1 49.7 41.8 54.6 83.6 72.9 99 98

38 0.405

89 China 45 9.7 21.3 54.8 70.4 74.5 84.8 86.9 91 98 e

89 0.653

90 El Salvador 170 82.7 16.7 41.9 48.2 50.5 81.2 72.5 94 84

72 0.599

91 Sri Lanka 58 29.8 5.8 56.0 57.6 38.5 80.3 68.0 99 99

69 0.586

92 Thailand 110 37.3 12.7 25.6 33.7 70.7 85.0 81.1 98 99

99 0.678

93 Gabon 520 89.9 16.1 53.8 34.7 71.1 82.9 32.7 94 86 j

.. ..

94 Suriname 72 39.5 25.5 .. .. 41.8 71.3 42.1 90 90 157

## STATISTICAL ANNEX

Gender Inequality Index Population

with at least

secondary Labour force Births attended

Antenatal

Contraceptive

education participation

Gender Maternal Adolescent Seats in by skilled health

coverage of at

prevalence rate,

rate

Inequality mortality fertility parliament (% ages 25

a b c personnel

least one visit

any method

Index ratio rate (%)

and older)

(%) (% of married

HDI rank Rank Value Female Female Male Female Male women ages 15–49) (%) (%)

d d d d d

2008 2008 2003–2008 1990–2008 2008 2010 2010 2008 2008 1990–2008 1990–2008 2000–2008

96 0.672

95 Bolivia, Plurinational State of 290 78.2 14.7 55.1 67.9 64.1 82.9 60.6 77 66

85 0.643

96 Paraguay 150 72.3 13.6 46.7 51.3 58.0 88.3 79.4 96 77

78 0.623

97 Philippines 230 45.0 20.2 65.9 63.7 50.2 80.6 50.6 91 62 j

91 0.663

98 Botswana 380 52.1 11.1 73.6 77.5 75.1 81.8 44.4 97 94

table j

40 0.429

99 Moldova, Republic of 22 33.8 21.8 85.8 92.3 53.4 55.6 67.8 98 100

4 57 0.523

100 Mongolia 46 16.6 4.2 83.0 81.8 70.0 79.5 66.0 99 99

108 0.714

101 Egypt 130 39.0 3.7 43.4 61.1 24.4 76.4 60.3 74 79 j

.. ..

102 Uzbekistan 24 12.9 16.4 .. .. 61.7 73.7 64.9 99 100

.. ..

103 Micronesia, Federated States of .. 25.4 0.0 .. .. .. .. .. .. 88 j

92 0.667

104 Guyana 470 62.7 30.0 42.6 43.7 49.2 85.4 34.2 81 83

75 0.615

105 Namibia 210 74.4 26.9 49.6 46.1 53.5 63.6 55.1 95 81 j

101 0.680

106 Honduras 280 93.1 23.4 31.9 36.3 43.4 84.6 65.2 92 67

59 0.533

107 Maldives 120 13.4 12.0 31.3 37.3 58.3 76.5 39.0 81 84 j

100 0.680

108 Indonesia 420 39.8 11.6 24.2 31.1 53.3 86.2 61.4 93 73 j

63 0.560

109 Kyrgyzstan 150 32.3 25.6 81.0 81.2 60.9 83.8 47.8 97 98

l

82 0.635

110 South Africa 400 59.2 33.9 66.3 68.0 51.0 67.0 60.3 92 91 j

103 0.687

111 Syrian Arab Republic 130 61.1 12.4 24.7 24.1 22.0 82.1 58.3 84 93 j

65 0.568

112 Tajikistan 170 28.4 19.6 93.2 85.8 59.1 79.8 37.9 89 83 j

58 0.530

113 Viet Nam 150 16.6 25.8 24.7 28.0 74.2 80.6 79.0 91 88

104 0.693

114 Morocco 240 18.9 6.2 20.1 36.4 28.7 83.6 63.0 68 63

97 0.674

115 Nicaragua 170 112.7 18.5 30.8 44.7 48.6 81.9 72.4 90 74

107 0.713

116 Guatemala 290 107.2 12.0 16.0 21.2 50.0 89.9 43.3 84 41 j

.. ..

117 Equatorial Guinea 680 122.8 6.0 .. .. 39.4 94.0 10.1 86 63 j

.. ..

118 Cape Verde 210 94.9 18.1 .. .. 56.2 82.7 61.3 98 78 j

122 0.748

119 India 450 68.1 9.2 26.6 50.4 35.7 84.5 56.3 74 47

.. ..

120 Timor-Leste 380 53.8 29.2 .. .. 61.6 84.8 10.0 61 19 j

93 0.668

121 Swaziland 390 83.9 22.1 49.9 46.1 55.2 75.8 50.6 85 74 j

88 0.650

122 Lao People’s Democratic Republic 660 37.4 25.2 22.9 36.8 81.4 80.6 32.2 35 20 e

.. ..

123 Solomon Islands 220 41.8 0.0 .. .. 24.6 50.4 .. 74 43

95 0.672

124 Cambodia 540 39.2 15.8 11.6 20.6 75.6 85.5 40.0 69 44

112 0.721

125 Pakistan 320 45.7 21.2 23.5 46.8 21.8 86.7 29.6 61 39 j

121 0.744

126 Congo 740 112.8 9.2 43.8 48.7 62.4 83.6 44.3 86 86

.. ..

127 São Tomé and Príncipe .. 66.1 7.3 .. .. 46.9 78.5 29.3 98 81

LOW HUMAN DEVELOPMENT 117 0.738

128 Kenya 560 103.5 9.8 20.1 38.6 77.6 88.9 39.3 92 42 j

116 0.734

129 Bangladesh 570 71.6 6.3 30.8 39.3 61.4 85.5 55.8 51 18

114 0.729

130 Ghana 560 64.0 7.9 33.9 83.1 75.2 75.6 23.5 90 57

129 0.763

131 Cameroon 1000 127.5 13.9 21.1 34.9 54.0 82.2 29.2 82 63

.. ..

132 Myanmar 380 18.4 .. 18.0 17.6 64.2 86.7 37.0 76 57

138 0.853

133 Yemen 430 68.1 0.7 7.6 24.4 20.1 74.3 27.7 47 36 j

127 0.759

134 Benin 840 111.8 10.8 11.3 25.9 68.1 79.0 17.0 84 78 j

.. ..

135 Madagascar 510 132.8 9.4 .. .. 86.0 89.3 27.1 80 51 j

118 0.738

136 Mauritania 820 90.0 19.9 8.0 20.8 60.4 82.2 9.3 75 61 e

133 0.784

137 Papua New Guinea 470 55.0 0.9 12.4 24.4 72.1 74.2 .. 79 39

110 0.716

138 Nepal 830 101.4 33.2 17.9 39.9 65.9 81.9 48.0 44 19 j

115 0.731

139 Togo 510 64.8 11.1 15.3 45.1 64.6 86.4 16.8 84 62 j

.. ..

140 Comoros 400 45.7 3.0 .. .. 74.6 85.9 25.7 75 62 j

102 0.685

141 Lesotho 960 73.5 25.8 24.3 20.3 71.9 78.7 37.3 90 55 j

.. ..

142 Nigeria 1100 126.6 7.3 .. .. 39.5 74.8 14.7 58 39

109 0.715

143 Uganda 550 150.0 30.7 9.1 20.8 80.5 91.2 23.7 94 42 j

113 0.727

144 Senegal 980 104.4 29.2 10.9 19.4 65.3 89.9 11.8 87 52 j

119 0.739

145 Haiti 670 46.4 5.2 22.5 36.3 58.4 83.0 32.0 85 26 j

.. ..

146 Angola 1400 123.7 37.3 .. .. 76.3 89.2 6.2 80 47 j

.. ..

147 Djibouti 650 23.0 13.9 .. .. 63.2 80.3 17.8 92 93 j

.. ..

148 Tanzania, United Republic of 950 130.4 30.4 .. .. 88.8 91.1 26.4 76 46

158 human development report 2010 Gender Inequality Index

Population

with at least

secondary Labour force Births attended

Antenatal

Contraceptive

education participation

Gender Maternal Adolescent Seats in by skilled health

coverage of at

prevalence rate,

rate

Inequality mortality fertility parliament (% ages 25

a b c personnel

least one visit

any method

Index ratio rate (%)

and older)

(%) (% of married

HDI rank Rank Value Female Female Male Female Male women ages 15–49) (%) (%)

d d d d d

2008 2008 2003–2008 1990–2008 2008 2010 2010 2008 2008 1990–2008 1990–2008 2000–2008

130 0.765

149 Côte d’Ivoire 810 129.9 8.9 13.6 25.2 51.3 82.4 12.9 85 57 j

124 0.752

150 Zambia 830 141.8 15.2 25.7 44.2 60.4 78.7 40.8 94 47 j

120 0.742

151 Gambia 690 88.1 9.4 16.5 31.6 71.2 85.1 17.5 98 57 j

83 0.638

152 Rwanda 1300 36.7 50.9 7.4 8.0 87.9 85.9 36.4 96 52 table

126 0.758

153 Malawi 1100 135.2 13.0 10.4 20.4 74.6 77.7 41.0 92 54 4

j

106 0.708

154 Sudan 450 56.8 16.8 12.8 18.2 32.3 74.0 7.6 64 49

134 0.797

155 Afghanistan 1800 121.3 25.9 5.8 34.0 33.3 85.5 18.6 16 14

m j

.. .. .. .. 82.3 90.0 9.1 88 38

156 Guinea 910 152.3 ..

.. ..

157 Ethiopia 720 104.4 21.4 .. .. 80.8 91.1 14.7 28 6 j

125 0.756

158 Sierra Leone 2100 126.0 13.2 9.5 20.4 67.1 68.1 8.2 87 42 j

132 0.768

159 Central African Republic 980 106.6 10.5 10.3 26.2 71.6 86.9 19.0 69 54 j

135 0.799

160 Mali 970 162.9 10.2 3.2 8.4 38.1 68.9 8.2 70 49

.. ..

161 Burkina Faso 700 130.9 15.3 .. .. 79.7 91.5 17.4 85 54

131 0.766

162 Liberia 1200 141.6 13.8 15.7 39.2 69.1 76.8 11.4 79 46

.. ..

163 Chad 1500 164.4 5.2 .. .. 64.0 78.3 2.8 39 14 j

.. ..

164 Guinea-Bissau 1100 129.2 10.0 .. .. 61.2 85.4 10.3 78 39 j

111 0.718

165 Mozambique 520 149.2 34.8 1.5 6.0 85.7 86.6 16.5 89 48

79 0.627

166 Burundi 1100 18.6 31.7 5.2 9.2 91.5 88.3 19.7 92 34

136 0.807

167 Niger 1800 157.4 12.4 2.5 7.6 37.9 88.1 11.2 46 18 j

137 0.814

168 Congo, Democratic Republic of the 1100 201.4 7.7 10.7 36.2 57.4 86.8 20.6 85 74

105 0.705

169 Zimbabwe 880 64.6 18.2 48.8 62.0 60.8 74.5 60.2 94 69

OTHER COUNTRIES OR TERRITORIES .. ..

Antigua and Barbuda .. .. 16.7 .. .. .. .. .. 100 100

.. ..

Bhutan 440 38.3 13.9 .. .. 54.1 71.9 30.7 88 51

47 0.473

Cuba 45 45.2 43.2 73.9 80.4 48.6 77.0 72.6 100 100

h h

.. .. 23.2 .. .. .. 100 94

Dominica .. .. 18.8 29.7 j

.. ..

Eritrea 450 66.9 22.0 .. .. 61.6 84.4 8.0 70 28

.. ..

Grenada .. 42.4 21.4 .. .. .. .. .. 100 99

123 0.751

Iraq 300 85.5 25.5 22.0 42.7 14.2 71.5 49.8 84 89

.. ..

Kiribati .. .. 4.4 .. .. .. .. 36.1 .. 90

.. ..

Korea, Democratic People’s Rep. of 370 0.0 20.1 .. .. 60.7 80.7 68.6 .. 97

.. ..

Lebanon 150 16.2 4.7 .. .. 24.1 74.8 58.0 96 98

.. ..

Marshall Islands .. .. 3.0 .. .. .. .. .. 81 95

.. ..

Monaco .. .. 25.0 .. .. .. .. .. .. ..

.. ..

Nauru .. .. 0.0 .. .. .. .. 35.6 95 97

.. ..

Occupied Palestinian Territories .. 78.7 .. .. .. 16.7 72.4 50.2 .. ..

.. ..

Oman 64 10.4 9.1 .. .. 26.1 79.1 .. 100 98

.. ..

Palau .. .. 6.9 .. .. .. .. 32.8 .. 100

.. ..

Saint Kitts and Nevis .. .. 6.7 .. .. .. .. .. 100 100

.. ..

Saint Lucia .. 61.6 17.2 .. .. 55.3 80.4 .. 99 98

.. ..

Saint Vincent and the Grenadines .. 58.9 18.2 .. .. 61.4 84.1 .. 95 100

.. ..

Samoa .. 27.6 8.2 .. .. 41.8 79.5 .. .. 100

.. ..

San Marino .. .. 15.0 .. .. .. .. .. .. ..

h h

.. .. 66.6 .. .. .. .. ..

Seychelles .. .. 23.5 66.9 j

.. ..

Somalia 1400 70.1 8.2 .. .. 58.0 86.0 14.6 26 33

.. ..

Tuvalu .. .. 0.0 .. .. .. .. .. 97 100

.. ..

Vanuatu .. 47.0 3.9 .. .. 79.7 88.6 .. 84 93 159

## STATISTICAL ANNEX

Gender Inequality Index Population

with at least

secondary Labour force Births attended

Antenatal

Contraceptive

education participation

Gender Maternal Adolescent Seats in by skilled health

coverage of at

prevalence rate,

rate

Inequality mortality fertility parliament (% ages 25

a b c personnel

least one visit

any method

Index ratio rate (%)

and older)

(%) (% of married

HDI rank Rank Value Female Female Male Female Male women ages 15–49) (%) (%)

d d d d d

2008 2008 2003–2008 1990–2008 2008 2010 2010 2008 2008 1990–2008 1990–2008 2000–2008

Developed — 0.317

OECD 8 19.4 20.6 84.0 86.6 65.5 80.1 .. .. 99

— 0.376

Non-OECD 16 11.2 18.1 70.4 72.1 58.2 82.3 .. 100 100

table

4 Developing — 0.699

Arab States 238 42.6 8.7 31.8 45.0 27.0 78.2 46.9 74 77

— 0.467

East Asia and the Pacific 126 18.1 19.8 48.2 61.4 70.1 84.5 .. 91 91

— 0.498

Europe and Central Asia 41 28.2 12.5 78.0 74.0 58.6 75.0 63.0 95 96

— 0.609

Latin America and the Caribbean 122 72.6 17.5 51.3 52.7 55.3 83.3 .. 95 91

— 0.739

South Asia 454 65.0 10.4 27.4 49.1 37.2 84.2 53.8 70 45

— 0.735

Sub-Saharan Africa 881 122.3 17.3 23.9 38.1 63.8 82.3 23.6 73 48

— 0.319

Very high human development 8 19.1 20.5 83.7 86.1 65.3 80.2 .. 100 99

— 0.571

High human development 82 47.7 13.3 61.2 61.3 52.7 79.5 66.3 95 96

— 0.591

Medium human development 242 41.8 16.0 40.9 57.4 54.7 84.1 68.4 84 74

— 0.748

Low human development 822 108.9 14.4 19.0 32.0 61.3 83.4 27.8 66 39

— 0.746

Least developed countries 786 104.5 16.6 17.8 29.1 64.7 85.2 29.5 63 36

— 0.560

World 273 53.7 16.2 51.6 61.7 56.8 82.6 .. 82 75

Notes

a i

See Technical note 3 for details on how the Gender Inequality Index is calculated. No women were elected in the 2008 elections; however, two women were

b Defined as maternal deaths per 100,000 live births. appointed to the cabinet in June 2008, and cabinet ministers also sit in parliament.

c j

Defined as the number of births per 1,000 women ages 15–19. Includes deliveries by cadres of health workers other than doctors, nurses and

d Data refer to the most recent year available during the period specified. midwives.

e k

Institutional births. No women were elected in 2008; however, one woman was appointed to the

f The denominator of the calculation refers to voting members of the House of cabinet, and cabinet ministers also sit in parliament.

l

Representatives only. Does not include the 36 special rotating delegates appointed on an ad hoc basis; all

g World Health Organization estimate. percentages are calculated based on the 54 permanent seats.

h m

United Nations Educational, Scientific and Cultural Organization Institute for The parliament was dissolved following the December 2008 coup.

Statistics estimate.

Sources

Columns 1 and 2: Calculated based on data from UNICEF (2010c), UNDESA (2009d),

IPU (2010), Barro and Lee (2010) and ILO (2010d).

Columns 3 and 11: UNICEF (2010c).

Column 4: UNDESA (2009d).

Column 5: IPU (2010).

Columns 6 and 7: Barro and Lee (2010).

Columns 8 and 9: ILO (2010d).

Column 10: UN (2009).

Column 12: WHO (2010).

160 human development report 2010

5

e

l Multidimensional Poverty Index

b

ta Population in Population with at Population below

Population

multidimensional poverty least one severe deprivation in income poverty line

at risk of

multidimensional

Intensity of Living PPP $1.25 National b b d d d b,c poverty deprivation standards a day poverty line Headcount Education Health Multidimensional a,b Poverty Index HDI rank (%) (%) (%) (%) (%) (%) (%) (%) e e e e e e e e e 2000–2008 2000–2008 2000–2008 2000–2008 2000–2008 2000–2008 2000–2008 2000–2008 2000–2008 ## VERY HIGH HUMAN DEVELOPMENT 0.000 28 Czech Republic 0.0 46.7 3.1 0.0 3.1 0.0 .. .. .. 29 Slovenia 0.0 0.0 0.4 0.0 3.1 0.0 <2 .. 0.000 31 Slovakia 0.0 0.0 0.0 0.0 3.8 0.0 .. 16.8 0.002 32 United Arab Emirates 0.6 35.3 2.0 0.6 5.4 0.0 .. .. 0.026 34 Estonia 7.2 36.5 1.3 7.3 5.1 0.1 <2 .. 0.003 36 Hungary 0.8 38.9 3.8 0.1 4.5 0.0 <2 .. .. 41 Poland .. .. .. .. .. .. <2 14.8 HIGH HUMAN DEVELOPMENT .. 44 Lithuania .. .. .. .. .. .. <2 .. .. 45 Chile .. .. .. .. .. .. <2 .. f f f f f f f 0.011 3.0 37.7 5.7 15.4 3.8 4.7 3.4 .. 46 Argentina 0.001 48 Latvia 0.3 46.7 1.3 0.1 1.6 1.1 <2 5.9 0.006 49 Montenegro 1.5 41.6 1.9 4.2 0.8 0.7 <2 .. .. 50 Romania .. .. 2.8 .. .. .. <2 28.9 0.007 51 Croatia 1.6 41.6 .. 2.3 2.4 0.4 <2 11.1 0.006 52 Uruguay 1.7 34.7 0.1 1.7 5.1 0.0 <2 .. .. 54 Panama .. .. .. .. .. .. 9.5 36.8 0.015 56 Mexico 4.0 38.9 5.8 10.1 9.2 6.7 4.0 47.0 .. 57 Malaysia .. .. .. .. .. .. <2 .. .. 58 Bulgaria .. .. .. .. .. .. <2 12.8 0.020 59 Trinidad and Tobago 5.6 35.1 0.4 1.5 5.6 0.8 .. .. 0.003 60 Serbia 0.8 40.0 3.6 5.2 0.4 0.8 <2 .. 0.000 61 Belarus 0.0 35.1 0.8 2.0 3.1 0.1 <2 17.4 .. 62 Costa Rica .. .. .. .. .. .. <2 23.9 0.085 63 Peru 19.8 43.1 17.1 8.5 14.6 38.2 7.7 51.6 0.004 64 Albania 1.0 38.1 9.4 6.6 7.2 0.9 <2 18.5 0.005 65 Russian Federation 1.3 38.9 0.8 1.6 3.5 0.4 <2 19.6 0.002 66 Kazakhstan 0.6 36.9 5.0 1.3 9.8 1.1 <2 15.4 0.021 67 Azerbaijan 5.4 38.6 12.4 10.2 20.3 4.2 <2 49.6 0.003 68 Bosnia and Herzegovina 0.8 37.2 7.0 11.1 0.4 0.8 <2 19.5 0.008 69 Ukraine 2.2 35.7 1.2 6.2 2.1 0.2 <2 19.5 .. <2 .. 70 Iran, Islamic Republic of .. .. .. .. .. .. 0.008 71 The former Yugoslav Republic of Macedonia 1.9 40.9 6.7 5.9 7.2 0.9 <2 21.7 0.039 73 Brazil 8.5 46.0 13.1 20.2 5.2 2.8 5.2 21.5 0.003 74 Georgia 0.8 35.2 5.3 2.4 5.9 4.6 13.4 54.5 .. 75 Venezuela, Bolivarian Republic of .. .. .. .. .. .. 3.5 .. 0.008 76 Armenia 2.3 36.5 5.5 9.5 14.6 0.8 3.7 50.9 0.009 77 Ecuador 2.2 41.6 2.1 2.3 4.6 3.9 4.7 38.3 0.024 78 Belize 5.6 42.6 7.6 8.5 13.3 7.0 .. .. 0.041 79 Colombia 9.2 44.1 8.3 13.2 17.5 9.7 16.0 45.1 .. 80 Jamaica .. .. .. .. .. .. <2 18.7 0.010 81 Tunisia 2.8 37.1 4.9 1.1 13.1 6.9 2.6 .. 0.010 82 Jordan 2.7 35.5 1.6 10.6 11.9 0.2 <2 14.2 0.039 83 Turkey 8.5 45.9 19.0 15.4 16.0 7.3 2.6 27.0 161 ## STATISTICAL ANNEX Multidimensional Poverty Index Population in Population with at Population below Population multidimensional poverty least one severe deprivation in income poverty line at risk of multidimensional Intensity of Living PPP$1.25 National

b b d d d

b,c

poverty

deprivation standards a day poverty line

Multidimensional

a,b

Poverty Index

HDI rank (%) (%) (%) (%) (%) (%) (%) (%)

e e e e e e e e e

2000–2008 2000–2008 2000–2008 2000–2008 2000–2008 2000–2008 2000–2008 2000–2008 2000–2008

MEDIUM HUMAN DEVELOPMENT 0.048

88 Dominican Republic 11.1 43.3 13.2 17.5 13.1 13.2 4.4 48.5

0.056

89 China 12.5 44.9 6.3 10.9 11.3 12.4 15.9 2.8

..

90 El Salvador .. .. .. .. .. .. 6.4 30.7

0.021

91 Sri Lanka 5.3 38.7 14.4 0.5 9.8 26.4 14 22.7

0.006

92 Thailand 1.7 38.5 9.9 12.6 5.6 1.5 <2 ..

0.161

93 Gabon 35.4 45.5 22.4 19.2 35.4 34.8 4.8 ..

0.044

94 Suriname 7.5 58.8 5.2 18.8 15.9 2.3 .. ..

0.175

95 Bolivia, Plurinational State of 36.3 48.3 21.6 37.8 31.4 38.0 11.7 37.7

table 0.064

96 Paraguay 13.3 48.5 15.0 7.5 13.1 32.4 6.5 ..

5 0.067

97 Philippines 12.6 53.5 11.1 13.6 14.2 18.2 22.6 ..

0.008

99 Moldova, Republic of 2.2 37.6 7.2 5.1 10.1 5.3 2.4 48.5

0.065

100 Mongolia 15.8 41.0 20.7 6.8 19.0 39.6 2.2 36.1

0.026

101 Egypt 6.4 40.4 6.9 18.0 16.9 0.9 <2 16.7

0.008

102 Uzbekistan 2.3 36.2 8.1 4.4 17.4 2.3 46.3 27.2

0.055

104 Guyana 13.8 39.7 6.5 4.7 12.4 10.8 .. ..

0.187

105 Namibia 39.6 47.2 23.5 16.0 37.2 60.8 .. ..

0.160

106 Honduras 32.6 48.9 17.8 46.6 21.1 30.8 18.2 50.7

0.095

108 Indonesia 20.8 45.9 12.2 12.6 14.4 31.2 29.4 16.7

0.019

109 Kyrgyzstan 4.9 38.8 9.2 18.7 2.1 8.3 3.4 43.1

0.014

110 South Africa 3.1 46.7 3.9 3.2 8.1 10.8 26.2 22.0

0.021

111 Syrian Arab Republic 5.5 37.5 7.1 20.4 13.6 1.3 .. ..

0.068

112 Tajikistan 17.1 40.0 23.1 14.3 35.6 21.9 21.5 53.5

0.075

113 Viet Nam 14.3 52.5 12.0 12.3 10.8 30.1 21.5 28.9

0.139

114 Morocco 28.5 48.8 11.4 36.3 31.5 21.4 2.5 ..

0.211

115 Nicaragua 40.7 51.9 15.7 36.4 25.9 54.1 15.8 45.8

0.127

116 Guatemala 25.9 49.1 9.8 26.8 15.0 40.5 11.7 51.0

..

118 Cape Verde .. .. .. .. .. .. 20.6 ..

0.296

119 India 55.4 53.5 16.1 37.5 56.5 58.5 41.6 28.6

..

120 Timor-Leste .. .. .. .. .. .. 37.2 39.7

0.183

121 Swaziland 41.1 44.4 24.5 25.9 33.5 66.3 62.9 69.2

0.267

122 Lao People’s Democratic Republic 47.3 56.5 14.1 43.9 22.3 59.7 44.0 33.5

0.263 40.9 36.0 78.4 25.8 30.1

124 Cambodia 53.9 48.9 20.2

g g g g g

0.275 51.0 54.0 11.8 51.2 29.2 42.9 22.6 ..

125 Pakistan 0.270

126 Congo 55.9 48.4 22.5 21.7 47.6 73.8 54.1 42.3

0.236

127 São Tomé and Príncipe 51.6 45.8 23.9 36.7 26.6 74.3 28.4 ..

LOW HUMAN DEVELOPMENT 0.302

128 Kenya 60.4 50.0 23.2 21.9 41.4 86.2 19.7 46.6

0.291

129 Bangladesh 57.8 50.4 21.2 31.4 53.1 76.3 49.6 40.0

0.140

130 Ghana 30.1 46.4 21.4 24.1 17.9 57.5 30 28.5

0.299

131 Cameroon 54.6 54.7 18.3 37.4 42.6 67.9 32.8 39.9

0.088

132 Myanmar 14.2 62.0 17.6 32.7 11.7 22.8 .. 32.0

0.283

133 Yemen 52.5 53.9 13.0 54.5 34.4 38.2 17.5 ..

0.412

134 Benin 72.0 57.3 13.2 62.8 51.7 79.1 47.3 39.0

0.413

135 Madagascar 70.5 58.5 14.8 55.4 49.6 83.7 67.8 68.7

0.352

136 Mauritania 61.7 57.1 15.1 55.3 44.1 66.8 21.2 46.3

0.350

138 Nepal 64.7 54.1 15.6 38.0 58.3 77.2 55.1 30.9

0.284

139 Togo 54.3 52.4 21.6 39.9 38.0 75.5 38.7 ..

0.408

140 Comoros 73.9 55.3 16.0 60.1 45.7 90.3 46.1 ..

0.220

141 Lesotho 48.1 45.8 27.5 29.7 22.1 82.4 43.4 56.3

0.368

142 Nigeria 63.5 57.9 15.7 42.4 59.5 72.1 64.4 ..

..

143 Uganda .. .. .. .. .. .. 51.5 31.1

0.384

144 Senegal 66.9 57.4 11.6 66.9 54.3 54.9 33.5 ..

0.306

145 Haiti 57.3 53.3 18.4 41.0 37.3 76.0 54.9 ..

0.452

146 Angola 77.4 58.4 10.7 56.9 60.8 82.0 54.3 ..

0.139

147 Djibouti 29.3 47.3 16.1 39.3 25.6 28.1 18.4 ..

162 human development report 2010 Multidimensional Poverty Index

Population in Population with at Population below

Population

multidimensional poverty least one severe deprivation in income poverty line

at risk of

multidimensional

Intensity of Living PPP $1.25 National b b d d d b,c poverty deprivation standards a day poverty line Headcount Education Health Multidimensional a,b Poverty Index HDI rank (%) (%) (%) (%) (%) (%) (%) (%) e e e e e e e e e 2000–2008 2000–2008 2000–2008 2000–2008 2000–2008 2000–2008 2000–2008 2000–2008 2000–2008 0.367 148 Tanzania, United Republic of 65.3 56.3 23.0 34.0 35.5 90.6 88.5 35.7 0.320 149 Côte d’Ivoire 52.2 61.4 16.4 62.7 40.6 37.7 23.3 .. 0.325 150 Zambia 63.7 51.1 17.8 30.1 51.3 78.3 64.3 68.0 0.324 151 Gambia 60.4 53.6 17.6 53.4 52.1 60.1 34.3 61.3 0.443 152 Rwanda 81.4 54.4 14.0 53.6 46.1 95.3 76.6 56.9 0.384 153 Malawi 72.3 53.2 19.8 43.6 45.2 93.9 73.9 52.4 .. 155 Afghanistan .. .. .. .. .. .. .. 42.0 0.505 156 Guinea 82.4 61.3 9.4 74.8 60.8 84.4 70.1 .. 0.582 157 Ethiopia 90.0 64.7 5.2 83.9 48.2 94.2 39 44.2 0.489 158 Sierra Leone 81.5 60.0 11.1 60.6 58.2 92.4 53.4 70.2 table 0.512 159 Central African Republic 86.4 59.3 7.6 72.7 56.2 92.3 62.4 .. 5 0.564 160 Mali 87.1 64.7 7.3 81.1 65.8 86.8 51.4 .. 0.536 161 Burkina Faso 82.6 64.9 8.6 80.4 62.9 81.6 56.5 46.4 0.484 162 Liberia 83.9 57.7 9.5 68.9 59.6 91.6 83.7 .. 0.344 163 Chad 62.9 54.7 28.2 39.4 8.2 95.2 61.9 .. .. 164 Guinea-Bissau .. .. .. .. .. .. 48.8 65.7 0.481 165 Mozambique 79.8 60.3 9.8 69.1 52.7 86.4 74.7 55.2 0.530 166 Burundi 84.5 62.7 12.2 71.6 35.5 97.3 81.3 .. 0.642 167 Niger 92.7 69.3 4.0 87.1 64.9 93.0 65.9 .. 0.393 168 Congo, Democratic Republic of the 73.2 53.7 16.1 48.4 48.2 85.5 59.2 71.3 0.174 169 Zimbabwe 38.5 45.2 24.6 15.1 29.6 64.5 .. .. ## OTHER COUNTRIES OR TERRITORIES .. Bhutan .. .. .. .. .. .. 26.3 .. 0.059 Iraq 14.3 41.3 14.3 32.0 20.0 5.2 .. .. 0.003 Occupied Palestinian Territories 0.7 38.2 12.7 14.6 2.8 0.8 .. .. .. Seychelles .. .. .. .. .. .. <2 .. 0.514 Somalia 81.2 63.3 9.5 74.5 47.6 86.7 .. .. Notes a e See Technical note 4 for details on how the Multidimensional Poverty Index is Data refer to the most recent year available during the period specified. f calculated. Estimates are for parts of the country only. b g Not all indicators were available for all countries; caution should thus be used Estimates should be interpreted as a lower bound because data on nutrition were in cross-country comparisons. Where data are missing, indicator weights are not available from the dataset used. adjusted to total 100 percent. For details on countries missing data, see Alkire and Santos (2010). c Additional number of people suffering overlapping deprivation when cutoff is set at two of the weighted indicators (K=2), expressed as a percentage of the population. d Percentage of the population suffering a deprivation in at least 1.5 of the weighted indicators in health, education or living standards. For details see Alkire and Santos (2010). Sources Columns 1, 2 and 4–7: Calculated based on data on household deprivation in health, education and living standards from various household surveys. Column 3: Based on various household surveys (Measure DHS Demographic and Health Surveys, United Nations Children’s Fund Multiple Indicator Cluster Surveys and World Health Organization World Health Surveys) conducted between 2000 and 2008. Columns 8 and 9: World Bank (2010c). 163 ## STATISTICAL ANNEX 6 e l Empowerment b ta Agency Political freedom Civil liberties Accountability Satisfaction with freedom of choice Human rights Press Journalists Corruption Democratic Political Democracy violations freedom imprisoned victims decentralization engagement (% satisfied) (% of people who faced a (% of people who voiced a b c d e HDI rank Total Female Score (0–2) bribe situation in the last year) Score (0–2) opinion to public officials) Score (1–5 ) (index) (number) 2009 2009 2008 2008 2009 2009 2008 2008 2008 ## VERY HIGH HUMAN DEVELOPMENT 1 Norway 93 93 2 .. 0.0 0 5 2 31 2 Australia 91 90 2 1 3.1 0 8 1 23 3 New Zealand 89 90 2 1 3.0 0 9 2 23 4 United States 83 85 2 3 4.0 0 9 2 32 5 Ireland 82 83 2 1 0.0 0 7 2 26 6 Liechtenstein .. .. 2 .. .. 0 .. .. .. 7 Netherlands 87 88 2 1 1.0 0 4 1 30 8 Canada 91 92 2 2 3.7 0 8 2 20 9 Sweden 90 81 2 1 0.0 0 6 2 29 10 Germany 85 86 2 1 3.5 0 4 2 35 11 Japan 70 75 2 1 3.3 0 3 2 22 12 Korea, Republic of 55 56 2 2 15.7 0 10 1 22 13 Switzerland 90 87 2 2 1.0 0 .. 2 36 14 France 79 78 2 2 10.7 0 6 2 23 f 23.8 0 11 .. 18 15 Israel 64 58 2 3 16 Finland 92 93 2 1 0.0 0 9 1 19 17 Iceland 86 87 2 .. 2.0 0 5 2 25 18 Belgium 86 85 2 2 2.5 0 6 .. 23 19 Denmark 96 93 2 2 0.0 0 5 2 37 20 Spain 70 70 2 3 11.0 0 6 2 17 21 Hong Kong, China (SAR) 90 90 .. .. 11.8 0 3 .. 5 22 Greece 43 39 2 3 9.0 0 15 2 16 23 Italy 63 60 2 2 12.1 0 6 2 14 24 Luxembourg 93 90 2 .. 4.0 0 4 .. 36 25 Austria 85 86 2 1 3.0 0 5 .. 36 26 United Kingdom 81 82 2 2 4.0 0 4 2 24 27 Singapore 73 73 1 1 45.0 0 1 0 12 28 Czech Republic 73 71 2 1 5.0 0 .. .. 27 29 Slovenia 89 88 2 1 9.5 0 9 .. 36 30 Andorra .. .. 2 .. .. 0 .. .. .. 31 Slovakia 49 51 2 1 11.0 0 .. 2 14 16 32 United Arab Emirates 83 85 0 2 21.5 0 20 0 33 Malta 76 73 2 2 2.5 0 5 1 21 34 Estonia 53 53 2 2 0.5 0 9 .. 16 35 Cyprus 74 73 2 1 5.5 0 18 2 16 36 Hungary 43 44 2 1 5.5 0 34 2 15 37 Brunei Darussalam .. .. .. .. .. 0 .. .. .. 38 Qatar 77 72 0 2 24.0 0 8 1 24 39 Bahrain .. 89 0 2 36.5 0 20 1 .. 40 Portugal 60 67 2 2 8.0 0 6 2 23 41 Poland 74 68 2 1 9.5 0 8 2 5 42 Barbados .. .. 2 .. .. 0 .. .. .. 164 human development report 2010 Empowerment Agency Political freedom Civil liberties Accountability Satisfaction with freedom of choice Human rights Press Journalists Corruption Democratic Political Democracy violations freedom imprisoned victims decentralization engagement (% satisfied) (% of people who faced a (% of people who voiced a b c d e HDI rank Total Female Score (0–2) bribe situation in the last year) Score (0–2) opinion to public officials) Score (1–5 ) (index) (number) 2009 2009 2008 2008 2009 2009 2008 2008 2008 ## HIGH HUMAN DEVELOPMENT 43 Bahamas .. .. 2 2 .. 0 .. .. .. 44 Lithuania 45 47 2 1 2.3 0 21 2 11 45 Chile 72 74 2 2 10.5 0 8 1 26 46 Argentina 62 59 2 2 11.3 0 8 .. 11 47 Kuwait 80 78 0 1 15.3 0 19 1 24 48 Latvia 39 41 2 2 3.0 0 22 .. 17 49 Montenegro 47 50 1 2 17.0 0 .. .. 13 50 Romania 54 52 2 3 12.5 0 36 2 9 51 Croatia 62 48 2 1 17.2 0 .. .. 19 52 Uruguay 80 80 2 1 7.6 0 5 .. 19 53 Libyan Arab Jamahiriya .. .. 0 3 64.5 0 .. 2 .. table 54 Panama 68 64 2 .. 14.5 0 6 1 30 6 55 Saudi Arabia 60 52 0 4 76.5 1 29 0 22 56 Mexico 66 66 2 4 48.3 0 11 2 22 57 Malaysia 83 83 1 2 44.3 0 4 .. 11 58 Bulgaria 48 45 2 2 15.6 0 .. 2 14 59 Trinidad and Tobago 81 83 2 3 7.0 0 4 .. 12 60 Serbia 42 37 2 .. 15.5 0 .. .. 12 61 Belarus 56 57 0 3 59.5 0 22 0 11 62 Costa Rica 87 87 2 .. 8.0 0 9 2 31 63 Peru 59 57 2 2 20.9 0 12 1 18 64 Albania 47 43 2 2 21.8 0 .. 2 14 65 Russian Federation 50 51 1 4 60.9 1 21 .. 13 66 Kazakhstan 71 69 1 3 49.7 1 23 .. 11 67 Azerbaijan 45 45 1 2 53.5 6 36 1 25 68 Bosnia and Herzegovina 32 25 0 2 10.5 0 .. 2 8 69 Ukraine 38 38 2 3 22.0 0 23 .. 13 70 Iran, Islamic Republic of 57 59 0 4 104.1 23 19 1 19 71 The former Yugoslav Republic of Macedonia 42 51 2 2 8.8 0 .. 2 12 72 Mauritius .. .. 2 .. 14.0 0 .. 2 .. 73 Brazil 76 73 2 4 15.9 0 5 2 19 74 Georgia 43 40 2 3 18.8 0 2 .. 23 75 Venezuela, Bolivarian Republic of 65 61 2 3 39.5 1 7 2 20 76 Armenia 39 39 2 3 31.1 0 17 2 12 77 Ecuador 73 71 2 2 20.0 0 7 2 15 78 Belize 62 62 2 .. .. 0 .. 0 22 79 Colombia 75 75 2 5 40.1 0 11 2 29 80 Jamaica 73 74 2 4 4.8 0 .. .. 15 81 Tunisia 70 76 1 3 61.5 2 14 2 16 82 Jordan 75 76 0 4 31.9 0 5 1 14 83 Turkey 38 46 2 3 38.3 1 13 2 12 84 Algeria 50 58 1 3 49.6 0 28 1 16 85 Tonga .. .. 1 .. .. 0 .. .. .. ## MEDIUM HUMAN DEVELOPMENT 86 Fiji .. .. 0 1 60.0 0 .. .. .. 87 Turkmenistan .. .. 0 2 107.0 0 .. 0 .. 88 Dominican Republic 83 83 2 4 26.8 0 12 2 16 89 China 70 68 0 4 84.5 24 .. 2 .. 90 El Salvador 64 63 2 2 17.3 0 6 2 14 91 Sri Lanka 74 74 2 4 75.0 1 5 2 12 92 Thailand 84 86 2 3 44.0 0 13 2 29 93 Gabon .. .. 1 .. 43.5 0 .. 2 .. 94 Suriname .. .. 2 1 10.6 0 .. .. .. 95 Bolivia, Plurinational State of 74 69 2 3 24.2 0 18 2 27 165 ## STATISTICAL ANNEX Empowerment Agency Political freedom Civil liberties Accountability Satisfaction with freedom of choice Human rights Press Journalists Corruption Democratic Political Democracy violations freedom imprisoned victims decentralization engagement (% satisfied) (% of people who faced a (% of people who voiced a b c d e HDI rank Total Female Score (0–2) bribe situation in the last year) Score (0–2) opinion to public officials) Score (1–5 ) (index) (number) 2009 2009 2008 2008 2009 2009 2008 2008 2008 96 Paraguay 69 67 2 3 14.3 0 10 .. 10 97 Philippines 87 87 2 4 38.3 0 13 2 24 98 Botswana 84 84 1 .. 15.5 0 10 1 18 99 Moldova, Republic of 48 46 2 3 33.8 0 34 .. 20 100 Mongolia 42 40 2 3 23.3 0 20 1 25 101 Egypt 60 55 1 4 51.4 3 24 0 12 102 Uzbekistan 76 71 1 3 67.7 7 12 1 23 103 Micronesia, Federated States of .. .. 2 .. .. 0 .. .. .. 104 Guyana 66 65 1 .. 10.5 0 .. 2 19 105 Namibia 76 75 1 1 9.0 0 .. .. 23 106 Honduras 64 64 2 2 42.0 0 9 2 13 107 Maldives .. .. 2 1 14.0 0 .. .. .. 108 Indonesia 75 75 2 3 28.5 0 4 2 11 table 109 Kyrgyzstan 63 64 2 1 40.0 0 24 1 12 6 110 South Africa 73 70 1 3 8.5 0 13 2 24 111 Syrian Arab Republic 72 66 0 4 78.0 1 24 .. 10 112 Tajikistan 59 65 1 2 32.0 0 17 1 19 113 Viet Nam 73 74 0 3 81.7 1 9 2 16 114 Morocco 71 81 0 3 41.0 1 24 0 6 115 Nicaragua 74 76 2 2 16.8 0 13 2 14 116 Guatemala 63 63 2 2 29.5 0 12 0 23 117 Equatorial Guinea .. .. 1 3 65.5 0 .. 0 .. 118 Cape Verde .. .. 2 .. 11.0 0 .. .. .. 119 India 66 60 2 4 29.3 1 15 1 12 120 Timor-Leste .. .. 2 2 16.0 0 .. 0 .. 121 Swaziland .. .. 0 3 52.5 0 .. .. .. 122 Lao People’s Democratic Republic 84 84 0 1 92.0 0 15 1 42 123 Solomon Islands .. .. 2 1 .. 0 .. .. .. 124 Cambodia 93 91 1 2 35.2 1 11 .. 14 125 Pakistan 31 40 2 4 65.7 0 9 1 15 126 Congo 52 55 1 3 34.3 0 43 .. 25 127 São Tomé and Príncipe .. .. 2 .. .. 0 .. .. .. ## LOW HUMAN DEVELOPMENT 128 Kenya 58 61 2 4 25.0 0 32 .. 23 129 Bangladesh 62 62 0 4 37.3 0 9 0 7 130 Ghana 74 72 2 2 6.0 0 14 .. 19 131 Cameroon 69 70 1 4 30.5 1 26 .. 20 132 Myanmar .. .. 0 5 102.7 9 .. .. 6 133 Yemen 62 54 1 4 83.4 2 41 1 9 134 Benin 67 66 2 2 16.0 0 20 2 21 135 Madagascar 33 29 2 .. 45.8 0 12 2 10 136 Mauritania 69 76 0 3 28.5 1 18 .. 28 137 Papua New Guinea .. .. 2 2 14.7 0 .. 2 .. 138 Nepal 58 57 2 4 35.6 0 8 2 11 139 Togo 24 23 1 2 15.5 0 22 2 19 140 Comoros 50 40 2 .. 19.0 0 11 .. .. 141 Lesotho .. .. 1 .. 27.5 0 .. .. .. 142 Nigeria 51 47 2 4 46.0 0 27 0 30 143 Uganda 76 78 1 3 21.5 0 23 .. 21 144 Senegal 54 57 2 3 22.0 0 20 0 26 145 Haiti 42 40 1 2 15.0 0 20 .. 26 146 Angola 69 70 0 3 36.5 0 33 0 39 147 Djibouti 65 65 0 .. 31.0 0 13 .. 29 148 Tanzania, United Republic of 54 58 1 2 15.5 0 27 .. 32 149 Côte d’Ivoire 76 75 0 3 29.0 0 22 .. .. 150 Zambia 71 68 1 .. 26.8 0 17 1 16 151 Gambia .. .. 1 2 48.3 1 .. 0 .. 166 human development report 2010 Empowerment Agency Political freedom Civil liberties Accountability Satisfaction with freedom of choice Human rights Press Journalists Corruption Democratic Political Democracy violations freedom imprisoned victims decentralization engagement (% satisfied) (% of people who faced a (% of people who voiced a b c d e HDI rank Total Female Score (0–2) bribe situation in the last year) Score (0–2) opinion to public officials) Score (1–5 ) (index) (number) 2009 2009 2008 2008 2009 2009 2008 2008 2008 152 Rwanda 77 74 1 2 64.7 0 10 1 26 153 Malawi 88 88 2 2 15.5 0 10 0 26 154 Sudan 69 69 0 5 54.0 0 .. .. 38 155 Afghanistan 63 56 1 5 54.3 0 31 0 22 156 Guinea 67 63 0 4 28.5 0 .. .. 30 157 Ethiopia 35 37 1 3 49.0 4 14 1 17 158 Sierra Leone 72 73 2 3 34.0 0 15 0 41 159 Central African Republic 66 67 1 4 17.8 0 .. 0 38 160 Mali 49 63 2 2 8.0 0 23 2 16 161 Burkina Faso 57 56 1 3 15.0 0 14 1 12 162 Liberia 72 71 2 2 15.5 0 29 .. 28 163 Chad 52 41 1 5 44.5 0 16 0 22 164 Guinea-Bissau .. .. 2 1 23.5 0 .. .. .. table 165 Mozambique 51 49 1 3 19.0 0 20 1 15 6 166 Burundi 43 44 2 4 29.0 0 14 2 13 167 Niger 88 87 2 3 48.5 0 17 .. 19 168 Congo, Democratic Republic of the 54 55 1 5 53.5 0 .. 0 19 169 Zimbabwe 41 43 1 4 46.5 0 33 .. 10 ## OTHER COUNTRIES OR TERRITORIES Antigua and Barbuda .. .. 2 .. .. 0 .. .. .. Bhutan .. .. 2 .. 15.8 0 .. .. .. Cuba 26 28 0 3 94.0 22 .. 1 40 Dominica .. .. 2 .. .. 0 .. .. .. Eritrea .. .. 1 3 115.5 19 .. 0 .. Grenada .. .. 2 .. .. 0 .. .. .. Iraq 37 39 0 5 53.3 1 36 .. 21 Kiribati .. .. 2 .. .. 0 .. .. .. Korea, Democratic People’s Rep. of .. .. 0 .. 112.5 0 .. 2 .. Lebanon 66 64 0 3 15.4 0 30 1 12 Marshall Islands .. .. 2 .. .. 0 .. .. .. Monaco .. .. .. .. .. 0 .. .. .. Nauru .. .. 2 .. .. 0 .. .. .. g 69.8 0 15 .. 20 Occupied Palestinian Territories 46 47 .. 5 Oman .. .. 0 1 29.5 0 .. 0 .. 2 .. .. 0 .. .. .. Palau .. .. Saint Kitts and Nevis .. .. 2 .. .. 0 .. .. .. Saint Lucia .. .. 2 .. .. 0 .. 2 .. Saint Vincent and the Grenadines .. .. 2 .. .. 0 .. .. .. Samoa .. .. 1 .. .. 0 .. 0 .. San Marino .. .. 2 .. .. 0 .. .. .. Seychelles .. .. 1 .. 16.0 0 .. .. .. Somalia .. .. 0 5 77.5 0 .. .. .. Tuvalu .. .. 2 .. .. 0 .. .. .. Vanuatu .. .. 2 .. .. 0 .. 2 .. Notes a e g 0 is nondemocratic, 1 is democratic with no alternation, 2 is democratic. 0 is no local elections, 1 is legislature elected but executive appointed, Refers to violence committed within the Occupied Palestinian Territories by b 1 is fewest human rights violations, 5 is most human rights violations. 2 is legislature and executive locally elected. Israeli forces. Violence committed in West Bank by actors working with or for the c f A lower score indicates more freedom of the press. Refers to Israel’s pre-1967 borders and does not include Occupied Territories Palestinian National Authority receives a score of 4. d Data refer to verified cases of journalists having been imprisoned as of December 1, (Gaza and the West Bank). 2009. Countries with a value of 0 did not have any verified cases as of that date. Sources Columns 1, 2, 7 and 9: Column 5: Gallup World Poll database (2010). Reporters Without Borders (2009). Column 3: Column 6: Cheibub, Gandhi, and Vreeland (2010). CPJ (2009). Column 4: Column 8: Gibney, Cornett, and Woods (2010). Beck and others (2001). 167 ## STATISTICAL ANNEX 7 e l Sustainability and vulnerability b ta Share of total primary Population without access Population Carbon Deaths due Population energy supply to improved SERVICES living on dioxide to indoor and affected by Adjusted Ecological degraded emissions Protected outdoor air and natural net footprint of Renewable Fossil b c a d e land per capita area water pollution disasters savings consumption sources Water Sanitation fuels (hectares per (% terrestrial (average per year, HDI rank (% of GNI) capita) (%) (%) (tonnes) area) (%) (%) (%) (per million people) per million people) 2008 2006 2007 2007 1990 2006 2009 2010 2008 2008 2004 2000–2009 ## VERY HIGH HUMAN DEVELOPMENT 1 Norway 16.2 4.2 69 31 7.4 8.6 14.4 0 0 0 65 49 2 Australia 15.0 .. 94 6 17.4 18.1 10.5 9 0 0 35 458 3 New Zealand .. 7.6 67 33 6.7 7.4 25.9 5 0 .. 0 189 4 United States 0.9 9.0 86 5 19.0 19.0 14.8 1 1 0 135 7,322 5 Ireland 7.5 8.2 91 3 8.8 10.4 1.0 0 0 1 0 46 6 Liechtenstein .. .. .. .. .. .. 42.4 .. .. .. 0 .. 7 Netherlands –1.2 4.6 93 4 11.2 10.3 12.4 5 0 0 203 0 8 Canada 7.6 5.8 76 16 16.2 16.7 8.0 3 0 0 84 63 9 Sweden 20.5 .. 33 31 6.0 5.6 11.3 0 0 0 55 4 f 9.7 40.5 8 0 0 124 449 10 Germany .. 4.0 81 9 12.1 11 Japan 15.3 4.1 83 3 9.5 10.1 16.3 0 0 0 194 1,378 12 Korea, Republic of 21.1 3.7 82 1 5.6 9.9 2.4 3 2 0 150 1,232 13 Switzerland .. 5.6 52 21 6.3 5.6 22.8 0 0 0 108 108 14 France 9.8 4.6 51 7 7.0 6.2 15.1 4 0 0 81 108 15 Israel 11.3 5.4 96 4 7.4 10.3 18.7 13 0 0 213 9 16 Finland 16.0 5.5 50 24 10.2 12.7 9.1 0 0 0 19 8 17 Iceland .. .. 19 81 8.1 7.4 9.7 0 0 0 0 44 18 Belgium .. 5.7 73 4 10.8 10.3 0.9 10 0 0 203 27 19 Denmark 13.8 7.2 82 18 9.8 9.9 5.0 9 0 0 111 0 20 Spain 10.1 5.6 83 7 5.9 8.0 8.6 1 0 0 137 20 21 Hong Kong, China (SAR) .. .. 95 0 4.8 5.5 41.8 .. .. .. 0 83 22 Greece –4.8 5.8 94 5 7.2 8.7 13.8 1 0 2 226 195 23 Italy 8.6 4.9 91 7 7.5 8.1 9.9 2 0 .. 137 127 24 Luxembourg .. .. 89 3 26.0 24.5 19.8 .. 0 0 0 0 22.9 3 0 0 147 820 25 Austria 17.6 4.9 73 26 7.9 8.6 26 United Kingdom 3.9 6.1 90 .. 10.0 9.4 24.4 3 0 0 189 683 27 Singapore 34.7 4.5 100 0 15.6 12.8 5.4 .. 0 0 262 52 28 Czech Republic 13.4 5.3 83 5 12.7 11.3 15.1 4 0 2 167 2,344 f 7.6 12.1 8 1 0 150 33 29 Slovenia 18.1 3.9 69 10 6.4 30 Andorra .. .. .. .. .. .. 6.0 .. 0 0 0 .. f 7.0 23.5 9 0 0 74 219 31 Slovakia –81.1 4.9 71 6 8.4 32 United Arab Emirates .. 10.3 100 0 29.4 32.8 5.6 2 0 3 51 .. 33 Malta .. .. 100 0 6.3 6.3 17.3 .. 0 0 0 .. f 13.1 20.0 5 2 5 74 8 34 Estonia 9.0 6.4 90 10 16.4 35 Cyprus –2.8 .. 97 3 6.8 9.2 11.0 11 0 0 242 0 36 Hungary 5.0 3.2 79 5 6.0 5.7 5.1 17 0 0 208 509 37 Brunei Darussalam .. .. 100 0 25.0 15.5 42.9 0 .. .. 0 .. 38 Qatar .. 9.7 100 0 25.2 56.2 0.7 0 0 0 0 .. 39 Bahrain 15.6 .. 100 0 24.1 28.8 1.4 0 .. .. 0 .. 40 Portugal 4.1 4.4 79 18 4.4 5.7 5.9 2 1 0 191 1,560 41 Poland 9.2 3.9 94 6 9.1 8.3 21.8 13 0 10 162 61 42 Barbados .. .. .. .. 4.0 4.6 0.1 .. 0 0 0 0 168 human development report 2010 Sustainability and vulnerability Share of total primary Population without access Population Carbon Deaths due Population energy supply to improved SERVICES living on dioxide to indoor and affected by Adjusted Ecological degraded emissions Protected outdoor air and natural net footprint of Renewable Fossil b c a d e land per capita area water pollution disasters savings consumption sources fuels Water Sanitation (hectares per (% terrestrial (average per year, HDI rank (% of GNI) capita) (%) (%) (tonnes) area) (%) (%) (%) (per million people) per million people) 2008 2006 2007 2007 1990 2006 2009 2010 2008 2008 2004 2000–2009 ## HIGH HUMAN DEVELOPMENT 43 Bahamas .. .. .. .. 7.6 6.5 13.7 .. .. 0 0 6,666 44 Lithuania 6.6 3.3 62 9 6.0 4.2 4.5 5 .. .. 204 0 45 Chile –0.4 3.1 78 22 2.7 3.7 16.5 1 4 4 161 4,774 46 Argentina 7.7 3.0 90 7 3.5 4.4 5.4 2 3 10 349 1,963 47 Kuwait 9.7 7.9 100 0 19.0 31.2 1.6 1 1 0 115 0 f 3.3 17.8 2 1 22 0 5 48 Latvia 14.8 4.6 64 30 5.1 49 Montenegro .. .. .. .. .. .. 13.3 8 2 8 0 273 50 Romania 13.7 2.7 83 13 6.8 4.6 7.1 13 .. 28 460 1,072 f 5.2 7.3 18 1 1 225 52 51 Croatia 11.3 3.3 87 7 3.7 52 Uruguay 7.2 .. 62 38 1.3 2.1 0.3 6 0 0 421 4,824 53 Libyan Arab Jamahiriya .. 3.2 99 1 9.2 9.2 0.1 8 .. 3 310 .. 54 Panama 18.9 3.2 75 25 1.3 2.0 18.7 4 7 31 189 2,950 55 Saudi Arabia –1.8 3.5 100 0 13.2 15.8 31.3 4 .. .. 108 61 56 Mexico 9.0 3.2 89 9 4.6 4.1 11.1 4 6 15 174 6,587 57 Malaysia .. .. 95 5 3.1 7.2 17.9 1 0 4 60 1,667 table 58 Bulgaria 2.9 3.3 78 5 8.7 6.3 9.1 8 0 0 437 203 7 59 Trinidad and Tobago –19.2 .. 100 0 13.9 25.3 31.2 .. 6 8 0 146 60 Serbia .. .. 89 11 .. .. 6.0 19 1 8 0 176 61 Belarus 19.8 4.2 92 5 9.6 7.1 7.3 5 0 7 10 0 62 Costa Rica 9.1 2.7 47 53 1.0 1.8 20.9 1 3 5 118 11,383 63 Peru 7.0 1.8 70 30 1.0 1.4 13.6 1 18 32 244 18,032 64 Albania 8.5 2.6 68 21 2.3 1.4 9.8 6 3 2 97 21,349 f 10.9 9.0 3 4 13 241 1,531 65 Russian Federation 1.6 4.4 89 3 13.9 f 12.6 2.5 24 5 3 358 571 66 Kazakhstan 2.5 4.4 99 1 15.9 f 2 5.9 4.2 7.2 4 20 55 525 474 67 Azerbaijan –0.1 2.3 98 f 7.0 0.6 6 1 5 79 10,832 68 Bosnia and Herzegovina .. 3.4 91 9 1.2 69 Ukraine 8.5 2.7 82 1 11.9 6.9 3.5 6 2 5 313 1,561 70 Iran, Islamic Republic of .. 2.7 99 1 4.0 6.6 7.1 25 .. .. 134 58,770 f 5.3 4.9 7 0 11 148 60,392 71 The former Yugoslav Republic of Macedonia 9.0 .. 85 8 5.6 72 Mauritius 8.5 .. .. .. 1.4 3.1 4.5 .. 1 9 81 220 73 Brazil 5.2 .. 53 44 1.4 1.9 28.0 8 3 20 269 3,908 f 1.2 3.7 2 2 5 421 18,916 74 Georgia –0.3 .. 70 30 2.9 75 Venezuela, Bolivarian Republic of 6.5 2.3 88 12 6.2 6.3 53.8 2 .. .. 69 506 f 1.5 8.0 10 4 10 1,045 10,704 76 Armenia 18.1 1.6 71 6 1.1 77 Ecuador 0.4 1.9 87 13 1.6 2.4 25.1 2 6 8 124 9,126 78 Belize 8.8 .. .. .. 1.7 2.9 28.0 1 1 10 0 54,328 79 Colombia 1.5 1.9 71 29 1.6 1.4 20.4 2 8 26 168 11,288 80 Jamaica .. .. 90 10 3.4 4.5 18.9 3 6 17 340 17,504 81 Tunisia 7.0 1.9 86 14 1.6 2.3 1.3 37 6 15 174 362 82 Jordan 3.6 2.0 98 2 3.2 3.6 9.4 22 4 2 204 2,639 83 Turkey 8.3 2.8 90 10 2.6 3.6 1.9 5 1 10 427 957 84 Algeria 21.4 1.9 100 0 3.1 4.0 6.3 29 17 5 324 622 85 Tonga .. .. .. .. 0.8 1.3 14.5 .. 0 4 0 18,168 ## MEDIUM HUMAN DEVELOPMENT 86 Fiji –7.1 3.7 .. .. 1.1 1.9 1.3 .. .. .. 0 6,720 f 9.0 3.0 11 .. 2 691 0 87 Turkmenistan .. 3.8 100 0 7.2 88 Dominican Republic –0.3 1.4 81 20 1.3 2.1 22.1 7 14 17 256 3,319 89 China 35.1 1.8 87 12 2.1 4.6 16.6 9 11 45 693 96,359 90 El Salvador –0.1 .. 42 58 0.5 1.0 0.8 6 13 13 215 39,965 91 Sri Lanka 10.4 0.9 46 55 0.2 0.6 20.8 21 10 9 315 31,444 92 Thailand 18.0 1.7 81 19 1.8 4.3 19.6 17 2 4 345 46,173 93 Gabon 3.6 .. 40 60 6.6 1.6 14.9 0 13 67 372 1,357 94 Suriname .. .. .. .. 4.5 5.4 11.4 0 7 16 0 6,744 0.8 1.2 18.2 2 14 75 633 17,895 95 Bolivia, Plurinational State of –4.7 2.4 82 18 169 ## STATISTICAL ANNEX Sustainability and vulnerability Share of total primary Population without access Population Carbon Deaths due Population energy supply to improved SERVICES living on dioxide to indoor and affected by Adjusted Ecological degraded emissions Protected outdoor air and natural net footprint of Renewable Fossil b c a d e land per capita area water pollution disasters savings consumption sources fuels Water Sanitation (hectares per (% terrestrial (average per year, HDI rank (% of GNI) capita) (%) (%) (tonnes) area) (%) (%) (%) (per million people) per million people) 2008 2006 2007 2007 1990 2006 2009 2010 2008 2008 2004 2000–2009 96 Paraguay 9.0 3.4 15 85 0.5 0.7 5.5 1 14 30 224 10,590 97 Philippines 22.3 .. 57 43 0.7 0.8 10.9 2 9 24 322 60,119 98 Botswana 37.2 3.9 69 23 1.6 2.6 30.9 22 5 40 771 7,925 f 2.0 1.4 22 10 21 340 86,995 99 Moldova, Republic of 17.3 1.7 90 2 4.8 100 Mongolia 3.0 .. 96 3 4.5 3.6 13.4 31 24 50 318 120,113 101 Egypt 2.1 1.4 96 4 1.4 2.2 5.9 25 1 6 345 2 f 4.3 2.3 27 13 0 715 2,431 102 Uzbekistan –14.1 1.7 99 1 5.3 103 Micronesia, Federated States of .. .. .. .. .. .. 4.0 .. .. .. 0 10,768 104 Guyana 14.4 .. .. .. 1.6 2.0 4.9 0 6 19 262 59,712 105 Namibia 9.9 3.0 68 21 0.0 1.4 14.5 28 8 67 152 42,577 106 Honduras 13.1 2.2 55 45 0.5 1.0 18.2 15 14 29 385 18,638 107 Maldives .. .. .. .. 0.7 2.9 .. .. 9 2 0 4,901 108 Indonesia –2.4 .. 69 31 0.8 1.5 14.1 3 20 48 505 4,935 109 Kyrgyzstan 10.4 1.3 61 39 2.5 1.1 6.9 10 10 7 736 518 110 South Africa –3.5 2.7 88 10 9.1 8.6 6.9 17 9 23 350 33,998 111 Syrian Arab Republic –15.2 1.6 98 2 2.9 3.5 0.6 33 11 4 222 8,263 f 1.0 4.1 10 30 6 1,302 100,709 112 Tajikistan 18.8 0.9 62 38 3.9 table 113 Viet Nam 9.7 1.0 51 49 0.3 1.2 6.2 8 6 25 438 25,632 7 114 Morocco 19.8 1.3 94 4 0.9 1.5 1.6 39 19 31 186 1,156 115 Nicaragua .. 2.3 41 59 0.6 0.8 36.7 14 15 48 316 10,527 116 Guatemala 5.3 1.7 46 54 0.6 0.9 30.6 9 6 19 468 27,087 117 Equatorial Guinea –38.5 .. .. .. 0.4 8.8 19.2 0 .. .. 1,182 155 118 Cape Verde .. .. .. .. 0.2 0.6 2.5 .. 16 46 213 11,020 119 India 24.2 0.8 70 29 0.8 1.3 5.3 10 12 69 954 55,557 0.2 6.1 .. 31 50 316 93 120 Timor-Leste .. .. .. .. .. 121 Swaziland 7.1 .. .. .. 0.5 0.9 3.0 0 31 45 718 156,115 122 Lao People’s Democratic Republic 17.1 1.0 .. .. 0.1 0.2 16.3 4 43 47 847 24,535 123 Solomon Islands 54.7 1.7 .. .. 0.5 0.4 0.1 .. .. .. 433 2,050 124 Cambodia .. 0.9 29 71 0.0 0.3 24.0 39 39 71 1,304 62,992 125 Pakistan 6.1 0.7 62 37 0.6 0.9 10.3 4 10 55 896 8,953 126 Congo –57.1 1.0 39 58 0.5 0.4 9.5 0 29 70 898 862 127 São Tomé and Príncipe .. .. .. .. 0.6 0.7 .. .. 11 74 666 .. ## LOW HUMAN DEVELOPMENT 128 Kenya 10.2 .. 20 80 0.2 0.3 11.6 31 41 69 1,106 94,526 129 Bangladesh 23.7 .. 66 34 0.1 0.3 1.6 11 20 47 821 49,538 130 Ghana –6.6 1.6 32 68 0.3 0.4 14.0 1 18 87 1,283 3,238 131 Cameroon .. 1.1 27 73 0.1 0.2 9.2 15 26 53 1,832 168 132 Myanmar .. 1.0 31 68 0.1 0.2 6.3 19 29 19 883 5,989 f 1.0 0.5 32 38 48 1,102 135 133 Yemen .. 1.0 99 1 0.8 134 Benin .. 1.0 37 62 0.1 0.4 23.8 2 25 88 2,037 3,832 135 Madagascar 7.0 1.2 .. .. 0.1 0.1 2.9 0 59 89 1,967 23,628 136 Mauritania .. 3.1 .. .. 1.4 0.5 0.5 24 51 74 1,273 37,166 137 Papua New Guinea 3.1 1.7 .. .. 0.5 0.7 3.1 0 60 55 737 5,078 138 Nepal 30.5 .. 11 89 0.0 0.1 17.0 2 12 69 877 9,611 139 Togo .. .. 13 85 0.2 0.2 11.3 5 40 88 1,403 2,991 140 Comoros 7.0 .. .. .. 0.1 0.1 0.0 .. 5 64 664 47,708 141 Lesotho 19.4 .. .. .. .. .. 0.5 64 15 71 304 52,807 142 Nigeria .. 1.6 19 81 0.5 0.7 12.8 12 42 68 2,120 432 143 Uganda 3.3 .. .. .. 0.0 0.1 9.7 23 33 52 1,692 10,899 144 Senegal 12.2 1.2 53 47 0.4 0.4 24.1 16 31 49 1,911 7,394 145 Haiti .. 0.5 28 72 0.1 0.2 0.3 15 37 83 1,080 12,150 146 Angola –42.6 0.9 34 66 0.4 0.6 12.4 3 50 43 5,225 5,421 147 Djibouti .. 0.9 .. .. 0.7 0.6 0.0 8 8 44 885 94,144 13,303 148 Tanzania, United Republic of .. 1.0 10 90 0.1 0.1 27.7 25 46 76 1,392 149 Côte d’Ivoire 1.7 0.9 23 77 0.5 0.4 22.6 1 20 77 1,884 39 150 Zambia –0.7 1.2 11 89 0.3 0.2 36.0 5 40 51 1,961 36,424 151 Gambia 3.9 1.1 .. .. 0.2 0.2 1.5 18 8 33 1,283 2,059 170 human development report 2010 Sustainability and vulnerability Share of total primary Population without access Population Carbon Deaths due Population energy supply to improved SERVICES living on dioxide to indoor and affected by Adjusted Ecological degraded emissions Protected outdoor air and natural net footprint of Renewable Fossil b c a d e land per capita area water pollution disasters savings consumption sources fuels Water Sanitation (hectares per (% terrestrial (average per year, HDI rank (% of GNI) capita) (%) (%) (tonnes) area) (%) (%) (%) (per million people) per million people) 2008 2006 2007 2007 1990 2006 2009 2010 2008 2008 2004 2000–2009 152 Rwanda 20.1 .. .. .. 0.1 0.1 10.0 10 35 46 3,345 21,544 153 Malawi 25.1 .. .. .. 0.1 0.1 15.0 19 20 44 2,395 70,315 154 Sudan –13.1 2.2 26 74 0.2 0.3 4.9 40 43 66 979 20,408 155 Afghanistan .. .. .. .. 0.2 0.0 0.4 11 52 63 5,125 23,278 156 Guinea –11.3 1.5 .. .. 0.2 0.1 6.8 1 29 81 1,759 3,227 157 Ethiopia 8.9 .. 9 92 0.1 0.1 18.4 72 62 88 2,571 37,289 158 Sierra Leone –1.0 0.8 .. .. 0.1 0.2 5.0 0 51 87 5,623 457 159 Central African Republic –4.6 1.4 .. .. 0.1 0.1 14.7 0 33 66 1,812 510 160 Mali .. 1.9 .. .. 0.1 0.0 2.4 60 44 64 3,367 9,531 161 Burkina Faso .. 1.4 .. .. 0.1 0.1 13.9 73 24 89 3,130 2,504 162 Liberia .. 1.2 .. .. 0.2 0.2 18.1 0 32 83 3,287 1,080 163 Chad –49.9 1.8 .. .. 0.0 0.0 9.4 45 50 91 2,547 31,625 164 Guinea-Bissau 16.6 1.0 .. .. 0.2 0.2 16.1 1 39 79 3,269 11,817 165 Mozambique –4.6 .. 5 95 0.1 0.1 15.8 2 53 83 1,428 47,950 166 Burundi .. .. .. .. 0.1 0.0 4.9 19 28 54 3,519 51,177 167 Niger .. 1.7 .. .. 0.1 0.1 6.8 25 52 91 5,445 50,079 168 Congo, Democratic Republic of the –2.5 0.7 4 96 0.1 0.0 10.0 0 54 77 3,260 1,288 table 169 Zimbabwe .. 1.0 28 70 1.6 0.8 28.0 29 18 56 889 75,240 7 ## OTHER COUNTRIES OR TERRITORIES Antigua and Barbuda .. .. .. .. 4.9 5.1 7.0 .. .. .. 0 32,725 Bhutan 50.4 .. .. .. 0.2 0.6 28.4 0 8 35 789 0 Cuba .. 2.3 87 13 3.1 2.6 6.3 17 6 9 233 97,163 Dominica .. .. .. .. 0.9 1.7 21.7 .. .. .. 0 12,965 Eritrea .. 0.8 27 74 .. 0.1 5.0 59 39 86 1,231 87,758 Grenada .. .. .. .. 1.3 2.3 1.7 .. .. 3 0 65,910 Iraq .. 1.3 99 0 2.8 3.2 0.1 5 21 27 1,244 276 .. .. .. 0.3 0.3 22.0 .. .. .. 0 0 Kiribati .. Korea, Democratic People’s Rep. of .. 1.4 88 12 12.2 3.6 4.0 3 0 .. 436 7,874 Lebanon 0.1 2.1 93 5 3.1 3.8 0.5 1 0 .. 149 460 Marshall Islands .. .. .. .. 1.0 1.6 3.1 .. 6 27 0 1,465 Monaco .. .. .. .. .. .. 23.7 .. 0 0 0 .. Nauru .. .. .. .. 14.4 14.1 .. .. .. .. 0 .. Occupied Palestinian Territories .. .. .. .. .. 0.8 .. .. 9 11 0 0 Oman .. 3.5 100 0 5.6 16.3 10.7 6 12 .. 117 783 Palau .. .. .. .. 15.7 5.8 2.0 .. .. .. 0 .. Saint Kitts and Nevis .. .. .. .. 1.6 2.7 3.6 .. 1 4 0 .. Saint Lucia .. .. .. .. 1.2 2.3 14.3 .. 2 .. 0 0 Saint Vincent and the Grenadines 7.6 .. .. .. 0.7 1.7 10.9 .. .. .. 0 1,557 Samoa .. .. .. .. 0.8 0.9 3.4 .. .. 0 0 3,277 San Marino .. .. .. .. .. .. .. .. .. .. 0 .. Seychelles .. .. .. .. 1.6 8.6 42.0 .. .. .. 0 22,448 Somalia .. 1.5 .. .. 0.0 0.0 0.6 26 70 77 3,490 67,697 Tuvalu .. .. .. .. .. .. 0.4 .. 3 16 0 .. Vanuatu .. .. .. .. 0.5 0.4 4.3 .. 17 48 0 36,308 Notes a d e Includes particulate emissions damage. Includes deaths from diarrhoea attributable to water, sanitation and hygiene; Natural disasters include droughts, earthquakes, epidemics, extreme temperatures, b Fossils fuels include coal and coal products, crude, natural gas liquids, feedstocks, deaths from acute respiratory infections (children under age 5), chronic obstructive floods, insect infestation, storms, volcanoes and wildfires. f petroleum products and natural gas. pulmonary disease (adults over age 30) and lung cancer (adults over age 30) Data refer to a year other than that specified. c Renewables sources include hydropower, geothermal power, combustible attributable to indoor smoke; and deaths from respiratory infections and diseases, renewables, waste, solar and wind, and exclude nuclear energy. lung cancer and selected cardiovascular diseases attributable to outdoor air pollution. Sources Column 1: Columns 5 and 6: Column 11: World Bank (2010a). Boden, Marland, and Andres (2009). Calculated based on data from WHO (2008) and UNDESA (2009d). Column 2: Column 7: Column 12: GFN (2009). UNEP-WCMC (2006). Calculated based on CRED EM-DAT (2010) and UNDESA (2009d). Columns 3 and 4: Column 8: Calculated based on data on total primary energy supply source FAO (2010a). Columns 9 and 10: from IEA (2009). WHO and UNICEF (2010). 171 ## STATISTICAL ANNEX 8 e l Human security b ta Limitations to freedom from fear Limitations to freedom from want a Conventional arms transfers Internally Refugees Civil war (1990$ millions) displaced

by country Prevalence of Intensity of food

b

persons

of origin

Exports Imports Fatalities Intensity undernourishment deprivation

(average per year of (average % shortfall in

conflict per million minimum dietary energy

c

HDI rank inhabitants) Score (0–2) requirements)

(thousands) (thousands) (% of total population)

d d

2008 2008 2008 2008 1990/2008 2008 1990–1992 2004–2006 1990/1992 2004/2006

## VERY HIGH HUMAN DEVELOPMENT

1 Norway 2 536 0.0 .. .. 0 <5 <5 .. ..

2 Australia 6 380 0.0 .. .. 0 <5 <5 .. ..

3 New Zealand .. 2 0.0 .. .. 0 <5 <5 .. ..

4 United States 6,093 808 2.1 .. .. 0 <5 <5 .. ..

5 Ireland 1 21 0.0 .. .. 0 <5 <5 .. ..

6 Liechtenstein .. .. .. .. .. 0 .. .. .. ..

7 Netherlands 554 132 0.0 .. .. 0 <5 <5 .. ..

8 Canada 236 427 0.1 .. .. 0 <5 <5 .. ..

9 Sweden 457 64 0.0 .. .. 0 <5 <5 .. ..

10 Germany .. .. 0.2 .. .. 0 <5 <5 .. ..

11 Japan .. 584 0.2 .. .. 0 <5 <5 .. ..

12 Korea, Republic of 80 1,821 1.1 .. .. 0 <5 <5 7 7

13 Switzerland 467 14 0.0 .. .. 0 <5 <5 .. ..

14 France 1,831 7 0.1 .. .. 0 <5 <5 .. ..

15 Israel 271 665 1.5 .. 78.5 1 <5 <5 .. ..

16 Finland 67 152 0.0 .. .. 0 <5 <5 .. ..

17 Iceland .. .. 0.0 .. .. 0 <5 <5 .. ..

18 Belgium 228 177 0.1 .. .. 0 <5 <5 .. ..

19 Denmark 15 90 0.0 .. .. 0 <5 <5 .. ..

20 Spain 603 361 0.0 .. 0.9 0 <5 <5 .. ..

21 Hong Kong, China (SAR) .. .. 0.0 .. .. 0 .. .. .. ..

22 Greece .. 563 0.1 .. .. 0 <5 <5 .. ..

23 Italy 424 189 0.1 .. .. 0 <5 <5 .. ..

24 Luxembourg .. .. .. .. .. 0 <5 <5 .. ..

25 Austria 16 220 0.0 .. .. 0 <5 <5 .. ..

26 United Kingdom 1,027 506 0.2 .. 1.3 0 <5 <5 .. ..

27 Singapore 1 1,123 0.1 .. .. 0 .. .. .. ..

28 Czech Republic 33 20 1.4 .. .. 0 <5 <5 7 10

29 Slovenia .. .. 0.1 .. .. 0 <5 <5 7 10

30 Andorra .. .. 0.0 .. .. 0 .. .. .. ..

<5 7 5

31 Slovakia 8 .. 0.3 .. .. 0 <5

32 United Arab Emirates .. 748 0.3 .. .. 0 <5 <5 6 20

33 Malta .. .. 0.0 .. .. 0 <5 <5 .. ..

34 Estonia .. 50 0.2 .. .. 0 <5 <5 10 9

e .. 0 <5 <5 6 10

35 Cyprus .. .. 0.0 200.5

36 Hungary .. 5 1.6 .. .. 0 <5 <5 6

37 Brunei Darussalam .. .. 0.0 .. .. 0 <5 <5 8

38 Qatar .. .. 0.1 .. .. 0 .. .. .. ..

39 Bahrain .. 19 0.1 .. .. 0 .. .. .. ..

40 Portugal 87 159 0.0 .. .. 0 <5 <5 .. ..

41 Poland 76 623 2.4 .. .. 0 <5 <5 6 10

42 Barbados .. 13 0.0 .. .. 0 <5 <5 7 8

172 human development report 2010 Human security

Limitations to freedom from fear Limitations to freedom from want

a

Conventional arms transfers Internally

Refugees Civil war

(1990 $millions) displaced by country Prevalence of Intensity of food b persons of origin Exports Imports Fatalities Intensity undernourishment deprivation (average per year of (average % shortfall in conflict per million minimum dietary energy c HDI rank inhabitants) Score (0–2) requirements) (thousands) (thousands) (% of total population) d d 2008 2008 2008 2008 1990/2008 2008 1990–1992 2004–2006 1990/1992 2004/2006 ## HIGH HUMAN DEVELOPMENT 43 Bahamas .. .. 0.0 .. .. 0 7 6 9 12 44 Lithuania .. 26 0.5 .. .. 0 <5 <5 8 10 45 Chile 133 577 1.0 .. .. 0 7 <5 9 11 46 Argentina .. 21 1.0 .. .. 0 <5 <5 7 11 47 Kuwait .. 5 0.9 .. .. 0 20 <5 12 7 48 Latvia .. 44 0.8 .. .. 0 <5 <5 7 0 49 Montenegro .. .. 1.3 .. .. 0 .. .. .. .. 50 Romania .. 70 4.8 .. .. 0 <5 <5 7 13 51 Croatia .. 99 97.0 2.4 269.4 0 .. <5 10 4 52 Uruguay .. 65 0.2 .. .. 0 5 <5 8 0 53 Libyan Arab Jamahiriya 9 .. 2.1 .. .. 0 <5 <5 7 4 54 Panama .. .. 0.1 .. .. 0 18 17 13 11 55 Saudi Arabia .. 115 0.7 .. .. 0 <5 <5 8 7 56 Mexico .. .. 6.2 5.5 0.7 0 <5 <5 10 12 57 Malaysia .. 541 0.6 .. .. 0 <5 <5 7 7 58 Bulgaria 8 123 3.0 .. .. 0 <5 <5 9 10 59 Trinidad and Tobago .. .. 0.2 .. 23.2 0 11 10 11 15 f .. 0 .. .. .. .. 60 Serbia .. .. 185.9 250 table 61 Belarus 292 .. 5.4 .. .. 0 <5 <5 6 18 8 62 Costa Rica .. 0.4 .. .. 0 <5 <5 8 8 63 Peru .. 2 7.3 150 21.9 1 28 13 14 14 64 Albania .. 13 15.0 .. .. 0 <5 <5 10 8 g 40.2 1 <5 <5 8 11 65 Russian Federation 6,026 .. 103.1 18–82 66 Kazakhstan .. 25 4.8 .. .. 0 <5 <5 6 10 h 236.6 0 27 11 12 7 67 Azerbaijan .. 21 16.3 573–603 68 Bosnia and Herzegovina .. .. 74.4 125 3,458.2 0 <5 <5 9 7 69 Ukraine 269 .. 28.4 .. .. 0 <5 <5 7 7 70 Iran, Islamic Republic of 2 91 69.1 .. 1.1 1 <5 <5 9 12 71 The former Yugoslav Republic of Macedonia .. .. 7.5 <1 60.6 0 <5 <5 10 8 72 Mauritius .. .. 0.0 .. .. 0 7 6 10 12 0 10 6 13 12 73 Brazil 72 212 1.4 .. .. i 289.0 1 47 12 14 9 74 Georgia .. 77 12.6 247–249 75 Venezuela, Bolivarian Republic of 3 764 5.8 .. 5.3 0 10 12 10 10 76 Armenia .. .. 16.3 8.4 .. 0 46 23 14 13 77 Ecuador .. 140 1.1 .. .. 0 24 13 12 5 78 Belize .. .. 0.0 .. .. 0 5 <5 9 25 j 44.7 2 15 10 13 9 79 Colombia .. 92 373.5 3,304–4,916 80 Jamaica .. 2 0.8 .. .. 0 11 5 10 9 81 Tunisia .. 7 2.3 .. .. 0 <5 <5 7 10 82 Jordan 28 136 1.9 .. .. 0 <5 <5 9 6 k 28.2 1 <5 <5 8 9 83 Turkey 43 578 214.4 954–1,200 84 Algeria .. 1,518 9.1 .. 134.8 1 <5 .. 10 10 85 Tonga .. .. 0.0 .. .. 0 .. .. .. .. ## MEDIUM HUMAN DEVELOPMENT 86 Fiji .. .. 1.9 .. .. 0 8 <5 10 2 l .. 0 9 6 10 9 87 Turkmenistan .. .. 0.7 .. 88 Dominican Republic .. .. 0.3 .. .. 0 27 21 13 12 89 China 544 1,481 175.2 .. .. 0 15 10 14 13 90 El Salvador .. .. 5.2 .. 210.2 0 9 10 11 11 91 Sri Lanka .. .. 137.8 380 193.8 2 27 21 15 14 92 Thailand .. 12 1.8 .. 5.5 1 29 17 15 11 93 Gabon .. 21 0.1 .. .. 0 5 <5 8 8 173 ## STATISTICAL ANNEX Human security Limitations to freedom from fear Limitations to freedom from want a Conventional arms transfers Internally Refugees Civil war (1990$ millions) displaced

by country Prevalence of Intensity of food

b

persons

of origin

Exports Imports Fatalities Intensity undernourishment deprivation

(average per year of (average % shortfall in

conflict per million minimum dietary energy

c

HDI rank inhabitants) Score (0–2) requirements)

(thousands) (thousands) (% of total population)

d d

2008 2008 2008 2008 1990/2008 2008 1990–1992 2004–2006 1990/1992 2004/2006

94 Suriname .. .. 0.1 .. .. 0 11 7 10 10

95 Bolivia, Plurinational State of .. 3 0.5 .. .. 0 24 23 13 15

96 Paraguay .. .. 0.1 .. .. 0 16 12 12 12

97 Philippines .. 10 1.4 125–188 8.0 1 21 15 15 14

98 Botswana .. .. 0.0 .. .. 0 20 26 13 13

99 Moldova, Republic of 20 .. 5.6 .. 170.7 0 <5 <5 9 9

100 Mongolia .. 14 1.3 .. .. 0 30 29 14 14

101 Egypt .. 214 6.8 .. 2.2 0 <5 <5 10 13

102 Uzbekistan .. .. 6.3 3 6.1 0 5 13 8 13

103 Micronesia, Federated States of .. .. .. .. .. 0 .. .. .. ..

104 Guyana .. 0.7 .. .. 0 18 6 12 13

105 Namibia .. 66 1.0 .. .. 0 29 19 14 8

106 Honduras .. 1.1 .. .. 0 19 12 15 13

107 Maldives .. .. 0.0 .. .. 0 9 7 10 5

108 Indonesia .. 241 19.3 70–120 2.2 0 19 16 13 13

109 Kyrgyzstan 16 .. 2.5 .. .. 0 17 <5 12 4

110 South Africa 161 387 0.5 .. .. 0 <5 <5 .. ..

m .. 0 <5 <5 9 7

111 Syrian Arab Republic .. 292 15.2 433

112 Tajikistan .. .. 0.5 .. 815.4 0 34 26 13 10

113 Viet Nam .. 250 328.2 .. .. 0 28 13 16 16

table 114 Morocco .. 49 3.5 .. .. 0 5 <5 11 13

8 115 Nicaragua .. .. 1.5 .. .. 0 52 21 21 18

n 44.5 0 14 16 12 12

116 Guatemala .. 5.9 ..

117 Equatorial Guinea .. 41 0.4 .. .. 0 .. .. .. ..

118 Cape Verde .. .. 0.0 .. .. 0 12 14 11 9

119 India 11 1,810 19.6 500 4.1 1 24 22 17 15

120 Timor-Leste .. .. 0.0 <1 .. 0 18 23 .. ..

121 Swaziland .. .. 0.0 .. .. 0 12 18 11 12

122 Lao People’s Democratic Republic .. 7 8.6 .. 4.6 0 27 19 16 15

123 Solomon Islands .. .. 0.1 .. .. 0 25 9 13 8

14

124 Cambodia .. .. 17.3 .. 13.6 0 38 25 16

o 11.4 2 22 23 16 16

125 Pakistan .. 939 32.4 1,250

126 Congo .. .. 19.9 7.8 582.3 0 40 21 17 14

127 São Tomé and Príncipe .. .. 0.0 .. .. 0 15 5 11 7

LOW HUMAN DEVELOPMENT p

128 Kenya .. .. 9.7 400 .. 0 33 30 15 13

129 Bangladesh .. 12 10.1 60–500 0.2 0 36 26 18 17

130 Ghana .. .. 13.2 .. .. 0 34 8 15 9

131 Cameroon .. 1 13.9 .. .. 0 34 23 15 9

q 42.1 1 44 17 17 17

132 Myanmar .. .. 184.4 470

133 Yemen .. 45 1.8 250 257.3 0 30 32 15 16

134 Benin .. .. 0.3 .. .. 0 28 19 15 12

135 Madagascar .. .. 0.3 .. .. 0 32 35 16 15

136 Mauritania .. .. 45.6 .. .. 0 10 8 12 7

137 Papua New Guinea .. .. 0.0 .. 10.7 0 .. .. .. ..

138 Nepal .. .. 4.2 50–70 45.1 0 21 16 14 11

139 Togo .. .. 16.8 <2 44.1 0 45 37 18 16

140 Comoros .. 5 0.4 .. 101.4 0 40 51 16 19

141 Lesotho .. .. 0.0 .. 60.4 0 15 15 13 6

r 1.0 0 15 8 13 11

142 Nigeria .. 17 14.2 .. s 25.1 0 19 15 14 11

143 Uganda .. 3 7.5 437

144 Senegal .. 1 16.0 24–40 14.3 0 28 25 14 10

145 Haiti .. .. 23.1 .. 52.9 0 63 58 24 23

146 Angola .. 20 171.4 20 313.7 0 66 44 24 17

147 Djibouti .. .. 0.7 .. 209.7 0 60 31 22 12

174 human development report 2010 Human security

Limitations to freedom from fear Limitations to freedom from want

a

Conventional arms transfers Internally

Refugees Civil war

(1990 $millions) displaced by country Prevalence of Intensity of food b persons of origin Exports Imports Fatalities Intensity undernourishment deprivation (average per year of (average % shortfall in conflict per million minimum dietary energy c HDI rank inhabitants) Score (0–2) requirements) (thousands) (thousands) (% of total population) d d 2008 2008 2008 2008 1990/2008 2008 1990–1992 2004–2006 1990/1992 2004/2006 148 Tanzania, United Republic of .. .. 1.3 .. .. 0 28 35 15 16 l 149 Côte d’Ivoire .. .. 22.2 .. 24.4 0 15 14 13 11 150 Zambia .. .. 0.2 .. .. 0 40 45 18 19 151 Gambia .. .. 1.4 .. .. 0 20 29 14 14 152 Rwanda .. 6 72.5 .. 279.4 0 45 40 20 19 153 Malawi .. .. 0.1 .. .. 0 45 29 20 17 t 47.9 1 31 20 15 14 154 Sudan .. 128 419.2 4,900 155 Afghanistan .. .. 2,833.1 240 299.1 2 .. .. .. .. 156 Guinea .. .. 9.5 .. 70.0 0 19 16 15 7 157 Ethiopia .. .. 63.9 200–400 38.6 2 71 44 25 18 158 Sierra Leone .. .. 32.5 .. 336.1 0 45 46 22 22 159 Central African Republic .. .. 125.1 162 29.2 0 47 41 19 16 160 Mali .. 2 1.8 .. 9.4 1 14 10 13 12 161 Burkina Faso .. .. 0.7 .. .. 0 14 9 13 10 u 660.9 0 30 38 18 18 162 Liberia .. .. 75.2 .. 163 Chad .. 89 55.1 168 97.8 1 59 38 22 17 164 Guinea-Bissau .. .. 1.1 .. 798.8 0 20 31 14 14 165 Mozambique .. .. 0.2 .. 260.3 0 59 37 22 16 166 Burundi .. .. 281.6 100 111.5 1 44 63 18 21 v 18.9 1 38 28 18 15 167 Niger .. 7 0.8 6.5 table w 331.4 1 29 75 15 25 168 Congo, Democratic Republic of the .. .. 368.0 19,000 8 169 Zimbabwe .. .. 16.8 570–1,000 .. 0 40 39 19 17 Notes a h q Indicates the monetary value of voluntary transfers by a supplier of weapons with Includes internally displaced persons from Nagorno Karabakh and the seven Rural areas of eastern Myanmar only. r a military purpose destined for the armed forces, paramilitary forces or intelligence occupied territories only. No reliable estimates exist on internally displaced persons in Nigeria, nor is there a i agencies of another country. Data indicate only the volume of international arms Some internally displaced persons displaced in 2008 have not yet been registered. general agreement on their numbers. s transfers, not the actual financial value of such transfers, and may underestimate According to the national law, returned and relocated internally displaced persons Does not include internally displaced persons in urban areas or those in the actual transfers of conventional weapons. retain their status. Karamoja region but does include returnees receiving ongoing assistance and b j Estimates are from the Internal Displacement Monitoring Centre, based on various Higher value is cumulative since 1985. protection. k t sources, and are associated with a high level of uncertainty. Based on Hacettepe University survey commissioned by the government. Includes 2.7 million internally displaced persons in Darfur, 1.7 million in the Greater c l 0 is no civil war, 1 is minor civil war (fewer than 1,000 deaths), 2 is major civil war Undetermined because there are no statistics on returns. Khartoum area, 390,000 in Southern Sudan and 60,000 in Southern Kordofan. m u (at least 1,000 deaths). Includes 433,000 people displaced from the Golan Heights in 1967. According to the government, all internally displaced persons have achieved d n Data refer to the most recent year available during the period specified. At the end of 2007 the government had not agreed on criteria to include internally durable solutions (integrated into their new locations); approximately 23,000 e Includes more than 200,000 Greek and Turkish Cypriots displaced in 1974. displaced persons in a national reparation programme, and it is unclear how many people are believed to remain in former internally displaced persons camps. f v Includes 207,000 registered internally displaced persons in Serbia, 20,000 people can still be considered displaced. Does not include estimated 4,500 internally displaced persons believed to have o unregistered Roma and 20,000 displaced persons in Kosovo. Conflict-induced displacement has taken place in the North West Frontier Province, returned to the town of Iferouane. g w Includes internally displaced persons from Chechnya and North Ossetia with forced Balochistan and Waziristan, but no estimates are available due to lack of access. Includes estimated number of people displaced in the eastern part of the country p migrant status in and outside the North Caucasus, as well as internally displaced Takes into account the Kenyan government’s return programme, which claims that during the 2009 fighting between militia and Congolese armed forces supported persons registered by the government. some 172,000 people displaced during the post-election violence in December by the United Nations. 2007 have returned as of May 2008. Sources Columns 1 and 2: SIPRI (2010a). Column 3: UNHCR (2010). Column 4: IDMC (2010). Column 5: Calculated based on data from Lacina and Gleditsch (2005) and UNDESA (2009d). Column 6: UCDP and PRIO (2009). Columns 7–10: FAO (2010a). 175 ## STATISTICAL ANNEX 9 Perceptions of individual e l well-being and happiness b ta Satisfaction with personal Elements of happiness dimensions of well-being (% answering “’yes’” to having the element) a Overall life satisfaction Personal Standard of Negative (0, least satisfied, a a a Job health living Purposeful life Treated with respect Social support network experience index 10, most satisfied) (% of (% of all (% of all employed respondents respondents respondents who are (0, most negative, who are who are HDI rank satisfied) Total Female Total Female Total Female 100, least negative) satisfied) satisfied) Total Female b b b b b b b b b b b b 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 ## VERY HIGH HUMAN DEVELOPMENT 1 Norway 8.1 8.2 .. 82 91 85 90 90 90 93 92 16 2 Australia 7.9 8.0 91 82 85 87 89 89 88 94 95 22 3 New Zealand 7.8 8.0 90 85 79 87 90 90 88 94 95 24 4 United States 7.9 7.9 86 83 75 94 95 89 88 91 90 28 5 Ireland 8.1 8.1 95 90 79 87 91 93 93 96 97 23 6 Liechtenstein .. .. .. .. .. .. .. .. .. .. .. .. 7 Netherlands 7.8 7.8 92 85 91 70 79 93 92 94 93 16 8 Canada 8.0 8.2 90 85 87 91 92 93 94 94 93 25 9 Sweden 7.9 7.9 93 80 89 85 91 93 92 91 89 16 10 Germany 7.2 7.4 88 82 88 85 87 90 88 91 91 22 11 Japan 6.8 7.0 73 68 64 76 77 60 65 89 92 21 12 Korea, Republic of 6.3 6.5 68 71 71 80 81 63 67 79 82 23 13 Switzerland 8.0 8.0 93 89 89 82 84 94 91 94 94 21 14 France 7.1 7.1 87 84 72 84 85 93 93 91 91 29 15 Israel 7.1 7.1 80 80 71 88 88 81 77 85 95 33 16 Finland 8.0 8.2 90 84 84 81 86 91 92 94 95 15 17 Iceland 7.8 7.9 .. 84 82 .. .. 97 95 98 98 17 18 Belgium 7.3 7.3 89 88 84 73 78 92 90 92 92 24 19 Denmark 8.2 8.3 94 84 93 89 91 94 93 95 93 15 20 Spain 7.6 7.6 86 84 78 86 88 97 96 92 91 29 21 Hong Kong, China (SAR) 6.0 .. 81 80 78 60 64 83 86 82 82 26 22 Greece 6.8 6.8 80 82 57 90 91 92 91 79 76 23 23 Italy 6.7 6.7 82 85 77 91 91 93 93 87 87 27 24 Luxembourg 7.7 7.8 .. 87 92 .. .. 94 93 94 95 24 89 93 85 18 25 Austria 7.8 7.8 91 85 86 72 73 92 26 United Kingdom 7.4 7.5 87 85 88 79 84 90 90 96 97 24 27 Singapore 6.7 6.7 88 95 79 90 89 81 83 84 83 19 28 Czech Republic 6.9 6.8 80 77 65 68 72 64 77 86 92 23 29 Slovenia 7.1 7.0 88 78 70 63 65 91 86 91 89 26 30 Andorra 6.8 .. .. .. .. .. .. .. .. .. .. .. 31 Slovakia 5.8 .. 76 72 47 85 87 78 79 93 94 27 32 United Arab Emirates 7.3 .. 84 93 78 95 94 94 95 86 84 28 33 Malta 7.1 7.1 .. 83 65 .. .. 93 92 90 92 31 34 Estonia 5.6 5.6 79 64 46 72 73 79 80 85 85 20 35 Cyprus 7.1 7.1 89 89 84 95 94 88 89 81 80 33 36 Hungary 5.7 5.6 83 69 43 88 86 88 87 90 92 26 37 Brunei Darussalam .. .. .. .. .. .. .. .. .. .. .. .. 38 Qatar 6.7 7.0 89 93 86 .. .. 93 89 91 87 26 39 Bahrain .. .. .. 86 66 .. .. 90 92 90 91 37 40 Portugal 5.9 5.7 90 80 47 92 90 93 95 87 83 28 41 Poland 6.5 6.6 82 72 67 87 91 91 91 89 94 20 42 Barbados .. .. .. .. .. .. .. .. .. .. .. .. 176 human development report 2010 Perceptions of individual well-being and happiness Satisfaction with personal Elements of happiness dimensions of well-being (% answering “’yes’” to having the element) a Overall life satisfaction Personal Standard of Negative (0, least satisfied, a a a Job health living Purposeful life Treated with respect Social support network experience index 10, most satisfied) (% of (% of all (% of all employed respondents respondents respondents who are (0, most negative, who are who are HDI rank satisfied) Total Female Total Female Total Female 100, least negative) satisfied) satisfied) Total Female b b b b b b b b b b b b 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 ## HIGH HUMAN DEVELOPMENT 43 Bahamas .. .. .. .. .. .. .. .. .. .. .. .. 44 Lithuania 5.8 5.8 78 64 33 78 77 54 52 83 85 22 45 Chile 6.3 6.2 81 73 68 90 88 93 91 83 83 27 46 Argentina 7.1 7.1 83 87 70 93 95 96 95 91 91 21 47 Kuwait 6.6 .. 89 89 77 97 98 91 93 86 83 24 48 Latvia 5.4 5.4 79 63 33 79 81 80 81 78 78 24 49 Montenegro 5.2 .. 63 72 45 84 93 76 81 81 82 27 50 Romania 5.9 6.0 74 65 42 74 73 89 87 79 82 25 51 Croatia 6.0 .. 78 77 48 83 83 74 76 90 83 28 52 Uruguay 6.8 6.7 79 84 67 87 89 94 94 91 93 23 53 Libyan Arab Jamahiriya .. .. .. 78 64 .. .. 64 55 .. .. .. 54 Panama 7.8 7.8 91 85 73 98 98 93 93 90 90 15 55 Saudi Arabia 7.7 7.6 92 84 77 95 93 77 69 91 86 19 56 Mexico 7.7 7.9 88 82 69 93 93 91 91 86 84 20 57 Malaysia 6.6 6.6 86 87 68 95 94 88 86 79 79 15 58 Bulgaria 4.4 .. 73 67 29 77 75 77 78 81 78 20 59 Trinidad and Tobago 7.0 .. 76 82 40 97 97 93 94 85 87 19 60 Serbia 5.6 .. 73 73 35 84 82 77 76 82 76 28 61 Belarus 5.5 5.5 66 55 34 70 73 71 71 88 87 20 62 Costa Rica 8.5 8.5 88 90 83 97 97 94 94 90 89 21 table 9 63 Peru 5.9 5.8 74 72 54 96 95 89 88 79 78 28 64 Albania 4.6 .. 72 75 43 78 91 68 80 79 77 20 65 Russian Federation 5.9 5.9 74 56 36 79 78 83 83 88 90 16 66 Kazakhstan 6.1 6.1 82 68 51 88 85 81 81 88 86 13 81 72 67 21 67 Azerbaijan 5.3 5.2 73 68 42 87 86 79 68 Bosnia and Herzegovina 5.8 .. 76 75 39 80 85 67 72 74 72 25 69 Ukraine 5.3 5.2 71 55 23 74 73 78 77 81 81 17 70 Iran, Islamic Republic of 5.6 5.8 71 82 55 87 87 81 81 62 65 32 71 The former Yugoslav Republic of Macedonia 4.7 .. 71 82 34 93 92 81 82 78 72 22 72 Mauritius .. .. .. .. .. .. .. .. .. .. .. .. 73 Brazil 7.6 7.6 86 82 74 96 97 94 95 91 91 24 74 Georgia 4.3 4.3 63 50 22 86 85 83 83 54 56 22 75 Venezuela, Bolivarian Republic of 7.8 7.7 86 90 80 100 100 92 92 94 94 19 76 Armenia 5.0 5.1 61 53 31 93 94 89 88 67 68 31 77 Ecuador 6.4 6.3 80 76 57 98 97 93 92 78 74 27 78 Belize 6.6 6.6 79 83 69 90 91 75 77 83 86 24 79 Colombia 7.3 7.3 82 84 69 98 98 96 96 88 87 25 80 Jamaica 6.7 .. 82 88 50 98 98 80 81 91 92 18 81 Tunisia 5.9 5.9 73 85 72 .. .. 91 89 86 90 30 82 Jordan 5.7 5.8 80 89 72 90 90 89 90 90 88 28 83 Turkey 5.5 5.5 71 76 44 85 85 68 75 64 73 28 84 Algeria 5.6 5.9 66 87 61 .. .. 84 86 87 90 33 85 Tonga .. .. .. .. .. .. .. .. .. .. .. .. ## MEDIUM HUMAN DEVELOPMENT 86 Fiji .. .. .. .. .. .. .. .. .. .. .. .. 87 Turkmenistan 7.2 7.3 .. 85 78 96 96 84 83 92 94 15 88 Dominican Republic 7.6 7.4 69 80 57 96 94 92 95 84 87 32 89 China 6.4 .. 78 80 60 .. .. 87 86 79 78 17 90 El Salvador 6.7 6.7 82 80 60 97 97 89 90 72 72 25 91 Sri Lanka 4.7 4.8 86 77 58 91 91 76 75 82 84 24 92 Thailand 6.3 6.3 91 79 63 95 94 75 80 82 87 16 93 Gabon .. .. .. .. .. .. .. .. .. .. .. .. 177 ## STATISTICAL ANNEX Perceptions of individual well-being and happiness Satisfaction with personal Elements of happiness dimensions of well-being (% answering “’yes’” to having the element) a Overall life satisfaction Personal Standard of Negative (0, least satisfied, a a a Job health living Purposeful life Treated with respect Social support network experience index 10, most satisfied) (% of (% of all (% of all employed respondents respondents respondents who are (0, most negative, who are who are HDI rank satisfied) Total Female Total Female Total Female 100, least negative) satisfied) satisfied) Total Female b b b b b b b b b b b b 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 94 Suriname .. .. .. .. .. .. .. .. .. .. .. .. 95 Bolivia, Plurinational State of 6.5 6.4 83 79 67 94 93 90 91 82 81 32 96 Paraguay 6.9 6.9 85 84 63 93 93 96 96 89 90 16 97 Philippines 5.5 5.5 83 77 68 96 96 94 95 77 76 34 98 Botswana 4.7 4.4 58 67 41 92 91 83 85 83 81 23 99 Moldova, Republic of 5.7 5.6 68 60 39 79 77 73 73 83 84 27 100 Mongolia 5.7 5.6 78 69 50 96 96 66 70 91 92 15 101 Egypt 5.8 6.2 84 86 82 86 87 90 84 74 75 33 102 Uzbekistan 6.0 6.0 86 79 69 97 97 92 91 90 89 14 103 Micronesia, Federated States of .. .. .. .. .. .. .. .. .. .. .. .. 104 Guyana 6.5 6.6 84 87 64 95 98 77 79 84 85 28 105 Namibia 5.2 .. 84 87 61 98 98 86 88 83 86 16 106 Honduras 7.0 7.0 84 83 65 95 94 91 92 81 83 24 107 Maldives .. .. .. .. .. .. .. .. .. .. .. .. 108 Indonesia 5.7 5.6 63 83 62 95 95 92 94 78 78 13 109 Kyrgyzstan 5.0 4.9 78 74 48 91 92 86 85 85 85 16 110 South Africa 5.0 4.7 66 79 42 97 96 83 83 88 89 24 111 Syrian Arab Republic 5.9 6.1 .. 89 67 .. .. 91 92 84 85 31 112 Tajikistan 5.1 4.9 78 75 69 91 90 76 77 65 67 21 113 Viet Nam 5.4 5.4 72 79 59 98 98 92 90 79 77 17 114 Morocco 5.8 6.0 69 88 71 90 91 89 87 85 87 19 115 Nicaragua 7.1 7.1 80 80 62 98 97 91 93 83 83 28 table 9 116 Guatemala 7.2 .. 92 88 76 97 96 91 91 83 81 23 117 Equatorial Guinea .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 118 Cape Verde .. .. .. .. .. .. .. .. .. 119 India 5.5 5.4 74 85 61 91 90 72 79 66 65 26 120 Timor-Leste .. .. .. .. .. .. .. .. .. .. .. .. 121 Swaziland .. .. .. .. .. .. .. .. .. .. .. .. 122 Lao People’s Democratic Republic 6.2 6.3 91 89 80 98 98 43 42 81 83 .. 123 Solomon Islands .. .. .. .. .. .. .. .. .. .. .. .. 124 Cambodia 4.9 4.9 80 69 51 81 79 87 85 82 79 19 125 Pakistan 5.4 5.5 77 75 53 72 73 89 81 44 50 32 126 Congo 3.6 .. 67 62 32 .. .. 80 82 55 57 25 127 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. ## LOW HUMAN DEVELOPMENT 128 Kenya 3.7 3.6 57 70 25 98 98 78 81 79 80 19 129 Bangladesh 5.3 5.4 76 73 63 94 92 87 86 53 51 22 130 Ghana 4.7 4.7 54 66 34 98 97 88 85 63 61 22 131 Cameroon 3.9 4.0 63 69 40 93 91 85 87 73 74 23 132 Myanmar .. .. 68 75 59 90 89 53 55 89 86 .. 133 Yemen 4.8 .. 74 80 53 88 87 84 90 75 73 35 134 Benin 3.0 2.9 53 63 23 96 95 79 80 38 34 24 135 Madagascar 3.7 3.7 46 76 24 96 95 77 75 77 74 19 136 Mauritania 5.0 5.0 57 79 47 93 93 85 85 81 80 19 137 Papua New Guinea .. .. .. .. .. .. .. .. .. .. .. .. 138 Nepal 5.3 5.5 80 84 51 93 93 48 44 80 80 21 139 Togo 2.6 2.7 31 40 11 99 99 54 55 28 24 30 140 Comoros .. .. .. 67 23 .. .. 87 89 62 62 16 141 Lesotho .. .. .. .. .. .. .. .. .. .. .. .. 142 Nigeria 3.8 4.9 65 80 40 92 90 81 80 72 69 23 143 Uganda 4.5 4.7 53 64 35 96 96 79 83 85 85 31 144 Senegal 4.5 4.6 39 68 27 89 88 85 80 81 80 22 145 Haiti 3.9 .. 51 51 35 81 81 66 64 64 65 27 178 human development report 2010 Perceptions of individual well-being and happiness Satisfaction with personal Elements of happiness dimensions of well-being (% answering “’yes’” to having the element) a Overall life satisfaction Personal Standard of Negative (0, least satisfied, a a a Job health living Purposeful life Treated with respect Social support network experience index 10, most satisfied) (% of (% of all (% of all employed respondents respondents respondents who are (0, most negative, who are who are HDI rank satisfied) Total Female Total Female Total Female 100, least negative) satisfied) satisfied) Total Female b b b b b b b b b b b b 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 146 Angola 4.3 4.2 72 67 54 90 89 83 83 58 59 27 147 Djibouti 5.7 5.7 89 86 77 .. .. 84 84 90 90 12 148 Tanzania, United Republic of 2.4 2.4 45 67 21 95 88 74 77 76 87 22 149 Côte d’Ivoire 4.5 4.5 .. 68 17 98 99 89 89 67 67 16 150 Zambia 4.3 4.2 48 78 34 93 94 83 83 62 76 18 151 Gambia .. .. .. .. .. .. .. .. .. .. .. .. 152 Rwanda 4.2 4.1 41 64 37 88 95 77 75 56 56 13 153 Malawi 6.2 5.9 62 77 64 99 99 88 90 72 70 14 154 Sudan 5.0 .. 65 77 64 97 97 89 90 89 90 28 155 Afghanistan 4.1 4.1 71 79 53 83 83 64 59 54 51 24 156 Guinea 4.5 .. 68 75 27 96 96 86 87 58 59 26 157 Ethiopia 4.2 .. 50 79 33 89 87 74 47 76 77 21 158 Sierra Leone 3.6 3.7 49 47 19 98 98 81 80 59 59 37 159 Central African Republic 4.6 .. 78 81 31 96 96 74 74 56 60 28 160 Mali 3.8 3.9 30 71 30 99 98 86 91 75 74 13 161 Burkina Faso 3.6 3.7 46 70 27 94 91 83 81 73 74 24 162 Liberia 3.4 3.4 47 70 46 100 99 82 80 58 58 27 163 Chad 5.4 5.0 78 69 52 93 83 79 74 57 67 20 164 Guinea-Bissau .. .. .. .. .. .. .. .. .. .. .. .. 165 Mozambique 3.8 3.9 74 82 46 93 92 89 90 75 77 22 166 Burundi 2.9 2.8 43 55 24 .. .. 81 83 32 30 16 167 Niger 3.8 3.7 54 82 52 99 99 93 94 77 79 14 table 9 168 Congo, Democratic Republic of the 4.4 3.6 60 74 40 98 .. 79 69 67 71 23 169 Zimbabwe 2.8 2.8 49 72 27 91 92 81 84 81 81 22 ## OTHER COUNTRIES OR TERRITORIES Cuba .. .. 68 76 .. 96 96 88 88 93 93 28 Iraq 5.5 5.3 64 66 41 .. .. 84 82 84 84 36 Lebanon 4.7 4.9 69 80 58 86 86 90 92 73 74 39 Occupied Palestinian Territories 5.0 5.0 .. 78 43 77 80 89 88 74 71 45 Somalia .. .. .. 87 73 .. .. 74 74 88 89 9 Notes a For details on satisfaction questions see the Gallup World Poll (www.gallup.com). b Data refer to the most recent year available during the period specified. Source Columns 1–12: Gallup World Poll database (2010). 179 ## STATISTICAL ANNEX 10 e l Civic and community well-being b ta Satisfaction with measures of well-being Crime and safety (% satisfied) Perception Affordable Healthcare Education system Water a b b b b b b Homicide rate Robbery rate Assault victims of safety housing quality and schools quality Community Air quality (per 100,000 (per 100,000 (% reporting having HDI rank people) people) been a victim) (%) c c c c c c c c c c 2003–2008 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2003–2008 ## VERY HIGH HUMAN DEVELOPMENT 1 Norway 0.6 34 3 81 .. 42 80 75 89 95 2 Australia 1.2 78 4 63 .. 42 79 68 89 88 3 New Zealand 1.3 53 1 57 .. 55 80 73 91 85 4 United States 5.2 142 2 75 75 70 76 70 85 87 5 Ireland 2.0 56 3 62 73 56 68 75 94 86 6 Liechtenstein 2.8 3 .. .. .. .. .. .. .. .. 7 Netherlands 1.0 84 3 74 .. 51 89 70 76 93 8 Canada 1.7 97 3 76 73 62 70 71 83 89 9 Sweden 0.9 97 4 69 .. 51 77 67 84 95 10 Germany 0.8 61 3 72 78 70 86 59 87 95 11 Japan 0.5 3 1 73 70 71 67 53 79 81 12 Korea, Republic of 2.3 10 3 60 68 60 64 51 78 83 13 Switzerland 0.7 56 3 76 .. 54 92 75 82 96 14 France 1.4 172 5 59 76 57 83 70 78 86 15 Israel 2.4 40 4 70 .. 45 71 57 57 53 16 Finland 2.5 32 3 75 .. 63 66 64 81 91 17 Iceland 0.0 14 3 77 .. 65 88 87 85 97 18 Belgium 1.8 1,837 6 64 .. 52 91 77 69 85 19 Denmark 1.4 62 1 83 .. 71 86 74 93 96 20 Spain 0.9 1,067 6 58 69 26 77 58 76 80 21 Hong Kong, China (SAR) 0.6 .. 1 85 .. 68 65 52 .. 71 22 Greece 1.1 26 3 60 63 63 51 50 74 69 23 Italy 1.2 122 4 61 64 42 64 61 71 83 24 Luxembourg 1.5 68 3 76 .. 52 90 73 78 89 25 Austria 0.5 62 4 75 .. 57 93 73 80 94 26 United Kingdom 4.8 282 2 64 77 59 88 70 87 93 27 Singapore 0.4 22 0 98 89 54 89 94 97 99 28 Czech Republic 2.0 45 6 60 .. 42 68 71 66 80 79 75 76 85 29 Slovenia 0.5 19 3 79 69 26 30 Andorra 1.3 .. .. .. .. .. .. .. .. .. 31 Slovakia 1.7 25 2 47 .. 38 58 53 62 78 32 United Arab Emirates 0.9 13 2 91 71 53 82 83 72 73 33 Malta 1.0 36 4 66 .. 41 69 63 41 65 34 Estonia 6.3 68 5 60 60 44 45 59 75 67 35 Cyprus 1.0 8 4 65 60 42 67 62 67 67 36 Hungary 1.5 31 5 61 .. 47 66 60 75 78 37 Brunei Darussalam 0.5 1 .. .. .. .. .. .. .. .. 38 Qatar 1.0 .. 4 87 70 49 85 77 81 80 39 Bahrain 0.8 39 5 79 71 61 84 88 72 62 40 Portugal 1.2 195 7 62 .. 35 64 69 88 88 41 Poland 1.2 55 1 61 .. 0 49 66 77 75 42 Barbados 8.7 .. .. .. .. .. .. .. .. .. 180 human development report 2010 Civic and community well-being Satisfaction with measures of well-being Crime and safety (% satisfied) Perception Affordable Healthcare Education system Water a b b b b b b Homicide rate Robbery rate Assault victims of safety housing quality and schools quality Community Air quality (per 100,000 (per 100,000 (% reporting having HDI rank people) people) been a victim) (%) c c c c c c c c c c 2003–2008 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2003–2008 ## HIGH HUMAN DEVELOPMENT 43 Bahamas 13.7 .. .. .. .. .. .. .. .. .. 44 Lithuania 8.6 104 4 29 51 20 37 40 66 71 45 Chile 8.1 180 13 42 65 46 47 61 60 85 46 Argentina 5.2 859 16 39 58 29 58 51 72 74 47 Kuwait 1.1 .. 5 86 62 61 72 62 37 52 48 Latvia 4.4 64 8 44 56 43 32 42 75 65 49 Montenegro 3.7 13 5 70 .. 38 66 72 70 69 50 Romania 2.2 12 4 51 57 23 49 58 70 67 51 Croatia 1.6 28 9 73 .. 39 66 67 83 81 52 Uruguay 5.8 277 11 46 74 41 77 76 87 94 53 Libyan Arab Jamahiriya 2.2 .. .. .. .. .. .. .. .. .. 54 Panama 13.3 38 11 47 67 54 64 70 82 74 55 Saudi Arabia 0.9 .. 6 77 63 58 65 67 55 52 56 Mexico 11.6 505 12 44 64 41 58 72 73 66 57 Malaysia 2.3 82 6 49 83 70 89 93 83 86 58 Bulgaria 2.3 38 4 56 .. 59 33 45 60 57 59 Trinidad and Tobago 39.7 .. 7 42 .. 45 57 70 76 74 60 Serbia 3.4 37 12 70 .. 30 51 64 63 58 61 Belarus 5.6 69 2 48 57 30 32 57 66 64 62 Costa Rica 8.3 527 16 44 73 57 72 84 84 87 63 Peru 3.2 156 15 43 52 39 46 51 61 62 64 Albania 3.3 5 1 54 .. 57 38 49 58 53 65 Russian Federation 14.2 173 3 31 45 24 29 42 54 42 66 Kazakhstan 10.6 72 4 52 53 35 39 54 61 60 67 Azerbaijan 2.0 7 2 71 56 57 41 59 65 55 68 Bosnia and Herzegovina 1.8 20 6 69 .. 43 53 59 76 77 69 Ukraine 6.3 59 4 31 45 29 17 38 53 44 table 10 70 Iran, Islamic Republic of 2.9 .. 7 55 .. 0 60 51 67 58 53 63 66 60 71 The former Yugoslav Republic of Macedonia 2.0 25 6 60 .. 40 72 Mauritius 3.8 98 .. .. .. .. .. .. .. .. 73 Brazil 22.0 .. 10 40 57 45 39 53 70 78 74 Georgia 7.6 62 1 79 64 51 47 60 68 66 75 Venezuela, Bolivarian Republic of 52.0 .. 11 23 61 35 67 78 70 60 76 Armenia 2.5 11 2 75 54 33 44 55 63 65 77 Ecuador 18.1 399 20 38 60 40 50 71 63 64 78 Belize 34.3 182 14 43 .. 40 43 58 71 63 79 Colombia 38.8 .. 13 45 66 46 64 73 69 73 80 Jamaica 59.5 .. 4 46 .. 50 71 69 86 89 81 Tunisia 1.5 .. 5 81 69 74 71 72 65 59 82 Jordan 1.7 14 3 84 65 53 73 67 58 45 83 Turkey 2.9 10 8 42 .. 63 59 50 63 53 84 Algeria 0.6 72 15 39 55 37 50 61 57 61 85 Tonga .. .. .. .. .. .. .. .. .. .. ## MEDIUM HUMAN DEVELOPMENT 86 Fiji 2.8 .. .. .. .. .. .. .. .. .. 87 Turkmenistan 2.9 3 .. .. .. .. .. .. 81 71 88 Dominican Republic 21.5 556 7 38 .. 42 52 74 72 65 89 China 1.2 .. 3 74 67 67 57 61 73 74 90 El Salvador 51.8 92 13 43 69 57 64 78 80 68 91 Sri Lanka 7.4 .. 4 72 77 36 75 83 89 86 92 Thailand 5.9 107 3 65 .. 87 87 88 82 84 93 Gabon .. .. .. .. .. .. .. .. .. .. 94 Suriname 13.7 .. .. .. .. .. .. .. .. .. 95 Bolivia, Plurinational State of 10.6 .. 20 37 64 43 52 77 75 80 181 ## STATISTICAL ANNEX Civic and community well-being Satisfaction with measures of well-being Crime and safety (% satisfied) Perception Affordable Healthcare Education system Water a b b b b b b Homicide rate Robbery rate Assault victims of safety housing quality and schools quality Community Air quality (per 100,000 (per 100,000 (% reporting having HDI rank people) people) been a victim) (%) c c c c c c c c c c 2003–2008 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2003–2008 96 Paraguay 12.2 31 12 40 65 54 55 75 88 83 97 Philippines 6.4 10 5 66 76 52 80 82 87 84 98 Botswana 11.9 .. 13 39 .. 65 64 68 84 69 99 Moldova, Republic of 5.1 25 6 37 49 26 41 58 59 56 100 Mongolia 7.9 31 6 40 .. 21 45 60 51 63 101 Egypt 0.8 1 4 73 63 39 61 61 76 74 102 Uzbekistan 3.2 .. 1 66 79 70 75 81 87 81 103 Micronesia, Federated States of .. .. .. .. .. .. .. .. .. .. 104 Guyana 20.7 .. 10 47 .. 42 63 61 79 54 105 Namibia 17.9 .. 14 33 .. 52 57 75 76 82 106 Honduras 60.9 .. 14 48 67 50 59 73 82 75 107 Maldives 2.6 196 .. .. .. .. .. .. .. .. 108 Indonesia 0.7 .. 3 83 67 40 74 78 76 82 109 Kyrgyzstan 7.8 43 3 52 64 57 55 68 86 70 110 South Africa 36.5 .. 15 20 60 39 50 66 74 70 111 Syrian Arab Republic 3.0 4 5 84 62 59 67 67 64 59 112 Tajikistan 2.3 3 2 73 63 52 50 68 83 47 113 Viet Nam 1.9 .. 2 80 71 59 68 83 73 79 114 Morocco 0.4 74 5 75 51 46 34 44 67 65 115 Nicaragua 13.0 441 13 49 64 40 60 71 82 65 116 Guatemala 45.2 .. 15 41 69 50 65 80 78 64 117 Equatorial Guinea .. .. .. .. .. .. .. .. .. .. 118 Cape Verde 11.4 .. .. .. .. .. .. .. .. .. 119 India 2.8 2 3 74 .. 62 59 72 86 67 120 Timor-Leste .. .. .. .. .. .. .. .. .. .. 121 Swaziland 12.6 .. .. .. .. .. .. .. .. .. 122 Lao People’s Democratic Republic .. .. 3 79 .. 44 72 83 89 83 123 Solomon Islands .. 10 .. .. .. .. .. .. .. .. 98 96 88 124 Cambodia 3.2 .. 1 60 82 41 86 table 10 125 Pakistan 6.8 .. 5 44 53 47 36 54 80 63 126 Congo .. .. 11 41 .. 28 24 41 65 33 127 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. ## LOW HUMAN DEVELOPMENT 128 Kenya 3.6 9 14 35 51 54 44 64 79 45 129 Bangladesh 2.6 .. 3 82 72 68 54 79 92 80 130 Ghana 1.7 .. 10 69 53 50 44 53 79 62 131 Cameroon 2.3 .. 8 47 55 53 50 70 77 51 132 Myanmar .. .. 1 81 .. 54 .. .. 88 91 133 Yemen 4.0 .. 10 65 49 .. 28 45 73 47 134 Benin .. .. 8 63 .. 48 40 46 78 56 135 Madagascar .. .. 2 57 .. 75 44 64 81 53 136 Mauritania .. .. 10 65 44 40 24 42 64 57 137 Papua New Guinea .. .. .. .. .. .. .. .. .. .. 138 Nepal 2.2 1 5 43 64 62 57 77 81 71 139 Togo .. .. 10 42 .. 27 20 30 52 34 140 Comoros .. .. 9 78 44 21 13 39 77 66 141 Lesotho 36.7 53 .. .. .. .. .. .. .. .. 142 Nigeria 1.3 .. 17 51 35 31 24 0 68 36 143 Uganda 8.7 13 24 51 49 37 38 49 83 53 144 Senegal 1.1 .. 10 63 41 55 16 30 69 44 145 Haiti .. .. 33 44 .. 18 22 35 43 37 146 Angola 5.0 .. 38 53 .. 38 49 62 60 47 147 Djibouti .. .. 11 84 56 43 41 72 69 63 148 Tanzania, United Republic of 7.7 .. 21 46 .. 28 26 55 62 34 149 Côte d’Ivoire 0.4 3 6 47 41 54 21 26 75 52 182 human development report 2010 Civic and community well-being Satisfaction with measures of well-being Crime and safety (% satisfied) Perception Affordable Healthcare Education system Water a b b b b b b Homicide rate Robbery rate Assault victims of safety housing quality and schools quality Community Air quality (per 100,000 (per 100,000 (% reporting having HDI rank people) people) been a victim) (%) c c c c c c c c c c 2003–2008 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2006–2009 2003–2008 150 Zambia .. .. 11 49 .. 45 44 55 79 54 151 Gambia 0.4 .. .. .. .. .. .. .. .. .. 152 Rwanda 4.2 .. 6 80 60 42 68 75 78 55 153 Malawi .. .. 14 55 65 57 62 67 91 62 154 Sudan .. 7 12 79 59 54 50 58 73 57 155 Afghanistan .. .. 16 37 48 35 32 58 69 61 156 Guinea 0.4 2 12 48 .. 36 27 55 55 38 157 Ethiopia 6.4 .. 16 49 .. 25 17 43 77 29 158 Sierra Leone 2.6 3 26 53 .. 21 19 34 64 28 159 Central African Republic .. .. 10 69 .. 34 34 35 77 40 160 Mali .. .. 5 77 .. 55 27 30 67 36 161 Burkina Faso 0.5 .. 7 60 .. 44 32 48 68 38 162 Liberia .. .. 24 34 .. 21 20 32 69 39 163 Chad .. .. 19 28 .. 23 34 48 45 31 164 Guinea-Bissau .. .. .. .. .. .. .. .. .. .. 165 Mozambique 5.1 .. 24 52 .. 60 66 76 79 71 166 Burundi .. .. 11 63 54 32 43 79 85 52 167 Niger .. .. 5 73 56 65 34 55 94 60 168 Congo, Democratic Republic of the .. .. 13 47 .. 25 29 28 54 42 169 Zimbabwe 8.7 71 12 41 51 59 32 31 80 62 ## OTHER COUNTRIES OR TERRITORIES Bhutan 1.4 .. .. .. .. .. .. .. .. .. Cuba .. .. 6 51 .. 14 60 78 53 59 Iraq .. .. 10 34 44 31 35 55 45 26 Lebanon 0.6 4 4 56 55 69 67 70 41 37 Monaco 0.0 12 .. .. .. .. .. .. .. .. Occupied Palestinian Territories 3.9 .. 6 47 54 54 57 59 52 49 Oman 0.9 9 .. .. .. .. .. .. .. .. table 10 Saint Kitts and Nevis 35.2 .. .. .. .. .. .. .. .. .. Saint Lucia 16.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Seychelles 8.4 .. .. .. Somalia .. .. 13 74 51 49 31 56 90 65 Notes a Refers to people answering “yes” to the question: “Do you feel safe walking alone at night?” b For details on satisfaction questions see the Gallup World Poll (www.gallup.com). c Data refer to the most recent year available during the period specified. Sources Columns 1 and 2: UNODC (2010). Columns 3–10: Gallup World Poll database (2010). 183 ## STATISTICAL ANNEX 11 e l Demographic trends b ta Population Total Average annual growth Urban Median age Dependency ratio Total fertility rate Sex ratio at birth (per 100 people (male births per a b HDI rank (millions) (%) (% of total) (years) ages 15–64) (births per woman) 100 female births) 1990 2010 2030 1990–1995 2010–2015 1990 2010 1990 2010 1990 2010 1990–1995 2010–2015 1990 2010 ## VERY HIGH HUMAN DEVELOPMENT 1 Norway 4.2 4.9 5.5 0.5 0.7 72.0 79.4 35.4 38.9 54.4 51.0 1.9 1.9 105.2 105.4 2 Australia 17.1 21.5 25.7 1.2 1.0 85.4 89.1 32.2 37.8 49.8 48.8 1.9 1.9 105.2 105.3 3 New Zealand 3.4 4.3 5.0 1.7 0.9 84.7 86.2 31.0 36.6 51.9 49.7 2.1 2.0 105.1 105.8 4 United States 254.9 317.6 370.0 1.2 0.9 75.3 82.3 32.8 36.6 51.7 49.6 2.0 2.0 104.9 105.1 5 Ireland 3.5 4.6 5.6 0.5 1.3 56.9 61.9 29.1 34.6 63.1 47.3 2.0 1.9 105.7 106.4 6 Liechtenstein 0.0 0.0 0.0 1.3 0.8 16.9 14.3 .. .. .. .. .. .. .. .. 7 Netherlands 15.0 16.7 17.5 0.7 0.3 68.7 82.9 34.5 40.8 45.1 49.2 1.6 1.8 104.7 105.2 8 Canada 27.7 33.9 40.1 1.1 0.9 76.6 80.6 32.9 39.9 47.0 43.8 1.7 1.6 104.9 105.1 9 Sweden 8.6 9.3 10.1 0.6 0.4 83.1 84.7 38.3 40.9 55.6 53.4 2.0 1.9 105.4 105.7 10 Germany 79.4 82.1 77.9 0.5 –0.2 73.1 73.9 37.7 44.3 45.0 51.1 1.3 1.3 105.5 105.4 11 Japan 123.2 127.0 117.4 0.4 –0.2 63.1 66.8 37.4 44.7 43.5 55.7 1.5 1.3 105.0 105.5 12 Korea, Republic of 43.0 48.5 49.1 0.8 0.3 73.8 83.0 27.0 37.9 44.1 37.4 1.7 1.3 112.6 110.0 13 Switzerland 6.7 7.6 8.1 0.9 0.4 73.2 73.6 36.9 41.9 46.2 48.0 1.5 1.5 104.4 105.1 14 France 56.8 62.6 66.5 0.4 0.4 74.1 85.3 34.9 40.1 52.1 54.7 1.7 1.9 104.9 104.3 15 Israel 4.5 7.3 9.2 3.5 1.4 90.4 91.9 25.8 29.7 67.7 60.8 2.9 2.6 104.9 105.9 16 Finland 5.0 5.3 5.5 0.5 0.3 79.4 85.1 36.4 42.0 48.6 50.9 1.8 1.9 104.5 104.6 17 Iceland 0.3 0.3 0.4 1.0 1.4 90.8 93.4 30.0 35.1 55.3 47.2 2.2 2.1 104.8 106.0 18 Belgium 9.9 10.7 11.3 0.3 0.3 96.4 97.4 36.3 41.3 49.3 51.9 1.6 1.8 105.5 104.8 19 Denmark 5.1 5.5 5.6 0.3 0.2 84.8 86.9 37.1 40.8 48.4 53.2 1.8 1.9 105.5 105.8 20 Spain 38.8 45.3 49.8 0.3 0.8 75.4 77.4 33.7 40.2 50.2 47.3 1.3 1.6 105.8 106.4 21 Hong Kong, China (SAR) 5.7 7.1 8.2 1.7 0.9 99.5 100.0 31.0 41.9 42.8 32.3 1.3 1.0 107.8 108.1 1.0 0.1 58.8 61.4 36.1 41.6 49.1 48.2 1.4 1.4 105.6 106.6 22 Greece 10.2 11.2 11.2 23 Italy 57.0 60.1 59.5 0.1 0.2 66.7 68.4 37.1 43.3 46.2 52.9 1.3 1.4 105.9 105.5 24 Luxembourg 0.4 0.5 0.6 1.4 1.1 81.0 85.2 36.4 39.3 44.5 46.3 1.7 1.7 104.4 106.5 25 Austria 7.7 8.4 8.6 0.7 0.2 65.8 67.6 35.7 41.8 48.0 47.7 1.5 1.4 105.3 105.4 26 United Kingdom 57.2 61.9 68.0 0.3 0.5 78.1 79.6 35.8 39.9 53.2 51.4 1.8 1.9 104.6 105.0 27 Singapore 3.0 4.8 5.5 2.9 0.9 100.0 100.0 29.3 40.6 37.1 34.7 1.8 1.3 107.4 107.3 28 Czech Republic 10.3 10.4 10.5 0.0 0.2 75.2 73.5 35.2 39.6 51.5 41.5 1.7 1.5 104.9 105.7 29 Slovenia 1.9 2.0 2.0 0.4 0.2 50.4 49.5 34.1 41.7 47.1 43.3 1.4 1.5 105.1 105.3 30 Andorra 0.1 0.1 0.1 4.1 1.5 94.7 88.0 .. .. .. .. .. .. .. .. 31 Slovakia 5.3 5.4 5.3 0.4 0.1 56.5 55.0 31.3 37.2 55.2 37.8 1.9 1.4 104.3 105.5 32 United Arab Emirates 1.9 4.7 6.6 5.3 2.0 79.1 84.1 27.4 31.7 45.2 25.2 3.9 1.9 104.1 105.3 33 Malta 0.4 0.4 0.4 1.0 0.3 90.4 94.7 33.0 39.0 51.3 42.9 2.0 1.3 105.7 106.0 34 Estonia 1.6 1.3 1.3 –1.7 0.0 71.1 69.5 34.4 39.6 51.0 48.0 1.6 1.8 105.0 105.6 35 Cyprus 0.7 0.9 1.1 1.4 1.0 66.8 70.3 30.9 36.5 58.1 44.2 2.4 1.6 107.1 106.8 36 Hungary 10.4 10.0 9.5 –0.1 –0.2 65.8 68.1 36.4 39.8 50.6 45.2 1.7 1.4 104.7 105.9 37 Brunei Darussalam 0.3 0.4 0.5 2.8 1.7 65.8 75.7 23.4 27.8 59.2 42.4 3.1 2.0 108.4 106.7 38 Qatar 0.5 1.5 2.0 2.4 1.6 92.2 95.8 29.6 30.1 40.5 20.5 4.1 2.3 103.8 105.4 39 Bahrain 0.5 0.8 1.1 3.2 1.8 88.1 88.6 25.9 28.1 50.8 39.3 3.4 2.1 107.5 105.2 40 Portugal 10.0 10.7 10.6 0.1 0.1 47.9 60.7 34.2 41.0 51.0 49.3 1.5 1.4 105.2 106.0 41 Poland 38.1 38.0 36.2 0.3 –0.1 61.3 61.0 32.3 38.2 54.3 39.4 1.9 1.3 105.0 105.7 42 Barbados 0.3 0.3 0.3 –0.1 0.2 32.7 44.5 28.4 37.8 51.5 37.9 1.6 1.6 102.8 103.4 ## HIGH HUMAN DEVELOPMENT 43 Bahamas 0.3 0.3 0.4 1.9 1.1 79.8 84.1 23.1 29.7 59.0 47.1 2.6 2.0 103.8 104.3 44 Lithuania 3.7 3.3 2.9 –0.4 –0.7 67.6 67.0 32.7 39.8 50.3 44.9 1.8 1.4 104.3 105.3 2.6 1.9 103.6 103.8 45 Chile 13.2 17.1 19.8 1.8 0.9 83.3 89.0 25.7 32.1 56.4 46.0 46 Argentina 32.5 40.7 47.3 1.4 0.9 87.0 92.4 27.6 30.4 65.4 55.2 2.9 2.2 103.4 103.6 184 human development report 2010 Demographic trends Population Total Average annual growth Urban Median age Dependency ratio Total fertility rate Sex ratio at birth (per 100 people (male births per a b HDI rank (millions) (%) (% of total) (years) ages 15–64) (births per woman) 100 female births) 1990 2010 2030 1990–1995 2010–2015 1990 2010 1990 2010 1990 2010 1990–1995 2010–2015 1990 2010 47 Kuwait 2.1 3.1 4.3 –4.3 2.0 98.0 98.4 22.8 30.6 60.9 34.5 3.2 2.1 103.3 102.7 48 Latvia 2.7 2.2 2.0 –1.3 –0.4 69.3 67.7 34.6 40.0 49.9 45.5 1.6 1.5 104.3 105.5 49 Montenegro 0.6 0.6 0.6 1.2 0.0 48.0 61.5 30.0 35.9 53.0 47.1 1.8 1.7 106.4 107.9 50 Romania 23.2 21.2 19.5 –0.5 –0.4 53.2 57.5 32.6 38.5 51.4 43.0 1.5 1.4 104.2 105.9 51 Croatia 4.5 4.4 4.2 0.7 –0.2 54.0 57.7 35.8 41.6 46.7 47.7 1.5 1.5 104.9 105.8 52 Uruguay 3.1 3.4 3.6 0.7 0.3 89.0 92.5 30.7 33.7 60.4 57.2 2.5 2.0 104.4 104.7 53 Libyan Arab Jamahiriya 4.4 6.5 8.5 2.0 1.8 75.7 77.9 17.9 26.2 84.4 52.5 4.1 2.5 104.4 104.9 54 Panama 2.4 3.5 4.5 2.0 1.5 53.9 74.8 21.9 27.3 67.1 55.4 2.9 2.4 104.0 104.5 55 Saudi Arabia 16.3 26.2 36.5 2.3 1.9 76.6 82.1 19.4 24.6 79.2 53.6 5.5 2.8 102.2 102.1 56 Mexico 83.4 110.6 126.5 1.9 0.9 71.4 77.8 19.8 27.6 75.0 52.7 3.2 2.0 104.0 104.3 57 Malaysia 18.1 27.9 35.3 2.6 1.5 49.8 72.2 21.5 26.3 69.7 51.3 3.5 2.4 106.4 105.8 58 Bulgaria 8.8 7.5 6.5 –1.1 –0.6 66.4 71.5 36.6 41.7 50.3 45.1 1.5 1.5 104.9 105.7 59 Trinidad and Tobago 1.2 1.3 1.4 0.7 0.4 8.5 13.9 23.5 30.8 65.9 37.9 2.1 1.7 103.0 103.1 60 Serbia 9.6 9.9 9.6 1.3 –0.1 50.4 56.1 33.6 37.6 48.9 46.9 2.0 1.6 107.6 107.8 61 Belarus 10.3 9.6 8.6 0.0 –0.5 66.0 74.7 33.0 38.2 50.9 39.0 1.7 1.3 105.1 106.1 62 Costa Rica 3.1 4.6 5.8 2.4 1.3 50.7 64.4 22.5 28.2 69.0 46.6 3.0 1.9 105.1 104.8 63 Peru 21.8 29.5 36.0 1.9 1.1 68.9 76.9 20.5 25.6 73.2 56.0 3.6 2.4 103.4 104.2 64 Albania 3.3 3.2 3.4 –1.0 0.5 36.4 51.9 23.8 30.0 61.6 48.5 2.8 1.9 108.2 107.0 65 Russian Federation 148.1 140.4 128.9 0.1 –0.3 73.4 73.2 33.3 38.1 49.4 38.7 1.6 1.5 104.4 105.5 66 Kazakhstan 16.5 15.8 17.2 –0.7 0.7 56.3 58.5 26.0 29.4 59.5 44.5 2.6 2.2 103.6 105.2 67 Azerbaijan 7.2 8.9 10.3 1.5 1.1 53.8 51.9 23.2 28.4 62.6 43.9 2.9 2.1 106.5 115.6 –0.2 39.3 48.6 29.7 39.3 43.5 41.0 1.5 1.2 103.3 106.7 68 Bosnia and Herzegovina 4.3 3.8 3.5 –5.1 69 Ukraine 51.6 45.4 40.2 –0.2 –0.6 66.8 68.8 35.1 39.5 50.6 41.8 1.6 1.5 105.1 105.5 70 Iran, Islamic Republic of 56.7 75.1 89.9 1.8 1.1 56.3 70.8 17.4 26.8 92.9 40.2 4.0 1.7 104.7 105.2 71 The former Yugoslav Republic of Macedonia 1.9 2.0 2.0 0.6 0.0 57.8 59.3 29.5 36.0 50.6 41.9 2.1 1.5 106.0 107.9 72 Mauritius 1.1 1.3 1.4 1.3 0.6 43.9 41.8 24.9 32.6 50.9 42.2 2.3 1.9 102.7 103.7 73 Brazil 149.6 195.4 217.1 1.6 0.7 73.9 86.5 22.5 29.0 65.9 47.9 2.6 1.7 103.5 104.2 74 Georgia 5.5 4.2 3.8 –1.5 –0.7 55.0 52.8 31.2 37.6 51.4 44.9 2.1 1.6 105.5 110.7 75 Venezuela, Bolivarian Republic of 19.7 29.0 37.1 2.3 1.5 84.3 93.4 21.0 26.1 71.7 54.1 3.3 2.4 104.2 104.5 76 Armenia 3.5 3.1 3.2 –1.9 0.3 67.4 64.2 27.0 32.0 56.2 45.5 2.4 1.8 103.2 116.5 77 Ecuador 10.3 13.8 16.7 2.1 1.2 55.1 67.0 20.1 25.4 75.9 59.5 3.4 2.4 103.6 104.4 78 Belize 0.2 0.3 0.4 3.0 1.9 47.5 52.3 17.9 22.3 90.0 62.9 4.4 2.7 103.1 102.6 79 Colombia 33.2 46.3 57.3 1.9 1.3 68.3 75.1 21.5 26.8 69.1 52.4 3.0 2.3 104.1 104.3 80 Jamaica 2.4 2.7 2.9 0.8 0.4 49.4 52.0 21.9 26.3 73.7 57.9 2.8 2.3 103.5 105.1 table 81 Tunisia 8.2 10.4 12.1 1.7 1.0 58.0 67.3 20.7 29.1 74.5 42.0 3.1 1.8 106.2 106.7 11 82 Jordan 3.3 6.5 8.6 5.6 1.4 72.2 78.5 16.3 22.8 100.0 60.4 5.1 2.8 106.7 104.4 83 Turkey 56.1 75.7 90.4 1.7 1.1 59.2 69.7 21.5 28.3 67.3 47.8 2.9 2.1 103.5 104.1 84 Algeria 25.3 35.4 44.7 2.2 1.5 52.1 66.5 18.2 26.2 87.4 46.3 4.1 2.3 104.6 104.6 85 Tonga 0.1 0.1 0.1 0.6 0.1 22.7 23.4 19.7 21.3 78.1 76.3 4.5 3.6 107.0 106.5 ## MEDIUM HUMAN DEVELOPMENT 86 Fiji 0.7 0.9 0.9 1.2 0.5 41.6 51.9 21.3 25.0 69.4 55.9 3.4 2.6 106.3 106.3 87 Turkmenistan 3.7 5.2 6.3 2.6 1.2 45.1 49.5 19.7 24.7 79.4 49.6 4.0 2.3 103.2 103.2 88 Dominican Republic 7.4 10.2 12.4 1.9 1.2 55.2 69.2 20.3 25.0 73.2 59.3 3.3 2.5 103.7 104.1 c c c 1,354.1 1,462.5 1.2 0.6 26.4 47.0 25.0 34.2 51.2 39.1 2.0 1.8 110.4 121.2 89 China 1,142.1 90 El Salvador 5.3 6.2 7.2 1.4 0.6 49.2 64.3 19.2 23.9 83.6 63.5 3.7 2.2 103.5 104.5 59.9 47.1 2.5 2.2 103.5 103.7 91 Sri Lanka 17.3 20.4 22.2 1.1 0.7 18.6 14.3 24.3 30.6 92 Thailand 56.7 68.1 73.5 1.2 0.5 29.4 34.0 24.6 33.2 53.0 41.2 2.1 1.9 104.5 104.6 93 Gabon 0.9 1.5 2.0 3.2 1.8 69.1 86.0 19.6 21.6 88.5 66.4 5.1 3.0 101.9 102.1 94 Suriname 0.4 0.5 0.6 1.4 0.8 60.0 69.4 23.0 27.6 61.2 53.9 2.6 2.3 106.4 107.2 95 Bolivia, Plurinational State of 6.7 10.0 13.0 2.3 1.6 55.6 66.6 19.2 21.9 80.8 68.2 4.8 3.1 103.6 104.1 96 Paraguay 4.2 6.5 8.5 2.4 1.6 48.7 61.5 19.3 23.1 83.3 63.2 4.3 2.8 103.5 103.9 97 Philippines 62.4 93.6 124.4 2.3 1.7 48.6 48.9 19.3 23.2 78.3 60.7 4.1 2.9 104.5 105.0 98 Botswana 1.4 2.0 2.4 2.7 1.3 41.9 61.1 17.3 22.8 90.9 58.2 4.3 2.7 101.5 101.8 99 Moldova, Republic of 4.4 3.6 3.2 –0.1 –0.6 46.8 47.0 29.9 35.2 56.8 38.4 2.1 1.5 104.3 105.8 100 Mongolia 2.2 2.7 3.2 0.5 1.1 57.0 62.0 18.8 26.3 84.2 42.1 3.5 1.9 102.3 104.1 101 Egypt 57.8 84.5 110.9 2.0 1.7 43.5 43.4 18.9 23.9 85.2 58.1 3.9 2.7 104.4 104.7 102 Uzbekistan 20.5 27.8 33.9 2.2 1.2 40.2 36.3 19.4 24.5 81.5 49.3 3.9 2.2 103.5 103.9 17 103 Micronesia, Federated States of 0.1 0.1 0.1 2.1 0.5 25.8 22.7 17.6 20.8 91.2 67.3 4.8 3.2 108.0 107.2 104 Guyana 0.7 0.8 0.7 0.3 –0.2 29.6 28.6 20.8 27.4 69.9 54.5 2.6 2.2 102.8 103.4 185 ## STATISTICAL ANNEX Demographic trends Population Total Average annual growth Urban Median age Dependency ratio Total fertility rate Sex ratio at birth (per 100 people (male births per a b HDI rank (millions) (%) (% of total) (years) ages 15–64) (births per woman) 100 female births) 1990 2010 2030 1990–1995 2010–2015 1990 2010 1990 2010 1990 2010 1990–1995 2010–2015 1990 2010 105 Namibia 1.4 2.2 3.0 2.7 1.7 27.7 38.0 17.8 21.1 88.9 66.8 4.9 3.1 100.8 101.3 106 Honduras 4.9 7.6 10.5 2.6 1.9 40.5 51.6 17.1 20.9 95.4 69.8 4.9 3.0 103.6 104.2 107 Maldives 0.2 0.3 0.4 2.8 1.5 25.8 40.1 16.3 24.4 99.3 46.0 5.3 1.9 104.0 103.0 108 Indonesia 177.4 232.5 271.5 1.5 1.0 30.6 44.3 21.7 28.2 65.6 48.7 2.9 2.0 103.5 104.1 109 Kyrgyzstan 4.4 5.6 6.5 0.9 1.1 37.8 34.6 21.6 25.1 74.1 51.7 3.6 2.4 102.9 104.8 110 South Africa 36.7 50.5 54.7 2.4 0.5 52.0 61.7 20.1 24.9 72.7 53.6 3.3 2.4 101.5 101.6 111 Syrian Arab Republic 12.7 22.5 30.6 2.8 1.7 48.9 55.7 15.7 22.5 104.3 61.2 4.9 2.9 104.1 104.5 112 Tajikistan 5.3 7.1 9.6 1.7 1.9 31.7 26.3 18.3 20.7 88.6 66.5 4.9 3.1 102.9 104.2 113 Viet Nam 66.2 89.0 105.4 1.9 1.0 20.3 30.4 20.0 28.5 78.9 45.8 3.3 2.0 104.0 105.9 114 Morocco 24.8 32.4 39.3 1.7 1.2 48.4 58.2 19.7 26.2 77.3 50.2 3.7 2.3 103.7 103.7 115 Nicaragua 4.1 5.8 7.4 2.4 1.5 52.3 57.3 16.8 22.0 96.6 64.2 4.5 2.6 103.4 104.3 116 Guatemala 8.9 14.4 21.7 2.3 2.4 41.1 49.5 17.1 18.8 95.1 85.0 5.5 3.7 104.1 103.8 117 Equatorial Guinea 0.4 0.7 1.1 3.5 2.4 34.8 39.7 21.2 19.3 76.1 77.3 5.9 5.1 100.5 101.3 118 Cape Verde 0.4 0.5 0.6 2.3 1.3 44.1 61.1 16.3 21.3 106.9 65.5 4.9 2.5 101.2 101.6 119 India 862.2 1,214.5 1,484.6 2.0 1.3 25.6 30.0 21.1 25.0 71.5 55.6 3.9 2.5 107.7 108.5 120 Timor-Leste 0.7 1.2 2.1 2.7 3.4 20.8 28.1 19.4 17.4 72.1 91.2 5.7 6.0 106.2 104.7 121 Swaziland 0.9 1.2 1.5 2.3 1.4 22.9 21.4 15.9 19.3 103.2 73.0 5.3 3.2 101.1 101.2 122 Lao People’s Democratic Republic 4.2 6.4 8.9 2.7 1.8 15.4 33.2 17.9 20.6 89.4 68.1 5.8 3.2 103.5 104.3 123 Solomon Islands 0.3 0.5 0.8 2.9 2.2 13.7 18.6 17.0 20.3 93.4 71.8 5.5 3.5 109.0 108.9 124 Cambodia 9.7 15.1 20.1 3.2 1.7 12.6 20.1 17.9 22.3 90.0 56.6 5.6 2.7 102.9 104.1 125 Pakistan 115.8 184.8 265.7 2.4 2.1 30.6 35.9 18.2 21.3 89.2 68.6 5.7 3.6 105.9 105.8 2.3 54.3 62.1 17.8 19.5 91.4 78.6 5.2 3.9 101.8 101.7 126 Congo 2.4 3.8 5.5 2.6 127 São Tomé and Príncipe 0.1 0.2 0.2 1.9 1.7 43.7 62.2 16.7 19.3 104.1 79.2 5.2 3.4 102.4 102.1 ## LOW HUMAN DEVELOPMENT 128 Kenya 23.4 40.9 63.2 3.2 2.6 18.2 22.2 15.5 18.4 106.8 83.3 5.6 4.5 101.5 101.5 129 Bangladesh 115.6 164.4 203.2 2.0 1.3 19.8 28.1 18.1 24.5 85.4 53.4 4.0 2.2 103.2 103.6 130 Ghana 15.0 24.3 34.9 2.8 2.0 36.4 51.5 17.7 20.6 89.1 71.8 5.3 4.0 104.2 104.5 131 Cameroon 12.2 20.0 28.6 2.8 2.1 40.7 58.4 17.3 19.2 95.7 79.6 5.7 4.2 101.6 101.6 132 Myanmar 40.8 50.5 59.4 1.4 1.0 24.7 33.7 21.3 27.9 71.0 47.2 3.1 2.2 101.1 101.2 133 Yemen 12.3 24.3 39.4 4.6 2.7 20.9 31.8 14.3 17.8 116.0 84.2 7.7 4.7 104.6 103.9 134 Benin 4.8 9.2 15.4 3.5 2.9 34.5 42.0 17.2 18.4 96.5 85.8 6.6 5.1 103.1 103.8 135 Madagascar 11.3 20.1 31.5 3.0 2.5 23.6 30.2 17.4 18.4 91.8 83.6 6.1 4.3 100.3 101.4 136 Mauritania 2.0 3.4 4.8 2.7 2.1 39.7 41.4 17.5 20.1 89.7 72.1 5.7 4.1 106.6 106.3 table 137 Papua New Guinea 4.1 6.9 10.1 2.6 2.2 15.0 12.5 18.6 20.0 78.2 72.3 4.7 3.8 106.3 107.8 11 138 Nepal 19.1 29.9 40.6 2.5 1.7 8.9 18.6 18.6 21.6 84.0 66.6 4.9 2.7 106.0 105.2 139 Togo 3.9 6.8 10.1 2.4 2.3 30.1 43.4 16.9 19.8 96.4 75.8 6.0 3.9 100.2 100.6 140 Comoros 0.4 0.7 1.0 2.4 2.1 27.9 28.2 16.8 21.1 97.0 69.9 5.1 3.6 102.7 103.4 141 Lesotho 1.6 2.1 2.4 1.5 0.8 14.0 26.9 17.2 19.8 97.1 76.2 4.7 3.1 101.3 101.4 142 Nigeria 97.3 158.3 226.7 2.5 2.1 35.3 49.8 17.1 18.6 95.0 83.5 6.4 4.8 101.6 102.6 143 Uganda 17.7 33.8 60.8 3.3 3.2 11.1 13.3 15.9 15.6 103.1 105.1 7.1 5.9 101.4 101.7 144 Senegal 7.5 12.9 19.5 2.8 2.4 38.9 42.4 16.5 18.0 97.2 84.2 6.5 4.5 102.0 102.3 145 Haiti 7.1 10.2 13.2 2.0 1.5 28.5 52.1 18.5 21.6 88.5 67.5 5.2 3.2 103.6 104.1 146 Angola 10.7 19.0 30.4 3.2 2.7 37.1 58.5 16.2 17.4 100.5 89.2 7.1 5.3 99.7 99.9 147 Djibouti 0.6 0.9 1.2 2.1 1.6 75.7 76.2 17.8 21.5 86.5 63.6 5.9 3.5 101.7 102.2 148 Tanzania, United Republic of 25.5 45.0 75.5 3.3 2.9 18.9 26.4 16.9 17.5 94.7 91.8 6.1 5.3 101.2 101.9 4.2 100.7 101.0 149 Côte d’Ivoire 12.6 21.6 32.6 3.4 2.3 39.7 50.6 17.7 19.5 90.3 79.6 5.9 150 Zambia 7.9 13.3 20.9 2.8 2.4 39.4 35.7 17.0 16.8 94.0 97.0 6.3 5.3 101.3 101.4 151 Gambia 0.9 1.8 2.7 3.8 2.5 38.3 58.2 18.7 18.8 84.0 81.6 6.0 4.6 101.1 101.8 152 Rwanda 7.2 10.3 16.1 –5.5 2.7 5.4 18.9 15.4 18.7 107.5 81.2 6.2 5.1 98.9 98.9 153 Malawi 9.5 15.7 25.9 1.4 2.7 11.6 19.8 16.7 16.8 97.7 96.2 6.8 5.1 101.5 102.2 154 Sudan 27.1 43.2 61.0 2.6 2.0 26.6 40.1 17.8 20.3 88.8 73.4 5.8 3.7 103.8 104.1 155 Afghanistan 12.6 29.1 50.6 7.3 3.2 18.1 22.6 16.8 16.9 94.0 92.8 8.0 6.3 106.1 106.0 156 Guinea 6.1 10.3 16.9 3.9 2.7 28.0 35.4 17.7 18.5 91.6 84.9 6.6 5.0 104.3 104.4 157 Ethiopia 48.3 85.0 131.6 3.3 2.5 12.6 16.7 17.4 18.0 92.0 86.5 7.0 4.8 100.8 101.6 158 Sierra Leone 4.1 5.8 8.9 –0.5 2.3 32.9 38.4 18.7 18.2 82.4 82.9 5.5 5.0 98.1 100.7 159 Central African Republic 2.9 4.5 6.1 2.6 1.8 36.8 38.9 18.4 19.5 88.9 79.3 5.7 4.3 99.9 100.0 160 Mali 8.7 13.3 20.5 2.0 2.4 23.3 35.9 17.3 17.6 91.6 86.5 6.3 5.2 101.7 102.2 161 Burkina Faso 8.8 16.3 27.9 2.8 3.1 13.8 25.7 16.2 16.7 99.7 93.9 6.7 5.6 103.5 103.8 162 Liberia 2.2 4.1 6.5 –2.2 2.6 40.9 47.8 17.5 18.5 92.7 83.9 6.4 4.7 100.2 102.1 186 human development report 2010 Demographic trends Population Total Average annual growth Urban Median age Dependency ratio Total fertility rate Sex ratio at birth (per 100 people (male births per a b HDI rank (millions) (%) (% of total) (years) ages 15–64) (births per woman) 100 female births) 1990 2010 2030 1990–1995 2010–2015 1990 2010 1990 2010 1990 2010 1990–1995 2010–2015 1990 2010 163 Chad 6.1 11.5 19.0 3.1 2.6 20.8 27.6 17.0 17.1 97.5 93.9 6.7 5.8 100.9 101.0 164 Guinea-Bissau 1.0 1.6 2.5 2.6 2.3 28.1 30.0 18.6 18.7 81.3 85.4 5.9 5.4 100.5 100.8 165 Mozambique 13.5 23.4 33.9 3.3 2.1 21.1 38.4 16.5 17.9 99.2 89.3 6.1 4.6 100.3 101.3 166 Burundi 5.7 8.5 11.9 1.6 2.0 6.3 11.0 17.4 20.3 93.9 68.7 6.5 4.0 100.6 100.9 167 Niger 7.9 15.9 32.6 3.3 3.7 15.4 17.1 15.4 15.0 104.8 108.8 7.8 6.9 104.0 104.3 168 Congo, Democratic Republic of the 37.0 67.8 108.6 3.9 2.6 27.8 35.2 16.4 16.6 99.6 96.2 7.1 5.5 100.8 100.7 169 Zimbabwe 10.5 12.6 17.9 2.3 2.1 29.0 38.3 16.8 19.0 96.1 77.3 4.8 3.1 100.8 101.0 ## OTHER COUNTRIES OR TERRITORIES Antigua and Barbuda 0.1 0.1 0.1 1.9 1.0 35.4 30.3 .. .. .. .. .. .. .. .. Bhutan 0.5 0.7 0.9 –1.5 1.7 16.4 34.7 18.7 24.2 85.2 53.2 5.4 2.4 102.3 103.0 Cuba 10.6 11.2 11.0 0.6 0.0 73.4 75.2 28.2 38.3 45.5 42.1 1.7 1.5 106.4 106.8 Dominica 0.1 0.1 0.1 0.0 0.1 67.7 67.2 .. .. .. .. .. .. .. .. Eritrea 3.2 5.2 8.1 0.3 2.8 15.8 21.6 16.5 19.1 95.8 78.6 6.1 4.2 100.6 102.4 Grenada 0.1 0.1 0.1 0.8 0.4 33.4 39.3 20.4 25.0 88.0 52.4 3.5 2.2 104.2 104.9 Iraq 18.1 31.5 48.9 3.0 2.6 69.7 66.2 17.0 19.3 95.6 78.3 5.8 3.7 105.8 106.0 Kiribati 0.1 0.1 0.1 1.5 1.5 35.0 43.9 .. .. .. .. .. .. .. .. Korea, Democratic People’s Rep. of 20.1 24.0 25.3 1.5 0.3 58.4 60.2 26.2 34.0 44.6 44.9 2.4 1.9 104.7 105.4 Lebanon 3.0 4.3 4.9 3.2 0.8 83.1 87.2 21.9 29.2 69.3 47.2 3.0 1.9 103.3 104.0 Marshall Islands 0.0 0.1 0.1 1.5 1.9 65.1 71.8 .. .. .. .. .. .. .. .. Monaco 0.0 0.0 0.0 0.9 0.3 100.0 100.0 .. .. .. .. .. .. .. .. Nauru 0.0 0.0 0.0 1.7 0.6 100.0 100.0 .. .. .. .. .. .. .. .. Occupied Palestinian Territories 2.2 4.4 7.3 3.9 2.9 67.9 74.1 16.4 17.6 100.4 90.1 6.5 4.5 103.2 104.5 Oman 1.8 2.9 4.0 3.3 1.9 66.1 73.0 18.3 24.3 85.4 51.5 6.3 2.8 104.4 104.9 0.0 2.7 0.5 69.6 83.4 .. .. .. .. .. .. .. .. Palau 0.0 0.0 Saint Kitts and Nevis 0.0 0.1 0.1 1.1 1.2 34.6 32.4 .. .. .. .. .. .. .. .. Saint Lucia 0.1 0.2 0.2 1.2 0.9 29.4 28.0 21.4 27.5 78.8 48.4 3.2 1.9 97.9 102.7 Saint Vincent and the Grenadines 0.1 0.1 0.1 0.1 0.0 41.4 49.3 20.4 27.8 78.9 49.8 2.9 2.1 101.3 102.0 Samoa 0.2 0.2 0.2 0.8 0.2 21.2 20.2 18.5 19.6 81.1 77.2 4.7 3.6 108.7 108.0 San Marino 0.0 0.0 0.0 1.2 0.6 90.4 94.1 .. .. .. .. .. .. .. .. Seychelles 0.1 0.1 0.1 1.0 0.3 49.3 55.3 .. .. .. .. .. .. .. .. Somalia 6.6 9.4 15.7 –0.2 2.7 29.7 37.5 17.6 17.6 90.0 90.8 6.5 6.2 100.6 101.2 Tuvalu 0.0 0.0 0.0 0.7 0.4 40.7 50.4 .. .. .. .. .. .. .. .. Vanuatu 0.1 0.2 0.4 2.8 2.4 18.7 25.6 18.1 20.5 90.5 71.2 4.8 3.6 108.5 106.1 table 11 Developed OECD 911.0 1,026.3 1,093.3 0.7 0.4 72.0 77.1 34.5 39.9 49.1 49.7 1.7 1.6 105.4 105.5 Non-OECD 19.3 29.7 36.3 2.5 1.2 89.9 91.7 29.2 35.5 49.9 39.6 2.2 1.9 106.2 106.5 Developing Arab States 226.4 348.2 477.9 2.4 1.9 49.2 55.3 18.2 23.1 87.8 61.9 4.7 2.6 104.2 104.3 East Asia and the Pacific 1,606.6 1,974.3 2,204.3 1.3 0.8 28.1 45.3 24.0 32.2 56.2 42.5 2.3 2.8 108.5 116.0 Europe and Central Asia 399.6 410.3 416.4 0.3 0.2 62.8 64.4 30.0 34.3 55.8 43.5 2.1 1.6 104.4 105.6 Latin America and the Caribbean 437.2 582.7 683.6 1.7 1.0 70.3 79.5 21.9 27.7 70.3 53.2 3.0 2.2 103.8 104.2 South Asia 1,200.0 1,719.1 2,158.2 2.1 1.4 26.5 31.7 20.3 24.5 75.8 56.8 4.1 2.5 106.8 107.5 Sub-Saharan Africa 483.1 808.8 1,228.6 2.8 2.4 28.3 37.0 17.2 18.5 94.2 84.8 6.1 3.6 101.3 101.9 Very high human development 930.3 1,056.0 1,129.5 0.7 0.5 72.3 77.5 34.4 39.8 49.1 49.4 1.7 1.8 105.5 105.6 High human development 873.1 1,052.4 1,175.1 1.2 0.7 67.8 75.8 25.3 30.4 65.0 47.2 2.7 1.8 104.2 104.8 Medium human development 2,739.1 3,597.3 4,239.7 1.6 1.1 28.5 39.9 22.5 28.6 64.3 49.5 3.0 2.7 107.8 112.2 Low human development 673.6 1,099.0 1,626.5 2.7 2.2 24.2 33.4 17.4 19.6 92.3 79.0 5.7 4.1 102.1 102.5 ## T T T 854.7 1,271.6 2.7 2.2 21.0 29.1 17.6 19.9 91.1 77.9 5.6 4.1 102.2 102.5 Least developed countries 524.8 T T T 6,908.7 8,308.9 1.6 1.1 42.6 50.5 24.4 29.1 65.4 54.0 3.1 2.3 106.0 108.4 World 5,290.4 Notes Sources b The natural sex ratio at birth is commonly assumed and empirically confirmed to be 17 a Columns 1–5 and 8–15: Because data are based on national definitions of what constitutes a city or UNDESA (2009d). 105 male births to 100 female births. Columns 6 and 7: c metropolitan area, cross-country comparison should be made with caution. UNDESA (2010). Includes Taiwan Province of China. T Data are aggregates provided by the original data source. 187 ## STATISTICAL ANNEX 12 e l Decent work b ta Employed Unemployment rate people living by level of education on less than Mandatory paid Employment to (% of labour force with b a$1.25 a day Child labour maternity leave

population ratio Formal employment Vulnerable employment given level of attainment)

(% of population (% of total Ratio of female (% of total Ratio of female (% of total Secondary (% of children

HDI rank ages 15–64) employment) to male rates employment) to male rates employment) Primary or less or above ages 5–14) (calendar days)

c c c c c c c c c

2000–2008 2000–2008 2000–2008 2000–2008 2000–2008 2000–2008 1999–2007 2007–2009

1991 2008 2000–2008

## VERY HIGH HUMAN DEVELOPMENT

1 Norway 57.7 62.3 94.3 1.05 5.7 0.42 .. 6.0 3.8 .. 126

2 Australia 55.6 59.4 90.7 1.05 9.3 0.61 .. 7.4 6.2 .. 0

3 New Zealand 55.4 62.7 87.9 1.05 11.9 0.68 .. 6.1 6.0 .. 98

d d

1.03 .. .. .. .. .. .. 0

4 United States 59.4 59.2 92.8

5 Ireland 43.5 57.8 88.3 1.14 11.7 0.31 .. 7.6 7.0 .. 182

6 Liechtenstein .. .. .. .. .. .. .. .. .. .. ..

7 Netherlands 51.4 59.3 90.5 1.02 9.4 0.80 .. 8.0 7.8 .. 112

8 Canada 57.8 61.2 89.6 1.04 10.4 0.71 .. 12.1 10.2 .. 119

9 Sweden 62.0 57.6 93.4 1.05 6.6 0.51 .. 12.7 8.8 .. 98

10 Germany 53.8 51.7 93.1 1.01 6.8 0.85 .. 16.8 12.1 .. 98

11 Japan 61.3 54.2 88.7 0.98 10.8 1.20 .. 4.4 .. .. 98 e

12 Korea, Republic of 58.6 58.1 74.9 0.94 25.2 1.18 .. 2.1 7.1 .. 60 f

13 Switzerland 65.0 61.2 89.8 0.99 10.1 1.09 .. 6.8 5.7 .. 112

14 France 47.2 47.9 94.1 1.02 5.9 0.69 .. 12.3 12.5 .. 112

15 Israel 45.2 50.4 91.5 1.04 7.4 0.59 .. 14.0 19.1 .. 84

16 Finland 57.2 54.7 91.0 1.05 9.0 0.59 .. 12.3 10.5 .. 263

17 Iceland 70.9 71.2 90.9 1.08 8.7 0.39 .. 5.1 4.1 .. 180

18 Belgium 43.8 46.5 90.0 1.03 10.0 0.78 .. 11.0 10.0 .. 105

19 Denmark 59.4 60.3 95.0 1.03 5.0 0.52 .. 7.2 7.8 .. 126

20 Spain 41.2 48.6 88.1 1.04 11.8 0.73 .. 10.5 13.4 .. 112 f

21 Hong Kong, China (SAR) 61.8 56.6 92.8 1.06 7.1 0.45 .. 5.6 6.3 .. 70 e

22 Greece 44.3 48.4 73.1 1.01 27.0 0.99 .. 7.5 16.1 .. 119

23 Italy 42.6 43.6 81.4 1.07 18.6 0.75 .. 7.3 10.0 .. 150

24 Luxembourg 49.3 51.2 95.9 0.98 5.2 1.06 .. .. .. .. ..

25 Austria 51.8 54.5 91.1 1.01 9.0 0.95 .. 8.8 6.1 .. 112 e

26 United Kingdom 55.6 56.3 89.2 1.08 10.5 0.50 .. 9.4 8.0 .. 365 e

27 Singapore 63.7 61.6 89.8 1.06 10.2 0.59 .. .. .. .. 84

28 Czech Republic 58.2 54.3 87.5 1.08 12.5 0.56 .. 20.2 6.3 .. 196

29 Slovenia 54.5 54.1 89.1 1.03 11.0 0.79 .. 7.9 9.5 .. 365

30 Andorra .. .. .. .. .. .. .. .. .. .. ..

31 Slovakia 54.5 52.6 89.3 1.09 10.6 0.44 .. 46.6 13.0 .. 196 f

32 United Arab Emirates 71.3 75.9 98.4 1.01 1.6 0.29 .. 2.4 7.9 .. 45

33 Malta 42.5 45.2 91.0 1.07 9.2 0.50 .. 8.5 2.7 .. ..

34 Estonia 61.2 54.5 95.5 1.02 5.8 0.48 .. 10.3 7.1 .. 140

35 Cyprus 59.9 57.5 85.5 1.06 14.4 0.69 .. 4.4 7.5 .. ..

36 Hungary 47.5 44.8 92.9 1.03 7.1 0.67 .. 17.3 9.5 .. 168

37 Brunei Darussalam 62.2 63.3 .. .. .. .. .. .. .. .. ..

38 Qatar 73.0 76.9 99.5 1.01 0.4 0.00 .. .. .. .. ..

39 Bahrain 61.0 61.0 .. .. .. .. .. .. .. 5 ..

40 Portugal 57.6 55.7 81.5 0.99 18.5 1.06 .. 8.0 15.6 3 120 e

41 Poland 53.0 48.2 81.2 1.03 18.9 0.89 .. 15.5 14.9 .. 112

42 Barbados 54.8 64.4 85.6 1.11 14.0 0.55 .. .. .. .. ..

188 human development report 2010 Decent work

Employed Unemployment rate

people living by level of education

on less than Mandatory paid

Employment to (% of labour force with b

a $1.25 a day Child labour maternity leave population ratio Formal employment Vulnerable employment given level of attainment) (% of population (% of total Ratio of female (% of total Ratio of female (% of total Secondary (% of children HDI rank ages 15–64) employment) to male rates employment) to male rates employment) Primary or less or above ages 5–14) (calendar days) c c c c c c c c c 2000–2008 2000–2008 2000–2008 2000–2008 2000–2008 2000–2008 1999–2007 2007–2009 1991 2008 2000–2008 HIGH HUMAN DEVELOPMENT d d 43 Bahamas 62.6 65.4 84.4 1.07 .. .. .. .. .. .. .. 44 Lithuania 53.7 50.2 90.7 1.04 9.4 0.72 .. 7.3 7.2 .. 126 45 Chile 50.6 49.6 75.2 1.02 24.8 0.94 .. 4.9 15.6 3 126 46 Argentina 53.0 56.5 79.9 1.06 20.1 0.78 3.5 9.9 18.1 7 90 f 47 Kuwait 61.9 65.3 .. .. .. .. .. .. .. .. 70 48 Latvia 57.6 55.0 93.2 1.03 6.8 0.70 .. 10.3 9.6 .. 112 d d e 1.11 .. .. .. .. .. 4 365 49 Montenegro .. .. 80.5 50 Romania 55.6 48.1 68.7 0.99 31.2 1.03 .. 7.1 9.8 1 126 51 Croatia 49.9 45.9 83.8 0.98 16.2 1.12 1.3 10.7 16.5 .. 365 52 Uruguay 52.7 56.4 74.7 1.02 25.1 0.92 .. 10.0 15.9 8 84 53 Libyan Arab Jamahiriya 45.3 48.6 .. .. .. .. .. .. .. .. .. e 54 Panama 49.5 58.7 72.3 1.09 27.7 0.78 11.8 5.4 15.7 3 98 f 55 Saudi Arabia 50.4 50.9 .. .. .. .. .. .. .. .. 70 56 Mexico 56.5 57.1 70.5 0.94 29.5 1.16 0.8 2.9 8.7 16 84 f 57 Malaysia 59.7 60.5 77.6 1.02 22.3 0.93 0.6 .. .. .. 60 58 Bulgaria 45.2 46.3 91.3 1.03 8.7 0.77 .. 17.5 8.2 .. 135 59 Trinidad and Tobago 44.5 60.7 83.4 1.05 15.6 0.76 .. .. .. 1 .. 60 Serbia .. .. 77.3 1.06 22.7 0.83 .. .. .. 10 365 61 Belarus 57.5 52.3 .. .. .. .. .. .. .. 5 126 e 62 Costa Rica 56.3 57.2 80.2 1.00 19.7 1.02 2.9 5.2 7.0 5 120 63 Peru 53.4 68.8 60.1 0.79 39.6 1.41 9.0 .. .. 19 90 64 Albania 48.9 46.2 .. .. .. .. 1.3 15.8 29.0 12 .. 65 Russian Federation 56.8 56.7 94.1 1.01 5.8 0.90 .. 13.2 11.8 .. 140 f 66 Kazakhstan 62.7 63.5 63.3 0.93 35.8 1.16 3.8 10.3 16.8 2 126 e 67 Azerbaijan 56.5 60.0 46.8 0.57 53.2 1.63 .. 11.3 11.3 7 126 d d 68 Bosnia and Herzegovina 42.3 41.5 72.9 1.01 .. .. .. 31.2 .. 5 365 d d 0.97 .. .. .. 6.7 14.6 7 126 69 Ukraine 56.9 53.5 80.7 70 Iran, Islamic Republic of 45.9 48.9 56.8 0.72 42.7 1.41 1.9 8.3 33.2 .. 90 71 The former Yugoslav Republic of Macedonia 37.1 34.8 77.8 1.05 22.2 0.84 .. .. .. 6 .. 72 Mauritius 55.5 53.8 82.4 1.04 16.8 0.82 .. 8.0 15.3 .. .. 73 Brazil 55.7 63.9 68.1 1.02 27.2 0.82 6.2 8.4 13.3 6 120 74 Georgia 57.4 54.3 37.8 0.97 62.2 1.02 17.4 7.1 30.3 18 126 e 75 Venezuela, Bolivarian Republic of 51.4 61.3 63.5 0.98 29.8 1.18 4.4 .. .. 8 126 76 Armenia 38.0 38.1 .. .. .. .. 18.9 .. .. 4 140 table 77 Ecuador 51.6 60.5 66.2 0.83 33.8 1.41 5.8 .. .. 8 84 12 78 Belize 47.3 56.9 76.4 1.04 23.5 0.87 .. 12.1 16.5 40 .. 79 Colombia 52.1 62.0 58.9 1.01 40.9 0.99 21.3 .. .. 5 84 f 80 Jamaica 60.7 56.2 64.3 1.11 35.4 0.82 .. .. .. 6 56 d 81 Tunisia 40.5 41.0 64.3 .. .. .. 3.9 .. .. .. .. f 82 Jordan 35.7 37.9 .. .. .. .. .. .. .. .. 70 83 Turkey 52.5 42.3 64.6 0.73 35.3 1.61 3.9 9.0 22.4 5 112 84 Algeria 39.2 49.4 64.8 0.76 34.9 1.53 .. 19.0 45.3 5 98 85 Tonga .. .. .. .. .. .. .. .. .. .. .. ## MEDIUM HUMAN DEVELOPMENT 86 Fiji 53.5 56.3 59.7 0.95 39.0 1.01 .. .. .. .. .. 87 Turkmenistan 55.6 58.3 .. .. .. .. .. .. .. .. .. f 88 Dominican Republic 43.5 53.3 57.6 1.36 42.4 0.62 4.9 12.3 35.3 10 84 f 89 China 75.1 71.0 .. .. .. .. 18.3 .. .. .. 90 f 90 El Salvador 58.6 54.3 59.0 0.66 35.5 1.51 15.6 .. .. 6 84 f 91 Sri Lanka 51.3 54.7 59.3 0.91 40.7 1.14 17.8 4.0 20.0 8 84 f 92 Thailand 77.3 71.5 46.6 0.90 53.3 .. .. .. .. 8 45 93 Gabon 58.1 58.2 .. .. .. .. 6.3 .. .. .. .. 94 Suriname 45.3 46.5 .. .. .. .. .. .. .. 6 .. 95 Bolivia, Plurinational State of 61.4 70.7 38.1 0.63 61.6 1.31 22.5 .. .. 22 60 189 ## STATISTICAL ANNEX Decent work Employed Unemployment rate people living by level of education on less than Mandatory paid Employment to (% of labour force with b a$1.25 a day Child labour maternity leave

population ratio Formal employment Vulnerable employment given level of attainment)

(% of population (% of total Ratio of female (% of total Ratio of female (% of total Secondary (% of children

HDI rank ages 15–64) employment) to male rates employment) to male rates employment) Primary or less or above ages 5–14) (calendar days)

c c c c c c c c c

2000–2008 2000–2008 2000–2008 2000–2008 2000–2008 2000–2008 1999–2007 2007–2009

1991 2008 2000–2008

96 Paraguay 61.1 72.8 53.2 0.89 46.8 1.13 7.3 4.6 13.6 15 84

97 Philippines 59.1 60.1 55.3 0.95 44.7 1.07 27.2 2.7 16.4 12 60 f

98 Botswana 46.7 46.0 75.9 0.96 11.7 2.29 .. .. .. .. 84 e

99 Moldova, Republic of 58.1 44.7 67.6 1.09 32.4 0.84 11.1 .. .. 32 126

100 Mongolia 50.2 51.6 39.9 1.12 59.7 0.93 30.5 .. .. 18 120 e

101 Egypt 42.6 43.2 75.2 0.71 24.8 2.13 2.7 .. .. 7 90 e

102 Uzbekistan 53.8 57.5 .. .. .. .. 59.7 .. .. .. 126

103 Micronesia, Federated States of .. .. .. .. .. .. .. .. .. .. ..

104 Guyana 51.4 57.8 .. .. .. .. .. .. .. 16 ..

105 Namibia 45.4 42.9 78.4 0.89 21.1 1.66 .. .. .. 13 90 e

106 Honduras 58.9 56.3 89.7 1.06 48.9 1.08 21.4 .. .. 16 70

107 Maldives 44.9 57.3 27.2 1.16 50.3 0.69 .. .. .. .. .. f

108 Indonesia 63.0 61.8 36.9 0.81 63.1 1.13 27.8 6.2 31.5 4 90

109 Kyrgyzstan 58.0 58.3 51.9 1.01 47.3 0.99 27.2 2.6 43.0 4 126

110 South Africa 39.4 41.1 97.1 0.99 2.7 1.50 44.4 23.4 34.8 .. 112 f

111 Syrian Arab Republic 46.6 44.8 57.5 0.81 42.4 1.28 .. .. .. 4 60

112 Tajikistan 53.8 55.4 .. .. .. .. 28.6 .. .. 10 ..

113 Viet Nam 74.8 69.4 26.1 0.71 73.9 1.13 24.2 .. .. 16 120

114 Morocco 45.9 46.1 47.1 0.67 51.1 1.40 3.4 8.8 54.2 8 98 f

115 Nicaragua 57.2 58.3 54.7 0.99 44.9 1.02 19.4 .. .. 15 84 f

116 Guatemala 55.1 62.4 34.2 0.74 55.0 1.20 14.6 .. .. 29 84

117 Equatorial Guinea 61.4 62.6 .. .. .. .. .. .. .. 28 ..

118 Cape Verde 56.7 55.7 41.4 0.74 39.6 1.23 26.6 .. .. 3 .. f

119 India 58.3 55.6 .. .. .. .. 51.4 .. .. 12 84

120 Timor-Leste 63.8 66.8 .. .. .. .. 63.2 .. .. 4 ..

121 Swaziland 54.2 50.4 .. .. .. .. 83.8 .. .. 9 .. e

122 Lao People’s Democratic Republic 80.2 77.7 .. .. .. .. 45.7 .. .. 11 90

123 Solomon Islands 67.1 64.5 .. .. .. .. .. .. .. .. .. f

124 Cambodia 77.2 74.6 13.1 0.71 86.7 1.07 45.7 .. .. 45 90 f

125 Pakistan 47.5 51.5 38.2 0.59 61.8 1.29 28.9 5.1 11.6 .. 84

126 Congo 65.5 64.6 .. .. .. .. 66.7 .. .. 25 ..

127 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. 8 ..

LOW HUMAN DEVELOPMENT f

128 Kenya 73.4 73.0 .. .. .. .. 22.9 .. .. 26 90 f

129 Bangladesh 74.0 67.9 14.2 0.80 85.0 1.02 56.9 .. .. 13 112

table f

130 Ghana 68.4 65.2 .. .. .. .. 37.6 .. .. 34 84

12 131 Cameroon 59.1 59.1 20.8 0.31 75.9 1.36 39.9 .. .. 31 98

132 Myanmar 74.2 74.4 .. .. .. .. .. .. .. .. .. f

133 Yemen 38.3 39.0 .. .. .. .. 26.0 .. .. 23 60

134 Benin 70.1 71.6 .. .. .. .. 55.6 .. .. 46 98 e

135 Madagascar 79.3 83.3 .. .. 82.2 1.08 76.7 .. .. 32 98

136 Mauritania 66.5 47.2 .. .. .. .. 24.6 .. .. 16 98

137 Papua New Guinea 69.9 70.2 .. .. .. .. .. .. .. .. 108 f

138 Nepal 59.6 61.5 28.4 0.44 71.6 1.34 67.6 .. .. 31 52 e

139 Togo 65.9 64.6 .. .. .. .. 45.9 .. .. 29 98

140 Comoros 70.0 69.4 .. .. .. .. 64.6 .. .. 27 ..

141 Lesotho 48.3 54.1 .. .. .. .. 61.0 .. .. 23 84 f

142 Nigeria 52.7 51.8 .. .. .. .. 72.2 .. .. 13 84 f

143 Uganda 81.8 83.0 14.8 0.34 85.2 1.19 55.7 .. .. 36 60

144 Senegal 66.8 66.0 .. .. .. .. 44.4 .. .. 22 98

145 Haiti 56.0 55.4 .. .. .. .. 66.9 .. .. 21 ..

146 Angola 76.5 76.4 .. .. .. .. 59.9 .. .. 24 56

147 Djibouti .. .. .. .. .. .. .. .. .. 8 .. f

148 Tanzania, United Republic of 87.4 78.0 12.3 0.40 87.7 1.13 90.0 .. .. 36 84

149 Côte d’Ivoire 62.5 60.4 .. .. .. .. 26.3 .. .. 35 98 f

150 Zambia 57.0 61.2 19.1 0.35 79.3 1.23 76.6 .. .. 12 84

151 Gambia 73.2 72.1 .. .. .. .. 42.7 .. .. 25 ..

190 human development report 2010 Decent work

Employed Unemployment rate

people living by level of education

on less than Mandatory paid

Employment to (% of labour force with b

a $1.25 a day Child labour maternity leave population ratio Formal employment Vulnerable employment given level of attainment) (% of population (% of total Ratio of female (% of total Ratio of female (% of total Secondary (% of children HDI rank ages 15–64) employment) to male rates employment) to male rates employment) Primary or less or above ages 5–14) (calendar days) c c c c c c c c c 2000–2008 2000–2008 2000–2008 2000–2008 2000–2008 2000–2008 1999–2007 2007–2009 1991 2008 2000–2008 e 152 Rwanda 86.6 80.3 .. .. .. .. 79.5 .. .. 35 98 f 153 Malawi 71.7 72.1 .. .. .. .. 79.8 .. .. 26 56 f 154 Sudan 46.1 47.3 .. .. .. .. .. .. .. 13 56 155 Afghanistan 54.1 55.2 .. .. .. .. .. .. .. 30 .. e 156 Guinea 82.1 81.2 .. .. .. .. 73.9 .. .. 25 98 f 157 Ethiopia 71.3 80.6 47.0 0.86 51.8 1.16 45.8 .. .. 53 90 158 Sierra Leone 63.6 64.8 81.9 0.92 .. .. 67.1 .. .. 48 .. 159 Central African Republic 73.3 72.6 .. .. .. .. 71.1 .. .. 47 .. d d 0.75 .. .. 60.6 .. .. 34 98 160 Mali 49.3 47.0 13.6 161 Burkina Faso 81.6 81.9 .. .. .. .. 60.7 .. .. 47 98 162 Liberia 65.7 65.9 .. .. .. .. 86.2 .. .. 21 .. 163 Chad 66.6 69.7 .. .. .. .. 72.1 .. .. 53 98 164 Guinea-Bissau 66.3 66.9 .. .. .. .. 55.3 .. .. 39 .. 165 Mozambique 79.9 77.9 .. .. .. .. 81.2 .. .. 22 .. 166 Burundi 84.9 84.2 .. .. .. .. 87.2 .. .. 19 .. f 167 Niger 59.4 59.8 .. .. .. .. 76.6 .. .. 43 98 e 168 Congo, Democratic Republic of the 67.8 66.7 .. .. .. .. 69.6 .. .. 32 105 169 Zimbabwe 70.1 64.9 38.2 0.45 61.9 1.58 .. .. .. 13 .. ## OTHER COUNTRIES OR TERRITORIES Bhutan 53.3 61.1 40.8 0.35 52.3 1.94 31.7 .. .. 19 .. d d 1.22 .. .. .. .. .. .. .. Cuba 52.4 54.4 83.1 Dominica .. .. 73.3 1.13 25.9 0.70 .. .. .. .. .. Eritrea 65.8 65.6 .. .. .. .. .. .. .. .. .. Iraq 36.8 37.1 .. .. .. .. .. .. .. 11 .. Korea, Democratic People’s Rep. of 62.1 63.9 .. .. .. .. .. .. .. .. .. e Lebanon 43.8 45.9 .. .. .. .. .. .. .. 7 49 Occupied Palestinian Territories 30.1 30.2 63.9 0.85 36.1 1.29 .. 24.7 41.8 .. .. .. .. .. .. .. .. 42 Oman 52.6 51.4 89.6 0.98 Saint Kitts and Nevis .. .. 88.4 1.04 8.5 0.70 .. .. .. .. .. Saint Lucia .. .. 69.5 1.12 28.7 0.80 .. .. .. .. .. Samoa .. .. 53.5 1.32 .. .. .. .. .. .. .. d d 1.05 .. .. .. .. .. .. .. San Marino .. .. 90.4 Somalia 65.6 66.5 .. .. .. .. .. .. .. 49 .. Tuvalu .. .. 97.9 1.01 2.0 0.81 .. .. .. .. .. table 12 Notes a Percentage of employed people engaged as unpaid family workers and own- account workers. b Number of days of maternity leave paid by the government, unless otherwise noted. Refers to women in formal employment. c Data refer to the most recent year available during the period specified. d Does not include data on employers. e Benefits paid by both the government and the employer. f Benefits paid by the employer. Sources Columns 1–9: ILO (2010d). Column 10: UNICEF (2010c). Column 11: World Bank (2010f). 191 ## STATISTICAL ANNEX 13 e l Education b ta ACHIEVEMENTS in Efficiency of primary Quality of primary education education education Access to education Tertiary Primary enrolment school Population ratio teachers Pupil– Repetition Dropout with at least Primary enrolment ratio Secondary enrolment ratio (% of tertiary trained to teacher rate, rate, secondary Adult literacy school-age (% of primary school-age (% of secondary school-age teach ratio all grades all grades education rate population) population) population (number of (% of total primary pupils per enrolment in (% ages 15 (% ages 25 (% of primary HDI rank teacher) (%) previous year) and older) and older) Gross Net Gross Net Gross school cohort) a a a a a a a a a a 2005–2008 2010 2001–2009 2001–2009 2001–2009 2001–2009 2001–2009 2005–2008 2005–2008 2005–2008 2005–2008 ## VERY HIGH HUMAN DEVELOPMENT 1 Norway .. 87.3 98.4 98.4 112.5 96.6 75.9 0.2 .. .. .. 2 Australia .. 73.4 104.9 97.0 147.9 87.5 75.0 .. .. 15.8 .. 3 New Zealand .. 67.9 101.2 99.2 120.4 90.8 79.1 .. .. 17.1 .. 4 United States .. 89.7 98.0 91.5 94.3 88.2 81.6 1.5 .. 14.3 .. 5 Ireland .. 64.1 105.4 96.9 113.4 88.1 61.2 .. 0.7 17.8 .. 6 Liechtenstein .. .. 109.6 89.3 106.1 65.2 31.2 18.2 .. 9.5 .. b .. .. .. 7 Netherlands .. 67.4 106.8 98.5 119.5 88.6 60.1 1.7 b .. .. .. .. 8 Canada .. 79.6 107.1 99.5 101.3 .. 62.3 9 Sweden .. 80.3 94.2 93.8 103.1 99.1 74.5 0.1 .. 10.7 .. b,c 105.7 98.2 100.6 .. .. 4.4 1.3 18.0 .. 10 Germany .. 97.2 11 Japan .. 71.9 102.2 100.0 100.7 98.0 57.9 .. .. 18.8 .. 12 Korea, Republic of .. 75.3 103.7 98.6 97.5 96.4 96.1 1.6 0.0 24.1 .. 13 Switzerland .. 71.0 102.4 93.5 95.7 84.7 47.2 .. 1.5 18.1 .. b 4.2 20.3 .. 14 France .. 55.7 110.2 98.5 113.3 98.3 54.7 2.0 15 Israel .. 61.8 110.9 97.1 91.5 87.6 60.4 0.4 1.5 17.2 .. 16 Finland .. 70.5 97.6 96.3 111.3 96.8 93.8 0.2 0.4 15.9 .. 17 Iceland .. 54.8 97.2 97.1 110.0 90.3 72.3 .. .. .. .. 18 Belgium .. 47.7 102.3 97.8 109.5 86.9 62.1 12.8 3.4 12.6 .. b .. .. .. 19 Denmark .. 68.1 99.0 95.6 119.2 89.6 80.3 7.9 20 Spain 97.6 46.9 105.4 99.7 119.1 94.3 68.5 0.1 .. 13.1 .. 21 Hong Kong, China (SAR) .. 62.7 101.0 93.5 82.9 75.2 34.3 0.0 0.9 .. 95.1 22 Greece 97.0 47.4 101.2 99.4 101.8 91.0 90.8 1.8 0.7 10.1 .. 23 Italy 98.8 46.7 103.8 98.6 99.9 92.4 67.1 0.4 0.2 10.4 .. b,c 100.3 95.5 95.4 83.0 10.0 13.5 3.8 13.1 .. 24 Luxembourg .. 78.1 b .. 50.3 2.2 1.2 12.9 .. 25 Austria .. 70.1 101.5 97.9 99.9 26 United Kingdom .. 58.2 104.0 97.2 97.4 91.3 59.0 .. .. 20.1 .. 27 Singapore 94.5 59.1 .. .. .. .. .. .. 0.3 19.5 97.1 b,c 102.1 92.2 95.0 .. 54.3 1.1 0.6 17.3 .. 28 Czech Republic .. 99.8 b,c 102.9 95.6 93.5 88.5 85.5 1.1 0.6 17.1 .. 29 Slovenia 99.7 94.3 b,c 86.7 80.1 82.2 71.4 11.0 .. 2.8 .. 100.0 30 Andorra .. 50.9 b,c b 101.9 91.8 92.8 .. 50.1 2.6 3.0 18.6 .. 31 Slovakia .. 98.8 32 United Arab Emirates 90.0 .. 107.9 91.6 93.8 83.8 25.2 0.0 1.9 17.2 100.0 b 0.8 12.1 .. 33 Malta 92.4 44.2 99.0 91.4 98.1 82.0 33.0 1.0 b,c 99.2 94.4 99.7 89.9 65.0 1.7 0.9 .. .. 34 Estonia 99.8 87.3 35 Cyprus 97.8 58.7 102.5 99.0 97.8 95.1 36.2 1.6 0.4 15.0 .. 36 Hungary 99.0 46.7 97.9 88.8 96.7 90.5 67.2 1.0 1.7 10.6 .. 37 Brunei Darussalam 95.0 .. 106.7 93.3 96.7 88.2 16.0 1.6 0.8 10.1 84.3 b,c 108.6 94.1 93.2 79.2 11.0 3.3 0.6 .. 52.3 38 Qatar 93.1 54.1 b 2.0 .. .. 39 Bahrain 90.8 48.1 105.3 97.9 96.8 89.4 29.9 1.3 40 Portugal 94.6 27.5 115.2 98.9 101.3 87.9 56.9 .. 10.2 11.7 .. 41 Poland 99.5 60.6 97.1 95.6 99.8 93.8 66.9 2.7 0.7 11.0 .. 42 Barbados .. 58.8 .. .. .. .. .. 6.1 .. 13.5 61.0 192 human development report 2010 Education ACHIEVEMENTS in Efficiency of primary Quality of primary education education education Access to education Tertiary Primary enrolment school Population ratio teachers Pupil– Repetition Dropout with at least Primary enrolment ratio Secondary enrolment ratio (% of tertiary trained to teacher rate, rate, secondary Adult literacy school-age (% of primary school-age (% of secondary school-age teach ratio all grades all grades education rate population) population) population (number of (% of total primary pupils per enrolment in (% ages 15 (% ages 25 (% of primary HDI rank teacher) (%) previous year) and older) and older) Gross Net Gross Net Gross school cohort) a a a a a a a a a a 2005–2008 2010 2001–2009 2001–2009 2001–2009 2001–2009 2001–2009 2005–2008 2005–2008 2005–2008 2005–2008 HIGH HUMAN DEVELOPMENT b,c 43 Bahamas .. 89.6 102.4 90.5 93.7 86.1 .. 9.1 .. 15.8 91.1 b,c 96.1 91.3 99.1 92.1 75.9 2.0 0.7 9.7 .. 44 Lithuania 99.7 88.6 45 Chile 98.6 51.8 105.6 94.4 90.6 85.3 52.1 5.1 2.4 26.2 .. 46 Argentina 97.7 44.6 114.6 98.5 85.3 79.4 68.1 5.1 6.1 14.8 .. b 47 Kuwait 94.5 56.9 95.5 87.6 90.8 79.9 17.6 0.5 0.9 9.1 100.0 b,c 48 Latvia 99.8 97.9 96.8 90.1 114.5 .. 69.2 4.3 3.3 12.8 .. b,c .. .. .. .. .. .. .. .. .. 49 Montenegro .. 98.2 b,c 104.7 93.9 87.5 73.0 58.3 6.7 1.7 16.3 .. 50 Romania 97.6 79.1 b,c b 98.6 90.2 93.6 88.3 47.0 0.2 0.3 17.3 100.0 51 Croatia 98.7 78.0 52 Uruguay 98.2 44.6 114.3 97.5 92.0 67.7 64.3 6.3 7.0 15.5 .. b .. .. .. .. 53 Libyan Arab Jamahiriya 88.4 .. 110.3 .. 93.5 .. 55.7 54 Panama 93.5 48.3 111.1 98.3 71.2 65.6 45.0 14.8 5.3 24.2 91.3 b,c 98.4 84.5 94.6 73.0 29.9 3.6 3.3 .. 91.5 55 Saudi Arabia 85.5 48.8 56 Mexico 92.9 40.3 112.9 97.9 87.4 70.9 26.3 8.5 3.6 28.0 95.4 b .. 57 Malaysia 92.1 50.5 97.9 97.5 69.1 68.7 29.7 7.8 .. 17.5 b,c 101.1 94.6 105.2 87.5 49.7 6.3 1.8 16.1 .. 58 Bulgaria 98.3 87.6 59 Trinidad and Tobago 98.7 48.6 103.4 91.8 88.8 73.9 11.6 4.2 6.6 17.2 86.6 60 Serbia .. .. 100.6 97.0 90.5 89.6 48.7 1.6 0.6 .. 100.0 61 Belarus 99.7 .. 99.2 94.4 95.3 86.8 72.8 0.5 0.0 .. 99.9 62 Costa Rica 96.0 29.9 109.9 .. 89.2 .. 25.3 5.7 7.0 19.0 86.0 63 Peru 89.6 50.5 112.8 96.8 97.6 75.9 34.5 17.0 7.2 20.9 .. b,c b b b 102.1 90.8 77.7 73.8 19.3 10.1 2.1 .. .. 64 Albania 99.0 75.7 65 Russian Federation 99.5 .. 96.8 .. 84.0 .. 75.0 4.8 0.4 .. .. b,c 108.8 89.3 94.9 86.9 41.0 1.0 0.1 .. .. 66 Kazakhstan 99.7 82.1 b,c 116.2 96.0 105.6 98.3 15.8 1.6 0.3 .. 99.9 67 Azerbaijan 99.5 92.8 68 Bosnia and Herzegovina 97.6 .. 111.0 .. 89.1 .. 33.5 .. 0.1 .. .. b,c 98.4 88.9 94.4 85.0 79.4 2.7 0.1 .. 99.8 69 Ukraine 99.7 88.2 b b b 1.8 20.0 100.0 70 Iran, Islamic Republic of 82.3 29.5 128.4 99.7 79.7 75.1 36.1 12.2 b,c 71 The former Yugoslav Republic of Macedonia 97.0 47.8 92.8 86.5 84.2 81.6 35.5 2.5 0.1 .. .. b 72 Mauritius 87.5 36.3 99.4 93.1 87.6 80.1 16.0 2.1 4.0 21.7 100.0 b 73 Brazil 90.0 21.9 129.6 92.6 100.1 77.0 30.0 24.4 18.7 23.0 .. b,c 107.4 98.7 90.0 80.8 34.3 4.9 0.3 12.5 95.0 74 Georgia 99.7 91.0 75 Venezuela, Bolivarian Republic of 95.2 27.7 103.1 90.1 81.1 69.5 78.1 19.3 3.4 16.2 83.5 b,c 79.6 74.0 88.1 85.7 34.2 2.3 0.2 .. 77.5 76 Armenia 99.5 91.1 table 77 Ecuador 84.2 37.0 118.5 96.9 69.6 59.2 35.3 18.6 2.5 22.6 100.0 13 b,c 120.5 97.7 75.0 63.4 11.2 9.5 8.2 24.5 42.8 78 Belize .. 24.5 79 Colombia 93.4 31.3 119.9 90.0 90.6 71.2 35.4 12.2 3.5 29.4 100.0 b b 12.8 3.0 29.1 79.5 80 Jamaica 85.9 42.1 90.1 85.1 90.2 76.7 19.3 81 Tunisia 78.0 23.1 107.6 97.7 90.2 65.8 31.6 5.9 8.5 17.3 .. 82 Jordan 92.2 54.2 96.3 89.1 86.3 83.7 37.7 0.9 0.6 12.2 .. 83 Turkey 88.7 22.3 97.6 93.9 82.1 71.2 37.1 5.8 2.1 .. .. 84 Algeria 72.6 25.9 107.5 94.9 83.2 66.3 23.9 7.1 7.8 .. 98.9 b 9.1 5.2 .. .. 85 Tonga 99.0 .. 111.8 99.0 102.7 66.2 6.4 ## MEDIUM HUMAN DEVELOPMENT 86 Fiji .. 41.9 94.2 91.2 80.9 79.1 15.4 5.4 1.7 26.1 97.8 87 Turkmenistan 99.5 .. .. .. .. .. .. .. .. .. .. b 31.2 3.4 19.6 89.2 88 Dominican Republic 88.2 27.6 104.3 80.0 74.9 57.7 33.3 89 China 93.7 38.4 112.1 .. 74.0 .. 22.1 0.4 0.3 18.3 .. 90 El Salvador 84.0 19.4 115.0 94.0 63.6 55.0 24.6 24.3 6.1 33.3 93.2 b .. 91 Sri Lanka 90.6 44.9 105.1 99.7 87.0 .. .. 2.0 0.8 22.5 92 Thailand 93.5 20.6 .. .. .. .. .. .. 9.2 21.2 .. 193 ## STATISTICAL ANNEX Education ACHIEVEMENTS in Efficiency of primary Quality of primary education education education Access to education Tertiary Primary enrolment school Population ratio teachers Pupil– Repetition Dropout with at least Primary enrolment ratio Secondary enrolment ratio (% of tertiary trained to teacher rate, rate, secondary Adult literacy school-age (% of primary school-age (% of secondary school-age teach ratio all grades all grades education rate population) population) population (number of (% of total primary pupils per enrolment in (% ages 15 (% ages 25 (% of primary HDI rank teacher) (%) previous year) and older) and older) Gross Net Gross Net Gross school cohort) a a a a a a a a a a 2005–2008 2010 2001–2009 2001–2009 2001–2009 2001–2009 2001–2009 2005–2008 2005–2008 2005–2008 2005–2008 b b b b 93 Gabon 87.0 .. 134.3 80.3 53.1 .. 7.1 44.5 34.4 36.0 100.0 b 94 Suriname 90.7 .. 113.8 90.1 75.4 64.6 12.3 32.3 17.2 13.2 100.0 b 95 Bolivia, Plurinational State of 90.7 29.3 108.3 93.7 81.8 69.9 38.3 19.8 2.5 25.1 90.6 b 96 Paraguay 94.6 26.4 108.3 92.4 65.9 57.7 25.5 20.9 4.1 16.6 .. b 97 Philippines 93.6 53.6 108.2 90.4 81.4 59.9 27.8 26.8 2.3 33.7 100.0 98 Botswana 83.3 24.7 109.7 87.2 80.2 56.5 5.2 13.2 4.7 25.4 94.3 99 Moldova, Republic of 98.3 .. 89.2 83.3 83.1 79.1 39.9 4.4 0.1 .. .. b,c 101.5 88.7 95.1 82.0 49.8 5.1 0.2 31.6 99.0 100 Mongolia 97.3 80.2 b b 99.9 101 Egypt 66.4 36.1 99.7 93.6 79.3 71.2 31.2 3.2 3.1 21.9 102 Uzbekistan 99.3 .. 94.4 89.9 102.4 91.7 9.9 1.3 0.0 .. 100.0 b .. .. .. .. 103 Micronesia, Federated States of .. .. 110.3 .. 90.5 .. 14.1 b 0.7 25.6 58.5 104 Guyana .. 40.0 108.7 94.7 102.1 .. 11.5 41.2 105 Namibia 88.2 .. 112.4 89.0 65.8 54.4 8.9 23.4 18.1 29.4 95.0 106 Honduras 83.6 17.1 116.0 96.6 64.5 .. 18.7 23.8 5.3 33.3 36.4 107 Maldives 98.4 .. 112.0 96.2 83.7 69.4 .. .. 4.3 13.3 67.9 b 108 Indonesia 92.0 26.8 120.9 94.8 75.8 69.7 18.0 19.9 2.9 21.4 93.5 b,c 109 Kyrgyzstan 99.3 89.2 94.7 83.5 85.1 80.5 52.0 1.7 0.1 .. 64.4 b b 8.0 .. 78.7 110 South Africa 89.0 57.9 104.5 87.5 95.1 71.9 .. 23.0 111 Syrian Arab Republic 83.6 33.5 124.4 94.5 74.0 67.7 .. 3.3 7.5 .. 88.4 b,c 102.2 97.3 84.4 82.5 20.2 0.5 0.3 22.2 88.3 112 Tajikistan 99.7 92.4 b 7.9 1.0 20.9 98.6 113 Viet Nam 92.5 .. 104.1 94.0 66.9 62.3 9.7 b 114 Morocco 56.4 .. 106.9 89.5 55.8 34.5 12.3 23.8 11.9 29.9 100.0 b 115 Nicaragua 78.0 25.4 116.9 91.8 67.9 45.2 18.0 51.6 11.0 29.2 72.7 56.6 39.9 17.7 35.3 12.4 29.4 .. 116 Guatemala 73.8 15.3 113.6 95.1 b b b 67.4 24.3 54.5 30.9 117 Equatorial Guinea 93.0 .. 98.7 66.4 26.2 21.6 3.3 b 84.7 118 Cape Verde 84.1 .. 101.3 84.4 67.7 56.7 11.9 12.9 11.6 24.4 119 India 62.8 22.2 113.1 89.8 57.0 .. 13.5 34.2 3.4 40.7 .. 120 Timor-Leste .. .. 106.6 75.9 54.7 31.4 15.2 .. 12.5 37.4 .. 121 Swaziland 86.5 32.6 107.9 82.8 53.3 28.6 4.4 26.3 18.0 32.4 94.0 122 Lao People’s Democratic Republic 72.7 .. 111.8 82.4 43.9 36.0 13.4 33.2 16.8 .. 96.9 b .. 107.3 67.0 34.8 30.2 .. .. .. .. .. 123 Solomon Islands 76.6 124 Cambodia 77.0 .. 115.9 88.6 40.4 34.1 7.0 45.6 11.2 48.5 98.2 125 Pakistan 53.7 16.8 84.8 66.1 32.9 32.5 5.2 30.3 4.4 40.7 85.1 b 29.8 22.4 51.8 89.0 126 Congo .. 34.8 114.0 58.9 43.1 .. 3.9 127 São Tomé and Príncipe 88.3 .. 133.3 96.1 51.3 38.1 4.1 26.1 24.2 30.8 .. table LOW HUMAN DEVELOPMENT 13 b 128 Kenya 86.5 15.5 111.5 81.5 58.3 49.1 4.1 16.4 5.8 46.5 98.4 129 Bangladesh 55.0 16.7 93.8 88.0 44.1 41.5 7.0 45.2 13.2 43.7 54.4 b 6.5 32.2 49.1 130 Ghana 65.8 28.7 101.8 73.9 54.1 46.4 6.2 40.0 131 Cameroon 75.9 13.1 110.9 88.3 37.3 .. 7.8 43.3 16.8 .. 61.8 132 Myanmar 91.9 16.6 115.0 .. 49.3 46.4 10.7 26.1 0.4 28.8 99.0 b 5.7 .. .. 133 Yemen 60.9 .. 85.4 72.7 45.7 37.4 10.2 40.5 b 14.3 44.6 71.8 134 Benin 40.8 9.8 116.6 92.8 36.3 19.6 5.8 36.9 135 Madagascar 70.7 .. 151.7 98.5 30.1 23.8 3.4 57.5 19.7 47.2 52.1 b 136 Mauritania 56.8 .. 98.2 79.7 23.3 16.3 3.8 18.1 2.0 37.2 100.0 b 137 Papua New Guinea 59.6 8.3 54.9 .. .. .. 2.0 .. .. .. .. b 38.4 16.8 37.8 66.4 138 Nepal 57.9 15.4 124.0 78.8 43.5 .. 5.6 139 Togo 64.9 14.1 105.0 83.5 41.3 22.5 5.3 55.5 23.7 37.6 14.6 b b 28.3 24.4 30.2 57.4 140 Comoros 73.6 .. 121.5 72.9 45.8 .. 2.7 141 Lesotho 89.5 13.1 107.7 72.7 39.9 25.2 3.6 54.2 21.0 37.0 71.4 b 2.9 46.3 51.2 142 Nigeria 60.1 .. 93.1 61.4 30.5 25.8 10.1 25.1 17 143 Uganda 74.6 11.0 120.2 97.1 25.3 19.2 3.7 67.6 11.0 49.9 89.4 194 human development report 2010 Education ACHIEVEMENTS in Efficiency of primary Quality of primary education education education Access to education Tertiary Primary enrolment school Population ratio teachers Pupil– Repetition Dropout with at least Primary enrolment ratio Secondary enrolment ratio (% of tertiary trained to teacher rate, rate, secondary Adult literacy school-age (% of primary school-age (% of secondary school-age teach ratio all grades all grades education rate population) population) population (number of (% of total primary pupils per enrolment in (% ages 15 (% ages 25 (% of primary HDI rank teacher) (%) previous year) and older) and older) Gross Net Gross Net Gross school cohort) a a a a a a a a a a 2005–2008 2010 2001–2009 2001–2009 2001–2009 2001–2009 2001–2009 2005–2008 2005–2008 2005–2008 2005–2008 b 144 Senegal 41.9 8.6 83.5 72.9 30.6 25.1 8.0 41.6 7.7 36.4 90.5 b 145 Haiti 61.0 13.3 .. .. .. .. .. .. .. .. .. 146 Angola 69.6 .. .. .. 17.3 .. 2.8 .. .. .. .. 147 Djibouti .. .. 55.5 45.3 29.5 24.4 2.6 .. 10.6 .. 80.3 b,c b 110.2 99.3 6.1 .. 1.5 17.2 4.2 52.2 100.0 148 Tanzania, United Republic of 72.6 6.0 b 149 Côte d’Ivoire 54.6 .. 74.5 56.0 26.3 21.2 8.4 10.5 18.0 41.9 100.0 b 150 Zambia 70.7 25.7 119.1 95.2 51.8 49.0 2.4 21.4 5.9 63.4 100.0 b b 29.7 5.4 34.4 74.7 151 Gambia 45.3 11.0 86.2 68.7 50.8 41.8 1.2 b 152 Rwanda 70.3 3.3 150.9 95.9 21.9 .. 4.0 69.1 17.7 70.2 94.2 153 Malawi 72.8 4.6 120.2 90.6 29.4 25.0 .. 64.3 20.1 .. .. b 6.9 4.9 36.7 61.0 154 Sudan 69.3 11.5 74.0 39.2 38.0 .. 5.9 b .. 16.3 .. .. 155 Afghanistan .. 6.4 106.1 .. 28.6 26.8 1.3 156 Guinea .. .. 89.9 71.3 35.8 27.7 9.2 45.1 15.4 44.1 82.1 b .. 97.8 78.2 33.4 25.3 3.6 59.7 5.0 59.3 89.7 157 Ethiopia 35.9 b .. 9.9 44.2 49.4 158 Sierra Leone 39.8 9.1 157.7 .. 34.6 24.9 2.0 159 Central African Republic 54.6 9.3 77.4 59.1 11.9 .. 2.3 54.4 25.6 100.2 .. 160 Mali 26.2 3.7 91.3 71.5 34.8 28.6 5.4 20.9 14.2 51.4 50.1 161 Burkina Faso 28.7 .. 78.5 63.3 19.8 15.4 3.1 28.9 10.5 48.9 87.7 b .. 6.7 23.9 40.2 162 Liberia 58.1 12.8 90.6 75.2 31.6 19.5 17.4 163 Chad 32.7 .. 82.7 61.0 19.0 10.5 1.9 70.2 21.8 176.2 35.5 164 Guinea-Bissau 51.0 .. 119.7 52.1 35.9 9.7 2.9 .. 18.7 88.1 35.1 165 Mozambique 54.0 3.2 114.2 79.9 20.6 6.2 1.5 56.3 5.5 64.1 67.0 166 Burundi 65.9 .. 135.6 99.4 17.9 .. 2.5 46.3 33.8 52.0 87.4 167 Niger 28.7 2.9 62.4 54.0 11.0 8.9 1.3 33.2 6.4 40.7 98.4 168 Congo, Democratic Republic of the 66.6 19.5 90.4 32.4 34.8 .. 5.0 20.5 15.3 39.0 93.3 b .. .. .. .. 169 Zimbabwe 91.4 33.4 103.6 89.9 41.0 38.0 3.8 OTHER COUNTRIES OR TERRITORIES b b Antigua and Barbuda 99.0 .. 102.5 74.0 105.2 .. .. 2.6 5.6 17.1 52.9 Bhutan 52.8 .. 109.1 87.4 61.7 47.5 6.6 9.9 6.4 29.9 91.5 b,c b 101.9 98.8 91.4 84.3 121.5 4.4 0.5 9.6 100.0 Cuba 99.8 68.8 b,c Dominica .. 26.5 81.6 72.3 104.8 68.1 .. 9.2 3.9 16.7 59.4 Eritrea 65.3 .. 52.3 38.9 30.5 26.0 2.0 26.7 15.4 47.4 89.3 b 2.9 22.6 73.5 Grenada .. .. 102.6 93.4 107.7 88.6 .. 17.4 b b 8.0 20.5 100.0 Iraq 77.6 26.3 98.0 87.3 46.8 39.6 15.7 29.9 b Kiribati .. .. 112.8 97.4 87.9 68.3 .. 18.6 .. .. 85.4 table Lebanon 89.6 .. 101.1 88.3 81.6 74.6 51.5 6.9 8.8 17.8 13.3 13 b b .. .. 16.9 .. Marshall Islands .. .. 93.0 66.3 66.4 44.9 17.0 Monaco .. .. 127.7 .. 153.4 .. .. .. .. .. .. b .. .. 74.2 Nauru .. .. 78.8 72.3 46.1 .. .. 74.6 b,c 80.4 73.3 92.4 88.6 47.2 0.9 0.5 29.0 100.0 Occupied Palestinian Territories 94.1 47.3 b Oman 86.7 .. 75.0 68.3 88.1 78.2 26.3 0.5 1.1 14.3 100.0 b Palau .. .. 98.8 .. 96.9 .. 40.2 .. 4.7 .. .. Saint Kitts and Nevis .. .. 85.3 70.6 88.2 78.7 .. 32.0 1.5 16.1 63.6 b 2.4 21.4 87.8 Saint Lucia .. .. 98.0 91.5 93.2 79.6 14.8 4.0 Saint Vincent and the Grenadines .. .. 109.0 94.6 108.2 90.3 .. 20.9 4.6 17.0 83.0 b 4.1 1.2 23.8 .. Samoa 98.7 .. 99.5 90.6 78.3 64.2 7.4 b,c b 125.3 99.4 111.8 94.3 .. 1.6 .. 13.1 77.9 Seychelles 91.8 66.8 b Tuvalu .. .. 105.6 .. .. .. .. 37.4 .. .. .. b 26.6 13.6 .. 100.0 Vanuatu 81.3 .. 108.7 97.3 40.1 38.1 4.8 195 ## STATISTICAL ANNEX Education ACHIEVEMENTS in Efficiency of primary Quality of primary education education education Access to education Tertiary Primary enrolment school Population ratio teachers Pupil– Repetition Dropout with at least Primary enrolment ratio Secondary enrolment ratio (% of tertiary trained to teacher rate, rate, secondary Adult literacy school-age (% of primary school-age (% of secondary school-age teach ratio all grades all grades education rate population) population) population (number of (% of total primary pupils per enrolment in (% ages 15 (% ages 25 (% of primary HDI rank teacher) (%) previous year) and older) and older) Gross Net Gross Net Gross school cohort) a a a a a a a a a a 2005–2008 2010 2001–2009 2001–2009 2001–2009 2001–2009 2001–2009 2005–2008 2005–2008 2005–2008 2005–2008 Developed OECD .. 73.8 101.7 95.6 101.1 91.8 71.4 2.9 .. .. .. Non-OECD .. 61.7 108.4 95.6 93.6 86.7 43.0 3.0 1.2 .. .. Developing Arab States 72.1 .. 96.4 80.9 68.8 60.4 22.7 9.5 5.7 .. .. East Asia and the Pacific .. .. 112.2 93.3 72.8 62.6 20.9 21.3 .. .. .. Europe and Central Asia 97.5 65.1 98.5 92.3 89.3 82.1 54.2 3.3 0.9 .. .. Latin America and the Caribbean 91.1 32.5 116.5 94.4 89.8 72.5 36.7 17.8 9.2 .. .. South Asia 62.4 21.6 108.2 86.9 53.5 42.0 12.8 24.1 5.0 .. .. Sub-Saharan Africa 62.4 .. 101.8 73.6 34.4 29.5 5.5 36.5 9.4 .. .. Very high human development .. 73.6 101.9 95.6 100.9 91.7 70.8 3.0 1.7 .. .. High human development 92.3 41.0 111.9 94.4 88.9 74.9 43.2 7.3 6.5 .. .. Medium human development 80.7 .. 110.2 88.5 64.7 57.0 17.6 22.6 2.9 .. .. Low human development 61.2 14.3 99.9 73.4 34.7 30.9 6.0 40.4 9.6 .. .. .. Least developed countries 59.9 .. 101.6 75.5 34.1 30.8 5.4 39.1 11.0 .. .. World .. .. 106.9 86.1 66.4 60.2 25.7 18.0 5.1 .. .. Notes a Data refer to the most recent year available during the period specified. b Refers to an earlier year than that specified. c UNESCO Institute for Statistics (2010a). Sources Columns 1 and 3–11: UNESCO Institute for Statistics (2010a). Column 2: Barro and Lee (2010). table 13 17 196 human development report 2010 14 e l Health b ta Resources Risk factors Mortality Infants lacking immunization against HIV prevalence Adult Age-standardized Under- death rates from non- Expenditure Hospital Youth Adult (% ages Infant five communicable diseases on health Physician beds DTP Measles 15–49) (% ages 15–24) (per 1,000 people) HDI rank Per capita (PPP$) (per 10,000 people) (% of one-year-olds) Female Male Total (per 1,000 live births) Female Male (per 100,000 people)

a

2007 2000–2009 2008 2007 2008 2008 2008 2008 2004

## VERY HIGH HUMAN DEVELOPMENT

1 Norway 4,763 39 39 6 7 0.1 0.1 0.1 3 4 53 81 391

2 Australia 3,357 10 39 8 6 <0.1 0.2 0.2 5 6 46 81 355

3 New Zealand 2,497 21 62 11 14 .. 0.1 0.1 5 6 57 88 398

4 United States 7,285 27 31 4 8 0.3 0.7 0.6 7 8 79 135 450

5 Ireland 3,424 31 53 7 11 0.1 0.2 0.2 3 4 56 90 459

6 Liechtenstein .. .. .. .. .. .. .. .. 2 2 .. .. ..

7 Netherlands 3,509 39 48 3 4 0.1 0.2 0.2 4 5 57 78 425

8 Canada 3,900 19 34 6 6 0.2 0.4 0.4 6 6 53 87 374

9 Sweden 3,323 36 .. 2 4 0.1 0.1 0.1 2 3 48 76 372

10 Germany 3,588 35 83 10 5 0.1 0.1 0.1 4 4 54 101 429

11 Japan 2,696 21 139 2 3 .. .. .. 3 4 43 87 284

12 Korea, Republic of 1,688 17 86 6 8 <0.1 <0.1 <0.1 5 5 43 108 470

13 Switzerland 4,417 40 55 5 13 0.5 0.4 0.6 4 5 44 76 360

14 France 3,709 37 72 2 13 0.2 0.4 0.4 3 4 55 119 387

15 Israel 2,181 36 58 7 16 0.1 <0.1 0.1 4 5 46 87 368

16 Finland 2,840 33 68 1 3 <0.1 0.1 0.1 3 3 57 129 405

17 Iceland 3,323 38 75 2 4 0.1 0.2 0.2 2 3 46 66 375

18 Belgium 3,323 42 53 1 7 0.1 0.2 0.2 4 5 61 110 437

19 Denmark 3,513 32 35 25 11 0.1 0.2 0.2 4 4 67 112 495

20 Spain 2,671 38 34 3 2 0.2 0.6 0.5 4 4 43 102 379

21 Hong Kong, China (SAR) .. .. .. .. .. .. .. .. .. .. .. .. ..

22 Greece 2,727 54 48 1 1 0.1 0.2 0.2 3 4 44 105 436

23 Italy 2,686 37 39 4 9 0.2 0.4 0.4 3 4 42 80 372

24 Luxembourg 5,734 29 63 1 4 0.1 0.2 0.2 2 3 56 101 419

50 99 409

25 Austria 3,763 38 78 17 17 0.1 0.2 0.2 3 4

26 United Kingdom 2,992 21 39 8 14 0.1 0.3 0.2 5 6 59 96 441

27 Singapore 1,643 15 32 3 5 0.1 0.2 0.2 2 3 47 82 345

28 Czech Republic 1,626 36 81 1 3 .. <0.1 .. 3 4 65 143 559

29 Slovenia 2,099 24 47 3 4 .. .. <0.1 3 4 55 132 480

30 Andorra 3,004 37 26 1 2 .. .. .. 3 4 44 99 373

31 Slovakia 1,555 31 68 1 1 .. .. <0.1 7 8 73 195 628

32 United Arab Emirates 982 15 19 8 8 .. .. .. 7 8 60 78 410

33 Malta 4,053 34 78 28 22 0.1 0.1 0.1 6 6 44 77 433

34 Estonia 1,094 33 56 5 5 0.7 1.6 1.3 4 6 84 249 664

35 Cyprus 3,034 23 37 3 13 .. .. .. 4 4 39 84 412

36 Hungary 1,388 28 71 1 1 <0.1 0.1 0.1 5 7 101 233 693

37 Brunei Darussalam 1,176 11 26 1 3 .. .. .. 6 7 80 106 473

38 Qatar 3,075 28 25 6 8 .. .. .. 9 10 53 77 512

39 Bahrain 1,199 30 20 3 1 .. .. .. 10 12 82 116 678

40 Portugal 2,284 34 35 3 3 0.3 0.5 0.5 3 4 52 128 456

41 Poland 1,035 20 52 1 2 0.1 0.1 0.1 6 7 77 205 583

b 76 7 8 0.6 1.3 1.2 10 11 108 168 531

## STATISTICAL ANNEX

Health Resources Risk factors Mortality

Infants lacking

immunization against HIV prevalence Adult Age-standardized

Under- death rates from non-

(% ages Infant five communicable diseases

on health Physician beds DTP Measles 15–49)

(% ages 15–24) (per 1,000 people)

HDI rank Per capita (PPP $) (per 10,000 people) (% of one-year-olds) Female Male Total (per 1,000 live births) Female Male (per 100,000 people) a 2007 2000–2009 2008 2007 2008 2008 2008 2008 2004 ## HIGH HUMAN DEVELOPMENT 43 Bahamas 1,987 .. 32 7 10 1.5 3.2 3.0 9 13 127 206 509 44 Lithuania 1,109 40 81 4 3 0.1 0.1 0.1 6 7 114 314 635 45 Chile 863 11 23 4 8 0.2 0.3 0.3 7 9 60 116 458 b 41 4 1 0.3 0.6 0.5 15 16 86 160 515 46 Argentina 1,322 32 47 Kuwait 814 18 18 1 1 .. .. .. 9 11 51 68 454 48 Latvia 1,071 30 76 3 3 0.5 0.9 0.8 8 9 115 311 710 49 Montenegro 1,107 20 40 5 11 .. .. .. 7 8 90 173 .. 50 Romania 592 19 65 3 3 0.2 0.2 0.1 12 14 90 220 706 51 Croatia 1,398 26 53 4 4 .. .. <0.1 5 6 65 163 578 c 6 5 0.3 0.6 0.6 12 14 85 158 521 52 Uruguay 916 37 29 53 Libyan Arab Jamahiriya 453 12 37 2 2 .. .. .. 15 17 97 170 654 54 Panama 773 15 22 18 15 0.6 1.1 1.0 19 23 83 140 417 55 Saudi Arabia 768 16 22 2 3 .. .. .. 18 21 103 186 678 c 2 4 0.2 0.3 0.3 15 17 89 154 501 56 Mexico 819 29 17 57 Malaysia 604 7 18 10 5 0.3 0.6 0.5 6 6 97 177 623 58 Bulgaria 835 37 64 5 4 .. .. .. 9 11 91 214 733 b 27 10 9 1.0 0.3 1.5 31 35 107 219 751 59 Trinidad and Tobago 1,178 12 60 Serbia 769 20 54 5 8 0.1 0.1 0.1 6 7 91 183 .. 61 Belarus 704 49 112 3 1 0.1 0.3 0.2 11 13 111 330 854 62 Costa Rica 899 13 13 10 9 0.2 0.4 0.4 10 11 68 124 439 63 Peru 327 .. 15 1 10 0.3 0.5 0.5 22 24 95 118 534 64 Albania 505 11 29 1 2 .. .. .. 13 14 91 141 752 65 Russian Federation 797 43 97 2 1 0.6 1.3 1.1 12 13 147 396 904 66 Kazakhstan 405 39 77 1 1 0.1 0.2 0.1 27 30 186 432 1,145 0.3 0.2 32 36 138 228 856 67 Azerbaijan 284 38 79 30 34 0.1 68 Bosnia and Herzegovina 767 14 30 9 16 .. .. <0.1 13 15 68 147 670 69 Ukraine 475 31 87 10 6 1.5 1.5 1.6 14 16 151 399 881 70 Iran, Islamic Republic of 689 9 14 1 2 0.1 0.2 0.2 27 32 95 152 687 71 The former Yugoslav Republic of Macedonia 669 25 46 5 2 .. .. <0.1 10 11 80 151 737 72 Mauritius 502 11 33 1 2 1.0 1.8 1.7 15 17 104 214 731 73 Brazil 837 17 24 3 1 0.6 1.0 0.6 18 22 106 210 625 74 Georgia 384 45 33 8 4 0.1 0.1 0.1 26 30 85 232 554 75 Venezuela, Bolivarian Republic of 697 19 13 53 18 .. .. .. 16 18 93 195 441 76 Armenia 246 37 41 11 6 0.1 0.2 0.1 21 23 101 240 1,064 c 25 34 0.2 0.4 0.3 21 25 121 207 484 77 Ecuador 434 15 6 c 6 4 1.5 0.5 2.1 17 19 129 223 677 78 Belize 279 11 12 79 Colombia 516 14 10 8 8 0.3 0.7 0.6 16 20 75 162 483 c 13 12 0.9 1.7 1.6 26 31 130 220 605 80 Jamaica 357 9 17 81 Tunisia 463 13 20 1 2 <0.1 0.1 0.1 18 21 72 132 537 82 Jordan 434 26 18 3 5 .. .. .. 17 20 116 179 711 83 Turkey 677 15 28 4 3 .. .. .. 20 22 73 138 701 table 14 84 Algeria 338 12 17 7 12 0.1 0.1 0.1 36 41 119 144 565 85 Tonga 167 3 24 1 1 .. .. .. 17 19 228 143 658 ## MEDIUM HUMAN DEVELOPMENT 86 Fiji 169 5 21 1 6 .. 0.1 0.1 16 18 156 249 767 87 Turkmenistan 153 24 41 4 1 .. .. <0.1 43 48 212 377 1,100 c 23 21 0.6 0.3 1.1 27 33 127 188 794 88 Dominican Republic 411 19 10 89 China 233 14 30 3 6 0.1 0.1 0.1 18 21 84 140 627 c 6 5 0.5 0.9 0.8 16 18 136 301 518 90 El Salvador 402 12 8 91 Sri Lanka 179 6 31 2 2 .. <0.1 .. 13 15 93 315 681 92 Thailand 286 3 22 1 2 1.2 1.2 1.4 13 14 140 276 516 c 62 45 3.9 1.3 5.9 57 77 301 353 716 93 Gabon 650 3 13 94 Suriname 527 5 31 16 14 1.4 2.7 2.4 25 27 128 218 728 198 human development report 2010 Health Resources Risk factors Mortality Infants lacking immunization against HIV prevalence Adult Age-standardized Under- death rates from non- Expenditure Hospital Youth Adult (% ages Infant five communicable diseases on health Physician beds DTP Measles 15–49) (% ages 15–24) (per 1,000 people) HDI rank Per capita (PPP$) (per 10,000 people) (% of one-year-olds) Female Male Total (per 1,000 live births) Female Male (per 100,000 people)

a

2007 2000–2009 2008 2007 2008 2008 2008 2008 2004

95 Bolivia, Plurinational State of 200 12 11 17 14 0.1 0.2 0.2 46 54 163 230 765

96 Paraguay 253 11 13 24 23 0.3 0.7 0.6 24 28 105 170 602

97 Philippines 130 12 5 9 8 .. .. .. 26 32 117 227 620

98 Botswana 762 4 18 4 6 15.3 5.1 23.9 26 31 394 419 594

99 Moldova, Republic of 281 27 61 5 6 0.2 0.4 0.4 15 17 141 312 963

100 Mongolia 138 26 60 4 3 .. 0.1 0.1 34 41 145 291 923

101 Egypt 310 24 21 3 8 .. .. .. 20 23 151 222 891

102 Uzbekistan 121 26 48 2 2 0.1 0.1 0.1 34 38 140 223 880

103 Micronesia, Federated States of 373 6 33 21 8 .. .. .. 32 39 156 187 682

104 Guyana 197 5 19 7 5 1.7 0.5 2.5 47 61 226 291 835

c 17 27 10.3 3.4 15.3 31 42 290 356 513

105 Namibia 467 3 27 c 7 5 0.4 0.7 0.7 26 31 129 227 761

106 Honduras 235 6 7

107 Maldives 514 9 26 2 3 .. .. .. 24 28 72 100 953

108 Indonesia 81 1 6 23 17 0.1 0.3 0.2 31 41 185 226 690

109 Kyrgyzstan 130 23 51 5 1 0.1 0.2 0.1 33 38 184 343 1,012

110 South Africa 819 8 28 33 38 12.7 4.0 18.1 48 67 479 563 867

111 Syrian Arab Republic 154 5 15 18 19 .. .. .. 14 16 120 179 679

112 Tajikistan 93 20 61 14 14 0.1 0.4 0.3 54 64 162 185 884

113 Viet Nam 183 6 28 7 8 0.3 0.6 0.5 12 14 110 192 611

114 Morocco 202 6 11 1 4 0.1 0.1 0.1 32 36 88 147 655

c 4 1 0.1 0.3 0.2 23 27 123 209 705

115 Nicaragua 232 4 9 c 15 4 1.5 .. 0.8 29 35 159 302 515

116 Guatemala 334 .. 6 c 67 49 2.5 0.8 3.4 90 148 356 366 938

117 Equatorial Guinea 543 3 19

118 Cape Verde 148 6 21 2 4 .. .. .. 24 29 115 274 591

0.3 0.3 52 69 173 250 713

119 India 109 6 9 34 30 0.3

120 Timor-Leste 116 1 .. 21 27 .. .. .. 75 93 204 275 663

121 Swaziland 287 2 21 5 5 22.6 5.8 26.1 59 83 616 631 707

122 Lao People’s Democratic Republic 84 3 12 39 48 0.1 0.2 0.2 48 61 288 317 828

123 Solomon Islands 123 1 14 22 40 .. .. .. 30 36 136 182 694

124 Cambodia 108 2 .. 9 11 0.3 0.8 0.8 69 90 216 294 832

125 Pakistan 64 8 6 27 15 0.1 0.1 0.1 72 89 190 216 717

126 Congo 90 1 16 11 21 2.3 0.8 3.5 80 127 374 389 716

127 São Tomé and Príncipe 183 5 32 1 7 .. .. .. 64 98 227 271 788

## LOW HUMAN DEVELOPMENT

128 Kenya 72 1 14 15 10 .. .. .. 81 128 364 382 729

129 Bangladesh 42 3 4 5 11 .. .. .. 43 54 230 247 730

130 Ghana 113 1 9 13 14 1.3 0.4 1.9 51 76 247 298 699

131 Cameroon 104 2 15 16 20 4.3 1.2 5.1 82 131 403 405 840

132 Myanmar 21 4 6 15 18 0.6 0.7 0.7 71 98 304 368 775 13

133 Yemen 104 3 7 31 38 .. .. .. 53 69 185 249 941

134 Benin 70 1 5 33 39 0.9 0.3 1.2 76 121 291 312 835

135 Madagascar 41 2 3 18 19 0.1 0.2 0.1 68 106 240 286 799 table

14

136 Mauritania 47 1 4 26 35 0.5 0.9 0.8 75 118 262 318 812

137 Papua New Guinea 65 1 .. 48 46 0.7 0.6 1.5 53 69 235 292 772

138 Nepal 53 2 50 18 21 0.3 0.5 0.5 41 51 273 281 769

139 Togo 68 1 9 11 23 2.4 0.8 3.3 64 98 296 351 818

140 Comoros 37 2 22 19 24 <0.1 0.1 <0.1 75 105 231 286 713

141 Lesotho 92 1 13 17 15 14.9 5.9 23.2 63 79 633 758 581

142 Nigeria 131 4 5 46 38 2.3 0.8 3.1 96 186 399 424 909

143 Uganda 74 1 4 36 32 3.9 1.3 5.4 85 135 424 451 786

c 12 23 0.8 0.3 1.0 57 108 247 293 852

144 Senegal 99 1 3

145 Haiti 58 .. 13 47 42 1.4 0.6 2.2 54 72 229 306 740

Angola 131 1 8 19 21 0.3 0.2 2.1 130 220 383 460 1,071

146

147 Djibouti 148 2 .. 11 27 2.1 0.7 3.1 76 95 283 335 862

148 Tanzania, United Republic of 63 <0.5 11 16 12 0.9 0.5 6.2 67 104 444 475 851 199

## STATISTICAL ANNEX

Health Resources Risk factors Mortality

Infants lacking

immunization against HIV prevalence Adult Age-standardized

Under- death rates from non-

(% ages Infant five communicable diseases

on health Physician beds DTP Measles 15–49)

(% ages 15–24) (per 1,000 people)

HDI rank Per capita (PPP $) (per 10,000 people) (% of one-year-olds) Female Male Total (per 1,000 live births) Female Male (per 100,000 people) a 2007 2000–2009 2008 2007 2008 2008 2008 2008 2004 149 Côte d’Ivoire 67 1 4 26 37 2.4 0.8 3.9 81 114 354 367 946 150 Zambia 79 1 19 20 15 11.3 3.6 15.2 92 148 498 538 833 151 Gambia 71 <0.5 11 4 9 0.6 0.2 0.9 80 106 253 300 830 152 Rwanda 95 <0.5 16 3 8 1.4 0.5 2.8 72 112 281 330 878 153 Malawi 50 <0.5 11 9 12 8.4 2.4 11.9 65 100 468 498 796 154 Sudan 71 3 7 14 21 1.0 0.3 1.4 70 109 304 335 986 155 Afghanistan 83 2 4 15 25 .. .. .. 165 257 398 543 1,309 156 Guinea 62 1 3 34 36 1.2 0.4 1.6 90 146 320 352 844 c 19 26 1.5 0.5 2.1 69 109 286 329 817 157 Ethiopia 30 <0.5 2 158 Sierra Leone 32 <0.5 4 40 40 1.3 0.4 1.7 123 194 368 422 1,033 159 Central African Republic 30 1 12 46 38 5.5 1.1 6.3 115 173 467 448 868 160 Mali 67 1 6 32 32 1.1 0.4 1.5 103 194 365 412 967 161 Burkina Faso 72 1 9 21 25 0.9 0.5 1.6 92 169 361 388 924 162 Liberia 39 <0.5 7 36 36 1.3 0.4 1.7 100 145 328 353 931 163 Chad 72 <0.5 4 80 77 2.8 2.0 3.5 124 209 429 465 910 164 Guinea-Bissau 33 <0.5 10 37 24 1.2 0.4 1.8 117 195 370 436 925 165 Mozambique 39 <0.5 8 28 23 8.5 2.9 12.5 90 130 458 485 777 166 Burundi 51 <0.5 7 8 16 1.3 0.4 2.0 102 168 401 425 919 167 Niger 35 <0.5 3 34 20 0.5 0.9 0.8 79 167 340 374 1,030 168 Congo, Democratic Republic of the 17 1 8 31 33 .. .. .. 126 199 373 443 921 169 Zimbabwe 20 2 30 38 34 7.7 2.9 15.3 62 96 752 812 816 ## OTHER COUNTRIES OR TERRITORIES Antigua and Barbuda 946 .. 17 1 1 .. .. .. 11 12 160 192 674 Bhutan 188 <0.5 17 4 1 <0.1 0.1 0.1 54 81 197 256 708 Cuba 917 64 60 1 1 0.1 0.1 0.1 5 6 81 122 437 Dominica 550 .. 38 4 1 .. .. .. 9 11 119 209 580 Eritrea 20 1 12 3 5 0.9 0.3 1.3 41 58 197 266 686 Grenada 591 .. 26 1 1 .. .. .. 13 15 209 245 827 Iraq 78 5 13 38 31 .. .. .. 36 44 179 377 1,018 Kiribati 358 2 15 18 28 .. .. .. 38 48 175 321 730 Korea, Democratic People’s Rep. of .. 33 132 8 2 .. .. .. 42 55 161 229 642 Lebanon 921 33 34 26 47 0.1 0.1 0.1 12 13 131 191 715 Marshall Islands 357 5 .. 7 6 .. .. .. 30 36 384 427 961 Monaco 2,139 .. .. 1 1 .. .. .. 3 4 53 118 321 Nauru 812 8 35 1 1 .. .. .. 36 45 303 448 1,093 Occupied Palestinian Territories .. .. .. .. .. .. .. .. 24 27 .. .. .. Oman 688 18 20 8 1 .. .. .. 10 12 84 155 664 Palau 812 16 50 8 3 .. .. .. 13 15 112 232 735 Saint Kitts and Nevis 863 11 55 1 1 .. .. .. 14 16 95 180 691 Saint Lucia 608 .. 28 4 1 .. .. .. 13 13 94 193 522 Saint Vincent and the Grenadines 474 8 30 1 1 .. .. .. 12 13 169 305 674 Samoa 237 3 10 54 55 .. .. .. 22 26 203 235 766 table 14 San Marino 2,810 .. .. 13 27 .. .. .. 1 2 48 59 357 Seychelles 1,094 15 39 1 1 .. .. .. 11 12 109 232 650 b .. 69 76 0.3 0.6 0.5 119 200 373 459 1,148 Somalia .. <0.5 Tuvalu 150 9 56 1 7 .. .. .. 30 36 279 257 979 Vanuatu 145 1 37 24 35 .. .. .. 27 33 162 202 749 200 human development report 2010 Health Resources Risk factors Mortality Infants lacking immunization against HIV prevalence Adult Age-standardized Under- death rates from non- Expenditure Hospital Youth Adult (% ages Infant five communicable diseases on health Physician beds DTP Measles 15–49) (% ages 15–24) (per 1,000 people) HDI rank Per capita (PPP$) (per 10,000 people) (% of one-year-olds) Female Male Total (per 1,000 live births) Female Male (per 100,000 people)

a

2007 2000–2009 2008 2007 2008 2008 2008 2008 2004

Developed

OECD 4,222 .. 63 4 7 .. .. .. 5 6 60 114 418

Non-OECD 1,807 .. 40 6 11 .. .. .. 5 6 54 93 416

Developing

Arab States 287 .. 16 15 19 .. .. .. 38 50 161 231 810

East Asia and the Pacific 207 .. 20 8 9 .. .. .. 23 28 110 170 636

Europe and Central Asia 623 .. 52 5 4 .. .. .. 20 22 127 296 847

Latin America and the Caribbean 732 .. 24 10 7 .. .. .. 19 23 102 185 560

South Asia 123 .. 17 28 25 .. .. .. 56 73 181 248 724

Sub-Saharan Africa 127 .. 19 29 28 .. .. .. 86 144 381 420 859

Very high human development 4,172 .. 49 5 7 .. .. .. 5 6 60 114 418

High human development 721 .. 34 6 5 .. .. .. 18 21 106 216 666

Medium human development 179 .. 20 20 18 .. .. .. 38 49 140 206 678

Low human development 66 .. 13 25 26 .. .. .. 83 134 339 376 851

Least developed countries 54 .. 18 22 24 .. .. .. 82 126 318 360 851

World 869 .. 30 18 17 .. .. .. 44 63 154 221 662

Notes

a Data refer to the most recent year available during the period specified.

b Refers to an earlier year than that specified.

c Public sector only.

Sources

Columns 1–5, 11 and 12: WHO (2010).

Columns 6–8: UNICEF (2010c).

Columns 9 and 10: UNDESA (2009d).

Column 13: WHO (2008). 13

table

14

201

## STATISTICAL ANNEX

15 Enabling environment: financial

e

l flows and commitments

b

ta Public expenditure Foreign direct Official development Remittance

investment assistance inflows

(% of GDP) Gross fixed

Research capital Per Allocated to

and Debt Tax Per

a

formation Net inflows Total capita social sectors

development Military service revenue

Education Health Total capita

HDI rank (% of GNI) (% of GDP) (% of GDP) (% of GDP) (% of GNI) ($) (% of total aid) (% of GDP) ($)

b b b

2000–2007 2000–2007 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008

2000–2007

## VERY HIGH HUMAN DEVELOPMENT

1 Norway 6.7 7.5 1.7 1.3 .. 28.1 20.8 –0.3 [0.88] .. .. 0.2 144

c .. .. 0.5 220

2 Australia 4.7 6.0 2.2 1.8 .. 23.1 28.3 4.7 [0.32] c .. .. 0.5 147

3 New Zealand 6.2 7.1 1.3 1.1 .. 31.7 23.3 4.2 [0.30] c .. .. 0.0 10

4 United States 5.5 7.1 2.7 4.3 .. 10.3 18.4 2.2 [0.19] c .. .. 0.2 146

5 Ireland 4.9 6.1 1.3 0.6 .. 25.4 26.3 –7.4 [0.59]

6 Liechtenstein .. .. .. .. .. .. .. .. .. .. .. .. ..

c .. .. 0.4 201

7 Netherlands 5.5 7.3 1.8 1.4 .. 23.6 20.5 –0.3 [0.80] c .. .. .. ..

8 Canada 4.9 7.1 2.0 1.3 .. 14.2 22.6 3.0 [0.32] c .. .. 0.2 89

9 Sweden 6.7 7.4 3.7 1.3 .. .. 19.5 8.7 [0.98] c .. .. 0.3 135

10 Germany 4.4 8.0 2.6 1.3 .. 11.8 19.2 0.6 [0.38] c .. .. 0.0 15

11 Japan 3.4 6.5 3.4 0.9 .. .. 23.4 0.5 [0.19]

12 Korea, Republic of 4.2 3.5 3.5 2.8 .. 16.6 29.3 0.2 .. .. .. 0.3 63

c .. .. 0.4 288

13 Switzerland 5.3 6.4 2.9 0.8 .. 10.2 22.0 1.3 [0.42] c .. .. 0.6 255

14 France 5.6 8.7 2.1 2.3 .. 21.8 21.9 3.5 [0.39]

15 Israel 6.4 4.5 4.7 7.0 .. 25.3 18.5 4.8 .. .. .. 0.7 195

c .. .. 0.3 156

16 Finland 5.9 6.1 3.5 1.3 .. 21.7 20.6 –2.8 [0.44]

17 Iceland 7.5 7.7 2.8 0.0 .. 24.6 23.9 4.2 .. .. .. 0.2 112

c .. .. 2.1 973

18 Belgium 6.1 7.0 1.9 1.2 .. 25.6 22.7 19.8 [0.48] c .. .. 0.3 162

19 Denmark 7.9 8.2 2.6 1.4 .. 35.6 21.5 0.9 [0.82] c .. .. 0.7 258

20 Spain 4.4 6.1 1.3 1.2 .. 10.6 29.4 4.4 [0.45]

21 Hong Kong, China (SAR) 3.3 .. 0.8 .. .. .. 19.7 29.3 .. .. .. 0.2 51

c .. .. 0.8 239

22 Greece 4.0 5.8 0.5 3.6 .. 19.9 19.3 1.5 [0.21] c .. .. 0.1 52

23 Italy 4.3 6.7 1.1 1.7 .. 22.6 20.9 0.7 [0.22] c .. .. 3.2 3,527

24 Luxembourg 3.7 6.5 1.7 .. .. 24.5 20.1 215.6 [0.97] c .. .. 0.8 389

25 Austria 5.4 7.7 2.5 0.9 .. 20.1 22.4 3.5 [0.43] c .. .. 0.3 128

26 United Kingdom 5.6 6.9 1.8 2.5 .. 28.6 16.7 3.5 [0.43]

27 Singapore 2.8 1.0 2.6 4.1 .. 14.6 28.5 12.5 .. .. .. .. ..

28 Czech Republic 4.6 5.8 1.6 1.3 .. 14.8 23.9 5.0 .. .. .. 0.7 136

29 Slovenia 5.2 5.6 1.5 1.5 .. 20.0 27.5 3.5 .. .. .. 0.6 170

30 Andorra 3.2 5.3 .. .. .. .. .. .. .. .. .. .. ..

31 Slovakia 3.6 5.2 0.5 1.5 .. 13.5 26.1 3.3 .. .. .. 2.0 365

32 United Arab Emirates 0.9 1.9 .. .. .. .. 20.4 .. .. .. .. .. ..

33 Malta 4.8 5.8 0.6 0.7 .. 28.6 19.4 12.7 .. .. .. 0.6 121

34 Estonia 5.0 4.1 1.1 2.2 .. 16.8 29.3 8.3 .. .. .. 1.7 297

35 Cyprus 7.1 3.0 0.4 1.8 .. 56.7 23.3 15.5 .. .. .. 1.1 323

36 Hungary 5.4 5.2 1.0 1.2 .. 23.6 20.1 40.6 .. .. .. 1.7 262

37 Brunei Darussalam 3.7 1.9 0.0 3.9 .. .. 13.0 0.8 .. .. .. .. ..

38 Qatar 3.3 2.9 .. .. .. 23.1 30.2 .. .. .. .. .. ..

39 Bahrain 2.9 2.6 .. 3.0 .. 1.5 31.9 8.2 0.0 0.0 .. .. ..

c .. .. 1.7 382

40 Portugal 5.3 7.1 1.2 2.0 .. 22.2 21.7 1.5 [0.27]

41 Poland 4.9 4.6 0.6 2.0 11.2 18.4 22.0 2.8 .. .. .. 2.0 274

42 Barbados 6.7 4.4 .. .. .. 35.6 22.5 6.8 .. 18.6 87.3 4.6 658

202 human development report 2010 Enabling environment: financial flows and commitments

Public expenditure Foreign direct Official development Remittance

investment assistance inflows

(% of GDP) Gross fixed

Research capital Per Allocated to

and Debt Tax Per

a

formation Net inflows Total capita social sectors

development Military service revenue

Education Health Total capita

HDI rank (% of GNI) (% of GDP) (% of GDP) (% of GDP) (% of GNI) ($) (% of total aid) (% of GDP) ($)

b b b

2000–2007 2000–2007 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008

2000–2007

## HIGH HUMAN DEVELOPMENT

43 Bahamas 3.6 3.7 .. .. .. 16.7 37.8 9.9 .. .. .. .. ..

44 Lithuania 4.7 4.5 0.8 1.5 20.6 17.4 24.4 3.7 .. .. .. 3.1 435

45 Chile 3.4 3.7 0.7 3.5 9.8 19.8 24.0 9.9 0.0 4.4 63.9 0.0 0

46 Argentina 4.9 5.1 0.5 0.8 3.0 14.2 23.3 3.0 0.0 3.3 69.5 0.2 17

47 Kuwait 3.8 1.7 0.1 3.2 .. 0.9 18.9 0.0 .. .. .. .. ..

48 Latvia 5.0 3.6 0.6 1.9 18.1 15.0 30.2 4.0 .. .. .. 1.8 265

49 Montenegro .. 5.1 1.2 1.8 1.4 .. 27.7 19.2 2.4 171.5 52.8 .. ..

50 Romania 4.4 3.8 0.5 1.5 9.3 17.9 31.1 6.9 .. .. .. 4.7 436

51 Croatia 3.9 6.6 0.9 1.9 .. 20.4 27.6 6.9 0.6 89.7 31.3 2.3 361

52 Uruguay 2.8 5.9 0.4 1.3 4.7 17.2 18.7 6.9 0.1 10.0 59.1 0.3 32

d 1.9 .. 1.3 .. .. 27.9 4.4 0.1 9.6 81.0 0.0 3

53 Libyan Arab Jamahiriya 2.7

54 Panama 3.8 4.3 0.2 0.0 7.2 9.3 22.2 10.4 0.1 8.4 50.7 0.9 58

55 Saudi Arabia 5.7 2.7 0.0 8.2 .. .. 19.3 4.8 0.0 0.0 .. 0.0 9

56 Mexico 4.8 2.7 0.5 0.5 3.9 11.7 22.1 2.1 0.0 1.4 66.0 2.4 247

57 Malaysia 4.5 1.9 0.6 2.0 4.1 16.6 21.7 3.3 0.1 5.9 52.5 0.9 71

58 Bulgaria 4.1 4.2 0.5 2.4 10.3 24.2 33.4 18.4 .. .. .. 5.3 346

59 Trinidad and Tobago 4.2 2.7 0.1 .. .. 25.9 25.3 3.8 0.1 9.1 63.2 0.5 82

60 Serbia 4.5 6.1 0.3 2.4 9.6 22.0 20.4 6.0 2.1 142.4 51.5 11.1 753

61 Belarus 5.2 4.9 1.0 1.5 2.0 25.5 32.7 3.6 0.2 11.4 81.3 0.7 46

62 Costa Rica 5.0 5.9 0.4 0.0 5.4 15.8 24.2 6.8 0.2 14.6 31.8 2.0 134

63 Peru 2.7 2.5 0.1 1.1 4.1 15.4 26.1 3.2 0.4 16.1 57.9 1.9 85

64 Albania 2.9 2.9 .. 2.0 1.3 17.3 32.4 7.6 3.0 122.8 55.7 12.2 476

.. 0.4 43

65 Russian Federation 3.9 3.5 1.1 3.5 4.1 15.7 22.0 4.3 .. ..

66 Kazakhstan 2.8 2.5 0.2 1.2 29.2 12.7 31.3 11.0 0.3 21.2 43.0 0.1 12

67 Azerbaijan 1.9 1.0 0.2 3.8 0.7 16.7 20.1 0.0 0.6 27.1 39.9 3.4 179

68 Bosnia and Herzegovina .. 5.6 0.0 1.4 2.3 21.0 24.4 5.7 2.5 128.0 62.0 14.8 725

69 Ukraine 5.3 4.0 0.9 2.7 10.1 17.8 25.6 6.1 0.3 13.3 56.2 3.2 125

e 1.4 84.5 0.4 16

70 Iran, Islamic Republic of 4.8 3.0 0.7 2.7 1.0 7.3 25.8 0.6 0.0

71 The former Yugoslav Republic of Macedonia 3.5 4.7 0.2 1.8 5.1 19.7 23.9 6.3 2.3 108.1 52.8 4.3 199

72 Mauritius 3.6 2.0 0.4 0.2 1.7 18.2 24.6 4.1 1.2 86.3 21.5 2.3 179

73 Brazil 5.2 3.5 1.0 1.5 3.6 16.4 19.0 2.9 0.0 2.4 67.4 0.3 27

74 Georgia 2.9 1.5 0.2 8.5 1.5 23.8 22.5 12.2 7.0 203.6 27.5 5.7 170

75 Venezuela, Bolivarian Republic of 3.7 2.7 .. 1.4 1.9 15.5 19.8 0.1 0.0 2.1 75.7 0.0 5

76 Armenia 3.0 2.1 0.2 3.3 3.0 17.0 40.0 7.8 2.4 98.3 43.3 8.9 345

77 Ecuador 1.0 2.3 0.2 2.8 5.0 .. 23.8 1.8 0.5 17.1 53.8 5.2 210

78 Belize 5.1 2.6 .. 1.1 8.2 22.9 25.5 14.0 2.1 81.4 19.0 5.8 243

79 Colombia 3.9 5.1 0.2 3.7 3.4 12.6 .. 4.3 0.4 21.8 70.7 2.0 109

80 Jamaica 6.2 2.4 0.1 0.6 7.9 25.4 .. 9.8 0.6 29.5 33.1 14.9 811

81 Tunisia 7.2 3.0 1.0 1.3 5.6 22.8 25.3 6.5 1.3 46.4 38.5 4.9 191

d 5.4 0.3 5.9 12.2 18.3 25.6 9.3 3.5 125.6 43.5 17.9 642

82 Jordan 4.9

83 Turkey 2.9 3.4 0.7 2.2 7.4 18.6 19.9 2.5 0.3 27.4 27.3 0.2 18

84 Algeria 4.3 3.6 0.1 3.0 0.8 46.5 27.0 1.6 0.2 9.2 49.0 1.3 64

85 Tonga 4.7 3.1 .. .. 1.9 .. 17.1 2.2 9.6 257.0 70.3 35.8 961

## MEDIUM HUMAN DEVELOPMENT

86 Fiji 6.2 2.8 .. 1.3 0.7 22.7 16.0 8.9 1.3 53.9 62.1 3.4 143 table

15

87 Turkmenistan .. 1.4 .. .. 1.2 .. 6.5 5.3 0.1 3.6 74.0 .. ..

88 Dominican Republic 2.2 1.9 .. 0.6 3.3 15.9 18.2 6.3 0.3 15.5 43.5 7.8 357

d 1.9 1.5 2.0 0.8 9.4 42.0 3.4 0.0 1.1 49.1 1.1 37

89 China 1.9 d 0.5 4.6 13.9 15.0 3.5 1.1 38.1 55.7 17.2 620

90 El Salvador 3.6 3.6 0.1

91 Sri Lanka .. 2.0 0.2 3.6 3.1 14.2 25.3 1.9 1.8 36.2 28.4 7.3 146

4.9 2.7 0.2 1.5 6.3 16.5 27.4 3.6 –0.3 .. 42.7 0.7 28

92 Thailand

93 Gabon 3.8 3.0 .. .. 4.7 .. 24.4 0.1 0.4 37.6 65.4 0.1 8

94 Suriname .. 3.6 .. .. .. .. 25.1 –7.7 3.7 195.2 30.1 0.1 4

95 Bolivia, Plurinational State of 6.3 3.4 0.3 1.5 5.9 17.0 17.2 3.1 3.9 64.9 53.5 6.9 118 203

## STATISTICAL ANNEX

Enabling environment: financial flows and commitments

Public expenditure Foreign direct Official development Remittance

investment assistance inflows

(% of GDP) Gross fixed

Research capital Per Allocated to

and Debt Tax Per

a

formation Net inflows Total capita social sectors

development Military service revenue

Education Health Total capita

HDI rank (% of GNI) (% of GDP) (% of GDP) (% of GDP) (% of GNI) ($) (% of total aid) (% of GDP) ($)

b b b

2000–2007 2000–2007 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008

2000–2007

96 Paraguay 4.0 2.4 0.1 0.8 2.9 12.5 19.6 2.0 0.8 21.4 42.0 3.1 81

97 Philippines 2.6 1.3 0.1 0.8 6.6 14.1 14.7 0.8 0.0 0.7 34.1 11.2 206

98 Botswana 8.1 4.3 0.4 2.7 0.5 .. 23.4 0.8 5.6 377.0 35.8 0.9 59

99 Moldova, Republic of 8.2 5.2 0.5 0.6 7.5 20.5 34.1 11.7 4.5 82.3 51.5 31.4 522

100 Mongolia 5.1 3.5 0.2 .. 1.4 23.2 35.7 13.0 4.8 93.7 39.4 3.8 76

101 Egypt 3.8 2.4 0.2 2.3 1.9 15.4 22.4 5.9 0.8 16.5 37.0 5.4 107

102 Uzbekistan .. 2.3 .. .. 2.5 .. 23.0 3.3 0.7 6.9 50.2 .. ..

103 Micronesia, Federated States of 7.3 12.6 .. .. .. .. .. .. 35.9 855.8 53.3 .. ..

104 Guyana 6.1 7.2 .. .. 2.3 .. 39.7 14.5 14.5 217.8 54.6 24.1 365

105 Namibia 6.5 3.2 .. 3.5 .. 27.2 23.4 6.1 2.4 98.0 66.3 0.2 6

106 Honduras .. 4.1 0.0 0.8 2.8 15.8 32.2 6.6 4.1 77.9 43.1 21.5 392

107 Maldives 8.1 6.4 .. .. 5.4 21.0 53.5 1.2 4.5 175.0 47.8 0.2 10

108 Indonesia 3.5 1.2 0.0 1.0 4.8 12.3 27.6 1.8 0.2 5.4 37.8 1.3 30

109 Kyrgyzstan 6.6 3.5 0.3 3.7 6.6 16.8 22.7 4.6 8.3 68.2 63.0 24.4 234

110 South Africa 5.1 3.6 1.0 1.3 1.7 27.7 23.2 3.5 0.4 23.1 66.8 0.3 17

111 Syrian Arab Republic 4.9 1.6 .. 3.4 .. .. 16.4 3.1 0.3 6.4 50.7 1.5 41

112 Tajikistan 3.5 1.1 0.1 .. 2.7 9.8 19.3 7.3 5.8 42.5 55.2 49.6 372

113 Viet Nam 5.3 2.8 0.2 2.4 1.5 .. 36.0 10.6 2.9 29.6 35.7 7.9 84

114 Morocco 5.7 1.7 0.6 3.4 4.8 27.5 33.1 2.8 1.4 39.0 47.6 7.8 218

115 Nicaragua 3.1 4.5 0.0 0.7 4.3 17.0 29.4 9.5 11.5 130.4 43.0 12.4 144

116 Guatemala 3.2 2.1 0.0 0.4 4.6 11.3 17.7 2.1 1.4 39.2 43.0 11.4 326

117 Equatorial Guinea 0.6 1.7 .. .. .. .. 28.2 .. 0.3 57.0 80.0 .. ..

311

118 Cape Verde 5.7 3.4 .. 0.5 2.0 23.9 46.6 13.3 12.8 437.1 37.6 9.7

119 India 3.2 1.1 0.8 2.6 2.7 12.9 34.8 3.6 0.2 1.8 50.4 4.3 44

120 Timor-Leste 7.1 11.5 .. 4.7 .. .. 21.8 .. 9.5 252.3 69.9 .. ..

121 Swaziland 7.9 3.8 .. .. 1.7 27.6 16.5 0.4 2.5 57.6 58.0 3.5 86

122 Lao People’s Democratic Republic 2.3 0.8 0.0 0.4 3.8 10.1 37.1 4.1 10.0 79.8 44.7 0.0 0

d 4.3 .. .. 2.8 .. 13.4 11.8 35.1 439.8 79.3 3.2 41

123 Solomon Islands 2.2

124 Cambodia 1.6 1.7 0.0 1.1 0.4 8.2 19.4 7.9 8.1 50.5 60.5 3.1 22

125 Pakistan 2.9 0.8 0.7 2.6 1.8 9.8 20.4 3.3 0.9 9.3 55.1 4.3 42

126 Congo 1.8 1.7 .. 1.1 1.3 6.2 20.5 24.5 6.0 139.5 15.8 0.1 4

127 São Tomé and Príncipe .. 5.3 .. .. 1.9 .. .. 18.9 26.3 293.9 43.2 1.1 13

## LOW HUMAN DEVELOPMENT

128 Kenya 7.0 2.0 .. 1.9 1.3 18.9 19.4 0.3 4.0 35.3 51.9 5.6 44

129 Bangladesh 2.4 1.1 .. 1.0 1.2 8.8 24.2 1.2 2.4 12.9 31.8 11.3 56

130 Ghana 5.4 4.3 .. 0.7 1.6 22.9 35.9 12.7 8.1 55.4 45.4 0.8 5

131 Cameroon 2.9 1.3 .. 1.5 1.6 .. 17.1 0.2 2.3 27.8 22.9 0.6 8

132 Myanmar 1.3 0.2 0.2 .. .. 3.3 11.7 .. .. 10.8 24.1 .. 3

133 Yemen 5.2 1.5 .. 4.2 1.2 .. 23.1 5.8 1.3 13.3 62.6 5.3 62

134 Benin 3.6 2.5 .. 1.1 1.5 17.3 20.7 1.8 9.6 74.0 48.5 4.1 31

135 Madagascar 2.9 2.7 0.1 1.1 0.3 11.4 35.6 15.6 9.5 44.0 40.5 0.1 1

136 Mauritania 4.4 1.6 .. 3.7 4.4 .. 25.9 3.6 .. 97.1 38.5 0.1 1

137 Papua New Guinea .. 2.6 .. 0.4 12.7 21.0 18.1 –0.4 4.1 47.2 61.3 0.2 2

14 138 Nepal 3.8 2.0 .. 2.0 1.3 10.4 21.1 0.0 5.6 25.1 46.2 21.6 95

139 Togo 3.7 1.5 .. 1.9 6.8 16.3 22.3 2.3 11.7 51.0 33.7 9.8 44

140 Comoros 7.6 1.9 .. .. 2.3 .. 16.1 1.5 7.0 58.2 60.4 2.3 22

141 Lesotho 12.4 3.6 0.1 1.6 1.8 58.9 28.3 13.4 7.0 71.0 71.9 27.0 214

table

15 142 Nigeria .. 1.7 .. 0.8 0.3 .. .. 1.8 0.7 8.5 72.9 4.8 66

143 Uganda 3.8 1.6 0.4 2.3 0.5 12.8 23.3 5.5 11.7 52.3 44.2 5.1 23

144 Senegal 5.1 3.2 0.1 1.6 1.4 16.1 30.2 5.3 8.1 86.6 42.9 9.7 105

.. .. 0.4 13.1 93.2 50.6 19.6 143

145 Haiti .. 1.2 .. 0.0 ..

146 Angola 2.6 2.0 .. 3.0 2.3 .. 12.4 2.0 0.5 20.5 69.1 0.1 5

147 Djibouti 8.7 5.5 .. 3.7 2.8 .. 38.9 28.9 12.7 142.2 40.3 3.5 36

148 Tanzania, United Republic of 6.8 3.5 .. 1.1 0.3 .. 16.4 3.6 11.7 54.9 51.3 0.1 0

149 Côte d’Ivoire 4.6 1.0 .. 1.5 4.7 15.6 10.1 1.7 2.7 29.9 45.6 0.8 9

17 150 Zambia 1.4 3.6 0.0 2.0 1.3 17.1 22.7 6.6 8.4 86.0 58.3 0.5 5

151 Gambia 2.0 2.6 .. .. 3.3 .. 24.8 8.9 12.8 56.5 15.7 8.2 40

204 human development report 2010 Enabling environment: financial flows and commitments

Public expenditure Foreign direct Official development Remittance

investment assistance inflows

(% of GDP) Gross fixed

Research capital Per Allocated to

and Debt Tax Per

a

formation Net inflows Total capita social sectors

development Military service revenue

Education Health Total capita

HDI rank (% of GNI) (% of GDP) (% of GDP) (% of GDP) (% of GNI) ($) (% of total aid) (% of GDP) ($)

b b b

2000–2007 2000–2007 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008

2000–2007

152 Rwanda 4.1 4.9 .. 1.5 0.4 .. 24.1 2.3 21.1 95.7 60.5 1.5 7

153 Malawi 4.2 5.9 .. .. 0.8 .. 24.2 0.9 21.5 63.9 56.1 0.0 0

154 Sudan .. 1.3 0.3 .. 0.8 .. 20.2 4.6 4.6 57.6 27.5 5.5 75

155 Afghanistan .. 1.8 .. 1.9 0.1 5.8 27.6 2.8 45.8 .. 47.7 .. ..

156 Guinea 1.7 0.6 .. .. 4.2 .. 15.5 10.1 7.6 32.4 33.0 1.9 7

157 Ethiopia 5.5 2.2 0.2 1.4 0.4 10.2 20.1 0.4 12.5 41.2 42.9 1.5 5

158 Sierra Leone 3.8 1.4 .. 2.4 0.3 10.8 14.7 –0.2 19.2 66.0 53.1 7.7 27

159 Central African Republic 1.3 1.4 .. 1.6 1.8 6.2 11.6 6.1 13.2 58.0 30.9 .. ..

160 Mali 3.8 2.9 .. 1.9 0.8 15.6 23.3 1.5 11.4 75.8 51.5 3.9 27

161 Burkina Faso 4.6 3.4 0.1 1.4 0.6 12.5 20.8 1.7 12.6 65.6 41.4 0.6 4

162 Liberia 2.7 2.8 .. 0.6 135.2 .. 16.4 17.1 185.0 329.9 13.7 6.9 15

163 Chad 1.9 2.7 .. 6.6 2.1 .. 14.1 9.9 6.2 37.6 24.9 .. ..

d 1.6 .. .. 4.0 .. 23.9 3.5 31.2 83.3 49.1 7.0 19

164 Guinea-Bissau 5.2

165 Mozambique 5.0 3.5 0.5 0.8 0.5 .. 18.5 6.0 22.9 91.5 49.3 1.2 5

166 Burundi 7.2 5.2 .. 4.0 3.7 .. 16.4 0.3 43.9 63.0 35.4 0.3 0

167 Niger 3.7 2.8 .. .. 0.5 11.5 18.9 2.7 11.3 41.3 45.2 1.5 5

168 Congo, Democratic Republic of the .. 1.2 0.5 1.4 6.2 6.3 23.9 8.6 15.6 25.1 46.8 .. ..

169 Zimbabwe 4.6 4.1 .. .. 7.3 .. 21.0 3.0 .. 49.0 35.1 .. ..

## OTHER COUNTRIES OR TERRITORIES

Antigua and Barbuda 3.9 3.2 .. .. .. .. 73.7 20.8 0.7 91.3 82.9 1.0 141

Bhutan 5.1 3.3 .. .. 6.3 7.9 46.4 2.3 6.2 125.4 46.5 .. ..

Cuba 13.6 9.9 0.4 .. .. .. .. .. .. 11.3 50.4 .. ..

Dominica 4.8 3.9 .. .. 5.4 .. 32.7 14.6 6.3 312.4 15.4 1.3 62

Eritrea 2.0 1.5 .. .. 0.9 .. 10.6 2.2 8.7 28.6 54.1 0.5 1

3.6 .. .. 3.9 .. 29.8 25.3 5.5 300.4 35.6 4.3 263

Iraq .. 1.9 .. 5.4 .. .. .. .. .. .. 18.1 .. 0

Kiribati 17.9 16.1 .. .. .. .. .. .. 13.9 269.0 57.7 6.6 93

Korea, Democratic People’s Rep. of .. 3.0 .. .. .. .. .. .. .. 9.1 11.2 .. ..

Lebanon 2.0 3.9 .. 3.9 15.6 16.3 30.7 12.3 4.0 259.9 45.3 24.5 1,712

Marshall Islands 12.3 14.3 .. .. .. .. .. .. 27.3 887.0 43.6 .. ..

Monaco .. 2.9 .. .. .. .. .. .. .. .. .. .. ..

Nauru .. .. .. .. .. .. .. .. .. 3,124.0 39.4 .. ..

Occupied Palestinian Territories .. .. .. .. .. .. 25.7 1.2 0.0 675.2 66.7 14.6 160

Oman 4.0 1.9 .. 7.7 .. 7.4 12.6 7.5 .. 11.4 83.0 0.1 16

Palau 10.3 8.5 .. .. .. .. .. .. 23.4 2,147.0 6.4 .. ..

Saint Kitts and Nevis 9.9 3.4 .. .. 8.8 22.2 41.6 16.1 9.1 924.8 5.0 0.8 91

d .. 5.2 .. 25.9 10.5 2.0 112.3 35.4 0.3 16

Saint Lucia 6.3 3.4 0.4

Saint Vincent and the Grenadines 7.0 3.3 0.2 .. 4.9 .. 37.9 20.0 4.7 243.6 33.3 1.8 101

Samoa 5.4 4.2 .. .. 2.7 .. .. 1.1 7.8 219.2 64.5 25.8 755

San Marino .. 6.1 .. .. .. 22.4 .. .. .. .. .. .. ..

Seychelles 5.0 3.6 0.4 1.3 12.6 26.0 28.3 43.7 1.6 134.2 37.4 1.4 138

Somalia .. .. .. .. .. .. .. .. .. 84.7 16.8 .. ..

Tuvalu .. .. .. .. .. .. .. .. .. 1,662.0 41.3 .. ..

Vanuatu 6.9 2.7 .. .. 0.8 .. 24.2 5.8 16.2 398.6 36.9 1.2 30

Notes table

a c

Data refer to allocation of aid to social infrastructure and services including health, Since 1970 developed countries committed to spending 0.7 percent of gross 15

education, water, sanitation, government, civil society and other services, expressed national income on official development assistance. Values in brackets refer to

as a percentage of total official development assistance received. Differences in official development assistance disbursed by donor countries.

d

allocation of funds exist between countries. Refers to an earlier year than that specified.

b e

Data refer to the most recent year available during the period specified. Refers to 2007.

Sources

Column 1: UNESCO Institute for Statistics (2010a).

Columns 2, 3, 5–8, 12 and 13: World Bank (2010g).

Column 4: SIPRI (2010b).

Columns 9–11: OECD-DAC (2010a). 205

## STATISTICAL ANNEX

16 Enabling environment:

e

l economy and infrastructure

b

ta Economy Physical infrastructure Media infrastructure

Population

transport

Consumer Road Rail electricity newspapers coverage coverage

(freight)

GDP GDP per capita price index density lines

Average

Average per sq. km of (million tonnes (% of (per thousand (% of (% of

annual

annual growth

## (PPP

HDI rank land area) (km) per km) population) people) population) population)

change (%)

rate (%)

($billions)$ billions) ($) a a a 2008 2008 2008 1970–2008 2000–2008 2004–2007 2004–2008 2005–2008 2008 2004 2005 2005 ## VERY HIGH HUMAN DEVELOPMENT 1 Norway 451.8 280.0 94,759 2.6 1.7 29 4,114 .. .. 516 100 98 2 Australia 1,015.2 831.2 47,370 1.9 3.0 .. 9,661 2,212 .. 155 100 100 3 New Zealand 129.9 116.4 30,439 1.2 2.7 35 .. 921 .. 182 100 100 4 United States 14,591.4 14,591.4 46,350 1.9 2.8 68 227,058 39,314 .. 193 .. .. 5 Ireland 267.6 185.2 60,460 3.5 3.6 .. 1,919 .. .. 182 .. .. 6 Liechtenstein .. .. .. 3.2 .. .. .. .. .. .. .. .. 7 Netherlands 871.0 673.6 52,963 1.9 2.0 372 2,896 4,903 .. 307 100 100 8 Canada 1,501.3 1,301.7 45,070 1.9 2.2 14 57,216 1,389 .. 175 92 95 9 Sweden 479.0 340.8 51,950 1.6 1.5 95 9,830 .. .. 481 100 100 10 Germany 3,649.5 2,904.6 44,446 1.9 1.7 181 33,862 8,353 .. 267 .. .. 11 Japan 4,910.8 4,358.5 38,455 2.1 –0.1 316 20,048 8,173 .. 551 .. .. 12 Korea, Republic of 929.1 1,344.4 19,115 5.6 3.1 103 3,381 8,727 .. .. 100 100 13 Switzerland 491.9 324.4 64,327 1.1 1.0 173 3,499 1,182 .. 420 100 99 14 France 2,856.6 2,121.7 44,508 1.8 1.9 172 29,901 6,188 .. 163 100 100 15 Israel 202.1 204.0 27,652 1.9 1.7 81 1,005 902 0.0 .. .. .. 16 Finland 272.7 192.3 51,323 2.2 1.5 23 5,919 543 .. 431 100 100 17 Iceland 16.7 11.7 52,479 2.5 4.9 13 .. .. .. 552 100 100 18 Belgium 504.2 377.3 47,085 2.0 2.2 499 3,513 982 .. 165 .. .. 19 Denmark 341.3 202.4 62,118 1.6 2.0 168 2,133 .. .. 353 100 100 20 Spain 1,604.2 1,442.9 35,215 2.1 3.2 .. 15,046 1,306 .. 144 .. .. 21 Hong Kong, China (SAR) 215.4 306.5 30,863 4.6 0.0 184 .. .. .. .. 48 23 22 Greece 355.9 329.9 31,670 2.0 3.3 89 2,552 78 .. .. 98 98 23 Italy 2,303.1 1,871.7 38,492 1.7 2.3 162 16,862 1,279 .. 137 100 100 .. 255 100 100 24 Luxembourg 53.7 38.6 109,903 2.9 2.4 201 275 .. 25 Austria 413.5 316.1 49,599 2.2 2.0 128 5,755 421 .. 311 100 98 26 United Kingdom 2,674.1 2,178.2 43,541 1.9 3.0 172 16,321 6,284 .. 290 .. .. 27 Singapore 181.9 238.5 37,597 5.0 1.3 472 .. .. 0.0 361 .. .. 28 Czech Republic 215.5 256.9 20,673 0.2 2.5 163 9,487 27 .. 183 .. .. 29 Slovenia 54.6 56.3 27,019 2.4 4.4 191 1,228 .. .. .. .. .. 30 Andorra .. .. .. 0.8 .. .. .. .. .. .. .. .. 31 Slovakia 98.5 119.7 18,212 0.9 5.1 89 3,592 46 .. 126 .. .. 32 United Arab Emirates .. .. .. 4.2 .. 5 .. .. 0.0 .. 100 100 33 Malta .. .. .. 4.3 2.5 705 .. .. .. .. 100 100 34 Estonia 23.4 27.7 17,454 0.7 4.3 128 816 1 .. 191 92 76 35 Cyprus 24.9 21.3 31,410 3.4 2.8 132 .. .. .. .. 75 75 36 Hungary 154.7 198.6 15,408 2.2 5.5 210 7,942 .. .. 217 100 100 37 Brunei Darussalam .. .. .. 0.2 0.1 63 .. .. 0.0 68 .. .. 38 Qatar .. .. .. 0.0 7.3 68 .. .. 0.0 .. 100 .. 39 Bahrain 21.9 27.0 28,240 1.0 1.8 .. .. .. 0.0 .. .. .. 40 Portugal 243.5 247.0 22,923 2.5 2.9 90 2,842 347 .. .. 83 100 41 Poland 527.9 658.6 13,845 2.7 2.4 83 19,627 79 .. 114 92 99 42 Barbados 3.7 .. 14,426 1.8 3.7 372 .. .. .. .. .. .. 206 human development report 2010 Enabling environment: economy and infrastructure Economy Physical infrastructure Media infrastructure Population Air without Daily Radio Television transport Consumer Road Rail electricity newspapers coverage coverage (freight) GDP GDP per capita price index density lines (km of road Average Average per sq. km of (million tonnes (% of (per thousand (% of (% of annual annual growth ## (PPP HDI rank land area) (km) per km) population) people) population) population) change (%) rate (%) ($ billions) $billions) ($) a a a

2008 2008 2008 1970–2008 2000–2008 2004–2007 2004–2008 2005–2008 2008 2004 2005 2005

## HIGH HUMAN DEVELOPMENT

43 Bahamas .. .. .. .. 2.2 .. .. 1 .. .. .. ..

44 Lithuania 47.3 59.6 14,098 –0.5 2.5 124 1,765 1 .. 108 100 100

45 Chile 169.5 242.4 10,084 2.8 3.2 .. 5,898 1,308 1.8 51 .. 98

46 Argentina 328.5 570.4 8,236 1.2 10.3 .. 35,753 132 2.8 36 .. ..

47 Kuwait 148.0 .. 54,260 –1.2 3.0 32 .. .. 0.0 .. .. ..

48 Latvia 33.8 37.1 14,908 1.3 6.1 108 2,263 .. .. 154 .. ..

49 Montenegro 4.9 8.3 7,859 0.0 .. .. .. .. .. .. .. ..

50 Romania 200.1 289.3 9,300 3.3 12.5 .. 10,784 6 .. 70 90 100

51 Croatia 69.3 78.3 15,637 2.1 2.8 51 2,722 2 .. .. .. ..

52 Uruguay 32.2 42.5 9,654 2.2 9.5 102 2,993 .. 0.0 .. 98 98

53 Libyan Arab Jamahiriya 93.2 101.9 14,802 –1.3 –0.5 .. .. 0 0.0 .. .. ..

54 Panama 23.1 42.4 6,793 2.8 2.1 .. .. .. 11.8 65 .. ..

55 Saudi Arabia 468.8 590.8 19,022 1.1 1.7 10 2,758 1,383 0.8 .. .. ..

56 Mexico 1,088.1 1,549.5 10,232 1.7 4.5 18 26,677 483 .. .. 98 92

57 Malaysia 221.8 383.7 8,209 4.4 2.3 28 1,665 2,444 0.7 109 .. ..

58 Bulgaria 49.9 89.9 6,546 3.3 6.3 37 4,159 2 .. 79 .. ..

59 Trinidad and Tobago 24.1 33.5 18,108 2.1 6.1 .. .. 49 0.0 .. .. ..

60 Serbia 50.1 77.6 6,811 –0.7 16.6 .. 4,058 .. .. .. .. ..

61 Belarus 60.3 118.8 6,230 1.2 20.2 46 5,491 1 .. 81 .. ..

62 Costa Rica 29.7 50.7 6,564 1.9 11.3 72 .. 11 0.0 65 .. ..

63 Peru 129.1 245.2 4,477 1.1 2.3 6 2,020 230 22.5 .. .. ..

64 Albania 12.3 22.9 3,911 2.2 2.9 .. 423 .. .. .. 98 95

65 Russian Federation 1,679.5 2,258.5 11,832 –0.8 12.6 5 84,158 2,400 .. 92 .. ..

.. .. .. ..

66 Kazakhstan 133.4 177.4 8,513 0.2 8.3 3 14,205 16

67 Azerbaijan 46.1 76.1 5,315 1.1 10.0 68 2,099 12 .. .. 100 100

68 Bosnia and Herzegovina 18.5 30.5 4,906 10.9 .. 43 1,016 .. .. .. .. ..

69 Ukraine 180.4 336.4 3,899 –1.9 9.8 28 21,676 63 .. 131 48 62

70 Iran, Islamic Republic of .. .. .. 0.2 15.0 10 7,335 97 1.6 .. .. ..

71 The former Yugoslav Republic of Macedonia 9.5 19.1 4,664 1.3 2.3 54 699 .. .. 89 .. ..

72 Mauritius 9.3 15.7 7,345 4.0 6.3 99 .. 191 0.0 77 100 100

73 Brazil 1,575.2 1,976.6 8,205 2.2 7.3 20 29,817 1,807 2.2 36 90 90

74 Georgia 12.8 21.4 2,970 0.3 7.1 29 1,513 .. .. 4 90 90

75 Venezuela, Bolivarian Republic of 314.2 357.8 11,246 0.1 20.6 .. 336 2 1.1 93 .. ..

76 Armenia 11.9 18.7 3,873 0.7 3.8 25 845 .. .. 8 .. ..

77 Ecuador 54.7 108.0 4,056 2.2 7.0 15 .. 5 8.2 .. .. ..

78 Belize 1.4 2.2 4,218 2.1 3.2 .. .. .. .. .. .. ..

79 Colombia 243.8 395.7 5,416 2.0 5.9 15 1,663 1,100 6.7 23 .. 91

80 Jamaica 14.6 20.7 5,438 0.3 11.4 201 .. .. 7.4 .. .. ..

81 Tunisia 40.3 82.1 3,903 3.1 3.2 12 2,218 .. 1.0 .. .. ..

82 Jordan 21.2 32.3 3,596 1.6 4.2 9 251 141 0.0 .. 100 97

83 Turkey 734.9 991.7 9,942 2.4 18.6 55 8,699 481 .. .. .. ..

84 Algeria 166.5 276.0 4,845 1.1 2.8 5 3,572 17 0.6 .. .. ..

85 Tonga 0.3 0.4 2,687 2.7 9.1 .. .. .. .. .. .. ..

## MEDIUM HUMAN DEVELOPMENT

86 Fiji 3.6 3.7 4,253 1.5 3.3 .. .. 96 .. 53 .. ..

87 Turkmenistan 15.3 33.4 3,039 0.3 .. .. 3,181 11 .. 9 .. ..

88 Dominican Republic 45.5 80.8 4,576 3.0 16.0 .. .. .. 4.0 39 70 .. table

89 China 4,327.0 7,903.2 3,267 7.9 2.2 36 60,809 11,386 0.6 74 94 96 16

90 El Salvador 22.1 41.7 3,605 1.1 3.9 .. .. 18 14.7 38 .. ..

91 Sri Lanka 40.6 91.9 2,013 3.4 11.0 .. 1,463 .. 23.4 .. .. ..

92 Thailand 272.4 544.5 4,043 4.4 3.0 35 4,429 2,289 0.6 .. .. ..

93 Gabon 14.5 21.1 10,037 0.5 1.5 3 810 68 62.1 .. .. .. 207

## STATISTICAL ANNEX

Enabling environment: economy and infrastructure

Economy Physical infrastructure Media infrastructure

Population

transport

Consumer Road Rail electricity newspapers coverage coverage

(freight)

GDP GDP per capita price index density lines

Average

Average per sq. km of (million tonnes (% of (per thousand (% of (% of

annual

annual growth

## (PPP

HDI rank land area) (km) per km) population) people) population) population)

change (%)

rate (%)

($billions)$ billions) ($) a a a 2008 2008 2008 1970–2008 2000–2008 2004–2007 2004–2008 2005–2008 2008 2004 2005 2005 94 Suriname 3.0 3.8 5,888 0.9 14.3 .. .. 28 .. .. .. .. 95 Bolivia, Plurinational State of 16.7 41.4 1,720 0.9 4.9 6 2,866 9 22.7 .. .. .. 96 Paraguay 16.0 29.3 2,561 1.5 8.7 .. .. 0 4.8 .. .. .. 97 Philippines 166.9 317.1 1,847 1.4 5.5 .. 479 277 13.8 79 .. .. 98 Botswana 13.4 26.1 6,982 5.9 8.7 4 888 0 52.1 41 .. .. 99 Moldova, Republic of 6.0 10.6 1,694 0.2 11.3 38 1,156 .. .. .. .. .. 100 Mongolia 5.3 9.4 1,991 2.3 8.1 .. 1,810 6 34.1 20 95 67 101 Egypt 162.3 442.0 1,991 2.5 7.2 9 5,063 195 0.6 .. 94 92 102 Uzbekistan 27.9 72.5 1,023 –0.4 .. .. 4,230 72 .. .. .. .. 103 Micronesia, Federated States of 0.3 0.3 2,334 1.1 .. .. .. .. .. .. .. .. 104 Guyana 1.2 2.3 1,513 1.6 6.6 .. .. .. .. .. .. .. 105 Namibia 8.8 13.6 4,149 0.5 5.4 .. .. 0 65.7 28 .. .. 106 Honduras 13.3 28.8 1,823 1.4 7.9 .. .. .. 28.7 .. .. .. 107 Maldives 1.3 1.7 4,135 5.0 .. .. .. .. .. .. .. .. 108 Indonesia 510.7 907.3 2,246 4.3 9.3 20 3,370 395 35.7 .. .. .. 109 Kyrgyzstan 5.1 11.6 958 –1.4 6.1 .. 417 2 .. 1 .. .. 110 South Africa 276.4 492.2 5,678 0.6 4.3 .. 24,487 761 24.2 30 .. .. 111 Syrian Arab Republic 55.2 94.2 2,682 2.2 5.9 21 2,139 14 7.1 .. 88 95 112 Tajikistan 5.1 13.0 751 –2.5 13.0 .. 616 5 .. .. .. .. 113 Viet Nam 90.6 240.1 1,051 4.2 7.1 49 3,147 296 10.9 .. .. .. 114 Morocco 88.9 136.8 2,769 2.4 1.9 13 1,989 55 2.8 .. .. .. 115 Nicaragua 6.6 15.2 1,163 –0.2 8.6 14 .. .. 28.2 .. .. .. 116 Guatemala 39.0 65.1 2,848 1.2 7.5 .. .. .. 19.7 .. .. .. .. .. .. 117 Equatorial Guinea 18.5 22.3 28,103 8.5 5.6 .. .. .. .. 118 Cape Verde 1.6 1.6 3,193 2.3 2.1 .. .. 2 .. .. 90 70 119 India 1,159.2 3,356.3 1,017 3.6 4.8 1,001 63,327 1,234 34.2 71 99 .. 120 Timor-Leste 0.5 0.9 453 1.0 5.2 .. .. .. 81.9 .. .. .. 121 Swaziland 2.8 5.7 2,429 3.7 6.9 .. 300 .. .. 24 .. .. 122 Lao People’s Democratic Republic 5.5 13.2 893 3.4 9.0 13 .. 3 43.5 3 .. .. 123 Solomon Islands 0.6 1.3 1,263 0.7 9.1 .. .. 1 .. 11 .. .. 124 Cambodia 10.4 28.4 711 1.9 5.6 22 650 1 76.9 .. .. 85 125 Pakistan 164.5 421.3 991 2.4 7.1 34 7,791 320 39.8 50 99 .. 126 Congo 10.7 14.3 2,966 2.0 3.1 5 795 .. 74.7 .. .. .. 127 São Tomé and Príncipe 0.2 0.3 1,090 0.7 .. .. .. 0 .. .. .. .. ## LOW HUMAN DEVELOPMENT 128 Kenya 30.4 60.1 783 0.5 10.7 11 1,917 295 84.6 .. .. .. 129 Bangladesh 79.6 213.5 497 1.8 6.7 .. 2,835 84 59.3 .. .. .. 130 Ghana 16.7 34.1 713 1.1 16.4 25 953 .. 47.1 .. .. .. 131 Cameroon 23.4 41.9 1,226 1.2 2.3 11 977 26 70.2 .. 65 50 132 Myanmar .. .. .. .. 23.7 4 .. 3 86.4 .. 90 .. 133 Yemen 26.6 55.3 1,160 2.2 11.7 14 .. 33 62.0 4 .. .. 134 Benin 6.7 12.8 771 0.6 3.0 17 758 .. 80.8 0 .. .. 135 Madagascar 9.5 20.1 495 –1.2 10.8 .. 854 12 85.8 .. .. .. 136 Mauritania 2.9 .. 889 0.6 7.5 1 728 0 .. .. 61 19 137 Papua New Guinea 8.2 14.3 1,253 1.8 5.9 .. .. 22 .. 9 .. .. 138 Nepal 12.6 31.8 438 1.7 5.5 12 .. 7 55.9 .. 70 .. 139 Togo 2.9 5.4 449 –0.4 2.7 .. .. .. 83.6 .. .. .. 140 Comoros 0.5 0.8 824 0.1 .. .. .. .. .. .. .. .. 141 Lesotho 1.6 3.2 791 2.8 7.8 .. .. .. 82.9 .. .. .. table 142 Nigeria 207.1 317.2 1,370 1.0 12.9 21 3,528 10 53.3 .. .. .. 16 143 Uganda 14.3 36.9 453 0.9 6.0 .. 259 .. 91.9 .. 80 40 144 Senegal 13.3 21.9 1,087 0.2 2.2 .. .. 0 60.6 9 .. .. 145 Haiti 7.2 11.1 729 –0.6 18.0 .. .. .. 60.8 .. 60 80 4,714 1.4 47.0 .. .. 71 71.6 2 .. .. 146 Angola 84.9 104.8 208 human development report 2010 Enabling environment: economy and infrastructure Economy Physical infrastructure Media infrastructure Population Air without Daily Radio Television transport Consumer Road Rail electricity newspapers coverage coverage (freight) GDP GDP per capita price index density lines (km of road Average Average per sq. km of (million tonnes (% of (per thousand (% of (% of annual annual growth ## (PPP HDI rank land area) (km) per km) population) people) population) population) change (%) rate (%) ($ billions) $billions) ($) a a a

2008 2008 2008 1970–2008 2000–2008 2004–2007 2004–2008 2005–2008 2008 2004 2005 2005

147 Djibouti 0.9 1.8 1,030 –2.1 .. .. 781 .. .. .. .. ..

148 Tanzania, United Republic of 20.5 53.7 496 0.9 6.0 .. 2,600 1 86.6 2 80 20

149 Côte d’Ivoire 23.4 34.0 1,137 –1.1 3.0 25 639 .. 50.5 .. .. ..

150 Zambia 14.3 17.1 1,134 –1.1 16.6 .. 1,273 0 78.4 5 .. ..

151 Gambia 0.8 2.3 489 0.4 8.1 33 .. .. .. .. 100 75

152 Rwanda 4.5 10.0 458 1.2 8.5 57 .. .. .. .. 100 ..

153 Malawi 4.3 11.9 288 1.9 12.7 .. 797 2 87.6 .. .. ..

154 Sudan 55.9 89.0 1,353 1.9 8.2 .. 4,578 47 65.3 .. 100 ..

155 Afghanistan 10.6 32.0 366 1.9 12.9 6 .. .. 85.6 .. .. ..

156 Guinea 3.8 10.4 386 0.7 .. .. .. .. .. .. .. ..

157 Ethiopia 25.6 70.1 317 1.3 11.1 3 .. 228 85.1 5 .. ..

158 Sierra Leone 2.0 4.3 352 0.2 .. .. .. .. .. .. .. ..

159 Central African Republic 2.0 3.2 458 –0.8 3.0 .. .. .. .. .. .. ..

160 Mali 8.7 14.3 688 1.4 2.2 1 .. .. .. .. .. ..

161 Burkina Faso 7.9 17.7 522 2.0 2.9 34 622 0 90.6 .. .. ..

162 Liberia 0.8 1.5 222 –2.0 .. .. .. .. .. .. .. ..

163 Chad 8.4 14.6 770 0.9 2.2 3 .. .. .. .. .. ..

164 Guinea-Bissau 0.4 0.8 273 1.7 2.3 .. .. .. .. .. .. ..

165 Mozambique 9.8 18.7 440 2.2 11.5 .. 3,116 7 86.2 3 .. ..

166 Burundi 1.2 3.1 144 –0.3 8.5 48 .. .. .. .. .. ..

167 Niger 5.4 10.0 364 –1.3 2.4 1 .. .. .. 0 100 ..

168 Congo, Democratic Republic of the 11.7 20.2 182 –3.0 26.9 .. 4,007 .. 88.7 .. 75 90

169 Zimbabwe .. .. .. –0.5 497.7 .. 2,583 7 62.6 .. .. ..

## OTHER COUNTRIES OR TERRITORIES

Antigua and Barbuda 1.2 1.8 14,048 3.7 .. .. .. .. .. .. .. ..

Bhutan 1.3 3.3 1,869 4.5 4.4 .. .. .. .. .. 100 20

Cuba .. .. .. .. .. .. 5,076 32 2.7 65 .. 98

Dominica 0.4 0.6 4,883 3.4 2.1 .. .. .. .. .. .. ..

Eritrea 1.7 3.2 336 0.9 .. .. .. .. 69.0 .. .. ..

Grenada 0.6 0.9 6,162 3.8 3.1 .. .. .. .. .. .. ..

Iraq .. .. .. .. .. .. 2,032 .. 14.0 .. .. ..

Kiribati 0.1 0.2 1,414 0.1 .. .. .. .. .. .. .. ..

Korea, Democratic People’s Rep. of .. .. .. .. .. 21 .. .. 74.3 .. .. ..

Lebanon 29.3 49.4 6,978 4.0 .. 67 .. .. 0.0 54 .. ..

Marshall Islands 0.2 .. 2,655 –0.1 .. .. .. 0 .. 0 .. ..

Monaco .. .. .. .. .. 3,850 .. .. .. .. .. ..

Occupied Palestinian Territories .. .. .. .. 3.9 .. .. .. .. 10 .. ..

Oman .. .. .. 3.4 2.3 16 .. .. 3.6 .. 100 100

Palau 0.2 .. 8,911 –0.1 .. .. .. .. .. .. .. ..

Saint Kitts and Nevis 0.5 0.8 11,046 3.7 3.8 .. .. .. .. .. .. ..

Saint Lucia 1.0 1.7 5,854 3.0 2.5 .. .. .. .. .. 98 ..

Saint Vincent and the Grenadines 0.6 1.0 5,480 3.9 3.2 .. .. .. .. .. 95 100

Samoa 0.5 0.8 2,926 1.4 6.1 .. .. 2 .. .. .. ..

San Marino .. .. .. .. 2.3 .. .. .. .. .. 100 100

Seychelles 0.8 1.9 9,580 3.2 4.4 .. .. 27 .. .. .. ..

Somalia .. .. .. –1.4 .. .. .. .. .. .. .. ..

Vanuatu 0.6 0.9 2,521 1.6 2.4 .. .. .. .. 14 .. .. table

16

209

## STATISTICAL ANNEX

Enabling environment: economy and infrastructure

Economy Physical infrastructure Media infrastructure

Population

transport

Consumer Road Rail electricity newspapers coverage coverage

(freight)

GDP GDP per capita price index density lines

Average

Average per sq. km of (million tonnes (% of (per thousand (% of (% of

annual

annual growth

## (PPP

HDI rank land area) (km) per km) population) people) population) population)

change (%)

rate (%)

($billions)$ billions) ($) a a a 2008 2008 2008 1970–2008 2000–2008 2004–2007 2004–2008 2005–2008 2008 2004 2005 2005 Developed OECD 41,979.1 37,872.1 40,976 2.4 .. 3,838 516,479 92,753 .. 254 .. .. Non-OECD .. .. .. 2.2 .. 6,060 .. .. .. .. .. .. Developing Arab States 1,357.1 1,951.6 4,774 –1.1 .. .. .. .. 15.2 .. .. .. East Asia and the Pacific 5,625.7 10,369.7 3,032 1.7 .. .. .. .. .. .. .. .. Europe and Central Asia 3,414.5 4,852.7 8,361 0.1 .. .. 176,175 .. .. .. .. .. Latin America and the Caribbean 4,202.9 5,963.9 7,567 2.0 .. .. .. .. .. .. .. .. South Asia 1,469.6 4,151.8 954 3.8 .. .. .. .. 36.9 .. .. .. Sub-Saharan Africa 928.5 1,595.1 1,233 2.7 .. .. .. .. .. .. .. .. Very high human development 42,652.4 38,697.1 40,748 2.3 .. 6,048 518,300 .. .. 254 .. .. High human development 8,552.4 11,832.1 8,937 1.1 .. 1,332 289,531 .. .. .. .. .. Medium human development 7,635.8 15,560.3 2,200 2.7 .. .. .. 17,542 .. .. .. .. Low human development 771.2 1,425.9 781 –0.4 .. .. .. .. .. .. .. .. Least developed countries 503.2 1,000.8 664 2.0 .. .. .. .. .. .. .. .. World 60,042.1 68,323.9 9,120 2.1 .. .. .. .. .. .. .. .. Note a Data refer to the most recent year available during the period specified. Sources Columns 1–3 and 6–8: World Bank (2010g). Column 4: Calculated based on data from World Bank (2010g) and IMF (2010a). Column 5: Calculated based on data on the consumer price index from World Bank (2010g). Column 9: Calculated based on data on population without electricity from IEA (2009) and data on population from UNDESA (2009d). Columns 10–12: UNESCO Institute for Statistics (2010b). table 16 210 human development report 2010 17 Access to information and e l communication technology b ta Telephones Internet Accessibility and cost Price of a Fixed-line Population 3-minute phone covered by Mobile phone local fixed-line connection mobile phone connection Mobile and fixed-line Personal Broadband a phone call charge network charge phone subscriptions computers Users subscriptions (per (% growth, (per (% growth, (per (per HDI rank 100 people) population-based) (%) 100 people) population-based) 100 people) 100 people) ($) ($) (US cents) b b b b 2008 2000–2008 2008 2008 2000–2008 2008 2006–2008 2006–2008 2006–2008 2006–2008 ## VERY HIGH HUMAN DEVELOPMENT 1 Norway 150 27 .. 82.5 228 33.3 62.7 17.6 175.5 22 2 Australia 147 66 99 70.8 66 24.4 .. 24.3 49.5 25 c 3 New Zealand 149 87 97 71.4 64 21.6 53.0 24.6 36.6 0 4 United States 140 41 100 75.9 87 23.5 78.7 0.0 39.0 24 5 Ireland 171 77 99 62.7 310 20.1 58.1 14.5 178.5 11 6 Liechtenstein 150 78 95 66.0 96 55.0 .. 33.1 35.5 15 7 Netherlands 170 36 98 87.0 106 35.1 90.9 14.6 69.6 10 c 8 Canada 121 37 98 75.3 94 29.6 94.4 0.0 92.8 0 9 Sweden 176 34 98 87.7 100 41.2 87.8 15.2 102.4 8 10 Germany 191 60 99 75.5 151 27.5 65.5 14.6 87.8 12 11 Japan 124 23 100 75.2 152 23.7 .. 0.0 373.8 .. 12 Korea, Republic of 138 27 94 75.8 94 32.1 58.1 0.0 54.4 0 13 Switzerland 180 37 100 75.9 66 34.2 97.6 45.2 39.7 23 14 France 149 46 99 67.9 396 28.5 65.2 22.0 80.5 20 15 Israel 167 65 100 47.9 175 23.9 .. 57.6 56.3 .. 16 Finland 160 29 100 82.5 127 30.5 .. 26.2 142.9 22 17 Iceland 169 30 99 90.0 127 32.9 53.1 28.4 33.0 7 18 Belgium 152 52 100 68.1 142 28.0 .. 12.5 96.6 24 19 Denmark 170 29 114 83.3 118 37.1 55.1 19.4 186.3 14 20 Spain 153 65 99 55.4 349 20.2 40.0 0.0 117.6 10 c 21 Hong Kong, China (SAR) 225 67 100 67.0 152 28.1 69.3 .. 0.0 0 22 Greece 176 69 100 43.1 379 13.5 9.4 7.3 51.1 13 23 Italy 186 60 100 41.8 88 18.9 .. 13.2 140.6 16 24 Luxembourg 198 72 100 79.2 280 29.8 67.7 0.0 84.2 10 25 Austria 169 40 99 71.2 120 20.7 .. 0.0 244.5 14 26 United Kingdom 180 40 100 76.0 195 28.2 80.2 0.0 229.8 13 27 Singapore 170 68 100 69.6 148 21.7 76.0 5.0 37.8 2 28 Czech Republic 154 94 100 57.8 500 17.1 .. 0.0 34.8 20 21.2 42.7 25.4 130.9 12 29 Slovenia 152 53 100 55.7 275 30 Andorra .. .. 99 70.5 .. 24.5 .. .. 52.8 .. 31 Slovakia 122 125 100 66.0 604 11.2 58.2 14.0 55.7 48 32 United Arab Emirates 242 344 100 65.2 282 12.4 33.1 44.9 49.0 3 33 Malta 152 95 100 48.3 287 24.8 .. 0.0 34.6 3 34 Estonia 225 180 100 66.2 127 23.7 25.5 4.7 0.0 13 35 Cyprus 163 113 100 38.8 179 16.4 38.3 37.5 147.1 7 36 Hungary 153 122 99 58.5 719 17.5 25.6 7.5 196.1 26 37 Brunei Darussalam 115 158 .. 55.3 623 3.6 .. .. 35.3 6 38 Qatar 152 593 100 34.0 1,353 8.1 15.7 54.9 54.9 .. 39 Bahrain 214 341 100 51.9 907 14.2 74.6 16.0 53.2 5 40 Portugal 179 74 99 42.1 168 15.3 18.2 .. 126.2 18 41 Poland 141 203 99 49.0 567 12.6 16.9 2.1 96.7 19 c 42 Barbados 218 265 100 73.7 1,780 64.8 .. 25.0 49.0 0 211 ## STATISTICAL ANNEX Access to information and communication technology Telephones Internet Accessibility and cost Price of a Fixed-line Population 3-minute phone covered by Mobile phone local fixed-line connection mobile phone connection Mobile and fixed-line Personal Broadband a phone call charge network charge phone subscriptions computers Users subscriptions (per (% growth, (per (% growth, (per (per HDI rank 100 people) population-based) (%) 100 people) population-based) 100 people) 100 people) ($) ($) (US cents) b b b b 2008 2000–2008 2008 2008 2000–2008 2008 2006–2008 2006–2008 2006–2008 2006–2008 ## HIGH HUMAN DEVELOPMENT 43 Bahamas 145 236 100 31.5 711 10.1 .. 50.0 .. .. 44 Lithuania 173 235 100 54.4 703 17.8 24.5 2.1 106.1 15 45 Chile 109 173 100 32.5 113 8.5 .. 1.9 92.1 9 46 Argentina 141 291 94 28.1 331 8.0 .. 48.4 47.7 2 c 47 Kuwait 126 284 100 36.7 601 1.4 .. 17.3 130.1 0 48 Latvia 127 152 99 60.4 809 8.9 32.8 2.0 .. 14 49 Montenegro 176 .. 99 47.2 .. 10.0 .. 7.3 .. 100 50 Romania 137 364 98 28.8 679 11.7 19.3 5.6 0.0 23 51 Croatia 175 176 100 50.5 632 11.9 .. 20.3 123.6 13 52 Uruguay 134 233 100 40.2 282 7.3 .. 46.1 52.1 10 53 Libyan Arab Jamahiriya 93 809 71 5.1 3,130 0.2 .. 3.8 38.1 .. 54 Panama 131 429 83 27.5 383 5.8 2.8 30.0 30.6 9 55 Saudi Arabia 163 837 98 31.5 1,612 4.2 68.3 26.7 80.0 4 56 Mexico 90 265 100 22.2 368 7.0 14.1 0.0 116.8 15 57 Malaysia 118 228 92 55.8 203 4.9 23.1 2.5 15.0 4 58 Bulgaria 166 252 100 34.7 517 11.1 11.0 .. 18.0 12 59 Trinidad and Tobago 136 279 100 17.0 127 4.6 13.2 0.0 23.9 12 60 Serbia 173 .. 93 44.9 .. 4.6 19.3 3.6 89.7 1 61 Belarus 122 321 99 32.1 1,553 4.9 .. 1.5 28.2 1 62 Costa Rica 74 199 69 32.3 540 2.4 .. 5.5 39.7 2 63 Peru 83 697 95 24.7 791 2.5 .. 13.7 122.1 5 64 Albania .. .. 99 23.9 21,329 2.0 4.6 0.0 143.0 4 65 Russian Federation 172 587 95 31.9 1,450 6.6 13.3 9.6 281.7 3 66 Kazakhstan 117 791 94 10.9 1,582 4.3 .. 5.7 117.3 1 c 67 Azerbaijan 91 541 99 28.2 20,206 0.7 8.0 4.9 97.3 0 68 Bosnia and Herzegovina 112 382 99 34.7 3,169 5.0 6.4 11.2 52.6 7 69 Ukraine 149 513 100 10.5 1,294 3.5 4.6 22.9 31.6 3 70 Iran, Islamic Republic of 94 532 95 32.0 3,483 0.4 10.4 30.8 106.1 1 36.8 14.3 34.9 7 71 The former Yugoslav Republic of Macedonia 145 375 100 41.5 1,596 8.9 72 Mauritius 110 204 99 22.2 225 7.2 17.4 3.5 40.4 8 73 Brazil 100 254 91 37.5 1,341 5.3 .. 18.7 62.7 15 74 Georgia 78 379 98 23.8 4,352 2.2 27.2 6.7 120.7 24 75 Venezuela, Bolivarian Republic of 120 319 90 25.7 776 4.7 .. 2.3 31.0 9 76 Armenia 120 572 88 6.2 378 0.2 .. 3.3 39.2 5 77 Ecuador 100 688 84 28.8 2,057 0.3 13.0 5.0 67.2 3 78 Belize 59 237 .. 10.6 110 2.6 15.3 25.0 50.0 11 79 Colombia 110 423 83 38.5 1,874 4.2 11.2 0.0 36.6 13 80 Jamaica 113 259 101 57.3 1,856 3.6 .. 0.0 9.1 3 81 Tunisia 95 813 100 27.1 973 2.2 9.8 4.1 16.2 2 82 Jordan 99 494 99 27.0 1,187 2.2 7.2 0.0 50.5 6 83 Turkey 113 141 100 34.4 916 7.8 .. 16.8 5.8 13 84 Algeria .. .. 82 11.9 2,633 1.4 .. 7.7 46.5 7 85 Tonga 73 669 90 8.1 250 0.7 .. 8.5 61.8 9 ## MEDIUM HUMAN DEVELOPMENT 86 Fiji 86 415 65 12.2 758 1.9 .. 6.2 57.7 8 87 Turkmenistan 32 334 14 1.5 1,150 0.1 .. .. .. .. 88 Dominican Republic 82 412 .. 21.6 556 2.3 .. 0.7 28.9 10 89 China 74 329 97 22.5 1,233 6.2 5.6 9.9 .. 3 90 El Salvador 131 486 95 10.6 829 2.0 .. 0.0 40.0 6 91 Sri Lanka 72 1,104 95 5.8 850 0.5 .. 5.5 129.2 5 92 Thailand 102 698 38 23.9 600 1.4 .. 1.5 119.6 9 table 93 Gabon 92 734 79 6.2 500 0.2 3.4 .. 104.1 15 17 94 Suriname 97 328 .. 9.7 327 1.1 .. 0.0 .. .. 95 Bolivia, Plurinational State of 57 405 46 10.8 775 0.7 .. 0.0 41.4 7 212 human development report 2010 Access to information and communication technology Telephones Internet Accessibility and cost Price of a Fixed-line Population 3-minute phone covered by Mobile phone local fixed-line connection mobile phone connection Mobile and fixed-line Personal Broadband a phone call charge network charge phone subscriptions computers Users subscriptions (per (% growth, (per (% growth, (per (per HDI rank 100 people) population-based) (%) 100 people) population-based) 100 people) 100 people) ($) ($) (US cents) b b b b 2008 2000–2008 2008 2008 2000–2008 2008 2006–2008 2006–2008 2006–2008 2006–2008 96 Paraguay 103 484 .. 14.3 2,136 1.4 .. .. 80.2 7 c 97 Philippines 80 659 99 6.2 265 1.2 7.2 0.9 44.9 0 98 Botswana 85 355 99 6.2 140 0.5 6.2 2.9 37.1 17 99 Moldova, Republic of 97 389 98 23.4 1,516 3.2 11.4 4.3 173.2 3 100 Mongolia 74 622 66 12.5 1,000 1.4 24.6 .. 43.8 .. 101 Egypt 65 678 95 16.6 2,916 0.9 3.9 4.0 74.0 2 102 Uzbekistan 53 746 93 9.0 1,938 0.2 3.1 7.0 12.0 .. c 103 Micronesia, Federated States of 39 343 .. 14.5 300 0.1 .. 50.0 24.0 0 104 Guyana .. .. .. 26.9 .. 0.3 .. 22.1 2.5 0 105 Namibia 56 520 95 5.3 278 0.0 23.9 5.9 35.5 18 106 Honduras 96 1,450 90 13.1 1,177 .. 2.5 5.0 25.8 8 107 Maldives 158 1,405 100 23.5 1,096 5.2 20.2 7.7 134.4 6 108 Indonesia 75 1,555 90 7.9 847 0.2 2.0 .. .. 3 109 Kyrgyzstan 74 927 24 16.1 1,576 0.1 .. 10.0 79.7 8 110 South Africa 102 272 100 8.6 75 0.9 .. 18.0 51.5 18 111 Syrian Arab Republic 52 547 96 17.3 12,156 0.1 8.8 5.7 28.7 .. 112 Tajikistan 58 1,703 .. 8.8 19,900 0.1 .. 3.7 .. .. 113 Viet Nam 116 2,881 70 24.2 10,286 2.4 9.5 3.1 25.0 2 114 Morocco 82 585 98 33.0 5,121 1.5 5.7 2.6 77.4 26 115 Nicaragua 60 1,242 .. 3.3 270 0.6 .. .. 101.8 4 116 Guatemala 120 969 76 14.3 2,350 0.6 .. 13.3 82.7 9 117 Equatorial Guinea 54 3,107 .. 1.8 1,614 0.0 .. .. .. .. 118 Cape Verde 70 370 96 20.6 1,185 1.5 14.0 26.6 29.1 6 119 India 34 979 61 4.5 850 0.5 3.2 2.3 6.9 2 120 Timor-Leste .. .. .. .. .. 0.0 .. 20.0 36.2 31 121 Swaziland 49 788 91 6.9 700 0.1 3.7 11.5 25.8 5 122 Lao People’s Democratic Republic 35 3,914 .. 8.5 8,691 0.1 .. 5.2 36.4 7 123 Solomon Islands 7 330 .. 2.0 400 0.3 .. 36.2 .. .. 10.1 50.6 3 124 Cambodia 29 2,551 87 0.5 1,133 0.1 0.4 125 Pakistan 56 2,632 90 11.1 .. 0.1 .. 7.1 10.7 3 126 Congo 51 1,888 53 4.3 19,275 .. .. .. .. .. 127 São Tomé and Príncipe 35 1,129 20 15.5 282 0.5 .. .. 29.5 11 ## LOW HUMAN DEVELOPMENT 128 Kenya 43 3,848 83 8.7 3,260 0.0 .. 34.7 33.2 12 129 Bangladesh 29 5,870 90 0.3 456 0.0 2.3 2.2 29.2 1 130 Ghana 50 3,319 73 4.3 3,223 0.1 1.1 7.0 42.8 16 131 Cameroon 33 3,107 58 3.8 1,712 .. .. 5.6 89.3 25 132 Myanmar 2 314 10 0.2 .. 0.0 0.9 .. .. .. 133 Yemen 21 1,172 68 1.6 2,367 .. 2.8 6.0 85.1 1 134 Benin 41 3,255 80 1.8 967 0.0 0.7 5.6 215.7 3 135 Madagascar 26 4,134 23 1.7 954 0.0 .. 2.0 34.5 35 136 Mauritania 67 6,227 62 1.9 1,100 0.2 4.5 11.1 18.5 22 137 Papua New Guinea 10 799 .. 1.8 167 .. .. 0.0 3.7 4 138 Nepal 17 1,706 10 1.7 898 0.0 .. 7.2 25.8 1 139 Togo 26 1,722 85 5.4 250 0.0 .. 3.3 111.7 14 140 Comoros 19 1,706 40 3.6 1,441 .. .. 0.0 120.6 15 141 Lesotho 32 1,375 55 3.6 1,733 0.0 .. 6.1 40.8 18 142 Nigeria 43 10,921 83 15.9 29,878 0.0 .. 84.4 75.9 14 143 Uganda 28 4,526 100 7.9 6,150 0.0 1.7 4.1 69.7 21 144 Senegal 46 1,134 85 8.4 2,450 0.4 .. 5.6 22.3 22 16 145 Haiti 33 2,495 .. 10.1 4,900 .. 5.1 .. .. .. 146 Angola 38 7,493 40 3.1 3,567 0.1 0.6 .. 60.0 27 147 Djibouti 15 1,186 85 2.3 1,253 0.3 3.8 28.1 56.2 8 table 148 Tanzania, United Republic of 31 4,522 65 1.2 1,200 0.0 .. 5.8 16.7 22 17 149 Côte d’Ivoire 52 1,367 59 3.2 1,550 0.1 .. 19.1 22.3 20 150 Zambia 29 1,892 50 5.5 3,400 0.0 .. .. 13.3 70 213 ## STATISTICAL ANNEX Access to information and communication technology Telephones Internet Accessibility and cost Price of a Fixed-line Population 3-minute phone covered by Mobile phone local fixed-line connection mobile phone connection Mobile and fixed-line Personal Broadband a phone call charge network charge phone subscriptions computers Users subscriptions (per (% growth, (per (% growth, (per (per HDI rank 100 people) population-based) (%) 100 people) population-based) 100 people) 100 people) ($) ($) (US cents) b b b b 2008 2000–2008 2008 2008 2000–2008 2008 2006–2008 2006–2008 2006–2008 2006–2008 151 Gambia 73 3,023 85 6.9 852 0.0 3.5 .. 28.0 7 152 Rwanda 14 2,268 92 3.1 5,900 0.0 0.3 3.2 46.5 18 153 Malawi 13 1,949 93 2.1 2,007 0.0 .. 3.1 .. 7 154 Sudan 30 2,916 66 10.2 46,567 0.1 10.7 2.4 0.0 6 155 Afghanistan .. .. 75 1.7 .. .. 0.4 24.8 31.4 41 156 Guinea 39 5,713 80 0.9 1,025 .. .. .. 36.9 .. 157 Ethiopia 4 1,042 10 0.4 3,500 .. 0.7 47.7 31.8 2 158 Sierra Leone 19 3,264 70 0.3 178 .. .. .. .. .. 159 Central African Republic 4 1,050 19 0.4 850 .. .. 2.2 79.1 13 160 Mali 28 6,994 22 1.6 1,233 0.0 0.8 2.2 86.3 12 161 Burkina Faso 18 3,337 61 0.9 1,456 0.0 0.6 6.7 55.8 14 162 Liberia 19 8,851 .. 0.5 3,900 .. .. .. .. .. 163 Chad 17 11,460 24 1.2 4,233 .. .. .. 101.6 .. 164 Guinea-Bissau 32 4,438 65 2.4 1,137 .. .. .. .. .. 165 Mozambique 20 3,178 44 1.6 1,650 0.1 .. 0.2 18.8 26 166 Burundi 6 1,307 80 0.8 1,200 .. 0.9 2.9 9.7 .. 167 Niger 13 8,801 45 0.5 1,900 .. .. 11.2 33.5 17 168 Congo, Democratic Republic of the .. .. .. .. .. .. .. .. .. .. 169 Zimbabwe 16 288 75 11.4 2,742 0.1 7.6 .. .. .. ## OTHER COUNTRIES OR TERRITORIES Antigua and Barbuda 202 190 100 75.0 1,200 14.5 20.7 .. 68.5 .. Bhutan 41 1,869 21 6.6 1,900 0.3 2.5 1.7 13.8 3 Cuba 13 190 77 12.9 2,317 0.0 5.6 120.0 .. .. Dominica 161 370 .. 37.6 338 15.4 .. .. 55.6 7 Eritrea 3 388 80 4.1 3,900 .. 1.0 91.1 65.0 4 Grenada 86 148 .. 23.2 484 9.8 .. 13.0 85.2 6 Iraq 61 2,652 72 1.0 .. .. .. .. 159.4 1 Kiribati 5 37 .. 2.1 33 .. .. .. .. .. Korea, Democratic People’s Rep. of 5 136 0 0.0 .. .. .. .. .. 3 Lebanon 52 65 100 22.5 215 5.0 10.2 47.0 29.9 8 .. .. .. Marshall Islands 9 21 .. 3.7 175 .. .. Monaco .. .. .. .. .. 41.9 .. .. .. .. Occupied Palestinian Territories 38 236 95 9.0 922 2.4 .. .. .. .. Oman 125 810 96 20.0 559 1.2 16.9 26.0 26.0 65 Palau 96 .. 95 .. .. 0.5 .. .. .. .. Saint Kitts and Nevis 204 334 .. 32.5 492 21.7 .. .. .. .. Saint Lucia 124 307 .. 58.8 1,142 9.1 .. 0.0 46.3 6 Saint Vincent and the Grenadines 140 461 100 60.5 1,786 8.6 .. 0.0 37.0 7 Samoa 85 1,287 .. 5.0 800 0.1 2.3 17.6 20.2 6 San Marino 146 .. 98 54.8 .. 15.7 79.0 .. 141.4 6 Seychelles 133 140 98 39.0 445 4.1 21.6 9.1 55.4 8 Somalia 8 592 .. 1.1 580 .. .. .. .. .. Tuvalu .. .. .. .. .. 4.6 .. .. 75.3 .. Vanuatu 20 562 50 7.3 325 0.1 .. 45.2 88.8 30 Notes Sources a Column 1: Number of subscriptions to digital subscriber lines, cable modems or other fixed Calculated based on data on cellular subscribers and telephone lines from broadbands expressed per 100 people. Includes digital subscriber line/analog World Bank (2010c). Columns 2 and 5: subscriber line connections with speeds of 56 kilobits per second and higher. Calculated based on data on cellular subscribers and telephone b Data refer to the most recent year available during the period specified. lines from World Bank (2010c) and data on population from UNDESA (2009d). c Columns 3 and 6–10: Locals calls are free. ITU (2009). Column 4: World Bank (2010c). table 17 214 human development report 2010 Technical notes Calculating the human development indices—graphical presentation Human Development Long and healthy life Knowledge A decent standard of living ## DIMENSIONS Index (HDI) Expected years of schooling Mean years of schooling Life expectancy at birth INDICATORS GNI per capita (PPP US$)

Life expectancy index Education index GNI index

## DIMENSION

INDEX Human Development Index (HDI)

Inequality-adjusted Long and healthy life Knowledge A decent standard of living

## DIMENSIONS

Human Development

Index (IHDI) Expected years of schooling

Mean years of schooling

Life expectancy at birth

INDICATORS GNI per capita (PPP US$) Life expectancy Years of schooling Income/consumption ## DIMENSION ## INDEX INEQUALITY-ADJUSTED Inequality-adjusted Inequality-adjusted Inequality-adjusted life expectancy index education index income index INDEX Inequality-adjusted Human Development Index (IHDI) Gender Inequality Health Empowerment Labour market ## DIMENSIONS Index (GII) Female and male population with Female and male shares of Female and male labour force Maternal Adolescent INDICATORS at least secondary education parliamentary seats participation rates mortality ratio fertility rate Female labour market index Female reproductive health index Female empowerment index Male empowerment index Male labour market index ## DIMENSION INDEX Female gender index Male gender index Gender Inequality Index (GII) Multidimensional Health Education Standard of living ## DIMENSIONS Poverty Index (MPI) Water Electricity Floor Assets Years of schooling Children enrolled Cooking fuel Toilet Nutrition Child mortality ## INDICATORS POVERTY Intensity of poverty Headcount ratio MEASURES Multidimensional Poverty Index (MPI) 215 ## STATISTICAL ANNEX Technical note 1. Calculating the Human Development Index Goalposts for the Human Development Index The Human Development Index (HDI) is a summary measure in this Report of human development. It measures the average achievements in a country in three basic dimensions of human development: a Dimension Observed maximum Minimum long and healthy life, access to knowledge and a decent standard Life expectancy 83.2 20.0 (Japan, 2010) of living. The HDI is the geometric mean of normalized indices Mean years of schooling 13.2 0 measuring achievements in each dimension. (United States, 2000) Expected years of schooling 20.6 0 (Australia, 2002) Data sources 0 Combined education index 0.951 • Life expectancy at birth: UNDESA (2009d) (New Zealand, 2010) • Mean years of schooling: Barro and Lee (2010) Per capita income (PPP$) 108,211 163

(United Arab Emirates, 1980) (Zimbabwe, 2008)

• E xpected years of schooling: UNESCO Institute for Having defined the minimum and maximum values, the sub-

Statistics (2010a) indices are calculated as follows:

• Gross national income (GNI) per capita: World Bank

(2010g) and IMF (2010a) actual value – minimum value .(1)

Dimension index = maximum value – minimum value

Creating the dimension indices For education, equation 1 is applied to each of the two subcom-

The first step is to create subindices for each dimension. ponents, then a geometric mean of the resulting indices is cre-

Minimum and maximum values (goalposts) need to be set in ated and finally, equation 1 is reapplied to the geometric mean

order to transform the indicators into indices between 0 and of the indices, using 0 as the minimum and the highest geo-

1. Because the geometric mean is used for aggregation, the metric mean of the resulting indices for the time period under

maximum value does not affect the relative comparison (in consideration as the maximum. This is equivalent to applying

percentage terms) between any two countries or periods of equation 1 directly to the geometric mean of the two subcom-

time. The maximum values are set to the actual observed max- ponents. Because each dimension index is a proxy for capabili-

imum values of the indicators from the countries in the time ties in the corresponding dimension, the transformation func-

series, that is, 1980–2010. The minimum values will affect tion from income to capabilities is likely to be concave (Anand

comparisons, so values that can be appropriately conceived and Sen 2000c). Thus, for income the natural logarithm of the

of as subsistence values or “natural” zeros are used. Progress actual minimum and maximum values is used.

is thus measured against minimum levels that a society needs

to survive over time. The minimum values are set at 20 years Aggregating the subindices to produce the

for life expectancy, at 0 years for both education variables Human Development Index

and at $163 for per capita gross national income (GNI). The The HDI is the geometric mean of the three dimension indices: life expectancy minimum is based on long-run historical evi- 1 Societies dence from Maddison (2010) and Riley (2005). . . ## I I 1/3 1/3 1/3 ).(2) can subsist without formal education, justifying the educa- (I Life Education Income tion minimum. A basic level of income is necessary to ensure Expression 2 embodies imperfect substitutability across all survival:$163 is the lowest value attained by any country in HDI dimensions. It thus addresses one of the most serious

recorded history (in Zimbabwe in 2008) and corresponds to criticisms of the linear aggregation formula, which allowed for

less than 45 cents a day, just over a third of the World Bank’s perfect substitution across dimensions. Some substitutability is

$1.25 a day poverty line. inherent in the definition of any index that increases with the values of its components. Example: China Indicator Value Life expectancy at birth (years) 73.5 Mean years of schooling (years) 7.5 Expected years of schooling (years) 11.4 GNI per capita (PPP US$) 7,263

Values are rounded.

Note:

216 human development report 2010 73.5 – 20 T1.1 Human Development Index 2010:

Life expectancy index = = 0.847 E

## GUR

83.2 – 20 new and old methodologies

## F

7.5 – 0 = 0.568

Mean years of schooling index = 13.2 – 0 1.0 HDI

high

0.9

11.4 – 0 = 0.553

Expected years of schooling index = Very

20.6 – 0 0.8 High HDI

0.7 HDI

methodology Medium

0.6

.

0.568 0.553 – 0 = 0.589

Education index = 0.5

0.951 – 0 new

2010,

0.4 HDI

HDI Low

0.3

ln(7,263) – ln(163)

Income index = = 0.584 Very high

0.2

ln(108,211) – ln(163) Low HDI Medium HDI High HDI HDI

0.1

0.1 0.2 0.4 0.5 0.6 0.7 0.8

0.3 0.9 1.0

HDI 2010, old methodology

. .

3 HDRO calculations using data from the HDRO database.

Source:

0.847 0.589 0.584 = 0.663

Human Development Index =

Overall effects of the Human Development were present. When unavailable for the whole time period,

Index methodological improvements gross enrolment ratios were projected using the last available

The methodological improvements in the HDI, using new value (for forward projections) and the first available value (for

indicators and the new functional form, result in substantial backward projections). A sensitivity analysis showed that the

changes (figure T1.1). Adopting the geometric mean produces results of the analysis were robust to alternative extrapolation

lower index values, with the largest changes occurring in countries techniques. See Gidwitz and others (2010) for further details

with uneven development across dimensions. The geometric on the construction of this data set.

mean has only a moderate impact on HDI ranks. Setting the The analysis in chapters 2 and 3 also uses the deviation from

upper bounds at actual maximum values has less impact on fit criterion to comparatively evaluate changes over time in the

overall index values and has little further impact on ranks. hybrid HDI. This measure evaluates the progress of countries

compared with the average progress of countries with a simi-

Analysis of historical trends in this Report lar initial HDI level. It is calculated as the residual of a second

The analysis of historical trends in chapters 2 and 3 uses a dif- degree fractional polynomial regression of the annual percent-

ferent version of the HDI, the hybrid HDI, which applies the age growth rate of the HDI on the logarithm of its initial HDI

same aggregation formula as the new HDI to the set of indica- value. Statistical table 2 reports the country rank in the devia-

tors and sources used in previous Reports (since 1995) in order tion from fit for the HDI for 1980–2010. See Royston and Alt-

to allow more extensive analysis over time. Linear interpolation man (1994) for a description of regression models based on frac-

was used to fill missing values when both earlier and later values tional polynomial functions of a continuous covariate.

Technical note 2. Calculating the Inequality-adjusted Human Development Index

The Inequality-adjusted Human Development Index (IHDI) HDI as inequality rises. In this sense, the IHDI is the actual

adjusts the Human Development Index (HDI) for inequality in level of human development (accounting for this inequality),

distribution of each dimension across the population. It is based while the HDI can be viewed as an index of “potential” human

on a distribution-sensitive class of composite indices proposed development (or the maximum level of HDI) that could be

by Foster, Lopez-Calva, and Szekely (2005), which draws on the achieved if there was no inequality. The “loss” in potential human

Atkinson (1970) family of inequality measures. It is computed development due to inequality is given by the difference between

as a geometric mean of geometric means, calculated across the the HDI and the IHDI and can be expressed as a percentage.

population for each dimension separately (for details, see Alkire Data sources

and Foster 2010). The IHDI accounts for inequalities in HDI

dimensions by “discounting” each dimension’s average value Since the HDI relies on country-level aggregates such as national

according to its level of inequality. The IHDI equals the HDI accounts for income, the IHDI must draw on alternative

when there is no inequality across people but is less than the sources of data to obtain the distribution of each dimension. 217

## STATISTICAL ANNEX

The distributions have different units—income and years of The geometric mean in equation 1 does not allow zero

schooling are distributed across individuals, while expected values. For mean years of schooling one year is added to all

length of life is distributed across age intervals. Available valid observations to compute the inequality. Income per capita

distributional data are not necessarily for the same individuals outliers—extremely high incomes as well as negative and zero

or households. incomes—were dealt with by truncating the top 0.5 percentile

The inequality in distribution of the HDI dimensions is of the distribution to reduce the influence of extremely high

estimated for: incomes and by replacing the negative and zero incomes with the

• Life expectancy, which uses data from abridged life tables minimum value of the bottom 0.5 percentile of the distribution

provided by UNDESA (2009d). This distribution is of positive incomes.

available across age intervals (0–1, 1–5, 5–10, ... , 85+), For more details on measuring inequality in the distribution

with the mortality rates and average age at death specified of the HDI indicators, see Alkire and Foster (2010).

for each interval. Step 2. Adjusting the dimension indices for inequality

• Years of schooling and household income (or consumption), –

## X

The mean achievement in a dimension, , is adjusted for

which use household survey data harmonized in inequality as follows:

international databases: Luxembourg Income Study,

Eurostat’s European Union Survey of Income and Living – – n

## X X A X …X

* = (1 – ) =

Conditions, the World Bank’s International Income .

x n

1

Distribution Database, the United Nations Children’s –

## X

Thus *, the geometric mean of the distribution, reduces the

Fund’s Multiple Indicators Cluster Survey, the US Agency mean according to the inequality in distribution, emphasizing

for International Development’s Demographic and Health the lower end of the distribution.

Survey, the World Health Organization’s World Health I , are obtained

Survey and the United Nations University’s World Income I X

I , by multiplying them by

from the HDI dimension indices,

Inequality Database. X

## A

A ), where is the corresponding Atkinson measure:

(1 –

• The inequality in standard of living dimension, which x x

uses disposable household income per capita, household .

I A I .

= (1 – )

consumption per capita or income imputed based on an asset I x X

## X

index matching methodology (Harttgen and Klasen 2010). I* , is based on the

The inequality-adjusted income index, I Income I* . This

unlogged gross national income (GNI) index,

For a full account of data sources used for estimating inequality, Income

enables the IHDI to account for the full effect of income

see Kovacevic (2010a). inequality.

Development Index Step 3. Computing the Inequality-adjusted Human

There are three steps to computing the IHDI. Development Index

Step 1. Measuring inequality in underlying distributions The IHDI is the geometric mean of the three dimension indi-

The IHDI draws on the Atkinson (1970) family of inequality ces adjusted for inequality. First, the IHDI that includes the

2 In

measures and sets the aversion parameter ε equal to 1. unlogged income index (IHDI*) is calculated:

this case the inequality measure is A = 1– g/μ, where g is the . .

3 I I*

## I

IHDI* =

=

geometric mean and µ is the arithmetic mean of the distribution. I IEducation IIncome

Life

This can be written: . .

. . .

3 A A

## A I I I*

(1– (1–

(1– ) ) ) .

Life Life Education Education Income Income

n X …X

n

1

A = 1 – (1)

x X

## X

where {X , … , } denotes the underlying distribution in

n

1 A is obtained for each variable

the dimensions of interest. x

(life expectancy, years of schooling and disposable income or

consumption per capita) using household survey data and the

3

life tables.

218 human development report 2010

The HDI based on unlogged income index (HDI*) is then individuals, or groups of individuals, and across dimensions

## IHDI*

calculated. This is the value that would take if all yields the same result—so there is no need to rely on a particu-

achievements were distributed equally: lar sequence or a single data source. This allows estimation for a

large number of countries.

Although the IHDI is about human development losses

. .

3 I I*

## I

HDI* = .

Life Education Income from inequality, the measurement of inequality in any

dimension implicitly conflates inequity and inequality due

## HDI*

The percentage loss to the due to inequalities in each to chance, choice and circumstances. It does not address the

dimension is calculated as: ethical and policy-relevant issues around whether these aspects

should be distinguished (see Roemer 1998 and World Bank

IHDI* 2005b for applications in Latin America).

. .

3

Loss A A A

= 1 – (1– ) (1– ) (1– )

= 1– .

HDI* The main disadvantage of the IHDI is that it is not

Life Education Income association sensitive, so it does not capture overlapping

Assuming that the percentage loss due to inequality in income inequalities. To make the measure association sensitive, all the

distribution is the same for both average income and its data for each individual must be available from a single survey

logarithm, the IHDI is then calculated as: source, which is not currently possible.

IHDI* . HDI

IHDI = Example: Slovenia

HDI* Dimension Inequality

which is equivalent to Indicator index measure (A1) Inequality-adjusted index

Life expectancy 78.8 0.930 0.043 (1–0.043) ∙ 0.930 = 0.890

Mean years of schooling 9 0.682

Expected years of schooling 16.7 0.811

. . .

3

## IHDI A A A HDI

= (1– ) (1– ) (1– ) . Education index 0.782 0.040 (1–0.040) ∙ 0.782 = 0.751

Life Education Income Logarithm of GNI 10.16 0.780

GNI 25,857 0.238 0.122 (1–0.122) ∙ 0.238 = 0.209

Notes on methodology and limits

The IHDI is based on an index that satisfies subgroup con- Human Development Inequality-adjusted Human Percent

sistency. This ensures that improvements or deteriorations in Index Development Index loss

distribution of human development within a certain group of HDI with 1–0.519/0.557

society (while human development remains constant in the . .

. .

3 3

0.930 0.782 0.238 = 0.557 0.890 0.751 0.209 = 0.519

unlogged = 0.068

other groups) will be reflected in changes in the overall measure income .

. .

3

of human development. This index is also path independent, 0.930 0.782 0.780 = 0.828

HDI (0.519 / 0.557) 0.828 = 0.772

which means that the order in which data are aggregated across Values are rounded.

Note:

Technical note 3. Calculating the Gender Inequality Index

The Gender Inequality Index (GII) reflects women’s disadvantage aggregation is by the geometric mean across dimensions; these

in three dimensions—reproductive health, empowerment and means, calculated separately for women and men, are then

the labour market—for as many countries as data of reasonable aggregated using a harmonic mean across genders.

quality allow. The index shows the loss in human development Data sources

due to inequality between female and male achievements in

these dimensions. It ranges from 0, which indicates that women • Maternal mortality ratio (MMR): United Nations

and men fare equally, to 1, which indicates that women fare as Children’s Fund (2010c)

poorly as possible in all measured dimensions. • Adolescent fertility rate (AFR): United Nations Department

The GII is computed using the association-sensitive inequal- of Economic and Social Affairs (2009d)

ity measure suggested by Seth (2009). The index is based on the • Share of parliamentary seats held by each sex (PR): Inter-

general mean of general means of different orders—the first parliamentary Union’s Parline database (2010) 219

## STATISTICAL ANNEX

Step 3. Aggregating across gender groups, using a harmonic mean

• Attainment at secondary and higher education (SE) levels: The female and male indices are aggregated by the harmonic

Barro and Lee (2010) mean to create the equally distributed gender index

• Labour market participation rate (LFPR): International

Labour Organization (2010d) –1 –1

(G ) + (G )

Computing the Gender Inequality Index –1

HARM , ) = .

## (G

F M 2

There are five steps to computing the GII.

Step 1. Treating zeros and extreme values Using the harmonic mean of geometric means within groups

captures the inequality between women and men and adjusts

The maternal mortality ratio is truncated symmetrically at for association between dimensions.

10 (minimum) and at 1,000 (maximum). The maximum of

1,000 is based on the normative assumption that countries Step 4. Calculating the geometric mean of the arithmetic means for

where the maternal mortality ratio exceeds 1,000 are not each indicator

different in their ability to create conditions and support for The reference standard for computing inequality is obtained by

maternal health. Similarly, it is assumed that countries with aggregating female and male indices using equal weights (thus

1–10 deaths per 100,000 births are essentially performing at treating the genders equally) and then aggregating the indices

the same level. across dimensions:

The female parliamentary representation of countries

reporting 0 percent is coded as 0.1 percent because the geometric

mean cannot have zero values and because these countries do . .

G Health Empowerment LFPR

3

=

have some kind of political influence by women. F,M

Step 2. Aggregating across dimensions within each gender group, 1 1

.

Health

using geometric means where + 1

= /2,

## MMR AFR

Aggregating across dimensions for each gender group by the

geometric mean makes the GII association sensitive (see Seth

2009). ( )

. .

Empowerment PR SE + PR SE

= /2 and

## F F M M

For women and girls, the aggregation formula is LFPR LFPR

+

LFPR .

= 2

1 1 1/2 . . .

.

G SE LFPR ,

3 1/2

= (PR )

## F F F F

MMR AFR Health should not be interpreted as an average of corresponding

female and male indices but as half the distance from the norms

and for men and boys the formula is established for the reproductive health indicators—fewer

maternal deaths and fewer adolescent pregnancies.

. . .

## G SE LFPR

3 1/2

= 1 (PR ) .

M M M M Step 5. Calculating the Gender Inequality Index

Comparing the equally distributed gender index to the reference

standard yields the GII, Harm (G G )

,

1 – .

– –

## G F, M

220 human development report 2010

Example: Brazil Reproductive health Empowerment Labour market

Labour market

Attainment at secondary participation

Maternal mortality ratio Adolescent fertility rate Parliamentary representation and higher education rate

Female 110 75.6 0.094 0.488 0.640

Male na na 0.906 0.463 0.852

( )

( )

. . .

(1/110) (1/75.6) + 1 /2 = 0.50 0.094 0.488 + 0.906 0.463 /2 = 0.431

(F+M)/2 (0.640 + 0.852) / 2 = 0.746

na is not applicable.

Using the above formulas, it is straightforward to obtain:

1 1 . .

. – –

( ). . . G 3

0.546 = 0.505 0.431 0.746

G 3 0.094 0.488 0.640

0.115 = F, M

F 110 75.6 GII 1–0.201/0.546 = 0.632.

. . .

G 3

0.820 = 1 0.906 0.463 0.852

M -1

1 1 1

G )

Harm +

0.201=

## (G

F , M 2 0.115 0.820

Technical note 4. Calculating the Multidimensional Poverty Index

The Multidimensional Poverty Index (MPI) identifies multiple The health thresholds are having at least one household

deprivations at the individual level in health, education and member who is malnourished and having had one or more chil-

standard of living. It uses micro data from household surveys, dren die. The education thresholds are having no household

and—unlike the Inequality-adjusted Human Development member who has completed five years of schooling and having

Index—all the indicators needed to construct the measure must at least one school-age child (up to grade 8) who is not attend-

come from the same survey. ing school. The standard of living thresholds relate to not having

Each person in a given household is classified as poor or electricity, not having access to clean drinking water, not having

nonpoor depending on the number of deprivations his or her access to adequate sanitation, using “dirty” cooking fuel (dung,

household experiences. These data are then aggregated into the wood or charcoal), having a home with a dirt floor, and owning

national measure of poverty. no car, truck or similar motorized vehicle, and owning at most

one of these assets: bicycle, motorcycle, radio, refrigerator, tele-

Methodology phone or television.

Each person is assigned a score according to his or her house- To identify the multidimensionally poor, the deprivation

hold’s deprivations in each of the 10 component indicators, (d). scores for each household are summed to obtain the household

c.

The maximum score is 10, with each dimension equally deprivation, A cut-off of 3, which is the equivalent of one-

weighted (thus the maximum score in each dimension is 3⅓). third of the indicators, is used to distinguish between the poor

c

4 If is 3 or greater, that household (and everyone

The health and education dimensions have two indicators each, and nonpoor.

in it) is multidimensionally poor. Households with a depriva-

so each component is worth 5/3 (or 1.67). The standard of liv- tion count between 2 and 3 are vulnerable to or at risk of becom-

ing dimension has six indicators, so each component is worth ing multidimensionally poor.

5/9 (or 0.56). 221

## STATISTICAL ANNEX

The MPI value is the product of two measures: the Weighted count of deprivations in household 1:

. . = 2.22

of poverty. 1 + 1

3 9

## H,

The headcount ratio, is the proportion of the population

who are multidimensionally poor: Headcount ratio

q

H = 7 + 5 + 4

n (H) = = 0.80

4 + 7 + 5 + 4

q

where is the number of people who are multidimensionally

n (80 percent of people live in poor households)

poor and is the total population.

## A,

The intensity of poverty, reflects the proportion of the

d, Intensity of poverty

weighted component indicators, in which, on average, poor

people are deprived. For poor households only, the deprivation . . .

(7.22 7) + (3.89 5) + (5.00 4)

(A) = = 0.56

scores are summed and divided by the total number of indica- .

)

( 7 + 5 + 4 10

tors and by the total number of poor persons: (the average poor person is deprived in 56 percent of the

q c

∑ 1 weighted indicators).

A = qd .

## H A

c MPI = = 0.450

where is the total number of weighted deprivations the poor

d

experience and is the total number of component indicators In sum, the basic intuition is that the MPI represents the share

considered (10 in this case). of the population that is multidimensionally poor, adjusted by

the intensity of the deprivations suffered.

Example using hypothetical data Household

1 2 3 4 Weights

Indicators

Household size 4 7 5 4

Health

At least one member is malnourished 0 0 1 0 5/3=1.67

One or more children have died 1 1 0 1 5/3=1.67

Education

No one has completed five years of schooling 0 1 0 1 5/3=1.67

At least one school-age child not enrolled in school 0 1 0 0 5/3=1.67

Living conditions

No electricity 0 1 1 1 5/9=0.56

No access to clean drinking water 0 0 1 0 5/9=0.56 NOTES

1 Lower values have occurred during some crisis situations (such as the Rwandan genocide) but were

House has dirt floor 0 0 0 0 5/9=0.56 2 The inequality aversion parameter guides the degree to which lower achievements are emphasized and

Household uses “dirty” cooking fuel (dung, firewood 1 1 1 1 5/9=0.56 higher achievements are de-emphasized

or charcoal) 3

A is estimated from survey data using the survey weights,

Household has no car and owns at most one of: bicycle, 0 1 0 1 5/9=0.56 x

motorcycle, radio, refrigerator, telephone or television w w

X …X n

1

1 n n

= 1 – , where ∑ w = 1.

Â

Results x 1 i

n

∑ w X

1 i i

Weighted count of deprivation, c (sum of each 2.22 7.22 3.89 5.00

deprivation multiplied by its weight) 4 Technically this would be 3.33. Because of the weighting structure, the same households are identified as

poor if a cut-off of 3 is used.

Is the household poor (c > 3)? No Yes Yes Yes

1 indicates deprivation in the indicator; 0 indicates non-deprivation.

Note:

222 human development report 2010

Definitions of statistical terms

Adjusted net savings Rate of savings in an and repayments to the International Monetary Fertility rate, adolescent Number of births to

economy after taking into account invest- Fund, expressed as a percentage of GNI. women ages 15–19, expressed per 1,000 women

ments in human capital, depletion of natural of the same age.

resources and damage caused by pollution, Degraded land, people living on Percent-

expressed as a percentage of gross national age of people living on severely and very Fertility rate, total Number of children that

income (GNI). Negative adjusted net saving severely degraded land. Land degradation is would be born to each woman if she were to

implies that total wealth is declining and that based on four aspects of ecosystem services: live to the end of her child-bearing years and

the economy is on an unsustainable path. biomass, soil health, water quantity and bio- bear children at each age in accordance with

diversity. Severe degradation indicates that prevailing age-specific fertility rates.

Births attended by skilled health personnel biotic functions are largely destroyed and

Percentage of deliveries attended by person- that land is non­reclaimable at the farm level. Food deprivation, intensity of Average

nel (including doctors, nurses and midwives) Very severe degradation indicates that biotic shortfall in kilocalories suffered by malnour-

trained to give the necessary care to women functions are fully destroyed and that land is ished people, expressed as a percentage of the

during pregnancy, labour and the postpartum nonreclaimable. minimum daily requirement of dietary energy

period. Excludes traditional birth attendants, intake. The lower the value, the less intense

whether trained or not. Democratic decentralization measure Score food deprivation is.

Civil war, fatalities Average number of fatali- tions indicating whether elections were held Foreign direct investment, net inflows Net

ties resulting from civil war per year of conflict, for the legislature and executive at the lowest inflows of investment to acquire a lasting man-

expressed per million people. For countries with subnational (municipal) level. Scores range agement interest (10 percent or more of voting

multiple wars, the best estimates for the total from 0 (no local elections) to 2 (legislators and stock) in an enterprise operating in an econ-

number of battle deaths from conflict are used. executives are locally elected). omy other than that of the investor. It is the

sum of equity capital, reinvestment of earnings,

Civil war, intensity Score indicating the level Dependency ratio Ratio of the population other long-term capital and short-term capital,

of intensity of civil war conflict. A score of 0 ages 0–14 and ages 65 and older to the work- expressed as a percentage of GDP.

indicates no conflict; 1 is a sign of minor civil ing-age population (ages 15–64), expressed as

war where the number of deaths in a year is less dependants per 100 people ages 15–64. Formal employment Wage and salaried work-

than 1,000; 2 indicates a major civil war where ers, plus employers, expressed as a percentage of

the number of deaths in a year is at least 1,000. Ecological footprint of consumption total employment.

Amount of biologically productive land and

Consumer price index Average price of a bas- sea area that a country requires to produce the GDP (gross domestic product) Sum of value

ket of goods and services purchased by house- resources it consumes and to absorb the waste added by all resident producers in the econ-

holds; the basket varies by country and may it generates, expressed in hectares per capita. omy plus any product taxes (less subsidies) not

be fixed or may change at specified intervals. included in the valuation of output, calculated

Changes in the consumer price index indicate Enrolment ratio, gross Total enrolment in without making deductions for depreciation

the change in the real value (purchasing power) a given level of education, regardless of age, of fabricated capital assets or for depletion and

of money. expressed as a percentage of the official school- degradation of natural resources. Value added

age population for the same level of education. is the net output of an industry after adding

Contraceptive prevalence rate, any method up all outputs and subtracting intermediate

Percentage of women of reproductive age (ages Enrolment ratio, net Enrolment in a given inputs. When expressed in US dollar terms, it

15–49) who are using, or whose partners are level of education of the official age for that is converted using the average official exchange

using, any form of contraception, whether level, expressed as a percentage of the total pop- rate reported by the International Monetary

modern or traditional. ulation of the same age group. Fund. An alternative conversion factor is

applied if the official exchange rate is judged to

Debt service, public expenditure on Sum Expected years of schooling Number of years diverge by an exceptionally large margin from

of principal repayments and interest actually of schooling that a child of school entrance age the rate effectively applied to transactions in

paid in foreign currency, goods or services on can expect to receive if prevailing patterns of foreign currencies and traded products. When

long-term debt (having a maturity of more age-specific enrolment rates were to stay the expressed in purchasing power parity (PPP)

than one year), interest paid on short-term debt same throughout the child’s life. US dollar terms, it is converted to international 223

## STATISTICAL ANNEX

PAGINE

238

PESO

13.07 MB

AUTORE

PUBBLICATO

+1 anno fa

### DESCRIZIONE DISPENSA

Materiale didattico per il corso di Differenziali Economici e Migrazioni della Prof.ssa Paola Giacomello e del Dott. Paolo Sellari. Trattasi del Rapporto sullo sviluppo umano 2010 redatto dall'Onu, all'interno del quale è analizzato il concetto di benessere e di sviluppo attraverso la misurazione di diversi parametri economici e sociali.

DETTAGLI
Corso di laurea: Corso di laurea in scienze politiche e relazioni internazionali (POMEZIA, ROMA)
SSD:
A.A.: 2011-2012

I contenuti di questa pagina costituiscono rielaborazioni personali del Publisher Atreyu di informazioni apprese con la frequenza delle lezioni di Differenziali Economici e Migrazioni e studio autonomo di eventuali libri di riferimento in preparazione dell'esame finale o della tesi. Non devono intendersi come materiale ufficiale dell'università La Sapienza - Uniroma1 o del prof Giacomello Paola.

Acquista con carta o conto PayPal

Scarica il file tutte le volte che vuoi

Paga con un conto PayPal per usufruire della garanzia Soddisfatto o rimborsato

Recensioni
Ti è piaciuto questo appunto? Valutalo!

Appunto

Appunto

Appunto

Appunto