WPS7020 Policy Research Working Paper 7020 Comparable Estimates of Returns to Schooling Around the World Claudio E. Montenegro Harry Anthony Patrinos Education Global Practice Group September 2014 Policy Research Working Paper 7020 Abstract Rates of return to investments in schooling have been esti- method for all surveys in the sample. The results of this mated since the late 1950s. In the 60-plus year history of study show that (1) the returns to schooling are more con- such estimates, there have been several attempts to synthe- centrated around their respective means than previously size the empirical results to ascertain patterns. This paper thought; (2) the basic Mincerian model used is more stable presents comparable estimates, as well as a database, that use than may have been expected; (3) the returns to school- the same specification, estimation procedure, and similar ing are higher for women than for men; (4) returns to data for 139 economies and 819 harmonized household schooling and labor market experience are strongly and surveys. This effort to compile comparable estimates holds positively associated; (5) there is a decreasing pattern over constant the definition of the dependent variable, the set of time; and (6) the returns to tertiary education are highest. control variables, the sample definition, and the estimation This paper is a product of the Education Global Practice Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at hpatrinos@ worldbank.org The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Produced by the Research Support Team Comparable Estimates of Returns to Schooling Around the World Claudio E. Montenegro World Bank and Department of Economics, University of Chile Harry Anthony Patrinos World Bank JEL codes: C13, J31 Keywords: Returns to schooling; Returns to experience; Investments in education I. INTRODUCTION Education is critical for economic growth and poverty reduction. Quality education systems produce the global economy’s workers and expand knowledge. Schooling enables students to learn the skills that propel individual labor productivity. A host of social and non-market benefits are also produced by schooling, including but not limited to increased child well-being, health status, efficiency of consumer choices, and social capital. The individual contribution of schooling has often been measured by labor market earnings. Similarly, potential experience is a proxy for skills learned in the workplace. In many poor economies, education and labor market experience are the only human assets for a vast part of the labor force. The study of the relationship between schooling and earnings has led to a number of empirical studies on a variety of social issues. These include, for example, racial and ethnic discrimination (McNaab and Psacharopoulos (1981); Chiswick (1988)); gender discrimination (Goldin and Polacheck (1987); income distribution (Mincer (1958); the determinants of the demand for education (Freeman (1976)); the impact of technology on wage differentials (Krueger (1993)); the impact of unexpected price, productivity and technology shocks (King, Montenegro, and Orazem (2012)); the impact of information on demand for schooling (Jensen (2010)); and the returns to schooling in the context of job creation (World Bank (2012). Under certain assumptions, earnings differentials by level of education have been used to identify the sources of economic growth (see, for example, Denison (1967). But perhaps the quintessential application has been the estimation of the rate of return to investment in schooling. Earnings of workers classified by some dimension have been at the core of empirical economics and other social sciences for many decades, starting with human capital theory (Schultz (1961); Becker (1964); Mincer (1974). For 40 years, researchers (Banerjee and Duflo (2005); Colclough, Gandhi Kingdon, and Patrinos (2010); Harmon, Oosterbeek, and Walker (2003); Psacharopoulos (1972), Psacharopoulos (1973), Psacharopoulos (1985), Psacharopoulos (1989), Psacharopoulos (1994); Psacharopoulos and Patrinos (2004), Psacharopoulos and Layard (2012)) have reported on the patterns of estimated returns to schooling across developing economies. The returns are typically in the form of the estimated proportional increase in an individual’s labor market earnings from each additional year of schooling completed. Among the consistent findings across the various surveys are: 1. Private returns to schooling are generally positive and the cross-economy average rate of return to schooling is 10 percent a year. 2. Returns to schooling seem to be higher in low or middle income economies than in high income economies. 3. Returns to schooling are highest at the primary level and become smaller (although still large) at the secondary and tertiary levels of schooling. 2 4. Estimated returns to schooling are higher for women than for men. 5. Returns to schooling have declined very modestly over time despite rising average levels of schooling attainment, suggesting that the world demand for skills has been increasing as the world skill supply has also increased. All but one of these findings survive our analysis and that is point 3; in fact, tertiary education now displays the highest average private rates of return. As discussed by Psacharopoulos and Patrinos (2004), the stylized facts presented above are based on compilations of studies that may not be strictly comparable. There are two main sources of non-comparability: data sample coverage and methodology. First, survey samples may not accurately reflect population means. For cost or convenience, surveys may concentrate on subpopulations that are easier or less expensive to reach, focusing on firms rather than households, or concentrating on urban populations while excluding rural residents. Second, studies rarely use the same model to estimate returns. Variation in control variables used can affect estimated returns, as can variation in the estimation strategy used. Both of these problems make it possible for observed variation in estimated returns to be due to these differences in sample design or estimation method and not to the true variation in returns. Another methodological limitation is that researchers often include in the regression model many independent variables (Becker (1964). This procedure leads to a lower estimated effect of education on earnings. While researchers who include other variables in earnings functions do so because they are interested in modeling earnings, not necessarily in estimating the rate of return to schooling, this nevertheless leads to biased estimates when the schooling coefficient is interpreted as a rate of return. This paper presents new and comparable estimates of the private returns to schooling (and to potential experience) using data from 139 economies with a total of 819 harmonized household surveys. The sample includes several economies for which there is more than one survey available. Private rates of return are used to explain the behavior of individuals in seeking different education levels. Estimates of the returns to schooling and to potential experience are a useful indicator of an individual’s productivity. This evidence can be used to guide public policy in the design of programs and crafting of incentives that both promote investment in education and ensure that low-income families make those investments. The paper sets out to describe the patterns and trends using the same specification and estimation procedure by making use of harmonized country surveys and by using comparable methods. This effort to compile comparable estimates addresses the issues in the literature such as by holding constant (i) the definition of the dependent variable; (ii) the variables used as controls; (iii) sample definitions; and (iv) estimation method for all the surveys in the sample. The results show (i) that the returns to schooling and potential experience are more concentrated around their respective means than previously thought; (ii) the basic Mincerian model used is more stable that one may have expected; (iii) the 3 returns to schooling are higher for women than for men; (iv) returns to education and to potential experience are strongly and positively associated; (v) returns demonstrate a decreasing pattern over time; and (iv) returns to tertiary education are the highest and to secondary education the lowest. II. METHODS The private rate of return compares the costs and benefits of schooling as incurred and realized by the individual student who undertakes the investment. Mincer (1974) has provided a great service and convenience in estimating returns to schooling by means of the semi-log earnings function (see also Becker and Chiswick (1966). The now standard method to estimate private returns per year of schooling is to estimate log earnings equations of the form: 2 (1) Ln( wi ) = a + β1Si + β 2 X i + β 3 X i + µi where Ln(wi) is the natural log (of hourly or annual, depending on data) earnings for the ith individual; S i is years of schooling (as a continuous variable); X i is labor market potential experience (estimated as agei - Si - 6); Xi2 is potential experience-squared; and µ i is a random disturbance term reflecting unobserved abilities. Therefore, β 1 can be viewed as the average rate of return to years of schooling to wage employment. The list of control variables is kept deliberately small to avoid overcorrecting for factors that are correlated with years of schooling. This is also known as the “Mincerian” method (Mincer (1974)). The earnings function method can be used to estimate returns at different schooling levels by converting the continuous years of schooling variable (S) into a series of dummy variables, say Dp, Ds and Dt (where p is primary schooling, s is secondary schooling and t is tertiary) to denote the fact that a person has achieved that level of schooling. The omitted level is people with no schooling and that dummy is not in the equation to avoid matrix singularity. The estimation equation in this case is of the form: (2) Ln(wi) = α + βpDpi + βsDsi + βtDti + β1Xi + β2X2i + μi After fitting this “extended earnings function” (using the above dummies instead of years of schooling in the earnings function), the private rate of return to different levels of schooling can be derived from the following formulas: (3) rp = (βp)/(Sp) (4) rs = (βs - βp)/(Ss - Sp) (5) rt = (βt - βs)/(St - Ss) 4 where Sp, Ss and St stand for the total number of years of schooling for each successive level. Care has to be taken regarding the foregone earnings of primary school-aged children. In the empirical analysis that follows we have assigned only three years of foregone earnings to this group, following tradition (see, for example, Psacharopoulos (1995)). The costs incurred by the individual are her foregone earnings while studying, plus any tuition fees or incidental expenses incurred during schooling. Since schooling is mostly provided free by the state, at least at the basic education level, then in practice the only cost in a private rate of return calculation is the foregone earnings. The private benefits amount to what a more educated individual earns (after taxes), above a comparable group of individuals with less schooling. This more or less refers to adjacent levels of schooling; for example, tertiary versus secondary school graduates. Although convenient because it requires less data, this method is slightly inferior to the full discount method (Psacharopoulos (1995)); in fact, it assumes flat age-earnings profiles for different levels of schooling (Psacharopoulos and Layard (1979)). From equation (1) the return to potential experience is given by: (6) β 2 + 2β 3 X i which needs to be evaluated at a given value of Xi. For each sample we use the average years of potential experience as the evaluation point. It is important to stress that in the empirical part when we refer to potential experience we are referring to the estimates based on equation (1). III. DATA Our findings are the result of studying a large database constructed from existing national household surveys through the use of the International Income Distribution Database (I2D2) World Bank (2014), initially compiled by the World Bank’s World Development Report unit over the period 2005-2011, and now under the World Bank’s Poverty and Inequality Unit (since 2012). These data have been used in recent World Development Reports and also in several Human Development Reports (see, for example, United Nations Development Program (UNDP) (2011). For a detailed description of the sample, see Montenegro and Hirn (2009). The database covers economies from developed and developing regions, with no censoring of any kind in the sample selection. For most of the economies it covers at least one point in time, and in many cases several points in time. An enormous effort was undertaken in standardizing the variable definitions across economies and time periods. The original data set includes 1,018 economies-years that represent 160 economies. Not all of the economy-year data points are included in our analysis because some surveys lack key variables. The basic specification (the one that requires the minimum set of variables, and hence the one that has the most estimates) was calculated for 819 economy-year points, and covers 139 economies. 5 The period of time under study is 1970 to 2013. However, less than 5 percent of observations are from before 1990, and only 25 percent before 2000; 75 percent of our estimates come from the period 2000-2013. Figure 1 presents the distribution of the sample by year. The most represented economies include Brazil (with 27 years of survey data), Costa Rica (21 years) and Argentina and Honduras (20 years each). On the other extreme, there are several economies with only one point in time, most of which are in Africa and Eastern Europe, or are small economies. Looking at the distribution of the sample by region, from Figure 1 it is immediately obvious that the Latin America and Caribbean region has the largest representation in the sample, at 36 percent, or 291 data points, of all estimates. This is exclusively a result of data availability. High Income Economies follow at 28 percent, then Sub-Saharan Africa at 11 percent, with East Asia and the Pacific at 8 percent, Europe and Central Asia at 10 percent, South Asia at 5 percent, and finally the Middle East and North Africa at 2 percent. Figure 1: Distribution of the sample Sub- East Asia & Saharan By regions Pacific Africa Europe & 8% South Asia 11% Central Asia 5% 10% Middle East & North Africa 2% High Income Latin 28% America & Caribbean 36% The sample definition used in this study includes only waged employees. Self-employed workers were eliminated because the database did not allow the separation of income into returns to labor and returns to capital. Family aid workers, apprentices and similar workers were also eliminated because their wages do not reflect market productivity. 6 The unemployed and people who work in voluntary services were also excluded. The same variables and sample definitions are used for all surveys, which gives us comparable economy-year results. For every survey, the top 0.5 percent of the sample was eliminated to avoid possible biases due to wage outliers. Like many other studies, school attainment is defined by the highest grade attended and completed; experience is defined as potential years of experience, where this is defined as age minus years of schooling minus six (as the typical school starting age). Both variables are measured in years. Annex Table 1 presents the list of economies and years used in this study, along with the returns to schooling (both as an aggregate variable and by levels). IV. RESULTS The basic earnings functions, equations (1) and (2), were applied to three different groups: (i) total sample, (ii) males and (iii) females (given the well-known differences in behavior for males and females in the labor market). As shown in the first three data rows of Table 1, the average rate of return to another year of schooling is 10 percent for the total sample. When considering only males, the rate of return to another year of schooling is 9.6 percent, and for females the rate of returns is much higher, at 11.7 percent. All of these estimates are based on 819 observations from 139 economies between 1970 and 2013. These results are similar to many other reviews of the literature. Table 1. Summary statistics of the returns to schooling Variable Mean N Years of schooling total 10.1 (3.3) 819 Years of schooling male 9.6 (3.2) 819 Years of schooling female 11.7 (3.3) 819 Primary schooling total 10.6 (6.4) 547 Secondary schooling total 7.2 (3.6) 619 Tertiary schooling total 15.2 (5.8) 762 Primary schooling male 10.0 (6.6) 543 Secondary schooling male 7.1 (3.8) 614 Tertiary schooling male 15.2 (5.8) 745 Primary schooling female 10.9 (7.6) 519 Secondary schooling female 8.7 (4.6) 607 Tertiary schooling female 16.8 (6.1) 738 Note: Standard deviations in parentheses The returns are also estimated for levels of schooling, shown in the second, third and fourth block of rows in Table 1. In particular, the second block presents the returns for the total sample, the third for males, and the fourth for females. Table 1 clearly corroborates a fact already known in the literature: the returns to education for females are higher than for males. This is true not only when considering 7 the returns to another year of schooling, but also for each one of the three levels of education examined here. To stress the results presented in Table 1, Figure 2 presents the averages returns to schooling (as a whole and by level). Figure 2 clearly shows the higher returns for women than for men. T-tests (not included here but available upon request) confirm that, in each and every case, the average returns are higher for females than for males (see Dougherty (2005) for an explanation as to why returns are higher for women). In all cases the results are statistically significant. Figure 2: Returns to schooling male female 9.6 years of education 11.7 10.0 primary 10.9 7.1 secondary 8.7 15.2 tertiary 16.8 One important thing to stress is that the estimates presented in this paper were obtained after estimating the returns in a comparable fashion (that is, the definition of the dependent variable, the control variables, the sample definition, and the estimation method were the same and applied to all the surveys in our sample). The similarity of our results to the ones presented by Psacharopoulos and Patrinos (2004) shows just how stable these estimates really are. The rate of return to another year of schooling is also well-behaved and has a normal distribution (for the three samples considered here), as shown in Figure 3. The same well-behaved normal distribution also applies when considering the breakdown by gender. When analyzing the returns to schooling by level, the returns are normally distributed for each level, but their distributions are different. As shown in Figure 3, the returns to 8 primary and tertiary are less concentrated around the mean, while the returns to secondary are much more concentrated around the mean. Figure 3: Returns to Schooling Total sample Male sample .15 .2 .15 .1 Density Density .1 .05 .05 0 0 0 10 20 30 0 10 20 30 Returns to schooling Returns to schooling Female sample .15 .1 Density .05 0 0 10 20 30 Returns to schooling 9 Figure 3 (cont’d): Returns to Schooling by Level Primary Secondary .15 .15 .1 .1 Density Density .05 .05 0 0 0 10 20 30 40 50 0 10 20 30 40 50 Returns to schooling level: Primary Returns to schooling level: Secondary Tertiary .15 .1 Density .05 0 0 10 20 30 40 50 Returns to schooling level: Tertiary Considering only the latest available estimate for each economy and the returns to schooling when using the total sample, the five economies with the lowest rate of return are: Afghanistan, Armenia, Russian Federation, Guyana and Iraq. The five economies with the highest returns are: Rwanda, South Africa, Ethiopia, Namibia, and Burundi. It is interesting to note that among the five highest returns, all are from Africa. This is shown in Table 2, which also presents the economies with the lowest and highest returns by gender. 10 Table 2: Highest and Lowest Returns to Schooling by Economy Overall Male Female Economy Return Economy Return Economy Return Afghanistan 1.6 Armenia 0.8 Afghanistan 3.0 Armenia 2.2 Afghanistan 1.3 Papua New Guinea 3.7 Lowest Russian Federation 2.6 Burkina Faso 2.8 Armenia 4.2 Guyana 3.3 Sierra Leone 3.1 Belarus 4.3 Iraq 3.4 Iraq 3.1 Cambodia 4.7 Rwanda 22.4 Rwanda 20.8 Rwanda 24.4 South Africa 21.1 South Africa 20.3 South Africa 23.3 Highest Ethiopia 18.5 Namibia 19.3 Ethiopia 19.3 Namibia 18.3 China 17.7 Kenya 19.3 Burundi 17.3 Burundi 17.2 Tanzania 19.2 The returns to another year of schooling by world region are highest in Sub-Saharan Africa (12.4 percent), significantly above the global average (9.7 percent; see Table 3). Returns are lowest in the Middle East/North Africa region (7.3 percent). Healthy returns are experienced in East Asia (9.4 percent) and Latin America (9.2 percent). There are below average returns in the Eastern European economies (7.4 percent) and in South Asia (7.7 percent). Regarding the returns by level (see Table 3), the returns are, in general, higher in Sub- Saharan Africa with only one exception: when considering the primary school level for females, but it is still higher than the global average. There are low returns to primary schooling in high income economies, as would be expected. There are high returns to primary schooling in the Middle East and North Africa, especially for females; by contrast, the returns to tertiary are low in the Middle East and North Africa. Returns to primary schooling are surprisingly low in South Asia. Table 3a. Average Returns to Schooling (latest period for each country) Average returns to Average years of schooling schooling Region total male female total male female N High Income economies 10.0 9.5 11.1 12.9 12.7 13.1 33 East Asia & Pacific 9.4 9.2 10.1 10.4 10.2 10.7 13 Europe & Central Asia 7.4 6.9 9.4 12.4 12.2 12.7 20 Latin America & 9.2 8.8 10.7 10.1 9.5 10.9 23 Caribbean Middle East & North 7.3 6.5 11.1 9.4 9.2 11.0 10 Africa South Asia 7.7 6.9 10.2 6.5 6.5 6.4 7 Sub-Saharan Africa 12.4 11.3 14.5 8.0 8.1 8.1 33 All economies 9.7 9.1 11.4 10.4 10.2 10.8 139 11 Table 3b. Average returns to schooling by levels Total Male Female Region Primary Secondary Tertiary Primary Secondary Tertiary Primary Secondary Tertiary High Income 4.9 6.6 11.1 3.3 7.5 10.7 7.2 5.2 12.3 East Asia 13.6 5.3 14.8 12.6 5.8 15.0 9.5 6.4 15.8 Europe/Central Asia 13.9 4.7 10.3 12.1 4.2 9.8 11.9 6.4 12.2 Latin America 7.8 5.4 15.9 7.9 5.3 15.7 8.7 6.5 17.4 Middle East/N. 16.0 4.5 10.5 12.7 4.3 10.2 21.4 7.4 13.5 Africa South Asia 6.0 5.0 17.3 4.7 3.9 16.6 4.8 6.2 23.3 Sub-Saharan Africa 14.4 10.6 21.0 12.5 10.1 21.0 17.5 12.7 21.3 All economies 11.5 6.8 14.6 10.1 6.7 14.4 13.2 8.2 16.1 Figure 4. Average returns to schooling by region and gender (ordered from lowest total to highest total) 12 The returns to another year of schooling tend to decline as the average level of schooling rises in an economy. This demonstrates that schooling increases respond to price signals. Therefore, as demand for education increases and the supply follows, the price tends to fall (see Figure 5). Figure 5: Returns to Schooling and Average Years of Schooling Total sample Male 25 25 20 20 Returns to schooling Returns to schooling 15 15 10 10 5 5 0 0 0 5 10 15 20 0 5 10 15 20 Average schooling Average schooling Female 30 Returns to schooling 10 0 20 0 5 10 15 20 Average schooling There is a positive correlation between the returns to schooling and the returns to experience. That is, the coefficients on schooling and experience are positively related (see Figure 6). 13 Figure 6: Correlation returns to schooling and returns to potential experience Total sample Male sample 6 6 4 4 Returns to experience Returns to experience 2 2 0 0 -2 -2 0 5 10 15 20 25 0 5 10 15 20 25 Return to schooling Return to schooling Female sample 8 6 Returns to experience 2 0 -2 4 0 10 20 30 Return to schooling There has been a tremendous increase in schooling attainment in recent decades. In 2010, the world population aged 15 and above was estimated to have an average of 8 years of schooling, having increased steadily from just over 5 years in 1980 (Barro and Wha Lee (2013)). As schooling in an economy increases, the returns to schooling tend to decrease, as show in Figure 7. Our new estimates show a sharp decline in returns during the past few decades, reflecting the sharp increase in schooling levels worldwide. 14 Figure 7: Returns Patterns over Time Returns to schooling 25 20 Returns to schooling 10 5 0 15 1970 1980 1990 2000 2010 Year The returns to schooling have declined significantly since the 1980s, when they were above 13 percent, to just over 9 percent in recent years (Table 4). This is due, at least partly, to the unprecedented expansion in schooling since the 1980s and, especially, since the late 1990s. Schooling has expanded by almost 50 percent since 1980. Over a 30 year period the returns to schooling have declined by 3.5 percentage points, or 0.1 percent a year. At the same time, schooling increased by more than 3 years, or 2 percent a year. On average, another year of schooling leads to a reduction of the returns to schooling by one percentage point. Table 4. Returns to Schooling and Average Years of Schooling by Period Average Returns to Number of years of Schooling surveys schooling 1980-1985 13.3 6.6 12 1986-1990 12.7 8.1 23 1991-1995 11.0 8.0 58 1996-2000 10.1 8.8 109 2001-2005 9.9 10.1 228 2006-2010 9.6 10.9 238 2011-2013 10.0 11.6 149 15 Figure 8: Average returns to schooling and average mean of education over time V. COMPARISON WITH ALTERNATIVE ESTIMATES Other studies find the average rate of return to another year of schooling is 10 percent (see, for example, Psacharopoulos and Patrinos (2004)). Returns to schooling by level of national income show that the highest returns are recorded for low-income and middle- income economies. Average returns to schooling are found to be highest in the Latin America and Caribbean region and for the Sub-Saharan Africa region. Returns to schooling for Asia are at about the world average. The returns are lower in the high- income OECD economies. Average returns to schooling are lowest for the non-OECD European, Middle East/North Africa group of economies. The only differences that we find are the relatively low returns to schooling for South Asia and the relatively high returns in high-income economies, though these differences may be due to economy coverage. Our data set and the compilation of studies by Psacharopoulos and Patrinos (2004) and Psacharopoulos and Patrinos (2014) show a decline in the rates of return over time. Overall, the average returns estimated by Psacharopoulos and Patrinos (2004) and Psacharopoulos and Patrinos (2014) are slightly lower. This is most likely due to additional control variables that are being used in the 16 studies that Psacharopoulos and Patrinos (2004) and Psacharopoulos and Patrinos (2014) review. Also, Psacharopoulos and Patrinos (2004) and Psacharopoulos and Patrinos (2014) cover, in general, a period prior to the estimates derived here. Figure 9: Returns to Schooling Estimates, all data points Returns to schooling 30 Returns to schooling 10 020 1950 1960 1970 1980 1990 2000 2010 Year This paper Fitted values Psararopoulos and Patrinos Fitted values Source: Our estimates and the reviews of Psacharopoulos and Patrinos (2004). Comparing these new, consistent estimates with Psacharopoulos and Patrinos (2004) and Psacharopoulos and Patrinos (2014), we estimate, in terms of latest year available, for 139 economies, an average rate of return of 10.0 percent (with a standard deviation of 3.4). Psacharopoulos and Patrinos (2004) and Psacharopoulos and Patrinos (2014), for 91 economies, estimate a rate of return of 9.4 percent (with a standard deviation of 3.9). Our new estimates contain 43 more economies. Together, the two compilations cover 149 economies (76 percent of the 193 economies recognized by the United Nations). In terms of world population in 2010, the estimates reviewed in Psacharopoulos and Patrinos (2004) and Psacharopoulos and Patrinos (2014) cover 84 percent of the globe. This new study covers 92 percent of the world’s population. Combined, the two studies cover more than 95 percent of the global population. In Figure 9 we plot all estimates, demonstrating the consistency and stability of the estimates. 17 VI. LIMITATIONS This study focuses on the returns to schooling as measured by labor market earnings. While a useful measure, it does mean that we do not include self-employed or informal sector workers because of methodological difficulties. This is not a problem in more advanced and growing economies, but it is a limitation in countries where a substantial proportion of the population is in the informal sector. Individual country work is needed to fill that gap (see, for example, Garcia-Mainar and Montuenga-Gomez (2005). Another potential limitation is endogeneity. The results reported here are correlations from earnings functions estimated using Ordinary Least Squares. To the extent that there are other factors that affect the schooling decision then there could be bias. To address the potential bias researchers have instrumented schooling or tried other techniques. The results reported confirm the estimates obtained here; in many cases the returns estimated using an instrumental variables (IV), which correspond to sub-populations and are therefore Local Average Treatment Effects (LATE), are typically higher than the average OLS estimate in the same country (Ichino and Winter-Ebmer (1999); Card (1995); Duflo (2001); Patrinos and Sakellariou (2006)). Therefore, we do not believe that the correlations reported here are biased, and are certainly not biased upward. The results reported here are private returns. They are based on what the individual will earn and the only costs considered are those incurred for attending school – fees, tuition and so on, as well as the indirect or opportunity cost of schooling in the form of foregone earnings. These estimates can help explain individual behavior about schooling decisions and can be used by policy makers to design school finance policies, especially for tertiary education. But for most policy decisions, policy makers would need to know the social returns to schooling. First, this would require full social returns estimates of social benefits (externalities and non-market effects), a difficult task for a single country (but see Acemoglu and Angrist (2001); Wolfe and Haveman (2002)), almost impossible for the global estimates we provide here. Second, one would need full social costs, in the form of what the government provides in terms of the supply of schooling. For narrow returns, one can use the private benefits and the social costs. This is something our future research will address. VII. CONCLUSION Our new data set of comparable estimates of the returns to schooling and to potential experience covers 139 economies. We use 819 harmonized household surveys to provide the estimates that cover the period from 1980 to 2013. This compilation of comparable estimates addresses several issues in the literature, such as: (i) the definition of the dependent variable—which we keep consistent throughout; (ii) the variables used as controls – we use the basic Mincerian specification; (iii) sample definitions – we limit the analysis to the same samples throughout in terms of age, employment status and earnings; and (iv) estimation method – which we apply consistently to every survey. 18 The results show: (i) that the returns to schooling are more concentrated around their respective means than previously thought; (ii) the basic Mincerian model used is more stable than one may have expected; (iii) the returns to schooling are higher for women than for men; (iv) returns to schooling and to experience are strongly and positively associated; (v) both returns show a decreasing pattern over time; and (vi) the returns to tertiary education are the highest and to secondary education the lowest. When we combine our new estimates with the Psacharopoulos and Patrinos (2004) review, we mostly confirm previous findings and stylized facts. The combination also allows us to create a time-trend dating back to the 1960s, confirming that returns to schooling decline over time. This comparable data set on returns to schooling and to potential experience should be helpful empirical work in a variety of fields. Our comparable estimates provide a reasonable proxy for the value of human capital for a broad group of economies. This new data set is useful for studying the links across economies between schooling attainment and the returns to schooling. Moreover, it can be used to examine economic growth, competitiveness, inequality, democracy, institutions and political freedom. Given the high returns to tertiary education, an immediate concern for policy makers is to consider the large implications. While our estimates are for private returns to schooling, the high returns to tertiary education will fuel demand for post-secondary education. Governments will need to consider the appropriate policy for financing tertiary education. 19 Annex Table 1: Returns to Schooling by Economy and Period Economy Year A B C D E F G H I J K Afghanistan 2007 1.6 2.9 4.1 3.5 3.6 Albania 2005 4.5 3.2 14.1 1.2 7.4 17.4 1.3 7.2 3.5 11.2 Argentina 1992 7.8 3.8 4.3 12.7 1.2 5 14.4 2.4 10.5 Argentina 1993 8.3 3.8 2.6 4.6 11.9 1.3 4.8 12.6 7.4 4.3 10.3 Argentina 1994 8.6 3.7 5.1 10 9.2 5.2 10.1 5.2 9.8 Argentina 1995 9 3.8 8.6 5.1 14.6 10.8 5.2 16.4 3.6 5.3 12.3 Argentina 1996 7.7 4.2 3.9 5.8 12.4 4.5 5.9 15.3 2.3 5.7 9.4 Argentina 1997 8.4 3.8 2.9 13.2 3.3 14.8 1.9 11.6 Argentina 1998 10.4 3.8 7.4 5.7 15.5 12.8 5.6 16.9 0.5 6.1 14.7 Argentina 1999 9.7 3.8 5.3 4.8 15.1 14.2 5 15.7 4.7 15 Argentina 2000 10.5 3.9 5.3 5.4 15.9 9.6 5.6 16.9 1.9 5.3 15.4 Argentina 2001 10.8 3.9 4.4 5.7 15.6 1.9 5.7 16 8.4 5.7 15.6 Argentina 2002 10.8 3.9 3.4 5.1 17.2 7 5.5 18.6 4.6 16.4 Argentina 2003 9.9 4 10.5 5.1 15.8 8.1 5.4 15.8 12.5 4.7 16.2 Argentina 2004 9.9 3.8 0.8 4.9 14.6 4.9 14.6 2.6 4.9 15.2 Argentina 2005 10.2 3.8 6.1 5 15.1 9.7 5.7 14.6 4.2 16.3 Argentina 2006 10.1 3.8 7.2 5.4 14.7 3.7 5.6 13.6 10.7 5.5 16.9 Argentina 2007 10 3.8 3.8 5.6 14.8 5.2 5.8 14.7 3.1 5.6 15.8 Argentina 2008 9.8 3.8 8.1 5.4 13.5 10 5 12.9 5.3 6.5 15.2 Argentina 2009 9.6 3.7 3.7 5.3 13.4 6.7 5.2 12.8 5.7 15 Argentina 2010 9.4 3.7 6 4.3 14 13.5 4.4 13.3 4.4 15.8 Argentina 2012 8.8 3.6 3.7 4.7 12 0 4.7 11.5 14.7 4.8 13.4 Armenia 1999 2.2 3.3 4.6 2.9 6.8 Australia 2001 9.8 2.1 12.2 11.3 10.2 12.9 Australia 2002 10.2 2 0.6 12.2 14.7 9.6 8.3 Australia 2003 11.1 2 1.2 13.5 7.9 11.3 2.6 Australia 2004 12.7 1.9 14.9 4.6 14.1 14.8 Australia 2005 11.8 1.8 4.9 13.7 3.5 11.3 Australia 2006 11.6 1.8 13.4 7 13.1 8.4 Australia 2007 11.3 1.7 13.3 11.9 12.6 12.6 Australia 2008 12.6 1.7 10 14.5 36.4 12.6 12.1 Australia 2009 12.7 1.7 5.9 15.1 24.2 14.7 18.5 Australia 2010 14.1 1.6 30.8 14.6 35.1 14.1 16.3 Austria 2004 9.4 2.3 8.4 8.1 10.3 Austria 2005 10.8 2.1 8.5 8 10.2 Austria 2006 11.6 2.1 9.4 8.8 10.7 Austria 2007 11.1 2.1 9.6 9.2 11.3 Austria 2008 10.7 2.1 8.6 8 10.5 Austria 2009 11.1 2.1 9.3 8.4 10.8 Austria 2010 9.1 2.3 8.7 8.4 9.8 Austria 2011 10.2 2.2 9 8.2 10.3 Austria 2012 9.9 2.2 8.8 9.1 9.2 Azerbaijan 1995 7.2 2.9 19.8 2.2 8.1 28.2 7.8 11 4.2 7.5 Bangladesh 2000 5.9 4.4 8.6 2.6 13.2 6.4 2.1 12.5 9 1.7 29.1 Bangladesh 2005 7.1 5.4 8.1 5 16 5.8 4.2 14.4 8.8 8.1 23 Belarus 1998 3.7 1 Belgium 2004 5.3 3.5 1.7 3.4 7.5 3.7 6.8 6.4 3.4 10.4 Belgium 2005 5.8 3.1 6.8 3.5 7.2 10.6 3.8 6.9 4.6 9 20 Economy Year A B C D E F G H I J K Belgium 2006 5.6 3 2.7 7.2 1.3 3.8 6.2 3.2 9.4 Belgium 2007 6.3 2.8 7.8 7 10.6 Belgium 2008 6.2 3 7.5 4.1 7.9 0.6 3.6 7.1 11.6 5 10.5 Belgium 2009 5.8 3.2 11.2 2.2 7.8 13.9 2.5 6.9 8.7 1.3 10.5 Belgium 2010 6.3 3.2 5.8 3.8 8.3 14 3.8 7.3 3.4 10.8 Belgium 2011 6.4 3 7.1 3.4 8.1 2.2 3.1 7.6 17.1 4 10.2 Belize 1993 9.4 3.4 1.6 7.7 13.2 0.4 7.6 12.6 5.4 8.7 13.9 Belize 1994 10.5 3.4 13.2 6.7 13.1 11 5.4 13.5 21.3 10.4 12.3 Belize 1996 9.1 3.4 7.2 6.1 12.1 7.8 5.3 10.1 5.5 8.6 13.6 Belize 1997 10.8 3.4 12 6.6 15.4 9.7 6.2 15 29.5 7.6 15.7 Belize 1998 10.6 3.4 5.5 7.9 14.5 6 7.2 14.1 5.1 10 15 Belize 1999 10.4 3.3 9.5 6.5 16 10.8 6 14.6 4.3 8.1 17.1 Bolivia 1992 11.7 4.2 14.7 7.2 17 9.5 4.3 16.7 10 10.5 20.3 Bolivia 1993 12.4 4.7 16.3 7.9 20.1 5.9 4.6 20.2 12.7 11.2 22.9 Bolivia 1997 11.4 4.8 13 7.2 20.2 8 4.6 19.9 7.7 12.9 21.7 Bolivia 1999 10.9 4.7 20.8 5.5 18.2 8.4 2.7 19.1 11 12.1 18.4 Bolivia 2000 11.5 4.8 11.9 5.6 22.5 10.8 3.1 23.4 7.2 9.6 22.2 Bolivia 2001 10.4 4.8 6.8 5 19.8 6.2 4.3 19.6 2.6 6.1 21.3 Bolivia 2002 10.3 4.8 4.7 4.8 21.9 8.1 3.8 20.8 6.7 24.5 Bolivia 2003 10.5 4.7 9.6 4.2 22.4 7 3.9 21.7 6.9 4.6 25 Bolivia 2005 11.6 4.8 8.9 6.3 21.3 4.2 5 21.8 7.8 8.8 21.7 Bolivia 2007 10.5 4.7 17.1 5.1 18.8 6.3 4.8 17.8 21 4.5 22.2 Bolivia 2008 8.5 4.6 13.7 2.7 16.9 9.1 1.8 16.4 11.1 4.6 19 Bolivia 2009 7 4.7 8.2 1.8 14.6 0.6 13.3 6.9 3.7 18 Bolivia 2011 6.8 4.8 7.9 2.4 13.3 1.9 1.3 12.2 8.7 4.8 17 Bolivia 2012 7.3 4.7 8.6 3.1 13.6 3.2 1.9 11.2 4.9 5.5 19 Bosnia and Herzegovina 2001 7.9 2.7 7.3 3.1 11.4 2.5 9.4 6.3 4.9 15.4 Brazil 1981 15.3 4.5 21 15 16.8 22 15.3 16.1 19.9 17.1 17.5 Brazil 1982 17.3 4.3 22.4 15.6 20.4 23.4 15.9 21.4 21.9 17.4 19.9 Brazil 1983 16.8 4.4 19.8 15.6 21 20.6 15.9 21.4 19.4 17.5 20.9 Brazil 1984 17.3 4.4 20.9 15.9 21.5 21.3 15.9 21.8 21.2 18.6 21.7 Brazil 1985 17.2 4.3 21.7 15.7 20.7 22.4 15.6 20.6 21.5 18.6 21.6 Brazil 1986 15.6 4.4 18.8 13.3 21.7 19.8 13.9 21.5 18.1 14.8 22.5 Brazil 1987 16.7 4.4 21.6 14.5 21.9 22.6 14.8 22.7 20.9 16.3 21.9 Brazil 1988 17.5 4.5 24.1 14.9 22.5 26 15.4 23.2 21.4 16.7 22.6 Brazil 1989 16.8 4.4 23.1 14 22.5 24.7 14.7 23.3 20.9 15.6 22.6 Brazil 1990 16.9 4.5 23.2 14.4 22.6 25.3 15.1 22.1 20.5 15.5 23.9 Brazil 1993 15.9 4.4 19.9 13.8 20.1 21.7 14.3 21.4 17.8 14.9 20.3 Brazil 1995 15.1 4.4 18.5 12.4 21.4 21 13.4 22.9 14.6 12.7 21.5 Brazil 1996 14.5 4.4 18 11.7 20.9 20.8 12.9 21.5 13.8 11.7 21.8 Brazil 1997 14.8 4.4 17.3 12 21 19.8 13 21.5 13.7 12.2 21.7 Brazil 1998 14.9 4.4 16.7 11.9 22 19.4 12.8 23.3 12.8 12.2 22.3 Brazil 1999 14.7 4.4 15.8 11.5 21.8 18.5 12.3 22.5 12.5 12.1 22.4 Brazil 2001 14.3 4.4 15.9 10.8 21.8 17.9 11.9 22.9 13.5 10.6 22.3 Brazil 2002 14.5 4.4 14.8 10.7 22.3 17.1 11.8 23.3 12 10.5 23 Brazil 2003 13.9 4.4 14.1 10 21.8 16.1 11.1 22.7 12.3 9.8 22.5 Brazil 2004 13.5 4.3 13.1 9.6 21.4 15 10.6 22.2 11.5 9.6 22.1 Brazil 2005 13.3 4.3 12.2 9.4 21.2 14.3 10.4 22 10 9.2 22 Brazil 2006 13.1 4.3 12 9 20.9 14.1 10 21.8 10.1 8.8 21.6 21 Economy Year A B C D E F G H I J K Brazil 2007 11.5 4.4 11.1 8.7 18.4 12.8 9.6 18.8 9.8 8.4 19.4 Brazil 2008 11.4 4.3 10.2 7.9 18.3 12.8 8.8 18.4 7.2 7.8 19.6 Brazil 2009 11.3 4.3 9.8 7.8 18 11.9 8.7 18.3 7.6 7.5 19.2 Brazil 2011 10.1 4.3 8.1 6.6 17.7 10.9 7.6 18.3 3.9 6.2 18.7 Brazil 2012 10.5 4.2 7.9 6.3 17.3 10.3 7.2 18 4.9 6.1 18 Bulgaria 2001 3.9 4.4 13.6 3.2 5 5.1 3.5 4.6 57.2 4.1 5.1 Bulgaria 2003 7.8 2.9 0.7 5 7.7 5.2 8.5 3.1 5.3 8.3 Bulgaria 2007 6.5 2.5 5.9 4.3 7.9 6.8 4.2 8.2 13.9 4.3 9.5 Bulgaria 2008 8 2.6 2.1 8.3 9.2 0.3 8.2 9.1 2.5 8.3 11.3 Bulgaria 2009 7.8 2.4 9 8.6 8.9 9.4 9.7 11.2 Bulgaria 2010 8.6 2.5 10.3 9.5 10.5 10 10.7 11.9 Bulgaria 2011 9.7 2.5 9.1 7.2 11.5 9.6 12.1 30.3 4.6 13.9 Bulgaria 2012 7.8 2.5 12 5.8 9.1 0.3 7.3 9.9 28.2 3.9 11.5 Burkina Faso 1994 15.7 5.2 39.1 10.4 13.9 36.5 10.5 13.8 60.1 8.2 15.8 Burkina Faso 1998 13.3 5.3 15.6 13.2 21.3 16.5 11.9 21.3 16.5 19.2 20.9 Burkina Faso 2003 12.2 5.7 12 12.2 19.6 12.2 10.9 27.6 12.8 17.6 12.5 Burkina Faso 2009 7.4 5.3 17.8 19.6 20.2 12.9 Burundi 1998 17.3 5.2 12.9 21.3 21.8 9.7 21.5 23.4 23.7 19.2 19.8 Cambodia 1997 6.4 3.7 15.8 3.6 12.1 3.8 25.1 2.8 Cambodia 2004 5.3 4.3 9.6 3.5 14.1 5 3.1 14 11.8 16.6 4 Cambodia 2007 5.6 4.3 0.9 3.5 15 2.5 15.7 3.4 14.2 4.7 Cambodia 2008 4.3 4.4 2.5 20.7 1 20.8 20.5 4 Cameroon 2001 14.1 4.3 16.9 12.1 23.2 15.5 12.5 21.2 22.4 28.2 12.8 Cameroon 2007 11.6 4.3 11.1 8.9 21.7 9.9 9.3 21 24.1 23.4 10.1 Canada 1981 9.2 2.7 8.6 6.8 10 Canada 1991 11.2 2.5 9.8 8.1 11.2 Canada 2001 12.1 2.4 10.1 8.2 12.4 Chad 2003 7.2 5.7 1.1 7.4 22.7 1.4 5.6 24.6 4.7 16.9 8.4 Chile 1987 12.7 4.3 7.6 8.8 22.6 8.6 8.9 25.5 7 8.9 20.8 Chile 1990 11 4.2 7.3 7.8 17.1 8.6 8 19.7 7 8.1 16.2 Chile 1992 8 4 6.2 7.2 10.5 7.2 7.4 12 2.7 6.8 10.2 Chile 1994 11.7 4.1 8.1 7.9 17.9 9.3 8.4 20.5 5.2 7.5 16.5 Chile 1996 12.8 4 6.5 8.7 18.7 8 9.1 20.5 1.3 8.8 18 Chile 1998 13 4 6.3 8.5 18.9 6.4 8.7 20.3 5.5 8.5 18.9 Chile 2000 13.2 3.9 4.7 7.5 19.8 4.7 8.2 20.7 4 6.9 19.9 Chile 2003 13.2 3.8 6.8 7.2 19.3 7.9 7.5 19.8 3.7 7.4 19.9 Chile 2006 12.4 3.7 4.2 6.2 17.5 4.6 6.8 17.5 3.3 6.1 18.9 Chile 2009 11.9 3.7 5.9 17.6 1.5 6.3 18.1 6 18.6 Chile 2011 12.3 3.6 3 5.6 17.6 2.6 5.7 17.8 4.1 6 18.8 China 2002 16.6 3.2 9.3 20.9 0.1 8.9 23.3 10.3 16.8 Colombia 2001 11.5 4.5 5.2 6.3 24.2 4.1 6.1 24.3 10.3 7 24.1 Colombia 2002 12 4.6 6.4 6.6 25.5 5.2 6.4 25.3 9.7 7.2 25.7 Colombia 2003 11.4 4.6 4.4 6.3 23.8 4.2 5.7 23.8 7.1 7.7 24 Colombia 2004 11.3 4.6 4 6.2 22.8 3 6.1 22.7 8.1 6.9 23.2 Colombia 2005 11.3 4.6 4.5 6 23 3.7 5.9 22.7 7.7 6.6 23.6 Colombia 2006 11.4 4.7 7 6.2 22.5 7.2 5.9 22.6 8.9 7.4 23.1 Colombia 2007 11.7 4.7 6.1 6.7 21.9 5.9 6.7 21.7 10.2 7.7 22.9 Colombia 2008 11.2 4.6 7.2 5.8 20.4 7.1 5.6 20.3 10.3 7 21.4 Colombia 2009 10.8 4.6 7 5.4 20 6.9 5.3 19.5 9.6 6.4 21.4 22 Economy Year A B C D E F G H I J K Colombia 2010 11 4.6 4.5 5.3 20.3 4.4 5.3 20.1 7.6 6.1 21.6 Colombia 2011 11 4.6 6.3 5.3 19.7 6.7 5.4 18.9 7.9 6.1 21.5 Colombia 2012 11 4.6 6 5.3 19.6 5.3 5.7 19.3 12.5 5.3 21.4 Comoros 2004 6.5 5.9 2.2 5.4 17.2 5.8 15.4 9.9 7 20.3 Congo, Dem. Rep. 2005 6.3 4.1 9 1.7 21.5 2.5 1.9 20.1 24.7 0.9 32.8 Costa Rica 1989 10.6 4 7.9 7.3 16 8.6 6.7 16.5 10.9 9.6 16.2 Costa Rica 1990 10.4 4 8.7 6.8 17 9.6 6.5 16.7 5.8 8.5 18.4 Costa Rica 1991 10.4 3.9 7 6.1 18.5 5.7 5.6 17 14.6 7.8 21.1 Costa Rica 1992 10 4 5 5.8 17.8 4.7 5.8 16.5 6.7 6.4 20.2 Costa Rica 1993 10.1 4.1 10.7 5.4 18 10.1 4.9 17.3 12.5 6.8 19.5 Costa Rica 1994 10.1 4 5.9 6.1 17.4 7.2 6.2 16.6 4.1 6.7 19.2 Costa Rica 1995 10.2 4 7.8 5.4 18 8.1 5.5 17.8 9.3 6 19.2 Costa Rica 1996 10.3 4 9.3 6.1 17.7 8.4 6 18 16.2 6.9 18.2 Costa Rica 1997 10.6 4 7.6 5.5 19.2 8.2 5.4 18.4 7.8 6.6 20.6 Costa Rica 1998 10 4.1 4.6 5.5 17.9 5 5.3 17.5 6.2 6.5 19.1 Costa Rica 1999 9.6 4.1 5.8 4.9 17.8 4.6 5 17.7 8.2 5.4 19.1 Costa Rica 2000 9.3 4.2 5.2 4.8 17.4 6.3 4.8 18.1 2.8 5.5 17.5 Costa Rica 2001 10.5 4.3 5.6 6 18.2 6.9 6 17.7 3.5 6.8 19.5 Costa Rica 2002 10.7 4.2 8.2 4.9 20 8.8 5.1 20.2 8.8 5.3 20.6 Costa Rica 2003 10.6 4.2 6.6 5.1 19.5 6.6 5.1 19.1 10.1 6.1 20.8 Costa Rica 2004 10.5 4.2 8.9 5 19.3 10.2 5 19.6 5.9 6 19.7 Costa Rica 2005 10.3 4.2 4 4.3 19.8 4.7 4.7 19 3.6 4.3 21.6 Costa Rica 2006 10.3 4.3 4.3 4.9 18.6 5.3 5 18.4 3.2 5.8 20 Costa Rica 2007 10.1 4.2 5.2 4.3 19.3 6.8 4.5 19.1 2.5 4.7 20.4 Costa Rica 2008 10.1 4.2 4.4 4.2 19.2 6.9 4.3 18.9 5.1 20.4 Costa Rica 2009 10.7 4.3 4.3 4.8 19.5 5.8 4.9 18.5 2 5.7 21.7 Croatia 2004 9.4 2.5 10.1 9.8 5.5 Croatia 2011 10.8 2 11.9 9.2 15.2 Croatia 2012 11.6 2 13.1 11.7 15.3 Czech Republic 2005 11.3 1.7 10.7 11.1 Czech Republic 2006 11.7 1.7 11.4 11.4 Czech Republic 2007 11.6 1.7 Czech Republic 2008 9.8 1.7 Czech Republic 2009 9.4 1.7 9 8.9 10 Czech Republic 2010 9.6 1.7 9.7 10.1 Czech Republic 2011 10.7 1.7 Czech Republic 2012 10.5 1.8 10.2 10.7 Côte d'Ivoire 2002 13.2 5.7 12.1 12.9 28.7 13.3 10.9 27.1 8.6 16.4 32.4 Côte d'Ivoire 2008 11.3 6.5 12.6 12.1 24.9 7.7 10.9 21.9 19.4 14.1 31 Denmark 2004 7.3 2.6 8.4 9.3 8.6 Denmark 2005 7.6 2.6 8.5 8.9 9.4 Denmark 2006 6.6 2.6 7.1 8.3 7.6 Denmark 2007 7.1 2.6 8.2 8.5 9.5 Denmark 2008 6.2 2.6 6.8 7.3 7.7 Denmark 2009 6.4 2.6 7.1 8.2 Denmark 2010 7.1 2.6 7.7 7.7 Denmark 2011 7.9 2.6 9.8 12.7 8.4 Denmark 2012 7.7 2.5 9.1 10.7 8.7 Djibouti 1996 15.5 5.3 32.5 8.9 16 19.6 7 16.5 33.4 10.7 10.7 23 Economy Year A B C D E F G H I J K Dominican Republic 1996 8.5 4.8 12 4.7 16 12.6 3.7 17.1 12.6 7.5 15.1 Dominican Republic 1997 7.3 5 6.7 5.5 13 7.4 5.1 13.3 4.9 6.7 13.6 Dominican Republic 2000 9.8 4.8 8 5.4 18.6 10.8 5.1 18.8 3.6 6.1 19.5 Dominican Republic 2001 9.5 4.8 9.5 5.6 18.1 10.5 5.2 19 7.7 7.2 18.6 Dominican Republic 2002 9.7 4.8 11.2 6.2 16.4 12.6 5.3 16.8 10.4 8.4 16.7 Dominican Republic 2003 10.1 4.8 12.9 5.3 18.1 13.8 5.2 18.7 10.7 6 18.8 Dominican Republic 2004 9.5 4.7 10.6 5.2 16.3 12.3 5.7 15.5 7.4 4.9 19.2 Dominican Republic 2005 9.5 4.7 8.7 5.2 17.3 7.1 4.9 15.8 10.3 6 20.3 Dominican Republic 2006 9.6 4.8 8.4 5.3 16.7 7.2 5.1 16.7 11.1 6 18.3 Dominican Republic 2007 9.5 4.6 8.9 5.8 15.8 10.7 5.5 15.7 5.4 6.3 17.6 Dominican Republic 2008 9.7 4.7 8.3 4.5 17.8 9 4.4 18.3 7 4.9 18.5 Dominican Republic 2009 9.8 4.6 10.1 5.4 16.9 10.9 5.6 16 9.9 5.4 19.2 Dominican Republic 2010 9.5 4.6 7.1 5 17.5 7.9 5.5 15.8 7.4 4.2 21.1 Dominican Republic 2011 9.4 4.5 8.3 4.9 15.8 10.9 4.6 15.2 6.2 5.8 18.1 Ecuador 1994 7.8 4.7 6.4 4.3 16.7 7.1 4.7 16.8 3.5 4.9 18.5 Ecuador 1995 9.3 4.5 10.6 2.8 6.7 10 2.3 6.1 8.4 2.5 7.3 Ecuador 1995 9.4 4.8 14.7 6.7 15.3 13.1 6 16.2 13.6 8.9 15.4 Ecuador 1998 9.6 4.6 7.9 5.1 19 6 4.7 18.2 8 7.2 21.5 Ecuador 1998 10.9 4.6 7.3 4.4 7.1 8.7 3.1 6.1 3.9 5.8 8.3 Ecuador 1999 9.7 4.7 7.7 4.5 19.2 5.7 4.2 21.6 10.5 5.5 16.4 Ecuador 2000 10.1 4.9 8.6 7.3 18.2 7.1 6.3 18.8 8.5 11 18.1 Ecuador 2003 8.4 4.8 4.7 5 16.5 4.3 4.4 17.9 3.2 7.3 15.9 Ecuador 2004 8.3 4.9 7.5 4.8 15.7 7 4.7 16.8 8.1 5.8 15.3 Ecuador 2005 8.7 4.8 8.6 5.1 16.8 7.4 5 17.6 11.8 5.7 17.1 Ecuador 2006 8.5 4.7 8.2 4.9 16 6.6 4.8 16.6 12 5.7 16.8 Ecuador 2006 13.4 4.7 16.3 10 21 16.5 10.7 21.4 16.5 8.3 21.6 Ecuador 2007 8.4 4.8 7.7 5 15.7 5.5 4.9 16.1 13.2 6 16.5 Ecuador 2008 7.9 4.8 5.4 4.4 15.4 4.9 4.5 15.3 6 4.9 17.2 Ecuador 2009 8.1 4.7 3.5 4.6 15.1 2.6 4.3 15.8 5.3 6.3 15.5 Ecuador 2010 7.8 4.8 7 4.2 14.4 5.6 4 15 10.2 5.2 14.6 Ecuador 2011 7.4 4.7 7.5 5 12.3 7.1 5 12.3 8 5.2 13.3 Ecuador 2012 7.2 4.7 4.6 4.5 12.3 2.2 4.9 11.9 12.3 4 14.3 El Salvador 1991 9.6 5.2 10.7 10.1 14.9 9 8.1 14.9 11.6 15.7 15.1 El Salvador 1995 9.9 5.3 12.6 10.1 14.8 12.6 8.3 14.4 13 15 15.7 El Salvador 1996 10.2 5.4 13.4 10 16.4 11.7 8.3 16.6 16.9 14.7 16.8 El Salvador 1998 10.1 4.9 13.6 9.3 15 13 9 14.2 13.5 10.7 16.1 El Salvador 1999 10.2 5 13.1 8.6 16.6 13.2 7.6 16.8 12.2 10.9 16.6 El Salvador 2000 10.4 5 13.2 8.5 16.7 12.9 8.2 16 14.5 9.6 17.8 El Salvador 2001 9.7 5 11 7.3 18.9 12.2 6.7 18.6 7.9 8.6 19.4 El Salvador 2002 9.8 4.9 11.8 7.8 16.7 12.2 7.2 16.3 10.9 9.4 17.4 El Salvador 2003 9 4.9 8.4 6.9 17.6 8.4 6.3 17.3 8.8 8.3 18.1 El Salvador 2004 8.7 4.9 8.6 6.2 17.7 8.2 6.1 16.2 9.4 6.9 19.7 El Salvador 2005 9.1 5.1 9.9 7.4 15.2 9.9 7.4 14.8 9.5 8 16.1 El Salvador 2006 7.6 5 7 5.6 15.5 5.9 6.1 13.6 8.9 5.4 17.8 El Salvador 2007 8.4 4.9 7.7 6 16.6 8.4 6 15.7 6.1 6.8 18 El Salvador 2008 8.6 4.7 4.4 10.2 4.6 9.4 3.7 11.8 El Salvador 2009 9.3 4.9 8 6.4 18.8 7.1 6.4 17.1 9.5 7 21 Estonia 2004 7.5 2.3 7.6 6.4 6.3 9.5 11.8 7.1 Estonia 2005 7.7 2.2 6.2 10 7.7 24 Economy Year A B C D E F G H I J K Estonia 2006 6.8 2.3 4.5 5.6 6.4 7.1 14.2 2.3 8.6 Estonia 2007 5.9 2.3 7.1 3.6 4.7 10.6 5.5 6.4 7.3 Estonia 2008 5.7 2.3 1.5 6.1 4.2 7 10 Estonia 2009 5.7 2.3 0.8 5.8 1.2 7 9.1 Estonia 2010 6.9 2.3 3.7 7.3 6.5 8.4 10.4 Estonia 2011 7.6 2.3 7.2 7.9 8.7 10.2 Estonia 2012 6.5 2.3 6.4 7.3 10.7 Ethiopia 2005 18.5 5.4 32.7 16.2 17 31.7 13.6 16.9 25.9 20.7 16.8 Finland 2004 7.6 2.5 Finland 2005 8.6 2.5 Finland 2006 8.1 2.5 Finland 2007 7.4 2.9 10.8 11.6 12.1 Finland 2008 9.3 2.5 Finland 2009 8.3 2.5 Finland 2010 7.7 2.4 Finland 2011 7.8 2.4 Finland 2012 7.9 2.4 France 2004 8.5 3.2 10.9 3.9 12.9 5.5 3.4 12.4 24.4 4.4 15.1 France 2005 8.4 3.2 5.2 4 12.6 7.1 3.4 12.2 8.5 4.9 14.7 France 2006 8 3.2 2.7 4 11.8 7.4 1.9 11.6 4.3 6 13.7 France 2007 8.3 3.1 4.7 4.7 11.5 7.1 3.7 11 5.7 5.9 13.9 France 2008 8.7 3.1 4.1 5 12 8.5 3.4 11.2 3.9 6 14.5 France 2009 9.2 3.1 3 5.1 12.7 3.2 3.9 12.3 6.7 5.7 15 France 2010 9.1 3.1 4.5 4.5 12.5 10.2 2.7 11.3 4.5 6.5 15.2 France 2011 9.1 2.9 2.2 5.3 12 0.2 3.7 11.9 12.7 7.1 13.6 France 2012 9 2.9 3.8 12.2 2.5 11.8 1.3 5.8 14.5 Gabon 2005 13.5 4.3 5.7 10.6 25.5 5 8.6 23.5 9.4 14.5 29.3 Gambia, The 1998 9.1 5.3 9.4 8.6 18.1 9.6 5.3 22.7 1.5 19.4 4.5 Georgia 2010 7.7 2.8 11.5 13.1 8.1 Germany 2005 11 2.3 10 9.7 10.3 Germany 2006 13.2 2.3 12.1 10.8 13.6 Germany 2007 14 2.3 13.3 11.7 14 Germany 2008 14.2 2.4 13.7 12.1 14.7 Germany 2009 15 2.3 14.5 11.9 15.3 Germany 2010 15.2 2.4 14.8 13 15.4 Germany 2011 14.3 2.3 14.3 12.2 15.3 Germany 2012 14.5 2.3 14.3 12.8 14.8 Ghana 1991 5.3 4.8 1.4 7.9 12.2 6.7 12.3 6.3 11.4 12.8 Ghana 2005 10.3 4.6 4.7 7.8 23.2 6.8 22 11.6 8.4 27.8 Ghana 2012 12.5 4.6 2.7 8.8 28.7 6.5 26.6 2.3 11 34.8 Greece 2004 7 3.4 7.8 7 10.2 Greece 2005 7.5 3.4 9.4 8.5 12.3 Greece 2006 7.3 3.4 8.8 9.1 10.7 Greece 2007 7.5 3.4 8.9 8.5 11.4 Greece 2008 7.6 3.4 5.2 9.2 5.5 8.7 4.6 11.8 Greece 2009 7.4 3.3 5.9 8.1 5.4 6.9 5.8 11.6 Greece 2010 7 3.2 5.4 5.2 8.3 0.4 4.1 7.5 12.7 6.1 11.3 Greece 2011 6.5 3.1 3.8 5.4 6.5 4.6 5.7 7.7 4.5 6.5 Greece 2012 6.4 3.1 2.7 3.1 7.6 3 2.4 9.7 4.2 6.4 25 Economy Year A B C D E F G H I J K Guatemala 2000 10.5 4.8 12.6 8.4 19.2 9.9 8.1 19.7 13.2 11.1 18.1 Guatemala 2002 10.1 4.9 11.6 9.4 18.2 10 8.5 18.5 13.2 12.9 17.9 Guatemala 2003 11.1 4.7 14.3 9.9 17.4 16.8 10.2 16.8 6.4 10.8 18.6 Guatemala 2004 10 4.7 14.6 8.9 15.1 12.3 8.8 16.7 18.7 11.2 14.1 Guatemala 2006 9.6 4.8 13.9 7.8 14.7 13.5 7.6 16.4 11.4 10 12.9 Guatemala 2011 10 4.8 3.4 4.1 19.5 2.9 2.8 18.9 7.1 4 24.5 Guinea 1994 6.3 7.2 19.5 8.8 19.4 10.4 24.4 0.5 4.4 Guyana 1992 3.3 2.9 0.6 2.6 1.4 3.6 1.8 6.4 Haiti 2001 8.3 8 23.8 14 18.4 20.8 12.3 21.9 23.9 18.3 11.5 Honduras 1991 12.9 4.5 13.8 13.1 20.9 12.5 11 20.8 26 18.9 21.1 Honduras 1992 12.6 4.6 12.8 13.3 19.6 12 11.2 20.4 22.4 18.2 18.2 Honduras 1993 12.8 4.5 13.3 13.2 19.1 13.6 10.5 20.5 15.6 18.8 17.2 Honduras 1994 13.5 4.4 19.2 12.8 19.7 20.7 11.5 21.1 15.5 15.8 17.7 Honduras 1995 11.7 4.4 11.4 11.8 17.8 12 10.2 19.8 13.7 15.7 15 Honduras 1996 12.3 4.6 15.4 11.4 18.8 14.1 10.3 18.9 26.4 14.9 18.5 Honduras 1997 11.4 4.4 12.3 10.4 20.2 12.5 8.5 20.7 18.7 14.4 19.4 Honduras 1998 11.1 4.6 12 10 20.8 12 7.8 22.1 15.6 14.7 19.5 Honduras 1999 11.8 4.5 12.4 11 19 10.5 9.4 18.8 22.9 14.8 19.5 Honduras 2001 12.7 4.5 13.7 11.7 19 14.1 10.3 19.9 14.2 14.7 18.3 Honduras 2002 11.4 5 12.9 11.5 20.8 12.6 10.9 20.7 17.5 13.3 21.2 Honduras 2003 12.7 4.5 13.2 10.9 23.1 12.9 10.8 23.6 14.9 11.2 22.8 Honduras 2004 12.9 4.6 14.1 11.7 19.2 15 11.1 20.5 10.5 13 17.9 Honduras 2005 13 4.5 9.7 11.7 21.1 10.1 11.8 21.5 6.5 11.7 21.1 Honduras 2006 12.9 4.6 15.1 11.3 19.9 14.5 11.1 20.3 18.6 11.5 19.6 Honduras 2007 13 4.5 14 10.6 21.9 14.3 10.5 21.8 13.2 11.1 22.1 Honduras 2008 12.2 4.6 13.3 10.1 20.7 13 9.7 21.2 15.6 11.2 20.4 Honduras 2009 12.2 4.5 11.9 11 19.2 11.5 10.1 19.7 15.3 12.7 18.5 Honduras 2010 12.3 4.6 11.8 10.6 20 11 9.9 20.9 17.7 12.2 19.3 Honduras 2011 12.4 4.6 12.1 10.7 19.8 12.4 10.1 20.4 10.8 11.7 19.3 Hungary 2004 11.9 2.7 13 13.3 13.3 Hungary 2005 13.3 2.2 9.4 16 11.1 17 16.5 4.4 16.1 Hungary 2006 14.7 2.2 21.1 8.4 16.5 7.7 9.3 18.2 8.4 Hungary 2007 14.1 2.2 15.4 16.1 16 Hungary 2008 13.9 2.2 15.1 16.5 15.4 Hungary 2009 14.1 2.2 14.7 16.9 14.3 Hungary 2010 13.7 2.2 14.6 16 15 Hungary 2011 12.6 2.1 13 14.3 13.4 Hungary 2012 13.2 2.1 13 14 14 Iceland 2004 9.5 2.7 11.2 10.7 13.5 Iceland 2005 8.7 2.7 10.6 10.3 12.8 Iceland 2006 8.1 2.7 9.5 9.8 11.7 Iceland 2007 6.5 2.7 7.8 6.9 11.4 Iceland 2008 7.2 2.8 8.8 9.3 11.1 Iceland 2009 8.2 2.7 10.2 10.1 12.1 Iceland 2010 7.2 2.8 8.9 8.6 12.4 Iceland 2011 7.4 2.8 9.4 8.1 13.2 Iceland 2012 7.2 2.8 9.4 9.3 12.2 India 1983 12.2 4.9 20.6 14.4 10.8 16.3 13.5 11 7.8 23 9.9 India 1993 12.7 5 15.7 11.9 20.4 11.9 10.9 20.2 6.3 16.1 23.7 26 Economy Year A B C D E F G H I J K India 1999 7 3.7 11.4 4.3 20.2 7.7 3.9 17.4 6.6 2.3 36.5 India 2004 8.7 5.9 11.7 5.4 18.7 7.9 4.8 17.9 4.7 6 28.4 India 2007 12.4 5.3 11.5 9.6 27.7 8.4 9.1 26.5 5 8.5 37.4 India 2009 8.3 5.5 5.8 6 20.8 2.8 5.3 19.7 1.8 5.2 31 Indonesia 1998 12.1 4.3 18.4 11.1 13.4 12.7 8.8 13.9 8.1 13.5 15 Indonesia 1999 10.6 4.3 12.8 10.4 12.1 8 8.7 12.7 6.3 13.2 12.2 Indonesia 2000 10.1 4.9 17.5 9.5 11.1 11.3 8.2 11.5 16.6 12.8 11.3 Indonesia 2002 10 4.9 14.6 10.3 12.7 10.8 8.6 13.5 13.4 13.2 12.3 Indonesia 2003 10.2 4.3 14.9 9.5 10.6 10.2 8.2 11.3 14.4 11.9 11.2 Indonesia 2004 10.2 4.2 13.7 9.4 10.5 10 8 11.2 12.5 12.1 10.9 Indonesia 2006 10.1 4.3 10.6 9.7 10.9 8 8.5 11.9 10.7 11.7 11 Indonesia 2008 10.1 4.7 13.1 10.3 10.2 10.2 8.9 11.5 12.5 12.1 11.5 Indonesia 2009 10.7 4.7 14.6 10.6 10.6 10.8 9.3 12.1 15.4 12.4 11.5 Indonesia 2010 10.4 4.7 12.7 10 11.5 9.6 8.7 12.6 12.7 12 12.9 Iraq 2006 3.4 4.8 7.7 1.2 3.2 6.3 1 3.9 40.4 5.7 4 Ireland 2004 8.3 3.3 11.3 9.6 13.6 Ireland 2005 7.8 3.3 10.9 8.6 14 Ireland 2006 9.1 3.2 11.6 11 13.4 Ireland 2007 8.9 3.2 11.9 10.6 15 Ireland 2008 8.8 3.2 10.9 9.6 13.7 Ireland 2009 8.1 3.2 10.8 10.7 11.7 Italy 2004 6.7 2.9 7.5 5.2 6.9 8.5 4.9 7.5 6.9 6.7 8 Italy 2005 6.6 2.9 10.4 4.5 7.2 13.5 4.1 7.9 6.2 5.7 7.9 Italy 2006 6.8 2.8 4.9 5.1 7.3 6 5.2 8.4 11 5.5 8.1 Italy 2007 7 2.9 7 4.4 7.6 5.6 4.2 8.6 13.2 6 8.6 Italy 2008 6.4 2.8 0 5.2 7.2 3.5 3.8 7.6 7.4 9 Italy 2009 7.1 2.8 3.5 4.9 8.3 9.2 4.4 8.7 6.6 9.8 Italy 2010 6.7 2.8 1.5 4.9 7.7 4.8 4.6 8.3 6.5 9.2 Italy 2011 7 2.7 1.3 6.2 7.4 5.9 5.1 8 9.5 9 Italy 2012 6.6 2.6 5.7 7.3 4.7 8.2 7.9 8.7 Jamaica 1990 7.4 2.8 3.2 14 4 16.5 2.6 15.3 Jamaica 1996 15.2 2.6 4 2.6 26.9 3.5 1.9 26.4 7.6 2.7 30.9 Jamaica 1999 6.3 3.1 1.5 1.9 12.7 2.3 13 15.6 1.8 14.8 Jamaica 2001 11.1 3.3 22.2 4 3.6 Jamaica 2002 10.3 2.8 9.3 1.2 22 16.9 2.823.9 22.3 Japan 2004 9.9 2.2 8.6 5 6.7 Japan 2007 14 2.1 9 7.4 3.1 Jordan 2002 8.9 3.8 10.3 4.2 8.4 8.4 4.5 10.1 16.7 6 11.2 Kenya 2005 16.9 3.8 17.6 15.9 22.4 19.1 14.5 21.2 9.6 19.6 24.9 Korea, Rep. 2010 13.2 2.2 12.7 12.7 10 Kosovo 2003 4.2 2.7 2.1 7.4 2.6 7 9.3 0.4 9.2 Kyrgyz Republic 1997 8.7 3 5.6 7 6.7 6.8 5.7 5.7 Lao PDR 1997 3.3 4.2 13.2 2.5 5.3 13.6 2.3 5.6 16.9 3.3 5.4 Lao PDR 2002 10.3 3.9 18.4 9.1 10.5 24.7 8.1 11 12.7 11.5 11.5 Lao PDR 2008 5.1 4 10.7 4.8 5.6 13.9 3.5 5.6 7.6 7.7 5.4 Latvia 2004 6.5 2.3 9.9 11.6 10.3 Latvia 2005 7.4 2.9 23.2 4.3 7.6 15.2 6.2 7.4 47.8 3.6 10.7 Latvia 2006 10.2 2.1 8.7 10.8 11.2 Latvia 2007 9.7 2.2 8.1 5.8 8.8 8.9 8.6 9.1 4.3 27 Economy Year A B C D E F G H I J K Latvia 2008 10 2.3 3.5 11.3 2.5 6.5 12.3 2.3 14.8 Latvia 2009 10.9 2.3 12.2 11.5 11.9 12 9.8 13.7 14.1 Latvia 2010 11.9 2.3 51.8 12.6 48.8 14.6 13.5 Latvia 2011 11.6 2.3 3.9 11.6 2.9 2.8 12.5 Latvia 2012 11.4 2.3 7.6 11.6 4.7 12.8 12.8 13.9 Lebanon 2011 5.5 4.2 9.8 7.6 16.6 Lithuania 2005 12.2 2.1 9.8 10.5 11.9 Lithuania 2006 12.9 2.1 10.2 11.5 12 Lithuania 2007 10.9 2 8 8.5 11.9 Lithuania 2008 9.9 2 7.2 7.6 11.2 Lithuania 2009 10.4 2.1 2 8.1 1.1 12.6 Lithuania 2010 12.4 2.1 1 10.7 13 Lithuania 2011 14.2 2.1 3.3 14 Lithuania 2012 12.9 2.1 10.9 4.2 14.4 Luxembourg 2004 10.7 3.6 12.9 11.8 13.6 Luxembourg 2005 10.9 3.6 13 10.9 15 Luxembourg 2006 11.2 3.6 13 10.8 15.5 Luxembourg 2007 11.3 3.6 14.1 11.3 16.3 Luxembourg 2008 10.7 3.6 11.8 9.7 13.7 Luxembourg 2009 11.3 3.6 13.3 12.2 14.5 Luxembourg 2010 10.6 3.6 12.9 11.4 14.9 Luxembourg 2011 10.6 3.6 13.1 11.4 15.1 Luxembourg 2012 10.6 3.6 13.6 11.7 15.5 Macedonia, FYR 2003 5.7 3.1 2.5 2.1 8.5 4.5 1.1 7.9 3.7 4.2 9.9 Macedonia, FYR 2004 6.7 3 3.1 9.5 2.7 8.9 4.3 4.6 11.2 Macedonia, FYR 2005 5.7 3.4 4.4 1.7 7.2 5 2.4 6.1 2.8 0.7 10 Madagascar 1993 12.4 4.5 13.9 9.8 20.2 11.2 8.8 16 11.5 13.8 27.5 Madagascar 1997 9.3 4.3 11.2 8.6 8.8 12.8 6.9 8.1 5.5 10.5 9.7 Madagascar 2001 10.5 4.6 6.7 11 13.3 7.8 10.4 13.7 5.2 11 12.1 Madagascar 2010 11.1 4.5 2.8 10.3 23.1 0.9 9.7 25.1 1.4 11.7 19.7 Malawi 2004 5.2 3.7 6.3 5 23.7 5.6 4.1 22.9 2.7 4.4 Malawi 2010 9.8 4.5 24.2 23.9 26 Malaysia 2007 11.7 4.1 8.4 9.7 21.4 7.2 8.9 22.4 7.4 12.6 20.9 Malaysia 2008 11.5 4.2 11.3 9.6 21.2 10.8 8.7 20.8 9.3 12.9 22.5 Malaysia 2009 12.7 4.3 9.8 10.6 23.4 8.6 9.9 23.4 9.5 13.7 24.3 Malaysia 2010 12 4.2 8.8 9.7 22 7.6 9.3 21.8 6.8 12.3 23.1 Maldives 1998 3.5 4.2 7.7 13 0.8 6.6 Maldives 2004 7.2 4.1 2.8 3.5 12.8 4.4 1.3 14.1 9.1 13.7 Mali 1994 13 5.8 21.2 12.4 19.3 14.3 11.1 18.8 39.5 16.1 17.9 Malta 2009 9.8 2.9 12.8 11.6 15.1 Malta 2010 9.7 3 1.7 13.3 2.1 12.5 2.4 0.9 14.4 Malta 2011 9.6 3.1 2.3 13.4 1.9 11.5 4.7 16.3 Malta 2012 9.8 3 0.7 12 1.8 0.4 11.5 2.7 13.4 Mauritania 2000 7.4 5.4 11.7 5.8 13.5 8 5 13.1 21.3 9.2 13.5 Mauritius 1999 12.7 3.5 9.4 10.8 23.2 3.8 8.6 22.4 13.9 23.8 Mauritius 2001 13.5 3.1 11.5 11.1 17.3 6.8 9.1 9.9 3 13.7 25.3 Mauritius 2002 12.4 3.6 11.7 8 16.7 5.9 6.5 17.4 9.7 17.1 Mauritius 2003 12.4 3.7 13.4 9 14.8 5 7.2 14.8 2.3 11.8 16.6 Mauritius 2004 14.8 3 13.9 11.6 3.9 9.5 7.2 15.8 28 Economy Year A B C D E F G H I J K Mauritius 2005 14.7 3.1 13.7 11.7 9.5 9.6 3.1 15.7 Mauritius 2006 13.5 3.8 15.6 11.5 14.1 7.5 9.5 15.9 7.9 14.6 13.3 Mauritius 2007 13.3 3.6 13.4 8 18.8 3.3 6.3 18.2 7.2 11.1 22 Mauritius 2008 13.8 3.7 12.9 7.9 18.6 6.3 6.1 18.6 6.5 10.8 21.3 Mauritius 2009 14.8 3.7 10.7 8.7 21.9 3.3 7.3 21.1 2.4 10.6 25 Mauritius 2010 15 3.7 12.6 8.7 21.2 4.5 7.1 20.5 5.1 10.6 24.4 Mauritius 2012 15.1 3.7 13.2 8.6 21.5 6.7 6.7 20.9 4.4 11.1 24.7 Mexico 1989 10.3 4.7 10.1 8.8 17.7 10.8 8.1 18.6 8.1 11.2 15.6 Mexico 1992 11.5 4.6 10.4 9.5 20.5 10.8 9 21.7 8.8 10.8 18.1 Mexico 1994 13 4.8 11.1 10.5 24.1 11 9.3 26 11 13.2 20.7 Mexico 1996 12.5 4.7 9.7 10.1 22.7 8.8 9.7 23.2 12.2 10.9 21.7 Mexico 1998 12.8 4.6 11.9 9.3 24 11.4 8.6 24.7 13.2 11.2 23 Mexico 2000 12.5 4.6 12 8.8 23.7 12.6 7.8 24.2 10.6 11.4 22.9 Mexico 2002 11.6 4.6 11 7.7 22.6 10.6 7.4 22.8 12.9 8.6 22.3 Mexico 2004 10.7 4.5 12.6 7.8 17.7 11.2 7.5 18.1 15.3 9.2 18.4 Mexico 2005 10.3 4.5 12.2 7.2 17.4 11.4 6.8 18 11.5 8.8 18 Mexico 2006 10.6 4.4 12 7.7 18.1 10.4 7 17.5 15.2 10.2 19.8 Mexico 2008 9.9 4.4 7 5.9 19.2 6.6 5.5 18.6 7.8 6.9 20.6 Mexico 2010 10.1 4.4 7.2 5.5 20.7 7 5.4 20 7.7 6 22.1 Mexico 2012 10.1 4.3 7.8 4.8 20.7 7.2 4.2 20.2 9.5 6 22 Moldova 2002 8.1 3.2 12.6 15.4 10.9 Moldova 2005 7 3.5 13.2 12.2 14.5 Mongolia 2002 6.6 2.3 4.4 6.7 3.8 6.8 7.9 7.6 Mongolia 2006 7 2.2 7.6 4.3 8.1 11.6 5.1 8.6 6 3 8 Mongolia 2007 6.6 1.8 7.6 1.2 8.3 7.4 Mongolia 2009 8.1 2.9 11.2 4.8 10.7 13.1 5.6 10.5 7.6 4.2 12.1 Mongolia 2010 9.4 2.4 9.3 5 10.9 11.9 5.8 11.2 3.1 5.2 12.1 Mongolia 2011 9.1 2.4 13.7 4.2 10.1 13.4 5.1 10.4 14.8 4.3 11.4 Morocco 1991 10 5.8 6.6 8.7 14.6 3.9 7.3 13.6 10.8 11.7 19.8 Morocco 1998 10 4.6 11.6 6.2 16.1 7.7 5.7 15.1 16.8 7.9 17.5 Mozambique 2002 13.8 3.6 23.6 5.9 6.1 22.2 6.1 3.8 29.9 5.4 15.9 Mozambique 2008 14.1 4.4 20.2 13.3 17.7 19.5 13.2 17.6 22.5 14.3 17.7 Namibia 1993 18.3 4 Nepal 1998 8.4 2.5 14.6 0.9 9.8 11.6 5.3 8.5 9.4 Nepal 2008 7.6 5.3 12.3 4.3 16.5 7.6 4.1 16.1 9.7 6.1 17.2 Nepal 2010 9.2 5.4 9.7 5.1 23.1 5.5 3.4 21.5 3.9 7.2 28 Netherlands 2005 8.9 2.9 11.5 10.6 12.4 Netherlands 2006 9.9 2.9 2.5 13.1 3.9 11.1 2.8 14.7 Netherlands 2007 8.9 2.9 3.8 11.7 4.3 10 5.2 12.7 Netherlands 2008 9.2 2.9 5.6 11.8 6.7 9.9 6 13.1 Netherlands 2009 9.3 2.8 4.7 12.5 4.9 10.6 5.9 14 Netherlands 2010 9.5 2.9 4.5 12.9 4.7 11.1 5.4 14.6 Netherlands 2011 9.6 2.9 2.2 13.3 4 11.2 1.4 14.9 Netherlands 2012 9.7 2.9 3.9 12.9 4.2 11.4 5.4 14.4 Nicaragua 1993 9.4 4.4 11.2 7 16.4 12.4 8 18 7.8 4.9 13.9 Nicaragua 1998 9 4.5 8.5 6.8 17.6 8.3 7.7 17.4 9.3 5.8 18.6 Nicaragua 2001 8.6 4.6 8.4 5.5 18.9 8.8 6.1 20.6 7.7 5.3 17 Nicaragua 2005 7.7 4.8 6 5.5 14.6 5.9 6.3 17.1 7.5 5 14 Nicaragua 2009 6 4.9 4.8 2.3 14.5 5.1 2.4 13.3 4.7 2.8 16.4 29 Economy Year A B C D EF G H I J K Niger 2002 10.9 6 5.2 11 2.6 11.1 23.7 18.9 22.3 9 19.5 Niger 2007 11.2 4.7 10.5 18 3.7 17.8 25.7 23.6 9.8 Niger 2011 14.6 4.2 38.7 29.7 40.5 6.3 35.8 25.7 11.6 28.3 Nigeria 2003 10.1 4.8 16.6 6.813 12.5 6.1 12.1 30.6 8.2 13.7 Norway 2004 9 2.2 9.9 0.3 9.6 11.1 Norway 2005 7.2 2.2 11.4 8.1 5.4 8.8 21.6 8.9 Norway 2006 8.6 2.6 7.7 9.4 6.1 10.2 11.9 10.3 Norway 2007 7.3 2.6 4 8.3 6.4 9.3 0.7 9.4 Norway 2008 7.6 2.6 0.5 8.6 9.2 10.6 Norway 2009 6.8 2.6 14.5 7.7 18.4 8.1 8.9 9 Norway 2010 8.3 2.6 40.4 5.7 9.5 60.4 6.8 9.2 16.6 4.4 11.2 Norway 2011 8.2 2.6 12 9.3 7.2 11.3 10.3 45.6 10 Norway 2012 8.9 2.6 2.6 9.9 4.3 9.6 11.9 Pakistan 1992 6.4 5.5 6.3 5.7 14.7 5 5.7 15 7.1 8.3 13.9 Pakistan 1999 6.3 5.6 7.3 4.7 14.6 4.2 5.1 14.5 11.1 7.6 19.1 Pakistan 2001 10.1 5.2 14.8 7 13.9 6.1 6.2 13.8 11.4 14.5 23.4 Pakistan 2004 9.1 5.3 14.9 6.4 14.7 8.9 6.8 13.9 10.1 10.9 22.6 Pakistan 2005 7.3 5.7 8.7 5.6 17.3 5.9 5.5 17.7 11 11.2 21.3 Pakistan 2006 9.2 5.3 13.4 6.8 16.1 8.5 6.5 16.5 15.5 13 19.9 Pakistan 2007 6.8 5.7 9.1 4.8 15.3 6.1 4.9 16.2 10.9 7 17.6 Pakistan 2008 6.8 5.7 7.6 5.5 15.4 4.2 5.5 16 11.6 9.9 19.7 Pakistan 2010 10.8 3.6 Palau 2000 12.4 3.1 6.3 5.1 15.8 12.1 5.4 14.3 5.8 18.3 Panama 1989 12.9 4.5 7 10.5 19.8 7.6 9.4 19.3 11.4 14 21 Panama 1991 12.6 4.5 1.7 9.8 20.6 2.1 8.7 20.1 5.9 12.9 22.2 Panama 1995 12.6 4.5 10.3 9.5 20.4 12.5 9.2 20.1 7.8 12.2 22.1 Panama 1997 12.3 4.5 10.5 9.3 20 11 8.7 20.1 14.2 11.9 21.5 Panama 1998 12.1 4.5 7.7 8.9 20.1 11.2 8.1 20.3 0.9 12.5 21.4 Panama 1999 11.9 4.5 9.9 8.3 20 10.7 8.1 19.9 12.4 11 21.8 Panama 2000 12.1 4.5 10.2 8 20.3 11.3 7.5 20.9 12.7 10.6 21.3 Panama 2001 12 4.5 10.7 8 20.2 11.4 7.5 20 19.6 11 21.6 Panama 2002 12.1 4.5 9.1 8.4 20.3 9.1 8.4 20.1 15.6 10.2 22.3 Panama 2003 12 4.5 8.3 8.1 20.1 10.1 8.2 19.5 5.5 9.6 22.6 Panama 2004 12 4.5 8 8.1 19.4 7.3 8.4 19 14.8 9 21.9 Panama 2005 11.5 4.4 9.9 8 18.5 11.4 7.7 18.2 9.9 10.5 20.5 Panama 2006 11.3 4.4 8.5 7.8 18.4 7.2 7.4 18.2 13 11.3 20.6 Panama 2007 10.7 4.4 12 7.6 16.8 12.4 7.6 16.3 12.8 9.8 19.4 Panama 2008 10.2 4.3 11.4 7 16.9 11.6 7.3 16.3 13.4 8.4 19.9 Panama 2009 9.9 4.2 5.3 5.4 16.5 5.8 5.4 17.4 2.7 6.5 17.1 Panama 2010 10 4.3 10.3 6.6 16.1 11.7 6.8 16.3 5.9 7.8 17.7 Panama 2011 9.5 4.4 7.9 6.4 15.5 10.6 6.6 15.9 0.7 7.5 16.9 Panama 2012 10 4.4 10.9 6.4 16.2 13.2 6.7 16.5 4.4 7.2 17.5 Papua New Guinea 2010 7.7 3.3 43.2 1.8 10 32.4 5.1 13.2 2 Paraguay 1990 12.6 4.1 8.6 11.5 18.6 7.2 18.5 12.3 14.4 20.8 Paraguay 1995 10.9 4.3 12.2 8.2 17.5 8.4 7.6 18.5 13.5 9.3 17.4 Paraguay 1997 11.5 4.1 12.1 7.3 19.4 12.7 7.6 19.2 12.2 6.6 20.6 Paraguay 1999 11.3 4.2 17.6 7.2 18 15.2 7.6 18.5 20.8 6.5 18.2 Paraguay 2001 11.8 4.4 17.4 7.3 21.6 22.2 7 23.6 7.2 7.6 19.4 Paraguay 2002 10.5 4.3 8.2 7.6 17 8.8 7.8 16.7 6.4 7.3 18.6 30 Economy Year A B C D E F G H I J K Paraguay 2003 11.2 4.4 6.6 7.4 19.9 7.4 7 20 5.2 7.7 20.7 Paraguay 2004 10.3 4.3 9.8 6.4 17.6 8.1 6 18.7 14.2 6.8 17.3 Paraguay 2005 10.9 4.3 4.7 7 19 2.6 7 19.1 6.9 6.6 20.1 Paraguay 2006 10.6 4.3 9.1 6.4 18.8 10.8 6.5 18.7 5 6.2 20.2 Paraguay 2007 9.7 4.3 2.2 6.5 15.8 2 6.4 16.2 1.1 6.7 16.3 Paraguay 2008 9.9 4.4 5.8 7.2 15.4 6.4 7.5 14.9 4.9 6.1 17.6 Paraguay 2009 9.5 4.2 0.3 5.4 16.8 4.8 16.1 6.6 18.9 Paraguay 2010 8.7 4.2 2.3 5.3 15.8 1.4 5.2 15.9 16.3 5.1 16.6 Paraguay 2011 9.3 4.3 4.8 5.2 16 7.5 4.8 16 6 17.6 Peru 1997 8.3 4 15 4.3 12.2 13.4 4.9 12.3 15.3 3 13.3 Peru 1998 9.1 4.1 19.4 6.4 12.8 15.1 6.2 14 20.1 6.4 11.5 Peru 1999 9.6 4.2 16 6.1 14.8 12.6 5.8 13.8 15.7 6.1 16.4 Peru 2000 7.4 3.9 6.1 5.8 11.7 0.5 6 10.9 10.2 4.8 13.5 Peru 2001 9.2 4.2 13.5 5.9 13.7 8.6 5.8 13.5 13.1 5.7 14.9 Peru 2002 10.3 4.1 15.6 5.8 16 11.1 6.1 15.6 14.4 4.4 17.4 Peru 2003 10 4.5 13.2 8.8 12.2 10.7 9.7 14.1 15.3 7.3 9.7 Peru 2004 10.2 4.1 12.9 5.8 15.6 15.5 5.3 15.1 7.1 6.1 17.2 Peru 2005 10.2 4.2 15.8 6.8 14 11.2 6.4 13.5 12.8 6.9 15.8 Peru 2006 10.8 4.1 17 6.6 15.7 12.9 6.1 15.6 14.6 6.7 16.5 Peru 2007 10.6 4.1 14.5 6.6 15.3 8.8 5.9 14.7 12.6 7 17.5 Peru 2008 9.5 4 13.7 6.1 13 12.8 4.8 13 9.6 7.5 14 Peru 2009 9.3 4 15.3 5.4 12.8 6.6 4.7 12.9 13.3 6 14.3 Peru 2010 8.4 4 13.3 5.6 10.8 5.3 4.7 10.5 13.6 6 12.9 Peru 2011 8 3.9 12.4 4.9 10.4 7.8 4.3 9.9 11.1 5 12.5 Peru 2012 8.1 3.9 14.6 4.9 10.4 8 3.9 10.3 16 5.4 12 Philippines 2003 8 5.4 8.9 6 20.9 10.7 6.5 18.5 5.5 5.5 26.4 Philippines 2004 8 5.4 8.8 5.9 21.2 10.3 6.3 18.9 5.7 5.4 26.6 Philippines 2005 8.1 5.3 7.9 5.9 20.5 9.8 6.3 17.8 3 5.7 26 Philippines 2006 8.6 5.3 9 6.4 22.3 10.7 6.7 19.3 5.5 6.8 28.4 Philippines 2007 8.6 5.3 9 6.4 22.3 10.7 6.7 19.3 5.5 6.8 28.4 Philippines 2008 8.4 5.2 9.7 5.7 21.1 11.7 6.1 18.3 5.2 5.7 26.7 Philippines 2009 8.6 5.3 9 5.8 23.6 10.6 6.3 20.7 6 5.4 29.8 Philippines 2010 8.6 5.3 9.7 5.9 23.5 11.2 6.4 20.6 6.6 5.6 29.7 Philippines 2011 8.6 5.3 6.4 5.8 23.2 7 6.4 20.1 3.7 6.1 29.4 Poland 2005 11.4 2.5 6.1 13.6 6.8 14.7 5.4 15.2 Poland 2006 11.8 2.4 5 14 5.8 14.8 4.4 16.4 Poland 2007 11.6 2.4 5.4 13.6 5.6 15 6 15.6 Poland 2008 10.7 2.4 4.6 12.3 15.9 4.6 13.8 5.4 14.4 Poland 2009 10.1 2.4 3 12.5 3.4 13.6 14.6 Poland 2010 10.8 2.4 5.2 3.8 12.6 4.5 4.1 13.2 9.7 4.2 15.2 Poland 2011 10.7 2.4 3.5 12.7 3.6 12.9 9 4.5 15.5 Poland 2012 10.5 2.4 5.2 3.1 12.3 3.2 3.7 15.6 Portugal 2004 11.1 3.7 17.9 6.9 17.9 8 6.4 18.4 11.5 8.5 19.1 Portugal 2005 11.7 3.7 18.6 18.6 20.4 Portugal 2006 11.3 3.7 18.1 17.9 19.9 Portugal 2007 10.9 3.7 17 17.6 18.4 Portugal 2008 10.2 3.6 15.5 14.8 17.6 Portugal 2009 10.3 3.6 15.6 14.2 18.4 Portugal 2010 9.9 3.6 15.7 14.1 18.4 31 Economy Year A B C D E F G H I J K Portugal 2011 10.1 3.7 15.8 14.9 17.9 Portugal 2012 9.2 3.8 14.5 13.3 16.8 Puerto Rico 1970 12.2 4.2 14.4 10 15.7 14.7 10.9 17.3 12.3 8.9 15.3 Puerto Rico 1980 12.7 3.9 5.8 9.1 16.7 8.4 9.6 18 8.7 16.4 Puerto Rico 1990 11.9 3.1 6.2 15.2 3 7.6 16.1 4.6 15.6 Puerto Rico 2000 10.9 3.1 0.9 4.8 14.3 3 6 15.9 2.9 15.7 Puerto Rico 2005 12.6 3 2.5 4.3 16.3 5.1 6.2 15.7 1.7 20.7 Romania 1994 5.8 3 Romania 2007 13.6 2.1 14.5 13.6 16.7 Romania 2008 12.6 2 13.2 13.1 14.7 Romania 2009 12.5 2.1 13.7 13.5 15.2 Romania 2010 11.1 2.1 12 12.4 12.9 Romania 2011 10.6 2.1 11.2 12 11.7 Romania 2012 10.3 2.1 11.2 11.5 11.9 Russian Federation 1994 3.8 1.3 3 3.7 Russian Federation 1995 4 1.2 7 Russian Federation 1996 7.6 1.2 30.5 25.2 Russian Federation 1999 3.9 1.1 27.9 34.5 Russian Federation 2000 3.7 1.1 23 16.4 Russian Federation 2001 1.5 1.1 12.6 3.1 Russian Federation 2002 0.2 1.1 22.7 Russian Federation 2003 3.2 1.1 Russian Federation 2004 3.9 1.1 16.2 20.1 Russian Federation 2005 2.2 1.1 10.6 9.8 Russian Federation 2006 3.8 1.1 Russian Federation 2007 4.8 1.1 0.9 Russian Federation 2008 5.7 1.1 Russian Federation 2009 2.6 1.1 7 6 Rwanda 1997 14.7 3.9 16.3 13.9 14.8 22.1 13.6 18.1 6.9 14.2 7.1 Rwanda 2005 17.5 4.5 16.9 17.8 35.3 15.4 16.8 34.7 19 21 34.6 Rwanda 2010 22.4 3.8 34.1 19.7 28.8 30.4 20.6 26 35.8 20.7 32.9 Senegal 2011 11.8 4.1 9.8 6.5 21.8 7.6 5.6 19.3 27.3 10.1 26.3 Serbia 2008 11.7 2.7 37.7 6.2 14 39.7 5.9 12.7 34.8 7.1 16.1 Sierra Leone 2003 4.2 4.3 6.4 15.2 6.6 11.9 6.4 29.4 Sierra Leone 2011 4.1 5.5 5.5 4.4 3.5 3.2 3.9 3.8 9.5 7 1.9 Singapore 1998 12.5 4.1 7.3 9.9 10.7 3.7 10.1 10.3 3.1 8.9 10.5 Slovak Republic 2003 9.2 1.9 10.2 10.3 10.3 Slovak Republic 2005 8.3 1.7 Slovak Republic 2006 8.9 1.7 9 9.7 Slovak Republic 2007 9.6 1.8 9.6 9.4 10.7 Slovak Republic 2008 8.6 1.7 8.2 8.2 Slovak Republic 2009 8.8 1.8 8.1 8.9 Slovak Republic 2010 8.7 1.9 8.5 8.2 Slovak Republic 2011 8 1.9 7.9 8.2 Slovak Republic 2012 8.5 1.9 8.2 8.6 9.4 Slovenia 2005 8.6 2.8 4.8 12 12.6 5.5 12.6 Slovenia 2006 9.7 2.6 6.1 4.6 13.2 4.1 13.6 33.2 5.3 14.3 Slovenia 2007 9.7 2.5 1.4 1.7 13.3 3.6 1.5 12.9 3.3 15.3 Slovenia 2008 10.2 2.4 13.2 13 14.8 32 Economy Year A B C D E F G H I J K Slovenia 2009 9 2.4 11.5 12.7 12.5 Slovenia 2010 9.9 2.4 12.2 13.9 13.1 Slovenia 2011 9.3 2.3 11.6 11.8 13.1 Slovenia 2012 9.6 2.4 11.7 12.2 13.3 Solomon Islands 2005 6 4.2 4.9 0.2 11.9 12.9 1.1 16.3 9.7 South Africa 2000 16.4 4.4 10.4 12.3 28.7 8.6 11.5 29.2 14.8 10.5 29.2 South Africa 2000 17.1 4.3 8.7 12.2 30.5 8 11.4 30 8.714.3 32.5 South Africa 2001 16.5 4.3 12.8 13.1 27.8 12.4 12.3 27.3 14.7 13.4 30.2 South Africa 2001 17.1 4.3 12.3 14 27.6 13.1 13.6 27.1 15.1 11.1 30.1 South Africa 2002 20.4 3.3 16.3 14.8 34.2 14.1 12.9 31.4 18.3 16.3 37.1 South Africa 2003 18.7 3.4 16.2 13.5 25.6 17.7 12.8 24.3 15.1 19.7 27.2 South Africa 2003 16.8 4.3 11.1 13.1 29.9 10.5 12.5 29.3 14.3 11.8 32.6 South Africa 2003 15.9 4.2 9.2 8.3 38.4 9.4 8.8 36.9 7.8 10.8 43.2 South Africa 2004 15.9 3.5 11.3 10.9 29.2 13.9 10.8 26.7 7.712.9 33.5 South Africa 2004 15.7 4.1 9.9 11.4 29.3 9.7 11.9 28.4 12.1 10.2 32.4 South Africa 2004 15.9 4.3 6.4 10.9 32.2 4.9 11.4 30.9 5.811.5 36.1 South Africa 2005 15.7 3.9 8.5 11.2 27.2 9 10.4 26.2 6.613.2 30.5 South Africa 2005 15.6 4 10.7 10.4 29.4 10.2 10.7 29.1 1011.5 31.8 South Africa 2005 6.8 2.9 3.4 5.9 4.2 0.3 3.4 24.8 3.86.4 2.3 South Africa 2006 16.1 4 12.1 11.2 27.2 13.2 10.8 27 12.3 10.2 29 South Africa 2006 3.4 2.9 2.3 11.4 6.3 1 15.9 2.6 3 South Africa 2006 16 3.9 10.2 11 28.9 12.5 10.4 28.6 4.9 13 30.8 South Africa 2007 16.3 3.9 6.8 11.2 29.9 6 11.1 31.5 6.6 12.6 30 South Africa 2007 5 2.8 8.6 3.5 18.1 2.8 7 3.7 South Africa 2007 15.7 3.8 9.8 10.6 27.2 9.6 9.8 25.3 9.2 13.1 30.6 South Africa 2008 6.6 2.9 9 3.9 1.4 0.8 12.8 5.3 South Africa 2009 19 3 18.2 10.8 35.8 35.3 10.5 35.4 12.5 36.4 South Africa 2010 19.1 3 14.8 11.4 32.9 4.5 11.7 31.8 15.4 11.3 35.2 South Africa 2011 21.1 3 8.9 12.3 39.5 3 12.5 40.2 20.4 12.7 39.5 Spain 2004 7.2 3.6 10.6 9.1 14.4 Spain 2005 7 3.7 11.4 9.9 15.3 Spain 2006 6.9 3.7 10.7 9.4 14 Spain 2007 6.9 3.6 10.7 9.3 14.2 Spain 2008 7 3.6 10.5 8.9 13.6 Spain 2009 7.9 3.5 12 10.1 15.3 Spain 2010 8.4 3.5 12.2 10.7 15.2 Spain 2011 7.7 3.5 11.5 9.8 15 Spain 2012 7.8 3.4 11.6 9.7 14.9 Sri Lanka 1993 23.8 1.6 11.8 17.1 12.5 17.5 6.3 18.1 Sri Lanka 1994 24.4 1.5 18.3 13 16.4 13.3 16.7 13.3 Sri Lanka 1995 26.1 1.5 17.9 12.7 12.8 11.2 16.8 15.3 Sri Lanka 1996 9.8 3.9 5.3 8.6 18.6 1.5 7.8 19.1 2.1 10.3 19.6 Sri Lanka 1998 9.7 3.8 4.6 7.8 21.1 2.6 7.2 21.7 0.4 8 23.1 Sri Lanka 1999 8.9 3.7 4.7 7.7 18.3 1.9 6.6 19.9 2.9 9.6 17.2 Sri Lanka 2000 10.2 3.7 4.1 8.8 21.9 3 7.3 22.3 12.2 23.2 Sri Lanka 2001 9.9 3.6 3.5 9.2 15 6 7.9 14.5 11.4 16.7 Sri Lanka 2002 10.3 3.8 4.6 8.8 18.1 3 7.8 19.6 0.3 10.6 18.5 Sri Lanka 2003 8.5 3.8 3.8 7.1 16.7 2.7 6.6 16.3 7.9 19 Sri Lanka 2004 8.6 4.2 5.9 8.8 14.9 3.5 7.8 14.5 1 12 16.7 33 Economy Year A B C D E F G H I J K Sri Lanka 2006 12.8 3.3 3.7 9.2 14.5 8.5 13.8 2.9 10.3 17 Sri Lanka 2006 9.5 4 5.7 5.9 15.1 6.3 5.5 14.4 0.9 5.7 19.4 Sri Lanka 2008 10.3 3.8 6.5 6.7 15 3.7 6.1 13.4 3 8.5 21.1 Sri Lanka 2009 9.5 3.7 5.8 5.6 14.1 6.4 5.2 13.2 4.3 20.7 Suriname 1999 9 4.5 3.8 9.4 13.9 10.114.1 8.8 8.5 15.3 Swaziland 2000 14.8 4.4 11.2 23.5 11.321.3 12.5 27.4 Sweden 2004 5.7 2.6 7.4 7.3 8.9 Sweden 2005 4.4 2.5 5.7 6.7 6.9 Sweden 2006 4.6 2.6 6.5 6.7 7.8 Sweden 2007 4.7 2.5 6.6 6.6 8.2 Sweden 2008 4.6 2.4 6.3 6.6 7.8 Sweden 2009 4.4 2.4 5.6 6 7.2 Sweden 2010 4.2 2.4 5.2 5.2 6.8 Sweden 2011 5.2 2.4 5.4 6.1 6.5 Sweden 2012 4.7 2.4 5.6 5.3 7.5 Switzerland 2011 11.8 3.1 10.3 13.6 12.1 11.2 2 8.1 12.5 Switzerland 2012 11.6 3.1 10.2 13.6 11.8 11.1 8.6 12.4 Syrian Arab Republic 2004 4.4 5.6 8.9 3.4 7.4 5.4 3.5 6.8 17.1 5.8 8.5 São Tomé and Principe 2000 7.4 3 16.2 2.4 11.1 0.5 9.8 São Tomé and Principe 2010 8.4 3.2 7.9 10.8 Tajikistan 2003 9 2.8 9.2 2.1 12.9 5.4 8.9 2.9 2.8 16.2 Tanzania 2000 15.2 3.2 25.4 12.7 14 20.4 12.6 12.2 39.6 13.6 26.9 Tanzania 2006 15 3.8 27.9 13.3 16.7 24.3 11.8 18.2 34.6 17.8 13.6 Tanzania 2009 18.4 3.7 33.4 14.1 23.7 28.5 10.8 23.7 24.8 22.2 23.7 Tanzania 2011 16.6 4 14.6 15 19.4 12.6 4.8 18.3 18.7 Thailand 1977 10.3 4 9.9 9.4 13 5.3 7.8 11.9 5.8 12.6 15.6 Thailand 1981 9.9 4.1 11.3 9.7 21.5 9.2 8.3 21.5 7.1 12 22.3 Thailand 1982 10.6 4 13 10.7 21.8 9.8 9.1 21.5 8.9 13.2 23 Thailand 1983 10.8 4.3 14.4 10.4 16.2 15 8.5 15.4 7.7 13.2 18.4 Thailand 1984 10.3 4.3 16.4 8.9 16.2 12.1 7.6 15.9 10.5 10.9 17 Thailand 1986 10.7 4.6 13.8 10.3 14 13.6 9 13.1 7.8 10.9 17.5 Thailand 1987 10.8 4.4 11.6 9.5 15.4 9.4 8.1 14.1 7.4 11.3 18.8 Thailand 1988 10.6 4.6 11.4 9 16.5 9.4 7.8 14.2 8.6 9.8 21.2 Thailand 1989 10.8 4.4 13.8 9.4 14.2 13.9 8.2 12.8 8.2 10.3 18.2 Thailand 1990 18.1 4.4 22.4 19.1 16.8 19.6 15.6 18.9 12.6 22.8 14.7 Thailand 1990 18.1 4.4 22.4 19.1 16.8 19.6 15.6 18.9 12.6 22.8 14.7 Thailand 1991 11.1 4.3 13.5 9.4 15.7 14.2 8.6 14.6 7.1 9.7 18.4 Thailand 1994 14.6 4.6 26.3 12.9 17.4 28.1 11.6 18.7 14.3 13.8 17.2 Thailand 2000 16 4.8 19.2 15.7 20.3 17.4 14.5 21.3 13.5 16.5 19.8 Thailand 2002 15.7 4.7 17.5 13.5 20.5 18.5 11.6 21.6 12 15.3 19.8 Thailand 2006 14.5 4.7 12.8 12 22.5 14.7 10.5 22.9 6.6 13.5 23.2 Thailand 2009 13.6 4.7 9.7 10.5 22.7 6.8 9.5 23.4 7.8 11.3 23.3 Thailand 2011 9.4 4.8 3.2 5.4 17.2 2.7 4.6 16.6 1.4 5.9 19.2 Timor-Leste 2001 5.5 4.7 Timor-Leste 2007 7.3 4.6 25.7 4.8 8.2 26.8 5.8 8 20 0.8 7.3 Togo 2006 9.6 4.9 16.8 5.1 9.6 5.7 25.9 4.5 Togo 2011 12.2 5.3 15 8.2 2.8 5.7 11.6 12.1 Tunisia 2001 8.5 5.2 12.3 8.1 17.4 11.4 7.9 16.7 11.4 8 18.7 Turkey 2002 10.8 4.2 13.8 8.2 18.3 10.6 7.6 18.1 7.9 11.1 19.5 34 Economy Year A B C D E F G H I J K Turkey 2002 12 3.9 20.2 9.8 13.6 15.2 8.7 12.9 10.9 15.3 15.9 Turkey 2003 11.4 3.9 15.5 8.7 14.5 9.4 8.1 14 10 12.4 16.8 Turkey 2003 10.1 4.2 12 7.5 17.6 9.4 6.9 17.5 2.6 11.2 18.6 Turkey 2004 11 4 18.2 8.5 12.9 11 7.4 12.1 14.7 12.6 15.5 Turkey 2004 8.5 4.2 9.8 6.1 15.5 7.1 5.5 15.3 5.1 9.6 16.3 Turkey 2005 8.7 4.3 11.2 5.8 16 8.9 5.3 15.8 6.3 8.9 16.9 Turkey 2005 10 3.9 15.8 7.3 12.6 11.3 6.5 12.4 8.2 10.7 14.4 Turkey 2006 9.1 3.8 11.2 6 13.2 10.5 5.8 12.7 2.1 7.7 16 Turkey 2006 8.6 4.3 8.5 5.5 16.4 7.2 5 16.4 1.6 8.7 17.4 Turkey 2007 8.5 4.3 8.3 5.1 16.6 6.5 4.6 16.6 2.8 8.1 17.7 Turkey 2007 9.9 3.9 11.9 7.3 13.7 10.2 5.9 13.3 3.2 13.4 15.6 Turkey 2008 8.6 4.4 8.3 5 17 7.3 4.5 17.1 1.5 8.5 17.6 Turkey 2008 10 4 15.4 7.1 12.3 13.3 5.9 11.7 5.5 11.4 16.2 Turkey 2009 9.2 4.3 7.7 5.2 17.8 7.8 4.6 18.1 8.9 18.3 Turkey 2009 11.3 4.1 15.2 8.2 14.6 14.5 7 13.7 2.4 12.6 18.2 Turkey 2010 9.3 4.3 6.5 5 18.5 5.2 4.4 18.8 1.7 8.4 19 Turkey 2010 10.7 4.1 14.2 7.3 14.7 8.9 5.9 14.5 10.1 11.7 17 Turkmenistan 1998 7.2 2.6 10.7 8.3 7 1.5 5.5 15.8 12.7 Tuvalu 2010 13.4 3.2 Uganda 1992 9.6 4.7 Uganda 2005 16.9 4.5 19.7 15 23.4 13.9 14.3 23.4 13.5 17.3 24.1 Uganda 2010 15.9 4.5 24.8 16.7 22.2 16.3 31.9 18.8 Ukraine 2000 10.8 2.7 10.1 8.1 12.1 7.8 13.6 26 8.6 11.5 Ukraine 2001 9.6 2.4 6.6 4.1 7.8 7.5 3.9 10.4 Ukraine 2002 8.6 2.3 4 Ukraine 2003 8.4 2.3 3.5 7.2 7.3 8 1.2 5.9 7.4 Ukraine 2005 6.8 2.2 5.1 United Kingdom 2005 8 2.4 United Kingdom 2006 7.6 2.5 United Kingdom 2007 10.8 2.2 United Kingdom 2008 11.8 2.3 United Kingdom 2009 11.4 2.4 United Kingdom 2010 9 2.4 United Kingdom 2011 11.3 2.4 United Kingdom 2012 11.9 2.3 United States 1990 11.8 2.6 4.1 3.6 12.2 6.6 5.9 11.7 3.8 12.9 United States 2000 12.4 2.6 1.6 4.5 12.7 3.3 6 12.9 5 13.5 United States 2005 13.8 2.7 4.7 14.8 5.9 14.9 6 16.1 United States 2010 13.3 2.8 4.8 14.6 6.1 15.1 5 15.7 Uruguay 1989 9.2 3.7 8.3 6.7 11.1 1.6 6.3 10.8 5.6 7.3 11.9 Uruguay 1992 9.7 3.7 10.3 5.8 16.7 11.4 5.5 17.6 4.6 6.4 17.7 Uruguay 1995 10.6 3.7 7.6 6.4 17.5 8.8 6.3 18.4 4.8 7 18.3 Uruguay 1996 10.9 3.8 11 6.5 17.9 14 6.6 18.9 5.5 6.9 18.5 Uruguay 1997 10.9 3.7 6.5 6.4 17.7 3.6 6.4 18.4 10.9 6.8 18.2 Uruguay 1998 10.5 3.7 8.8 5.8 18 16.7 6 18.4 5.7 19.2 Uruguay 2000 10.7 3.7 5.6 18.6 3.3 5.7 19.4 5.6 19.3 Uruguay 2001 11.2 3.8 18.3 19 18.7 Uruguay 2002 10.9 3.9 17.3 18.2 17.3 Uruguay 2003 11.1 3.9 17.9 18.5 18.4 35 Economy Year A B C D E F G H I J K Uruguay 2004 11.5 3.9 18.2 18.7 19.1 Uruguay 2005 11.4 3.8 17.7 17.3 18.8 Uruguay 2006 11.2 3.8 4.4 5.6 19.2 5.3 6 19.9 4 5.6 20.1 Uruguay 2007 11.3 3.8 4.4 5.7 19.4 4.5 6 19.2 5.9 6 21.1 Uruguay 2008 10.1 3.8 7.1 5.2 17 9.3 5.6 18.7 3.7 5.8 17.7 Uruguay 2009 11.1 3.8 5.4 18.2 5.6 17.2 6.2 20 Uruguay 2010 10.9 3.7 9.9 5.4 18.9 11.2 5.3 18.6 8.6 6.5 20.6 Uruguay 2011 10.2 3.8 8.5 5 17.2 8 5 16.6 13.6 6.1 19.2 Uruguay 2012 9.8 3.6 4 4.8 15.7 5.4 4.5 15.4 2.5 6.1 17.5 Venezuela, RB 1989 9.5 4.2 12.8 7 15.4 13.1 6.3 15 14.3 9.6 16.3 Venezuela, RB 1992 8.1 4.3 0.8 0.8 0.8 Venezuela, RB 1995 8.3 4.2 10.7 5.6 14.5 11.6 5.6 14.4 11 7 15.3 Venezuela, RB 1998 8.8 4.2 8.8 5.5 15.9 9.6 5.6 16.6 8.9 6.9 16.5 Venezuela, RB 1999 9.1 4.3 9 6 16 10.6 5.8 15.5 4.9 7.9 17.7 Venezuela, RB 2000 7.5 4.4 6.7 4.9 13.7 6.3 5 12.7 8.6 5.2 15.2 Venezuela, RB 2001 9.2 4.3 8.6 5.2 17 9 5.1 16.3 8.6 6.4 18.5 Venezuela, RB 2002 9.5 4.3 9.4 5.8 16.8 9.6 5.7 16.4 10.7 6.9 18.1 Venezuela, RB 2003 9.1 4.3 8.8 5.7 15.9 8.9 5.6 15.7 9.3 6.7 16.9 Venezuela, RB 2004 8.9 4.3 9.9 5.7 14.9 9.8 5.5 14.9 12.1 6.8 15.7 Venezuela, RB 2005 8.2 4.3 10.3 5.2 13.5 10.2 5 13.3 12.7 6.8 14.7 Venezuela, RB 2006 7.3 4.3 8.1 4.3 12.6 8.2 4.1 12.3 10.8 6.3 14.2 West Bank and Gaza 1998 1.4 3.9 7.9 0.7 0.1 4.5 1.1 0.2 11.3 0.3 12.7 West Bank and Gaza 1999 1.8 3.8 6.1 1.2 0.2 3.7 1.4 0.4 7.8 2.9 12.7 West Bank and Gaza 2000 1.6 3.9 5.8 0.5 0.7 3.2 0.8 0.7 9.7 3.5 11.5 West Bank and Gaza 2001 0.7 3.9 1.5 1.6 1.9 8.9 2.3 4.8 West Bank and Gaza 2002 2.8 3.9 11.6 5.1 9 5.1 10 14.5 West Bank and Gaza 2003 3 3.9 10.5 0.4 4.2 9.9 0.7 4.1 1.3 5.6 12.9 West Bank and Gaza 2004 4.3 3.9 11 1 5.6 6.3 1.3 5.4 3.1 22.6 15 West Bank and Gaza 2005 4 3.8 17 1.1 5 11 1.2 5.3 2.6 22.6 14.4 West Bank and Gaza 2006 5 3.9 13.4 1.7 5.8 12.4 1.9 5.7 1.8 6.7 17.6 West Bank and Gaza 2007 5 3.8 8.4 1.6 5.9 7.4 1.7 6 4.5 1.1 12.9 West Bank and Gaza 2008 3.8 3.8 28.7 0.2 5.5 29.7 0.9 5.2 14 21 Yemen, Rep. 2005 5.4 3.9 3.8 3.7 8 Zambia 1998 12.9 3.4 9.2 10.6 12 9.5 10 12.4 6.3 13.2 9.7 Zambia 2003 19.2 3.2 13.6 12.1 24.2 14 11.6 25.6 10.3 13.7 23.4 Zambia 2010 12.6 4 8.2 18.2 9.5 19.6 2.9 8.1 16.6 A educyT Return to another year of schooling B edusdT Standard deviation of return to another year of schooling C educyL_P_T Returns to education total primary D educyL_S_T Returns to education total secondary E educyL_T_T Returns to education total tertiary F educyL_P_M Returns to schooling male primary G educyL_S_M Returns to schooling male secondary H educyL_T_M Returns to schooling male tertiary I educyL_P_F Returns to schooling female primary J educyL_S_F 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