metadata: authors: 0: author: Montenegro,Claudio E.
1: author: Patrinos,Harry Anthony
count: World
docna: 0: docna: Comparable estimates of returns to schooling
            around the world
docty: Policy Research Working Paper
subtopic: Economic Theory & Research,Industrial Economics,Labor Markets,Tertiary Education,Educational Sciences,Gender and Development,Economic Growth,Rural Labor Markets
teratopic: Education
abstracts: cdata!: Rates of return to investments in
            schooling have been estimated since the late 1950s. In the
            60-plus year history of such estimates, there have been
            several attempts to synthesize the empirical results to
            ascertain patterns. This paper presents comparable
            estimates, as well as a database, that use the same
            specification, estimation procedure, and similar data for
            139 economies and 819 harmonized household surveys. This
            effort to compile comparable estimates holds constant the
            definition of the dependent variable, the set of control
            variables, the sample definition, and the estimation method
            for all surveys in the sample. The results of this study
            show that (1) the returns to schooling are more concentrated
            around their respective means than previously thought; (2)
            the basic Mincerian model used is more stable than may have
            been expected; (3) the returns to schooling are higher for
            women than for men; (4) returns to schooling and labor
            market experience are strongly and positively associated;
            (5) there is a decreasing pattern over time; and (6) the
            returns to tertiary education are highest.
repnme: repnme: Comparable estimates of returns to
            schooling around the world
display_title: Comparable estimates of returns to
            schooling around the world
listing_relative_url: /research/2014/09/20173085/comparable-estimates-returns-schooling-around-world
topicv3: Economic Growth m1326241 471,Tertiary Education m1326349 482,Labor Markets m1326488 855,Education m1327048 470,Gender m1327621 615
publishtoextweb_dt: 2014-09-01T00:00:00Z
historic_topic: Education
no_of_pages: 41
author_keys: 0: author_key: 99069
1: author_key: 95903
model_extractions: 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 estimated since the late 1950s. In the 60-plus year history of such estimates, there have been several attempts to synthesize the empirical results to ascertain patterns. This paper presents comparable estimates, as well as a database, that use the same specification, estimation procedure, and similar data for 139 economies and 819 harmonized household surveys. This effort to compile comparable estimates holds constant the definition of the dependent variable, the set of control variables, the sample definition, and the estimation method for all surveys in the sample. The results of this study show that (1) the returns to schooling are more concentrated around their respective means than previously thought; (2) the basic Mincerian model used is more stable than may have been expected; (3) the returns to schooling are higher for women than for men; (4) returns to schooling and labor market experience are strongly and positively associated; (5) there is a decreasing pattern over time; and (6) the returns to tertiary education are highest.

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.

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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: where _Ln(wi)_ is the natural log (of hourly or annual, depending on data) earnings for the _i_ th individual;<sup>_S_</sup> _i_<sup>is years of schooling (as a continuous variable);</sup> _X i_ is labor market 2 potential experience (estimated as _agei_ - Si - 6); _Xi_ 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: 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: 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: 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
<!-- Start of picture text --> By periods 15701989<br>, 5%<br><!-- End of picture text -->
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**<br>|**the returns to s**<br>|**chooling**||
|---|---|---|---|
|**Variable**|**Mean**||**N**|
|Years of schooling total|10.1|(3.3)|819|
|Years of schooling male|9.6|(3.2)|819|
|Years of schoolingfemale|11.7|(3.3)|819|
|Primary schooling total|10.6|(6.4)|547|
|Secondary schooling total|7.2|(3.6)|619|
|Tertiaryschoolingtotal|15.2|(5.8)|762|
|Primary schooling male|10.0|(6.6)|543|
|Secondary schooling male|7.1|(3.8)|614|
|Tertiaryschoolingmale|15.2|(5.8)|745|
|Primary schooling female|10.9|(7.6)|519|
|Secondary schooling female|8.7|(4.6)|607|
|Tertiaryschoolingfemale|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**

<!-- Start of picture text --> male female<br>9.6<br>years of education<br>11.7<br>10.0<br>primary<br>10.9<br>7.1<br>secondary<br>8.7<br>15.2<br>tertiary<br>16.8<br><!-- End of picture text --> 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**

<!-- Start of picture text --> Total sample Male sample<br>0 10 20 30 0 10 20 30<br>Returns to schooling Returns to schooling<br>Female sample<br>0 10 20 30<br>Returns to schooling<br>.15 .2<br>.15<br>.1<br>.1<br>Density Density<br>.05<br>.05<br>0 0<br>.15<br>.1<br>Density<br>.05<br>0<br><!-- End of picture text --> 9
**Figure 3 (cont’d): Returns to Schooling by Level**

<!-- Start of picture text --> Primary Secondary<br>0 10 20 30 40 50 0 10 20 30 40 50<br>Returns to schooling level: Primary Returns to schooling level: Secondary<br>Tertiary<br>0 10 20 30 40 50<br>Returns to schooling level: Tertiary<br>.15 .15<br>.1 .1<br>Density Density<br>.05 .05<br>0 0<br>.15<br>.1<br>Density<br>.05<br>0<br><!-- End of picture text --> 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.

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**Table 2: Highest and Lowest Returns to Schooling by Economy**

||**Overall**||**Male**||**Female**||
|---|---|---|---|---|---|---|
||**Economy**<br>Afghanistan|**Return**<br>1.6|**Economy**<br>Armenia|**Return**<br>0.8|**Economy**<br>Afghanistan|**Return**<br>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 SubSaharan 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)**

||**Ave**<br>|**rage return**<br>**schooling**<br>|**s to**<br>|**Aver**<br>|**age yea**<br>|**rs of scho**<br>|**oling**<br>|
|---|---|---|---|---|---|---|---|
|**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
<!-- Start of picture text --> All economies<br>Middle East & North Africa<br>Europe & Central Asia<br>South Asia<br>female<br>= male<br>Latin America & Caribbean = total<br>East Asia & Pacific<br>High Income economies<br>Sub-Saharan Africa<br>0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0<br><!-- End of picture text -->
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**

<!-- Start of picture text --> Total sample Male<br>0 5 10 15 20 0 5 10 15 20<br>Average schooling Average schooling<br>Female<br>0 5 10 15 20<br>Average schooling<br>25<br>25<br>20<br>20<br>15 15<br>10 10<br>Returns to schooling Returns to schooling<br>5 5<br>0 0<br>30<br>20<br>Returns to schooling 10<br>0<br><!-- End of picture text --> 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**

<!-- Start of picture text --> Total sample Male sample<br>0 5 10 15 20 25 0 5 10 15 20 25<br>Return to schooling Return to schooling<br>Female sample<br>0 10 20 30<br>Return to schooling<br>6 6<br>4 4<br>2 2<br>Returns to experience 0 Returns to experience 0<br>-2 -2<br>8<br>6<br>4<br>2<br>Returns to experience<br>0<br>-2<br><!-- End of picture text --> 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**

<!-- Start of picture text --> Returns to schooling<br>1970 1980 1990 2000 2010<br>Year<br>25<br>20<br>15<br>10<br>Returns to schooling<br>5<br>0<br><!-- End of picture text --> 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.

**<u>Table 4. Returns to Schooling and Average Years of Schooling by Period</u>**

||**Returns to**<br>**Schooling**|**Average**<br>**years of**<br>**schooling**|**Number of**<br>**surveys**|
|---|---|---|---|
|**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
<!-- Start of picture text --> 20<br>18<br>16<br>i4<br>12<br>10<br>3<br>6<br>4<br>2<br>o<br>1982 1983 1984 1985 1956 1987 1958 1989 19950 1991 1992 1995 1994 1995 1996 1997 1998 1999 2000 2001 2002 2008 2004 2005 2006 2007 2008 2009 2010 2011 2012<br>—— Average returns to schooling ——Average years of education<br><!-- End of picture text -->
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**

<!-- Start of picture text --> Returns to schooling<br>1950 1960 1970 1980 1990 2000 2010<br>Year<br>This paper Fitted values<br>Psararopoulos and Patrinos Fitted values<br>30<br>20<br>10<br>Returns to schooling<br>0<br><!-- End of picture text --> 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 Tab**<br>|**le 1: R**<br>|**eturn**<br>|**s to Sch**<br>|**ooling**<br>|**by Eco**<br>|**nomy a**<br>|**nd Per**<br>|**iod** <br>||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|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<br>|1997<br>|8.4<br>|3.8<br>||2.9<br>|13.2<br>||3.3<br>|14.8<br>||1.9<br>|11.6<br>|
|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|
|<br>Belgium|2007|6.3|2.8|||7.8|||7|||10.6|
|<br>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|
|<br>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|
|||||2|1||||||||
|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|
|<br>Bulgaria|2003|7.8|2.9|0.7|5|7.7||5.2|8.5|3.1|5.3|8.3|
|<br>Bulgaria|2007|6.5|2.5|5.9|4.3|7.9|6.8|4.2|8.2|13.9|4.3|9.5|
|<br>Bulgaria|2008|8|2.6|2.1|8.3|9.2|0.3|8.2|9.1|2.5|8.3|11.3|
|<br>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|19.8|19.2|
|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|4|16.6|
|Cambodia|2007|5.6|4.3|0.9|3.5|15||2.5|15.7|3.4|4.7|14.2|
|Cambodia|2008|4.3|4.4||2.5|20.7||1|20.8||4|20.5|
|Cameroon|2001|14.1|4.3|16.9|12.1|23.2|15.5|12.5|21.2|22.4|12.8|28.2|
|Cameroon|2007|11.6|4.3|11.1|8.9|21.7|9.9|9.3|21|24.1|10.1|23.4|
|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||||
|<br>Czech Republic|2006|11.7|1.7|||11.4|||11.4||||
|<br>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|
|<br>Czech Republic|2010|9.6|1.7|||9.7||||||10.1|
|Czech Republic|2011|10.7|1.7||||||||||
|<br>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|<br>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|
|<br>Dominican Republic|1997|7.3|5|6.7|5.5|13|7.4|5.1|13.3|4.9|6.7|13.6|
|<br>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|
|<br>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|
|<br>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|
|<br>Dominican Republic|2008|9.7|4.7|8.3|4.5|17.8|9|4.4|18.3|7|4.9|18.5|
|<br>Dominican Republic|2009|9.8|4.6|10.1|5.4|16.9|10.9|5.6|16|9.9|5.4|19.2|
|<br>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|<br>7.1|
|<br>Estonia|<br>2005|<br>7.7|<br>2.2|||<br>6.2||<br>10||||<br> <br>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||
|<br>Germany|2005|11|2.3|||10|||9.7|||10.3|
|Germany|2006|13.2|2.3|||12.1|||10.8|||13.6|
|<br>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|
|<br>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|<br>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|
|<br>Hungary|2005|13.3|2.2||9.4|16||11.1|17|16.5|4.4|16.1|
|<br>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|
|<br>Hungary|2010|13.7|2.2|||14.6|||16|||15|
|Hungary|2011|12.6|2.1|||13|||14.3|||13.4|
|<br>Hungary|2012|13.2|2.1|||13|||14|||14|
|<br>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|
|<br>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|
|<br>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|
|<br>Italy|2009|7.1|2.8|3.5|4.9|8.3|9.2|4.4|8.7||6.6|9.8|
|<br>Italy|2010|6.7|2.8|1.5|4.9|7.7|4.8|4.6|8.3||6.5|9.2|
|<br>Italy|2011|7|2.7|1.3|6.2|7.4|5.9|5.1|8||9.5|9|
|<br>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|2.8|23.9|||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|
|<br>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|
|<br>Latvia|<br>2007|<br>9.7|<br>2.2|8.1|5.8|<br>8.8|8.9|8.6|<br>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|
|<br>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|
|<br>Madagascar|1993|12.4|4.5|13.9|9.8|20.2|11.2|8.8|16|11.5|13.8|27.5|
|<br>Madagascar|1997|9.3|4.3|11.2|8.6|8.8|12.8|6.9|8.1|5.5|10.5|<br>9.7|
|Madagascar|2001|10.5|4.6|6.7|11|13.3|7.8|10.4|13.7|5.2|11|12.1|
|<br>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|
|<br>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|<br>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|<br>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|<br>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|
|<br>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||
|<br>Mongolia|2009|8.1|2.9|11.2|4.8|10.7|13.1|5.6|10.5|7.6|4.2|12.1|
|<br>Mongolia|2010|9.4|2.4|9.3|5|10.9|11.9|5.8|11.2|3.1|5.2|12.1|
|<br>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|
|<br>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|
|<br>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|E|F|G|H|I|J|K|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Niger|2002|10.9|6|5.2|11|22.3|2.6|11.1|23.7|18.9|9|19.5|
|<br>Niger|2007|11.2|4.7|10.5|18||3.7|17.8||25.7|23.6|<br>9.8|
|Niger|2011|14.6|4.2|38.7|6.3|29.7|40.5||35.8|25.7|11.6|28.3|
|Nigeria|2003|10.1|4.8|16.6|6.8|13|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|<br>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|
|<br>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|<br>10|
|Norway|2012|8.9|2.6||2.6|9.9|4.3||9.6|||11.9|
|<br>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|||
|<br>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|
|<br>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|
|<br>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|
|<br>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|
|<br>Philippines|2004|8|5.4|8.8|5.9|21.2|10.3|6.3|18.9|5.7|5.4|26.6|
|<br>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|
|<br>Philippines|2007|8.6|5.3|9|6.4|22.3|10.7|6.7|19.3|5.5|6.8|28.4|
|<br>Philippines|2008|8.4|5.2|9.7|5.7|21.1|11.7|6.1|18.3|5.2|5.7|26.7|
|<br>Philippines|2009|8.6|5.3|9|5.8|23.6|10.6|6.3|20.7|6|5.4|29.8|
|<br>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|
|<br>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|
|<br>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|<br>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|
|<br>Slovak Republic|2003|9.2|1.9|||10.2|||10.3|||10.3|
|<br>Slovak Republic|2005|8.3|1.7||||||||||
|<br>Slovak Republic|2006|8.9|1.7|||9|||9.7||||
|<br>Slovak Republic|2007|9.6|1.8|||9.6|||9.4|||10.7|
|Slovak Republic|2008|8.6|1.7|||8.2|||8.2||||
|<br>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|
|<br>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|16.3|1.1|9.7|
|South Africa|2000|16.4|4.4|10.4|12.3|28.7|8.6|11.5|29.2|10.5|14.8|29.2|
|South Africa|2000|17.1|4.3|8.7|12.2|30.5|8|11.4|30|8.7|14.3|32.5|
|South Africa|2001|16.5|4.3|12.8|13.1|27.8|12.4|12.3|27.3|13.4|14.7|30.2|
|South Africa|2001|17.1|4.3|12.3|14|27.6|13.1|13.6|27.1|11.1|15.1|30.1|
|South Africa|2002|20.4|3.3|16.3|14.8|34.2|14.1|12.9|31.4|16.3|18.3|37.1|
|South Africa|2003|18.7|3.4|16.2|13.5|25.6|17.7|12.8|24.3|19.7|15.1|27.2|
|South Africa|2003|16.8|4.3|11.1|13.1|29.9|10.5|12.5|29.3|11.8|14.3|32.6|
|South Africa|2003|15.9|4.2|9.2|8.3|38.4|9.4|8.8|36.9|10.8|7.8|43.2|
|South Africa|2004|15.9|3.5|11.3|10.9|29.2|13.9|10.8|26.7|7.7|12.9|33.5|
|South Africa|2004|15.7|4.1|9.9|11.4|29.3|9.7|11.9|28.4|10.2|12.1|32.4|
|South Africa|2004|15.9|4.3|6.4|10.9|32.2|4.9|11.4|30.9|5.8|11.5|36.1|
|South Africa|2005|15.7|3.9|8.5|11.2|27.2|9|10.4|26.2|6.6|13.2|30.5|
|South Africa|2005|15.6|4|10.7|10.4|29.4|10.2|10.7|29.1|10|11.5|31.8|
|South Africa|2005|6.8|2.9|3.4|5.9|4.2|0.3|3.4|24.8|3.8|6.4|2.3|
|South Africa|2006|16.1|4|12.1|11.2|27.2|13.2|10.8|27|10.2|12.3|<br>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|<br>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|
|<br>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|
|<br>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|
|<br>Sri Lanka|<br>2004|<br>8.6|<br>4.2|<br>5.9|<br>8.8|<br>14.9|<br>3.5|<br>7.8|<br>14.5|1|<br>12|<br>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||10.1|14.1|8.8|8.5|15.3|
|Swaziland|2000|14.8|4.4||11.2|23.5||11.3|21.3||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|
|<br>São Tomé and Principe|2000|7.4|3|16.2|2.4||11.1|0.5||9.8|||
|<br>São Tomé and Principe|2010|8.4|3.2||7.9||||||10.8||
|<br>Tajikistan|2003|9|2.8|9.2|2.1|12.9|5.4||8.9|2.9|2.8|16.2|
|<br>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||
|<br>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|
|<br>Turkey|2003|11.4|3.9|15.5|8.7|14.5|9.4|8.1|14|10|12.4|16.8|
|<br>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|
|<br>Turkey|2007|8.5|4.3|8.3|5.1|16.6|6.5|4.6|16.6|2.8|8.1|17.7|
|<br>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|
|<br>Turkey|2008|10|4|15.4|7.1|12.3|13.3|5.9|11.7|5.5|11.4|16.2|
|<br>Turkey|2009|9.2|4.3|7.7|5.2|17.8|7.8|4.6|18.1||8.9|18.3|
|<br>Turkey|2009|11.3|4.1|15.2|8.2|14.6|14.5|7|13.7|2.4|12.6|18.2|
|<br>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|
|<br>Uganda|2010|15.9|4.5|24.8|16.7||22.2|16.3||31.9|18.8||
|<br>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||||||||||
|<br>United Kingdom|2006|7.6|2.5||||||||||
|<br>United Kingdom|2007|10.8|2.2||||||||||
|<br>United Kingdom|2008|11.8|2.3||||||||||
|<br>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|
|<br>Uruguay|1996|10.9|3.8|11|6.5|17.9|14|6.6|18.9|5.5|6.9|18.5|
|<br>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|
|<br>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|
|<br>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|
|<br>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|5.6|1.3|12.9|
|West Bank and Gaza|2004|4.3|3.9|11|1|5.6|6.3|1.3|5.4|22.6|3.1|15|
|West Bank and Gaza|2005|4|3.8|17|1.1|5|11|1.2|5.3|22.6|2.6|14.4|
|West Bank and Gaza|2006|5|3.9|13.4|1.7|5.8|12.4|1.9|5.7|6.7|1.8|17.6|
|West Bank and Gaza|2007|5|3.8|8.4|1.6|5.9|7.4|1.7|6|1.1|4.5|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||
|<br>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 Returns to schooling female secondary K educyL_T_F Returns to schooling female tertiary 36