World Bank Reprint Series: Number 362 George Psacharopoulos Retums to Education: A Further International Update and hnplications Reprinted with permission from The Journal of Human Resources, vol. XX, no. 4 (Fall 1985), pp. 584-604, published by The University of Wisconsin Press. RETURNS TO EDUCATION: A FURTHER INTERNATIONAL UPDATE AND IMPLICATIONS* GEORGE PSACHAROPOULOS ABSTRACT This paper updates evidence on the returns to investment in education by adding estimates for new countries and refining existing estimates to bring the total number of country cases to over 60. The new cross-country evi- dence confirms and reinforces earlier patterns, namely, that returns are highest for primary education, the general curricula, the education of women, and countries with the lowest per capita income. The findings have im- portant implications for directing future investment in education which, for efficiency and equity purposes, should concentrate on these priority areas. Estimates of the profitability of investment in human capital have pro- liferated since the field was established in the early 1 960s. Such estimates have been used to illuminate a number of key developmen'tal issues, like the explanation of past economic growth rates (Schultz [74]), the opti- mality of resource allocation within education and between education and other sectors (Dougherty and Psacharopoulos [ 17]), the determinants of income distribution (Chiswick and Mincer [13]), and the behavior of students and their families as investors and consumers of education (Free- man [21]). One of the earliest questions following the human capital revolution in economic thought was: If education is a form of capital, what is the rate of return to it? This led to a related question: How does the prof- The author is an Economist in the Education and Training Department of the World Bank. * I am grateful to all those who over the years have kept me informed on their work, and especially those who by correspondence provided clarifications so that the figures ap- pearing here are more comparable. The views expressed are those of the author and should not be attributed to the World Bank. [Manuscript received February 1985, ac- cepted April 1985.] The Journal of Human Resources * XX * 4 0022-166X/85/0004-0583 $01.50/0 © 1985 by the Regents of the University of Wisconsin System 584 i THE JOURNAL OF HUMAN RESOURCES itability of investment in education compare to investment in physical capital? Such comparisons, it was thought, would serve as ex ante signals to guide resource allocation between two forms of capital an develop- mental planning. They have also been used ex post to explain a great part of the "residual" that puzzled scholars examining economic growth in the 1950s. Other questions follow. What priority should be given to primary versus university education? Allocative decisions have to be made within education, and rates of return have been used as guides to such decisions. Furthermore, a given level of education can offer various types of cur- ricula-for example, secondary general versus secondary technical-and estimates of the profitability of investment by type of schooling can il- luminate decisions on where the relative emphasis should lie. If human capital investment is like any other type of investment, diminishing returns should apply to it. Hence, another major issue in the early days was whether and by how much the yield on human capital investment would decline following the expansion of education. When the human investment revolution began, there were no time-series es- timates of the rate of return. The contrast between the social and private rate of return could highlight the extent of public subsidization of education. The size of the private returns could also explain the individual demand for certain types of schooling. And since the private rate of return is the price one receives on his or her human resource endowments, it could further explain per- sonal income distribution. For all the above reasons researchers in the United States, and later around the world, began estimating the returns to investment in edu- cation. The first rate of return to education collection appeared in the Summer 1967 issue of the Journal of Human Resources and covered only four countries-Mexico, Italy, the United States, and Great Britain. Three years later Hansen [28] produced another review covering 14 countries as background for an OECD conference on education. My 1973 book [56] attempted to derive rate-of-return patterns based on evidence from 32 countries. Seven years later I updated and expanded the rate-of-return estimates, covering 45 countries, as a background to the World Bank's World Development Report that dealt with human resources (Psacharo- poulos [57]). Since that collection, further estimates have been published for additional countries or for more recent years in countries for which evidence on the returns to education already existed. As a result of the literature growth in this field, my "Rate of Return-New Estimates" file has become overly thick and unmanageable. Perhaps the time has come for another stock-taking exercise to determine if the earlier documented rate-of-return patterns have been maintained, or whether new ones are Psacharopoulos 1 585 emerging. The enlarged and updated datta set on which this paper is based covers 61 countries. THE EVIDENCE The rate-of-return evidence has been organized into a set of master tables that appear in the Appendix. The tables correspond roughly to issues to be discussed in this paper. When severai rate-of-return estimates were available for a given country, year, or level of education, I have selected for inclusion in the master tables the one that in my judgment would be most comparable to the rest. This was not an easy task since many authors of the original studies do not always state explicitly the nature of the sample used (for example, urban, rural, national) or the methodology according to which the estimates are made (especially what adjustments have been made on the benefits side). Although correspondence with several authors has resulted in a more comparable set of figures, meth- odological and sample-reference differences remain. Hence, the reader should be cautious in attaching importance to one (or even two) per- centage point differences in the returns across countries and years. Of course, greater reliance should be placed on within-country estimates (for example, by level of education or by gender) that are based on a common sample and methodology. Most of the lengthy reference list is "'marginal" in the sense that the reader can refer to Psacharopoulos [56, 58] to trace the original source of previously reviewed estimates. The reader is also referred to these earlier publications for details on the theoretical and methodological as- pects of rate-of-return estimations. Table 1 is a summary of the master table that provides estimates of' average private and social returns by level of education for countries grouped by their level of economic development.' The table confirms the earlier well-documented declining rate of re- turn pattern by level of education. Primary education is the most prof- itable educational investment opportunity, followed by secondary edu- cation. This decline is the result of the interaction between the low cost of primary education (relative to other levels) and the substantial pro- ductivity differential between primary school graduates and those who are illiterate. The productivity of primary school graduates is not only proxied by their earnings, but has also been confirmed by studies using differences in physical output as an educational outcome.2 I All figures in the text tables are simple arithmetic averages of the corresponding rates in the master tables. 2 See D. Jamison and L. Lau, Farmer Education and Farm Egfficiency (Baltimore: Johns Hopkins University Press, 1982). 586 | THE JOURNAL OF HUMAN RESOURCES TABLE I AVERAGE RETURNS TO EDUCATION BY COUNTRY TYPE AND LEVEL (percent) Region/ Social Private Country Type Primary Secondary Higher Primary Secondary Higher Africa 26 17 13 45 26 32 Asia 27 15 13 31 15 18 Latin America 26 18 16 32 23 23 Intermediate 13 10 8 17 13 13 Advanced NA 11 9 NA 12 12 Source: Based on Appendix Table A-1, latest year available. Note: NA - not available because of lack of a control group of illiterates. TABLE 2 INDEX OF PUBLIC SUBSIDIZATION OF EDUCATION BY LEVEL AND REGION Educational Level Region/Country Type Primary Secondary Higher Africa 92 51 157 Asia 58 13 9 Latin America 104 47 50 Intermediate 51 6 7 Advanced NA 21 44 Source: Based on Appendix Table A-1, strictly comparable rates. Notes: The subsidization index for a given level of education is defined as the percent by which the private rate of return exceeds the social rate. NA not available. The declining rate-of-return pattern is aiso observed across levels of er capita income. For example, the returns to any level of education are highest in Africa and lowest in the advanced industrial countries. This is explained by the relative scarcity of human-to-physical capital within each group of countries. In all countries and levels of schooling, private returns exceed social returns because education is publicly subsidized. However, the private- public distortions are greatest in the poorest group of countries and in the higher levels of education (Table 2). Figure 1 illustrates this phenom- enon for Africa. Whereas the social rates of return follow a declining Psacharopoulos 1 587 Rate of return (percent) 50 40 - Private rate 30 - 20 - Social rate 10 Educational level Primary Secondary Higher FIGURE 1 DIFFERENCES BETWEEN THE PRIVATE AND SOCIAL RETURNS TO EDUCATION IN AFRICA Source: Based on Appendix Table A-I, strictly comparable rates. pattern by ascending level of education, the private rates are not only higher than social rates, but they increase after the secondary level. Table 3 gives means of the regression coefficient on years of schooling in a semi-log (Mincer-type) earnings function in which log earnings is a function of years of schooling, years of experience, and years of experience squared. The figures are interpreted as private returns to the typical year of education (that is, undifferentiated by level). Again, the declining pat- tern of the retums across countrv type is largely maintained. Rate-of-return estimates in recent years have been refined in the sense that they are increasingly based on the earnings of those employed in the competitive sector of the economy where the benefits of education better reflect the worker's productivity. Table 4 shows that in studies where the returns have been differentiated by economic sector, the returns in the competitive setting exceed those in the noncompetitive sector by 588 THE JOURNAL OF HUMAN RESOURCES TABLE 3 MINCER-TYPE RETURNS TO EDUCATION BY COUNTRY TYPE Coefficient on Years of Schooling Region/Country Type (percent) Africa 13 Asia 11 Latin America 14 Intermediate 8 Advanced 9 Source: Master table listing the individual country rates is available from the author on request. Note: The following countries are included in each region: Africa: Ethiopia, Kenya, Morocco, Tanzania; Asia: Hong Kong, Malaysia, Pakistan, Singapore, South Korea, South Vietnam, Sri Lanka, Taiwan, Thailand; Latin America: Brazil, Chile, Colombia, Costa Rica, El Salvador, Guatemala, Mexico, Venezuela; Intermediate: Cyprus, Greece, Iran, Portugal; Advanced: Australia, Canada, France, Germany, Japan, Sweden, United Kingdom, United States. TABLE 4 AVERAGE RETURNS TO EDUCATION BY ECONOMIC SECTOR Rate of Return Sector Specification (percent) Competitive, private 13 Noncompetitive, public 10 Source: Master table listing individual countries is available from the author on request. Note: The countries included in this table are Brazil, Colombia, Greece, Guatemala. Japan, Malaysia, Pakistan, Portugal, United Kingdom, Tanzania, and Venezuela, three percentage points. This means that previous estimates based on the earnings of workers in all sectors have in fact underestimated the retums to education. The inclusion of public-sector earnings in particular, be- cause of the equalization policy of pay scales, flattens mean earnings differentials and, hence, depresses the returns to education. For a variety of reasons, women in all countries earn on average substantially less than men. Because the rate of return is a relative con- cept, it should not be surprising if the profitability of investment in wom- en's education is greater thani that of men. This is, indeed, the case, as Psacharopoulos 1 589 shown in Table 5, where in developing countries the Mincer-type average rate of return for women exceeds that for men by four percentage points. This rate-of-return differential in favor of women may be an underesti- mate because the rate of return to investment in women's education, as commonly calculated, does not take into account the increased proba- bility of more educated. women participating in the labor force. For ex- ample, Mohan [47] reports that in Colombia in 1984 the labor force participation rate of working-zge women aged over 15 ranged from 31 percent for those who had no schooling to 53 percent for those with a university education. It is commonly thought that introducing a vocational element in the secondary school curriculum, especially in developing countries, is con- ducive to economic develornment. But, as shown in Table 6, the returns to investment in traditional academic (general) curricula are greater on average than the returns to investment in specialized subjects. Again, this is due to the higher unit cost of producing technical graduates and the fact that graduates from both streams are absorbed equally well by the labor market. TABLE 5 AVERAGE RETURNS TO EDUCATION BY GENDER (percent) Country Group Educational Level Men Women All countries Primary 19 17 Secondary 16 21 Higher 15 14 Developing countries Overall 11 15 Source: Based on Appendix Table A-2. TABLE 6 AVERAGE RETURNS TO ALTERNATIVE SECONDARY SCHOOL CURRICULA Curriculum Type Rate of Return (percent) General, academic 16 Vocational, technical 12 Source: Master table listing individual countries is available from the author on request. Note: Countries included in this table are Colombia, Cyprus, France, Indonesia, Liberia, Taiwan, and Tanzania. 590 | THE JOURNAL OF HUMAN RESOURCES The same pattern observed regarding the type of secondary school curriculum also applies to higher education programs. The high-cost spe- cialties like agronomy exhibit low returns, whereas humanities and the social sciences exhibit high returns (Table 7). Rate-of-return estimates over time within countries are rare. What is even rarer are estimates based on the same sampling frame and meth- odology from year to year. In the country where the highest quality time series data exist, the United States, the returns have shown a remarkable stability over a 30-year period. For example, the social returns to higher education fluctuated around the 10-11 percent mark between 1939 and 1969 (Appendix Table A- 1). In Japan, the corresponding returns fell from 6.4 to 5.7 percent in a seven-year period. In Great Britain, the returns remained virtually constant between 1971 and 1978. In Colombia, the returns to education (Mincer-type estimation) declined from 17.6 to 14.4 percent between 1973 and 1978, while in the same five-year period the percentage with higher education in the labor force has more than doubled (from 6 percent in 1973 to 13 percent in 1978. based on Mohan [48], pp. 40, 43). This relative stability of average returns over time has been explained by the fact that the demand for educated manpower has kept increasing along with the supply of education (a phenomenon Jan Tinbergen has lucidly described as the race between technology and education [80]). Table 8 presents comparisons of average returns to physical and human capital in two time periods. Given the roughness of the data, the evidence suggests that in advanced countries the gap has narrowed some- what between the retums to physical and human investment, and the convergence indicates that a IO percent return may be indicative of some equilibrium. In developing countries, however, there is a clear advantage of human versus physical capital investments. Of course this advantage TABLE 7 AVERAGE RETURNS FOR SELECTED UNIVERSITY PROGRAMS Program Rate of Return (percent) Economics I ? Law 1 2 Social sciences 1 1 Medicine 12 Engineering 12 Sciences, math, physics 8 Agriculture 8 Source: Based on Appendix Table A-3. Psacharopoulos 591 TABLE 8 RETURNS TO HUMAN AND PHYSICAL CAPITAL BY TYPE OF COUNTRY (percent) 1960s 1970s Type of country Human Physical Human Physical Developing 20 > 15 15 > 13 Advanced 8 < 10 9 < 11 Source: 1960s from Psacharopoulos [563, Table 5.3; 1970s from Psacharopoulos [643, Table 8. Note: Developing countries included in the table are Mexico, Colombia, Venezuela, Chile, Brazil. India, Philippines, Ghana, Kenya, Uganda, and Nigeria. Advanced countries are United States, United Kingdom, Canada, Netherlands, and Belgium. diminished from the 1960s to the 1970s, following the relatively greater investment in developing countries. LV!PLICA TIONS These rate-of-retum patterns have several implications for the shaping of educational policy, especially in developing countries. Underinvestment exists at all levels of education, especially in Africa. This proposition is supported by evidence that the social returns to ed- ucation in the region are well above any plausible social discount rate used in project evaluation. Primary schooling remains the number-one priority for investment. This is evidenced by the fact that the social rate of return to primary education exceeds by several percentage points the returns to secondary and higher education. The degree of public subsidization of higher education is such that there is considerable margin for reducing subsidy levels. This stems from the calculations that a reduction of public subsidies to higher education would drive down the private rate closer to the social rate, still leaving an attractive return to private investment. The savings from the reduction of university subsidies could be used to expand primarv education. Reducing public subsidies to higher education and reallocating them to primary education would have additional benefits that can be viewed as equitable. To a great extent, universities are attended by those who can afford to pay, whereas the less well-off portion of the population would now find educational opportunities more open and accessible. 592 | THE JOURNAL OF HUMAN RESOURCES Expanding the provision of school places to cover women is not only equitable but socially efficient as well. Although counter-intuitive, this proposition is based on the evidence that the rate of return to women's education is at least as attractive as the rate of return on investment for men. Within the secondary or university level, the general curricula or programs offer as good investment opportunities as the more vocational pursuits. This is because the higher unit costs of vocational/technical education depress the social rate of return to this type of schooling. Judging from past trends and the degree of underinvestment in ed- ucation in developing countries, the fears that further educational ex- pansion would lead to unemployed graduates or would lower social rates of return are unfounded. This proposition is based on time series evidence which shows that rates of return have not changed much as educational investment increases. The traditionally estimated returns on the basis of observed earnings may underestimate the true social profitability of education. The flatness of civil service pay scales depresses the size of earnings differentials on which early rate-of-return estimates were based. 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Higher .4frica Botswana 1983 42.0 41.0 15.0 99.0 76.0 38.0 Ethiopia 1972 20.3 18.7 9.7 35.0 22.8 27.4 Ghana 1967 18.0 13.0 16.5 24.5 17.0 37.0 Kenya 1971 21,7 19.2 8.8 28.0 33.0 31.0 1980 13.0 14.5 Lesotho 1980 10.7 18.6 10.2 15.5 26.7 36.5 Liberia 1983 41.0 17.0 8.0 99.0 30.5 17.0 Malawi 1978 15.1 1982 14.7 15.2 11.5 15.7 16.8 46.6 Morocco 1970 50.5 10.0 13.0 Nigeria 1966 23.0 12.8 17.0 30.0 14.0 34.0 Rhodesia 1960 12.4 Sierra Leone 1971 20.0 22.0 9.5 Somalia 1983 20.6 10.4 19.9 59.9 13.0 33.2 Sudan 1974 8.0 4.0 13.0 15.0 Tanzania 1982 5.0 Uganda 1965 66.0 28.6 12.0 Upper Volta 1970 25.9 60.6 1975 27.7 30.1 22.0 1982 20.1 14.9 21.3 .4sia Hong Kong 1976 15.0 12.4 18.5 25.2 India 1965 13.4 15.5 10.3 17.3 18.8 16.2 1978 29.3 13.7 10.8 33.4 19.8 13.2 Indonesia 1977 25.5 15.6 1978 21.9 16.2 14.8 Malaysia 1978 32.6 34.5 Pakistan 1975 13.0 9.0 8.0 20.0 11.0 27.0 1979 14.6 6.7 9.4 Philippines 1971 7.0 6.5 8.5 9.0 6.5 9.5 1977 8.5 16.0 Singapore 1966 6.6 17.6 14.1 20.0 25.4 South Korea 1967 9.0 5.0 1969 11.0 9.5 1971 14.6 9.3 16.1 16.2 1973 12.2 8.8 1980 8.1 11.7 Taiwan 1970 26.5 15.0 17.6 18.4 1972 27.0 12.3 17.7 50.0 12.7 15.8 Psacharopoulos l 599 APPENDIX TABLE A-I (Continued) Social Private Country Year Prim. Sec. Higher Prim. Sec. Higher Thailand 1970 30.5 13.0 11.0 56.0 14.5 14.0 1972 63.2 30.9 18.4 Latin Am77erica Bahamas 1970 20.6 26.1 Brazil 1970 23.5 13.1 24.7 13.9 Chile 1959 24.0 16.9 12.2 Colombia 1973 15.1 15.4 20.7 1976 18.4 24.9 1981 9.6 Costa Rica 1974 13.1 8.7 25.7 Mexico 1963 25.0 17.0 23.0 32.0 23.0 29.0 Paraguay 1982 14.0 11.0 13.0 Peru 1972 46.9 19.8 16.3 1974 34.3 9.0 15.0 1980 41.4 3.3 16.1 Puerto Rico 1959 24.0 34.1 15.5 68.2 52.1 29.0 Venezuela 1957 82.0 17.0 23.0 18.0 27.0 1984 32.5 11.7 20.6 Intermediate Cyprus-l 1975 15.0 11.2 14.8 1979 8.6 8.1 14.1 Cyprus-2 1975 10.5 9.7 11.6 8.6 1979 7.7 6.8 7.6 15.4 7.0 5.6 Greece 1962 6.3 13.7 7.2 14.0 1977 16.5 5.5 4.5 20.0 6.0 5.5 Iran 1972- 34.0 11.5 15.0 1976 15.2 17.6 13.6 21.2 18.5 Iran-2 1975 10.6 15.3 19.3 Israel 1958 16.5 6.9 6.6 27.0 6.9 8.0 Spain 1971 17.2 8.6 12.8 31.6 10.2 15.5 Turkey 1968 8.5 24.0 26.0 Yugoslavia 1969 9.3 15.4 2.8 7.6 15.3 2.6 .4di anced Australia 1969 14.0 13.9 1976 16.3 8.1 21.1 Austria 1981 11.3 4.2 Belgium 1960 17.1 6.7 21.2 8.7 Canada 1961 11.7 14.0 16.3 19.7 Denmark 1964 7.8 10.0 600 THE JOURNAL OF HUMAN RESOU RCES APPENDIX TABLE A-1 (Continued) Social Private Country Year Prim. Sec. Higher Prim. Sec. Higher France 1962 14.3 11.5 9.3 1969 10.1 10.9 16.2 12.0 9.6 1976 13.5 10.8 9.3 Germany 1964 4.6 1978 6.5 10.5 Great Britain 1971 11.0 7.0 14.0 27.0 1972 3.6 8.2 11.7 9.6 1973 8.0 8.0 6.0 16.0 1975 7.0 7.0 9.0 22.0 1977 8.0 6.0 9.0 17.0 1978 9.0 7.0 11.0 23.0 Italy 1969 17.3 18.3 Japan 1967 10.5 1973 4.6 6.4 5.9 8.1 1976 9.6 8.6 6.9 13.4 10.4 8.8 1980 5.7 8.3 Netherlands 1965 5.2 5.5 8.5 10.4 New Zealand 1966 19.4 13.2 20.0 14.7 Norway 1966 7.2 7.5 7.4 7.7 Sweden 1967 10.5 9.2 10.3 United States 1939 18.2 10.7 1949 14.2 10.6 1959 10.1 11.3 1969 10.7 10.9 18.8 15.4 1970 11.3 8.8 1971 12.5 8.0 1972 11.3 7.8 1973 12.0 5.5 1974 14.8 4.8 1975 12.8 5.3 1976 11.0 5.3 Sources: Australia: 1976, Miller [44], Tables I and 2; Austria: Clement [15]; Bahamas: Gabregiorgis [22]. Table 33: Botswana: Botswana Ministry of Finance [91, Table 2-50, Columbia: 1976. Higher, Rodriguez [711] Table 6. 1981, Psacharopoulos and Zabalza [68], average of all secondary school subjects; Costa Rica: based on Baldares-Carazo [6], Table 7.19: Cyprus-I: regression derived rates (1979), private rates, House and Stylianou [32], Table VI-4, 1975. private rates, Psacharopoulos [58], Table 1: Cyprus-2: rates refer to males, House and Stylianou [321, Table VI-3: France: 1962, Riboud [701, 1969 and 1976. Mingat and Jarousse [451, social and private rates not comparable for 1969 as estimation in each year based on different methodologies, see Psacharo