,JV WPQ80 Policy Research WORKING PAPERS Education and Employment Technical Department Latin America and the Caribbean Region The World Bank December 1992 WPS 1056 Earnings and Education in Latin America Assessing Priorities for Schooling Investments George Psacharopoulos and Ying Chu Ng In most Latin American countries, the earnings premium re- ceived by graduates of higher education decreased in the 1980s. Investment in primary education shows the highest rate of return among all levels considered. ThePolicy Research Working Papers dissemninate thefindings of work in progress and encouragetheexchangeof ideas among Bank staff and all others interested indevloprenttissues Thesepapers, distLibuted by the Research Advisory Staff, carry thenames of the authors, reflectonlytheirviews,and should beused and cited accordingly.Thefmdings,intespretations, andconclusions aretheauthors'own.They should not be attributed to the World Bank, its Board of Dircwtors, its management, or any of its member countries. Policy Researchl Education and Employment WPS 1056 This paper- a product of the Technical Department, Latin America and the Caribbean Region - is part of a larger effort in the department to document the role of education in the region's development efforts. Copies of the paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Liliana Longo, room 14-187, extension 39244 (December 1992, 93 pages). Psacharopoulos and Ng use household survey sector of employment, by nature of the second- dzta for 18 Latin American countries to assess ary school curriculum, and over time. earnings differentials by level of education, and to assess how these differentials changed in the The results show that, in most countries, the 1980s. earnings premium received by graduates of higher education decreased in the 1980s. Invest- Introducing the cost of education allows ment in primary education shows the highest rate them to estimate private and social rates of return of return among all levels considered - and is on investments on education across several still the number one investment priority in most dimensions: by gender, by level of education, by countries. The Policy Research Working Paper Series disseminates the findings of work under way in the Bank. An objective of the series is to get these findings out quickly, even if presentations are less than fully polished. The findings, interpretations, and conclusions in these papers do not necessarily represent official Bank policy. Produced by the Policy Research Dissemination Center EARNINGS AND EDUCATION IN LATIN AMERICA: ASSESSING PRIORITIES FOR SCHOOLING INVESTMENTS George Psacharopoulos Ying Chu Ng Technical Department Latin America and the Caribbean Region The World Bank TAxi OF CONTW8 I. Introduction .. .. .. . .. .,,,,,.,,,,., ......... . .. . v. .1 . II. Methodology ................................... .. .. . 3 The Full Discounting or Elaborate Method ................ 3 The Earnings Function Method ............................... 6 The Short-cut Method . ......... . ..... . ,...... . ... 8 III. Empirical Findings ..... ............. ..... . 8 Basic Earnings Functions ................................... 9 Overtime Changes in Relative Earnings .. 14 Overtime Returns to Education ....................... ..... 20 Extended Earnings Functions .... .. ............. ...... . . 25 Secondary General versus Vocational Education ... . ........... 28 Private Returns to Education ................... 29 Social Returns to Education .... ................... ...... 31 IV. Conclusion ... .. . .. . . . . ....... . 37 References ....... 39 Annex 1. Survey Data Description .0.00000.....0.0.0.41 Annex 2. Variable Definitions .. .. ....0.0...... .44 Annex 3. Basic Eanings Functions ..... .............0... 48 Annex 4. Extended Earnings Functions ..... . ............ 77 LIST OF TABLES 1. Mean Earnings, Years of Schooling and Mincerian Returns to Education: Entire Sample, circa 1989 ........... ;....... 10 2. Mean Earnings, Years of Schooling and Mincerian Returns to Education: by Gender, circa 1989 .... ..12 3. Mean Eamings, Years of Schooling and Mincerian Retums to Education: by Sector, circa 1989.. 13 4. Over Time Earnings Differentials by Educational Level .15 5. Over Time Educational Attainment of the Labor Force .18 6. Mean Earnings, Years of Schooling and Mincerian Returns to Education: Entire Sample, circa 1980 ............... .21 7. Mean Earnings, Years of Schooling and Mincerian Returns to Education: by Gender, circa 1980 ..22 8. Mean Earnings, Years of Schooling and Mincerian Returns to Education: by Sector, circa 1980 .24 9. Mean Earnings and Mincerian Returns to Education: by Level of Education ...... 26 10. Private Retums to Education by Level of Education: Full Method .30 11. Social Direct Unit Cost per Year by Level of Education .33 12. Social Returns to Education by Level of Education: Full Method . 35 13. Index of Public Subsidization of Education by Level ...... 38 Lwsr OF FIGURES 1. Age - Earnings Profiles by Level of Education, Brazil 1989 ................ 5 2. Time Trend of Earnings Differentials by Level of Education in Four Countries .... 17 I. INTRODUCrION The study of the relationship between earnings and education has been the cornerstone of the economics of education. There are several reasons why this relationship has been investigated extensively throughout the world since "human capital" was established in the economic growth and development literature in the early 1960s (see Schultz, 1961). First, differences in mean earnings between graduates of successive levels of education reflect the premium associated with educational investment. This premium is definitely "private", in the sense that it accrues to the person who undertook the investment. Under certain conditions, however, this premium can also be used as a proxy for the higher social productivity of the graduate, e.g. as evidenced by earnings differentials in the competitive sector of the economy. Thus, earnings differentials by level of education provide an expedient, empirical way of documenting first order relative scarcities in the market for graduates in a given society, and may provide a guide for educational investments. Second, the above earnings premium can be combined with the cost (either private or social) of investing in different levels of education, thus leading to a cost-benefit analysis of investment in schooling, which is very similar to traditional cost-benefit analysis in other sectors of the economy. Since the 1960s there has been an immense literature devoted to the profitability of investments in human capital. Estimates of such profitability are better known as "rates of return to investment in education" (for a review see Psacharopoulos, 1985a). -2- Third, and beyond the above efficiency considerations, the earnings premium associated with different levels of education leads to equity assessments in a given society, e.g. how does the provision of education, and at what level, contributes to poverty alleviation or a more equal income distribution? The purpose of this paper is to present evidence on the relationship between earnings and education in Latin America for the latest year possible, and to discuss the implications of the findings for school investment priorities in the region. The analysis is necessarily macro, in the sense that a large number of countries has been covered, using a consistent methodology, although at the expense of performing more detailed within-country analyses. Thus the findings presented here should be considered as indicative regarding educational investment priorities in the region, pending more detailed country-specific work. This study improves upon the previous cross-country studies by applying a consisten. mrethodology of estimation!'. Moreover, the database comes from representative national data sets of the countries in question. The data also allow for the study of time trends of rates of return to cducation, as well as assessing the profitability of different types of the secondary school curriculum. The next section presents the methodology of estimation, followed by a section on the evidence. The implications of the findings are discussed in the concluding section. I/ Previous studies on the returns to education in Latin America are listed in the Peferences. -3- II. MErHODOLOGY Estimates of the profitability of investment in education can be arrived at using different methods. The method adopted by various authors is often dictated by the nature of the available data. In what follows we briefly describe the available methods as background to the estimates ,we present later in this paper. (1) The Full Discountinlg or Elaborate Method This method amounts to finding the discount rate (r) that equates a stream of benefits to a stream of costs at a given point in time: = (y(+C)C(+r) * (1) :-+1 ( +r) t-I where (Yb-Ya)t is the earnings differential between a more educated person (subscript b) and a less educated person (subscript a, the control group). Cb represents the direct costs of schooling consisting of tuition and fees, books, etc., and Y. denotes the student's foregone earnings or indirect costs. On the assumption that the direct costs of acquiring the next higher level of education are roughly the same as the income one would earn from part-time or summer job during the study, equation (1) can be simplified to: -4- *"1 t r)' S(Y,)S(l +r) (2) There is an important asymmetry between computing the returns to primary education and those to the other levels. Primary school children, mostly aged 6 to .2 years, do not forego earnings during the entire length of their studies. In the empirical analysis that follows we have assumed only two years of foregone earnings for primary school children. The resulting r by solving the above equation can be considered to be a "private" rate of return. When the direct cost paid by the individual is replaced by the true full cost of someone's education (paid by the state in most countries) one can arrive at a "social" rate of return. Private rates of return are used to explain people's behavior in seeking education of different levels and types, and as distributive measures of the use of public resources. Social rates of return, on the other hand, can be used to set investment priorities for future educational investments. The discoundng of actual net age-earnings profiles is the most appropriate method of estimating the returns to education because it takes into account the most important part of the early earning history of the individual. But this method is very thirsty in terms of data -- one must have a sufficient number of observations in a given age-educational level cell for constructing "well-behaved" age-earnings profiles. (An example of such profile is given in Figure 1.) This has been rarely the case in the early days of the economics of education, and thus researchers have resorted to less data-demanding methods. u iXf < Co %.~~~~~~~ 0~~ o~~ o - ~ ~ r ¢ D -6- (2) The Earnings Function Method This method is derived from Mincer (1974) and involves the fitting of a function specified as: In1I - a +,PSI+Y,EX4+Y2EX2+eI, (3) where S is the number of years of schooling of individual i, and EX and EX2 are years of experience and its square, respectively. Often weeks-worked or hours-worked are added as independent variables to this function as compensatory factors. We call the above a "basic earnings function." In this semi-log specification the coefficient of S (O) can be interpreted as the average private rate of return to one additional year of schooling, regardless of the educational level this year of schooling refers to. The earnings function method can be used to estimate returns to education at different levels by converting the continuous years of schooling variable (S) into a series of dummy variables, say PRIM, SEC, UNIV, to denote the fact that a person has completed the corresponding level of education, and that of course there are also people in the sample with no education in order to avoid matrix singularity. Then, after fitting the following "extended earnings function": lnYI' g+P,PR!M1+f32SEC,+P,UN7Vl+y1EX1+y2E i+e. (4) the private rate of return to different levels of education can be derived from the following formulas: r(PRJM = S SPRIM r(m TU SSEC-S t = S- where SpRIM, SsEc, and SU,V stand for the total number of years of schooling for each successive level of education (primary education completed, secondary education completed, and university education completed, respectively). Again, care has to be taken regarding the foregone earnings of primary school-aged children. In the empirical analysis that follows we have assigned only two years of foregone earnings to this group. Although convenient, because it requires less data, this method is slightly inferior to the previous one as it in fact assumes flat age-earnings profiles for different levels of education (see Psacharopoulos ard Layard, 1979). -8 - (3) The Short-cut Method This estimation method is based on a simple formula: *= S(t*-,) where Y refers to the mean earnings of an individual with the subscripted educational level, k is the higher educational level in the comparison, and AS represents the difference in years of schooling between k and the control group. Although this method is very easy to use, it is by definition very inferior relative to, any of the other methods described above. The weakness of the method lies in the abstraction from the fact that age-earnings profiles are concave (see Figure 1), and that the discounting process (in estimating the true rate of return) is very sensitive to the values of the early ages entering the calculation. Hence we will not use this method in the empirical analysis that follows. IH. EMPIRCAL FmDIGS The data used in this analysis come from a series of Household Surveys conducted in the region around 1989. For some countries the same survey was also conducted around 1980. Details on the nature of the surveys appear in Annex 1. Variable definitions appear in Annex 2. -9- A. Basic Earnings Functions As a way of summarizing the data, we first fit basic earnings functions (see Annex 3). Table 1 shows the resulting average rate of return, along with the mean years of schooling of the sample. In comparing mean years of schooling across counties, it should be noted that the countries with the highest mean years of schooling, Bolivia and Peru, refer to urban samples. Among the eighteen countries, twelve of them have an average return to schooling of 10 percent or above. The mean of years of schooling ranges from 4.3 to 10.1 years. The lowest mean years of schooling are found in Guatemala and Brazil, while Bolivians and Peruvians generally have more than 10 years of schooling because of the urban nature of the samples. It is not surprising, therefore, to find that the average private rate of return to schooling in Bolivia and Peru is relatively lower than that in Guatemala and Brazil. - 10 - Table.it Mean Earnings, Years of Schooling and Mlncerian Returns to Education: Entlre Sample circa 1989 Country Survey Earnings Mean Rate of Year (in local Years of Return (%)y currency) Schooling Argentina 1989 7,456 9.1 10.3 Bolivia 1989 364 10.1 7.1 Brazil 1989 6,969 5.3 14.7 Chile 1989 40,275 8.5 12.0 Colombia 1989 53,643 8.2 14.0 Costa Rica 1989 16,346 6.9 10.9 Dominican Republic 1989 652 8.8 9.4 Ecuador 1987 27,313 9.6 10.8 El Salvador 1990 899 6.9 9.7 Guatemala 1989 242 4.3 14.9 Honduras 1989 453 6.5 17.6 Jamaica 1989 5,886 7.2 28.8 Mexico 1984 81,029 6.6 14.1 Panama 1989 292 9.2 13.7 Paraguay 1990 239,861 9.1 11.5 Peru 1990 9,912 10.1 8.1 Uruguay 1989 145,840 9.0 9.7 Venezuela 1989 6,894 9.1 8.4 Source: Annex 3. Notes: I' Coefficient of the years-of-schooling variable in the basic earnings function, times 100. - 11 - The earnings functions have been fitted to male and female sub-samples in order to examine differences in returns to education by gender. As seen in Table 2, working females generally attain more education than their male counterparts in all countries except Ecuador, El Salvador, Paraguay, and Peru. This, however, does not gives females an advantage over males in acquiring better pay in absolute terms. The mean earnings of each country shows that males in fact earn more than females2'. However, the rate of return being a reli concept, this does not prevent females realizing a higher payoff than men to their schooling investment in fifteen out of the eighteen cases reported in Table 2. Table 3 presents the results of an alternative partitioning of the sample into public and private employment. As found elsewhere, public sector employees have more years of schooling than their private sector counterparts, and also a lower rate of return on their schooling investments (Psacharopoulos, 1983). 2/ For a more detailed analysis of the male-female earnings differentials using the same samples and selectivity correction, see Psacharopoulos and Tzannatos (1992a) and (1992b). - 12 - Table 2. Mean Earnings, Years of Schooling and Mincerian Returns to Education: by Gender, circa 1989 Country Year Earnings Years of Rate of Return (ocal curr.) Schooling (percent) Males Females Males Females Males Females Argentina 1989 8,563 5,629 8.7 9.8 10.7 11.2 Bolivia 1989 402 270 9.5 11.5 7.3 7.7 Brazil 1989 7,151 6,640 5.0 5.9 15.4 .14.2 Chile 1989 43,878 31,373 8.2 9.4 12.1 13.2 Colombia 1989 60,592 43,124 8.1 8.3 14.5 12.9 Costa Rica 1989 17,283 13,928 6.4 8.1 10.5 13.5 Dominican Republic 1989 722 522 8.4 9.5 7.8 12.0 Ecuador 1987 32,049 19,360 9.7 9.5 9.8 11.5 El Salvador 1990 988 766 7.0 6.7 9.6 9.8 Guatemala 1989 256 207 4.0 4.8 14.2 16.3 Honduras 1989 488 384 6.1 7.1 17.2 19.8 Jamaica 1989 9,829 1,047 7.0 7.4 28.0 31.7 Mexico 1984 84,520 71,533 6.3 7.5 14.1 15.0 Panama 1989 312 258 8.6 10.1 12.6 17.1 Paraguay 1990 290,496 165,787 9.1 8.9 10.3 12.1 Peru 1990 11,482 6,937 10.2 9.8 8.5 6.5 Uruguay 1989 178,086 97,865 8.7 9.3 9.0 10.6 Venezuela 1989 7,858 6,067 7.9 10.2 8.4 8.0 Source: Annex 3. - 13 - Table 3. Mean Earnings, Years of Schooling and Mincerian Returns to Education: by Employment Sector, circa 1989 Country Year Earnings Years of Schooling Rate of Return (local curr.) (percent) Private Public Private Public Private Public Argentina 1989 7,155 8,463 8.5 11.C 11.1 8.9 Bolivia 1989 361 369 8.7 11.7 8.7 6.7 Brazil 1989 9,979 7,746 4.1 8.2 15.0 11.4 Chile 1989 38,232 58,044 8.1 12.3 11.4 11.2 Colombia 1989 50,279 80,116 7.8 11.2 13.7 11.9 Costa Rica 1989 14,245 26,079 6.2 10.1 9.3 8.5 Dominican Republic 1989 n.a. n.a. n.a. n.a. n.a. n.a. Ecuador 1987 26,254 32,258 8.9 12.8 11.3 7.1 El Salvador 1990 835 1,215 6.1 10.9 9.4 6.2 Guatemala 1989 219 455 3.7 9.1 14.1 8.7 Honduras 1989 406 714 5.9 9.9 17.4 12.3 Jamaica 1989 6,443 3,140 6.9 8.5 24.9 16.0 Mexico 1984 73,448 108,503 5.7 9.7 15.4 8.0 Panama 1989 232 434 8.2 11.5 12.2 11.0 Paraguay 1990 ,236,360 264,629 8.6 12.6 11.9 8.3 Peru 1990 8,002 10,295 9.6 12.5 9.0 9.0 Uruguay 1989 146,073 145,069 8.6 10.2 10.5 5.7 Venezuela 1989 6,700 7,037 7.3 10.5 9.7 - 6.6 Source: Annex 3 n.a. = not available - 14 - B. Overtime Changes in Relative Earnings Before we turn to the discussion of the time trends of the rate of return to schooling, let us examine the behavior of earnings differentials in Latin American countries. Owing to the availability of data, calculation of earnings differentials over time is only allowed for twelve countries. Table 4 presents the earnings differentials in absolute and index values by level of education, and Table 5 provides the corresponding structure of the labor force by level of education. N. As seen in Table 4 and depicted in Figure 2, the relative earnings of individuals with either secondary or university education decreased over time in most conntries with the exception of Bolivia, Guatemala and Panama. This is expected since the number of workers as a percentage of the labor force with post-compulsory schooling increased during the same time period in all countries expect Hondurasl'. This implies a strong relationship between schooling and income distribution in society. Earnings differentials narrow as the educational attaintment of the labor force increases. I/ The overtime comparability of the Honduras, Peru and Uruguay data sets is limited given the fact the later surveys refer only to urban areas. - 15- Table 4. Over Time Earnings Differentials by Educational Level Earnings Oocal curr.) Index (Prim. =100) Country Educational Level (Early-Late) Early Late Early Late Argentina No Education n.a. 2,724 n.a. 56 1980-89 Less than Primary 511 4,099 83 85 Primary 615 4,843 100 100 Secondary 976 7,757 159 160 University 2,381 13,231 387 272, Bolivia No Education 134,311 268 64 95 1986-89 Primary 208,855 281 100 100 Secondary 235,632 363 113 129 University 463,970 795 222 283 Brazil No Education 7,399 5,257 69 74 1979-89 Primary 10,791 7,145 100 100 Secondary 17,398 8,772 161 123 University 39,934 17,658 370 247 Colombia No Education 3,690 24,004 65 65 1980-89 Primary 5,643 36,769 100 100 Secondary 12,719 57,529 225 156 University 31,413 145,487 557 396 Costa Rica No Education 1,256 10,389 87 79 1981-89 Primary 1,437 13,222 100 100 Secondary 2,763 20,956 192 158 University 5,043 42,323 351 320 Guatemala No Education 92 134 48 54 1986-89 Primary 192 246 100 100' Secondary 354 444 184 180 University 762 1,096 - 397 446 Honduras No Education 180 n.a. 59 n.a. 1986-89 Less than Primary 269 263 88 72 Primary 307 363 100 100 Secondary 647 700 211 193 University 1,667 1,853 543 510 Continued - - 16- Table 4 cont'd. Earnings (local curr.) Index Country Educational Level - --- - (Early-Late) Early Late Early Late Panama No Education 115 167 70 93 1979-89 Primary 164 180 100 100 Secondary 279 335 170 186 University 592 750 361 417 Paraguay Less than Primary* 26,290 145,371 87 82 1983-90 Primary 30,064 177,895 100 100 Secondary 55,837 282,777 186 159 University 112,866 599,067 375 337 Peru No Education 2,661 6,593 36 89 1985-90 Primary 7,493 7,431 100 100 Secondary 10,432 9,014 139 121- University 27,463 22,778 367 307 Uruguay No Education 2,132 68,495 58 52 1981-89 Primary 3,646 132,583 100 100 Secondary 5,278 171,160 145 129 University 8,157 263,405 224 199 Venezuela No Education n.a. 3,778 n.a. 63 1981-89 Less than Primary 1,940 4,869 84 81 Primary 2,321 5,983 100 100 Secondary 3,367 8,013 145 134 University 6,138 13,802 264 231 Source: Annex 3. Notes: n.a. = not available. * Due to the sample size, individuals with no education or less-than-primary education are grouped into less-than-primary education. - 17 - Figurie 2. Time Trend of Earnings Differentials by Level of Education In Four Countries O Lug fm MmP a Sftm° o No *t1a Sw Y a imiverity a LrlvmsIty 400 , ~~~~~~~~~~~~~~~~~400 200. 200 jjo _ _ _ _ _ _ -j0 _ _ _ _ _ _ 0 ~~~~~~~~~~~~~~~~~~~0 lgho Yh 19gh YW Cduobb4 It" V-u=t, IN49 N om E*gatla a S,ec Y O Lm Then Ptiwy a 9Sm1cn'y 0 UseoIYUdvet I00~~~~~~~~~~~~~~~~~~0 - 400- 200 Soo 200, 1 *, _ _ _ _ _ _ 010 0 0 Wb toh Y jg - 18 - Table S. Over Time Educational Attainment of the Labor Force Attainment (X) Index Country Educational Level (Early-Late) Early Late Early Late Argentina No Education n.a. 1.4 n.a. 4 1980-89 Less than Primary 19.9 13.6 55 42 Primary 36.1 321 100 100 Secondary 11.6 14.0 32 44 University 3.7 6.8 10 21 Bolivia No Education 4.9 2.1 104 39 1986-89 Primary 4.7 5.4 100 100 Secondary 27.1 17.9 577 331 University 8.9 10.5 189 194 Brazil No Education 19.2 22.7 202 295 1979-89 Primary 9.5 7.7 100 100 Secondary 9.4 12.4 99 161 University 4.1 6.3 43 82 Colombia No Education 4.2 2.4 20 12 1980-89 Primary 20.9 19.3 100 100 Secondary 10.2 19.5 49 101 University 5.6 9.2 27 48 Costa Rica No Education 6.0 5.5 19 16 1981-89 Primary 32.4 34.7 100 100 Secondary 9.9 12.2 31 35 University 3.7 5.0 11 14 Guatemala No Education 30.3 31.0 194 200' 1986-89 Primary 15.6 15.5 100 100 Secondary 7.9 6.1 51 39 University 2.0 2.4 13 15 Honduras No Education 11.9 n.a. 52 n.a. 1986-89 Less than Primary 26.4 41.1 115 146 Primary 22.9 28.1 100 100 Secondary 19.1 14.8 83 53 University 4.8 4.1 21 15 Continued - - 19- Table 5 cont'd. Attainment (%) Index Country Educational Level - (Early-Late) Early Late Early Late Panama No Education 4.0 3.4 14 13 1979-89 Primary 28.1 25.2 100 100 Secondary 18.4 21.1 65 84 University 5.8 9.2 21 37 Paraguay Less than Primary* 23.9 15.0 86 59 1983-90 Primary 27.9 25.3 100 100 Secondary 14.9 23.5 53 93 University 5.9 6.4 21 25 Peru No Education 11.1 19.4 65 96 1985-90 Primary 17.1 20.2 100 100 Secondary 32.4 36.2 189 179 University 5.6 10.0 33 50 Uruguay No Education 1.6 0.9 5 2 1981-89 Primary 30.2 51.6 100 100 Secondary 4.7 13.0 16 25 University 8.3 5.7 27 11 Venezuela No Education n.a. 2.8 n.a. 11 1981-89 Less than Primary 22.0 8.8 67 34 Primary 32.8 25.6 100 100 Secondary 9.2 10.0 28 39 University 4.1 13.1 13 51 Notes: n.a. = not available. * Due to the sample size, individuals with no education or less-dhan-primary education are grouped into less-than-primary education. -20- C. Overtime Returns to Education Among the eighteen Latin America countries, eight country data sets allow us to examine the change in returns to education over the past decade and of comparing the results shown in Table 6 to those in Table 1. There exists a slight declining trend in the returns to education, while the ten year difference in the returns to education in Argentina and Panama is only marginal. (See also Psacharopoulos (1987), Psacharopoulos and Velez (1988) and Riveros (1990), on the experiences of other countries). The behavior of rates of return to schooling by gender over time demonstrates an interesting pattern (Table 7). In the earlier period females did not have such a clear advantage over men in the returns they realized on their schooling investment; while in the early eighties, only three out of the eight countries show that the average rate of return to males is greater than their female counterparts. - 21- Table 6. Mean Earnings, Years of Schoolng and Mincerian Returns to Education: Entire Sample, chrca 1980 Country Year Earnings Years of Rate of local curr.) Schooling Return (m ) Argentina 1980 735,000 7.9 9.3 Brazil 1979 10,244 5.3 11.4 Colombia 1980 8,401 6.9 18.6 Costa Rica 1981 1,925 6.7 16.8 Panama 1979 231 8.5 13.0 Paraguay 1983 42,203 8.2 11.6 Uruguay 1981 4,375 8.5 10.3 Venezuela 1981 2,619 7.3 11.8 Source: Annex 3. -22- :ble 7. Mean Earings, Yem of Schooling and Mincerian Returns to Education: by Gender, circa 1980 Country Year Earnings (ocal curr.) Years of Schooling Rate of Return (%) Males Females Males Females Males Females Argentina 1980 1,234Q9O0 333,000 8.1 7.8 8.0 9.8 Brazil 1979 10,943 6,813 5.2 5.5 11.8 8.9 Colombia 1980 10,124 5,626 7.0 6.8 18.6 17.3 Costa Rica 1981 1,539 3,334 5.9 9.5 14.8 10.4 Panama 1979 193 281 7.3 10.0 13.4 10.5 Paraguay 1983 51,043 28,678 8.4 7.7 10.5 11.7 Uruguay 1981 4,549 4,318 9.9 8.0 7.3 10.5 Venezuela 1981 2,545 2,799 6.7 8.7 12.1 10.9 Source: Annex 3. - 23 - Unlike previous researchi', the results of the present study for the time trend in rate of return to education by gender is mixed. Although the overall average schooling for both males and females increased over time, the figures presented in Table 7 strongly support an obvious declining trend in the average rate of return for males, but not in the case of females. In five out of the eight countries studied, an increase over time in average years of schooling of females is associated with a higher rate of return. This interesting result implies that the "race" between technology and education is more relevant in the case of males than their female counterparts. The relatively higher educational attainment of public employees has not changed during the past decade (Table 8). The behavior of the average rate of return, however, has changed during the 1980s. In early 1980s, the average rates of return for the public employees in Argentina, Costa Rica, Panama, Uruguay and Venezuela were higher than those of individuals who worked in the private sector. Towards the end of the decade, the opposite is observed. This may be due to the economic crisis and fiscal constraints during the period. g/ See Psacharopoulos (1987), Psacharopoulos and Steier (1988), and Riveros (1990). -24 - Table S. Mean Earnings, Years of Schooling and Mincerlan Returns to Education: by Sector of Employment, circa 1980 Country Year Earnings (local curr.) Years of Schooling Rate of Return (%) Private Public Private Public Private Public Argentina 1980 657,000 1,319,000 7.7 9.5 6.3 9.7 Colombia 1980 10,374 3,442 7.7 5.0 16.7 14.0 Costa Rica 1981 1,990 1,744 6.3 7.7 15.6 20.6 Panama 1979 250 198 7.8 9.6 12.3 15.7 Paraguay 1983 40,880 51,151 7.6 11.9 12.0 9.2 Uruguay 1981 5,331 2,748 8.3 8.7 9.1 11.9 Venezuela 1981 2,895 1,898 7.1 7.8 11.2 14.0 Source: Annex 3. - 25 - D. Extended Earnings Functions Table 9 reports the results of fitting the extended earnings functions in order to disaggregate the retums to education by level of schooling. As shown in this table, all countries except Chile, Costa Rica, Panama, Paraguay and Peru are found to have the highest rate of return in primary education compared to other educational levels. This result is consistent with studies by Psacharopoulos (1972, 1981, 1985a, 1988). Consequently, primary education remains the most profitable investment in human capital, at least from the individual point of view. - 26 - Table 9. Mean Earings and Mincerlan Retums to Educatlon: by Level of Education Country Year Earnings Oocal curr.) Rate of Retum (%) No Ed. Primary Secondary/ Univ. Primary Secondary/ Univ. Gen-Voc Gen-Voc Argentina 1989 2,724 4,843 7,757 13,231 17.90 11.32 15.40 7,321" 12.30( 7,915F 10.98W Bolivia 1989 268 281 363 795 19.40 7.60 17.40 351w 6.63W 398W 10.43# Brazil 1989 5,257 7,145 8,772 17,658 49.55 16.40 25.75 Chile 1989 21,253 28,451 48,309 150,269 16.65 9.45 16.70 48,165" 9.43w 77,109k' 13.08Wf Colombia 1989 24,004 36,769 57,529 145,487 28.35 12.22 19.92 Costa Rica 1989 10,389 13,222 20,956 42,323 17.05 11.44 17.60 20,89(0 11.78W 21,365k 12.25' Dom. Rep. 1989 376 506 668 1,677 24.50 10.78 13.98 669" 10.83W 656k 10.28W Ecuador 1987 12,931 18,725 30,101 64,584 27.25 11.37 11.40 El Salvador 1990 495 741 1,180 2,458 23.75 11.35 8.93 Guatemala 1989 134 246 444 1,096 46.55 15.02 18.38 Honduras 1989 263 363 700 1,853 23.30L' 19.94 19.90 693", 19.80W 1,091W 28.10Y Jamaica 1989 301 4,285 6,604 7,473 23.45 38.27 9.68 Mexico 1984 18,613 54,558 100,393 173,304 51.85 12.40 12.95 101,402W 12.42" 93,182k' 12.33kv Panama 1989 167 180 335 750 11.80 14.25 18.12 342" 15.02w 274W 9.86w Continued - - 27 - Table 9 cont'd. Country Year Earnings (local curr.) Rate of Retun (%) No Ed. Primary Secondary/ Univ. Primary Secondary/ Univ Gen-Voc Gen-Voc Paraguay 1990 145,371 177,895 282,777 599,067 10.801' 11.82 13.77 Peru 1990 6,593 7,431 9,014 22,778 9.90 4.14 13.28 9,013" 4.04p 9,036 6.362' Uruguay 1989 68,495 132,583 171,160 263,405 30.55 8.98 14.05 173,317WV 8.151' 168,486' 10.15k Venezuela 1989 3,778 5,983 8,013 13,802 17.55 9.66 8.12 7,672W 8.9421 9,994' 13.10( Source: Annex 4. Notes: ' The rate of retum is with respect to less-than-primary education. Earnings for individuals of secondary general education. E Eamings for individuals of secondary vocational education. SJ Rate of return to secondary generl education with respect to pinmy education. J' Rate of return to secondary vocational education with respect to primary education. - 28 - On the other hand, only three of the countries demonstrate a declining trend of rates of return by level of education (El Salvador, Honduras and Venezuela). The "law of diminishing returns" in investment in human capital in Latin America is found wamting. E. Secondary General versus Vocational Education Ten of the data sets distinguish the type of secondary education attended. It has been argued that secondary vocational education provides individuals with potentially a better match between skills acquired in school and the world of work. Previous studies have shown that empirical evidence on this issue is ambiguous5'. We use both the earnings function and elaborate methods to estimate rates of return to secondary general or secondary vocational education with respect to primary education. For both methods, the results are very similar. Six out of the eleven countries show that the rate of return to secondary vocational education is higher than that of secondary general education (Tables 9 and 10). Moreover, in seven out of eleven countries, the private return to secondary general education does not differ from that of secondary vocational education&'. The results suggest that individuals who graduated from a vocational track of the secondary level generally have a relatively higher rate of return to their investment in education. S/ See Bellew and Moock (1990), Psacharopoulos (1985a, 1985b, 1987), Psacharopoulos and Velez (1992), and Velez and Psacharopoulos (1987). f/ Rates of return to vocational and general secondary graduates do not differ in Dominican Republic and Mexico. -29 - F. Private Returns to Education We now use the full discounting method described earlier to compute more accurate returns to education for each level and type of schooling. As shown in Table 10, among the eighteen countries, in only about half of them does primary education remain the most profitable investment by the end of the 1980s. The number of countries whose rate of return to secondary education with respect to primary education is the lowest is eight when the elaborate method is adopted. This provides stronger evidence that higher education is worthwhile to attain from an individual point of view. While El Salvador, Jamaica, Paraguay and Venezuela demonstrate a declining trend of rates of return by educational level, rates of return at each successive level increases the higher the level of education in Argentina, Chile and Honduras. - 30 - Table 10. Private Returns to Education by Level of Education: FuU Method (percent) Country Year Primary Secondary University All General Vocational Argentina 1989 10.14 14.16 15.69 13.42 14.92 Bolivia 1989 9.84 8.12 7.08 8.51 16.42 Brazil 1989 36.61 5.13 n.a. n.a. 28.17 Chile 1989 9.7 12.91 12.91 8.59 20.69 Colombia 1989 27.69 14.66 n.a. n.a. 21.66 Costa Rica 1989 12.18 17.60 16.72 17.08 12.93 Dominican Rep. 1989 85.11 15.11 14.98 negative 19.43 Ecuador 1987 17.09 17.16 n.a. n.a. 12.67 El Salvador 1990 18.90 14.51 n.a. n.a. 9.50 Guatemala 1989 33.75 17.85 n.a. n.a. 22.22 Honduras 1989 20.84" 23.29 22.08 26.78 25.94 Jamaica 1989 20.44 15.65 n.a. n.a. n.a. Mexico 1984 21.57 15.13 15.05 15.77 21.74 Panama 1989 5.71 21.03 21.02 32.55 20.99 Paraguay 1990 23.741' 14.64 n.a. n.a. 13.73 Peru 1990 13.22 6.26 6.18 negative 39.65 Uruguay 1989 27.80 10.31 10.09 10.29 12.80 Venezuela 1989 36.32 14.58 14.13 15.38 10.96 n.a. = not available Notes: 1' The rate of return is with respect to less-than-primary education. - 31 - G. Social Returns to Education In order to provide insight on the issues of resource allocation among different levels of education we present the social rates of return by educational level. Given the availability of information on unit costs of different levels of schooling, as shown in Table 11, we calculate the social rates of return to education for fourteen Latin American countries using the elaborate method discussed earlier. From Table 12, it is obvious that social rates of return are lower than the private rates of return presented in Table 10 for the corresponding countries. This is consistent with previous findings.Y In addition, in ten out of the fourteen countries the social rates of return to investment in primary education is the highest. This result is consistent with studies by Fiszbein and Psacharopoulos (1991), Gomez-Castellanos and Psacharopoulos (1990), Kugler and Psacharopoulos (1989), Psacharopoulos and Velez (1992), and Riveros (1990). It also suggests that investment in primary education is still the number one priority for most of the Latin American countries. With the lowest social rate of return to secondary education, countries such as Argentina, Bolivia, Brazil, Colombia, Mexico and Uruguay may have reached the equilibrium at this particular level of education. As seen from the estimates of social returns to both primary and university education for these six countries, with the exception of Argentina, it is profitable to 7/ See Gomez-Castellanos and Psacharopoulos (1990), Fiszbein and Psacharopoulos (1991), Kugler and Psacharopoulos (1989), Psacharopoulos (1981, 1985a, 1988), Psacharopoulos and Velez (1992), and Riveros (1990). - 32 - devote resources not only to primary education, but also to higher education. Results for Argentina, Brazil, Chile Honduras, Mexico and Uruguay indicate that on efficiency grounds, investments in higher and primary education are both profitable and that expansion of secondary education is an alternative for Chile, Costa Rica and Honduras. - 33 - Table 11. Social Direct Unit Cost per Year by Level of Education Education Unit Cost/Year Source Country/Year Level $US Local Curr. Index Argentina Primary 142 18,759 100 Inflated from 1985 figures. 1989 Secondary 310 41,157 219 Kugler and Psacharopoulos - General (1989). - Vocational University 577 76,603 408 Bolivia Primary 72 228 100 Bolivia Central Bank, Memoria 1990 Secondary 101 320 140 1990. UDAPE, "Basic - General Statistics on the University - Vocational System," 1992. Exchange rate University 504 1598 701 3.17. Brazil Primary 243 689 100 Reports from Human Resources 1989 Secondary Operations Division, Country - General 434 1,231 179 Department I, Latin America - Vocational 3,174 8,996 1,306 and Caribbean Region Office, Uk.versity 5,911 16,752 2,431 World Bank.Y1 Chile Primary 181 48,280a 100 Inflated from 1987 figu'res, 1989 Secondary 173 46,201' 96 World Bank estimates by - General 169 45,090 93 McMeekin. - Vocational 192 51,200 106 University 1,006 268,829 557 Colombia Primary 80 44,080 100 Fundacion para la Educacion 1990 Secondary 191 95,860 217 Superior y Desarrollo, - General communication to the World - Vocational Bank, August 11, 1992. University 1013 509,020 1155 Costa Rica Primary 144 11,750 100 Inflated from 1986 figures in 1989 Secondary 1978 constant prices. Cota - General 222 18,133 154 Rica Public Sector Expenditure - Vocational 423 34,476 293 Review, Report No. 7877-CR, University 1,541 125,614 1,069 Latin America and the Canbbean Regional Office, The World Bank (1989). Continued - 34 - Table 11 cont'd. Education Unit Cost/Year Source Country/Year Level $US Local Curr. Index Ecuador Primary 97 16,500 100 Gomez-Castellanos and 1987 Secondary 218 37,200 225 Psacharopoulos (1990). - General - Vocational University 652 111,200 674 El Salvador Primary 63 502 100 Fundacidn Miguel Kast (1990). 1990 Secondary 66 533 106 - General - Vocational University 227 1,852 364 Honduras Primary 115 229 100 Deflated from 1990 figures. 1989 Secondary 185 369 161 Honduras Social Sector - General Programs by W. McGreevey, - Vocational The World Bank, 1990. University 1,233 2,465 1,076 Jamaica Primary 127 729 100 Inflated from 1987 figures.y 1989 Secondary 323 1,854 254 Access. frality and Efficiency in - General Caribbean Education: A - Vocational Regional Study. Population and University 6,452 37,062 5,084 Human Resources Division, Country Dept. Ell, Latin American and Caribbean Regional Office, The World Bank, 1992. Continued - - 35 - Table 11 cont'd. Educational Unit Cost/Year Source Country/Year Level USS Local Curr. Index Mexico Primary 135 22,663 100 Based on SEP (1985), p.8. 1984 Secondary 589 98,846t 436 - General - Vocational University 1,035 173,658 766 Paraguay Primary 50 61,623 100 Public Ex= 1ditue Reviews The 1990 Secondary 144 176,259 286 Social S n, Report No. - General 10193-PA, The World Bank, - Vocational 1992. University 710 872,685 1,416 Uruguay Primary 256 154,900 100 Psacharopoulos and VElez 1989 Secondary (1992). - General 306 185,100 119 - Vocational 450 272,200 176 University 614 371,500 240 Venezuela Primary 198 7,668 100 Fiszbein and Psacharopoulos 1989 Secondary 347 13,420 175 (1991). - General 315 12,170 159 - Vocational 471 18,198 237 University 1,625 62,795 819 Source: Annex 1. Notes: Y Primary education unit cost comes from Public Sendina on Social Prosram=,while secondary educadon unit costs come from Secondary Education and Trainina in Bmzil: Adaotin to New Economic Realiis. llhzr Educaion Reform in Brazil provides the unit cost of higher education. Information for both pnmary and secondary education has to be inflated to 1989 current prices. Unit cost for nine years of primary education. I Weighted average of academic and vocational tracks (4.5: I ratio, respectively from Unesco, Statisti Xmuboic, 1990) for 3 years of secondary education. FUnit cost refers to upper secondary education. - 36 - TIble 12. Social Returns to Education by Level of Education: Full Method (percent) Country Year Primary Secondary University All General Vocational Argentina 1989 8.44 7.06 n.a. n.a. 7.55 Bolivia 1989 9.31 7.31 n.a. n.a. 13.13 Brazil 1989 35.55 5.08"' n.a. n.a. 21.44 Chile 1989 8.05 11.10 11.13 7.23 13.96 Colombia 1989 20.04 11.36 n.a. n.a. 14.03 Costa Rica 1989 11.16 14.43W 13.74 11.86 9.03 Ecuador 1987 14.71 12.73 n.a. n.a. 9.87 El Salvador 1990 16.38 13.33 n.a. n.a. 8.00 Honduras 1989 18.181 19.72 n.a. n.a. 18.93 Jamaica 1989 17.73 7.92 n.a. n.a. n.a. Mexico 1984 19.04 9.57 n.a. n.a. 12.91 Paraguay 1990 20.30-' 12.74 n.a. n.a. 10.84 Uruguay 1989 21.61 8.05"' 8.16 7.08 10.29 Venezuela 1989 23.41 10.18 9.99 10.42 6.16 n.a. = not available. Notes: LI Same cost as secondary general education. 1' The rate of return is with respect to less-than-primary education. - 37 - As suggested by Psacharopoulos (1988), results of vocationalization may not always match expectations. The estimates of social rates of return to general versus vocational secondary education shown in Table 12 demonstrate mixed results. Given the limitation of the data and the limited availability of unit cost estimates, the present study is not able to provide any conclusive argument on this issue. By comparing the private and social rates of return by level of education, one can address the extent of public subsidization of education. Table 13 presents the index of subsidization of education by level, showing that in nearly all countries university education is the most heavily subsidized level of schooling. This finding points to the regressive allocation of public finds -- a finding common in the world today. IV. Conclusion In this paper we have adopted a macro, although consistent, approach to study earnings differentials by level of education in 18 Latin American countries and used altemative methodologies to assess the private and social retums to investment in each level of education. The results document that primary education is still the number one investment priority in most countries, and that the earnings premium of higher education graduates has declined during the eighties. Given the macro nature of our findings, these should be used only as a starting point for more detailed within-country work in order to assess education investment priorities in the respective country. - 38- Table 13. Index of Pubic Subsidization of Education by Level (percent) Country Year Primary Secondary Higher Argentina 1989 17 50 49 Bolivia 1989 6 10 20 Brazil 1989 3 1 30 Chile 1989 17 14 33 Colombia 1989 28 22 35 Costa Rica 1989 8 18 30 Ecuador 1989 14 26 22 El Salvador 1989 13 8 16 Honduras 1989 13 17 27 Jamaica 1989 13 49 n.a. Mexico 1989 12 37 41 Paraguay 1989 14 13 21 Uruguay 1989 22 22 20 Venezuela 1989 36 30 44 Source: Based on Tables 10 and 12. n.a. - not available. Note: The subsidization index is defined as the percent by which the private rate of return exceeds the social rate. - 39 - REFEENCES Bellew, Rosemary and Peter Moock. 1990. "Vocational and Technical Education in Peru." Economics of Education Review 9(4):365-75. Bourgouignon, F. 1980. "The Role of Education in the Urban Labour Market During the Process of Development: The Case of Colombia." Paper presented at the VI World Congress of the International Economic Association, Mexico, August 1980. Gomez-Castellanos, Luisa and George Psacharopoulos. 1990. "Earnings and Education in Ecuador: Evidence from the 1987 Household Survey." Economics of Education Reiew 9(3):219-27. Kugler, Bernardo and George Psacharopoulos. 1989. "Earnings and Education in Argentina: An analysis of the 1985 Buenos Aires Household Survey.' Economics of Education 8(4):353-65. Mincer, J. 1974. Schooling. Experience and Earnings. New York: Columbia University Press. Fiszbein, Ariel and George Psacharopoulos. 1991. "A Cost Benefit Analysis of Educational Investment in Venezuela, 1989." Views from LATHR, Latin America and the Caribbean Technical Department, The World Bank. Psacharopoulos, George. 1972. "Rates of Return to Investment in Education Around the World." Comparative Education Review 16(1):54-67. Psacharopoulos, George and R. Layard, 1979. "Human Capital and Earnings: British Evidence and a Critique, "The Review of Economic Studies, Vol. LVI, No. 3, July 1979; 485- 503. Psacharopoulos, George. 1981. "Returns to Education: An Updated International Comparison." Comparative Education Review 17(3):321-41. Psacharopoulos, George. 1983. "Education and Private versus Public Sector Pay." IAour and SggipU 8(2):123-34. Psacharopoulos, George. 1985a. "Returns to Education: A Further International Update and Implications." The Journal of Human Resources 20(4):583-604. Psacharopoulos, George. 1985b. "An Evaluation of Curriculum Diversification in Colombia and Tanzania." Comparative Education Review 29(4):507-25. - 40 - Psacharopoulos, George. 1987. "Earnings and Education in Brazil: Evidence from the 1980 Census." Education and Training Department, Research Division, The World Bank. Psacharopoulos, George. 1988. "Education and Development: A Review." The World Bank Research Observer 3(l):99-116. Psacharopoulos, George. 1989. "Time Trends of the Returns to Education: Cross-National Evidence." Economics of Education Review 8(3):225-31. Psacharopoulos, George and Francis Steier. 1988. "Education and the Labor Market in Venezuela, 1975-84." Economics of Education Review 7(3):321-32. Psacha,opoulos, George, Ana-Maria Arriagada and Eduardo Velez. 1992. "Earnings and Education among Self-Employed Males in Colombia." Bulletin of Latin American Research 2(l):69-89. Psacharopoulos, George and Zafiris Tzannatos. 1992a. Women's Employment and Pay in Latin America: Overview and Methodology. Washington, DC: The World Bank. Psacharopoulos, George and Zafiris Tzannatos, eds. 1992b. Case Studies on Women's Employment and Pay in Latin America. Washington, DC: The World Bank. Psacharopoulos, George and Eduardo Velez. 1992. "Education and the Labor Market in Uruguay." Views from LATHR, I-atin America and the Caribbean Technical Department, The World Bank. Riveros, Luis A. 1990. "The Economic Return to Schooling in Chile. An Analysis of its Long- Term Fluctuations." Economics of Education Review 9(2): 111-21. * Schultz, T. W. 1961. "Investment in Human Capital." American Economic Review. March. Tinbergen, Jan. 1975. Income Distribution: Analysis and Policies. Amsterdam: North-Holland. Velez, Eduardo and George Psacharopoulos. 1987. "The External Efficiency of Diversified Secondary Schools in Colombia." Economics of Education Review 6(2):99-110. - 41 - ANNEx 1. SURVEY DATA DuscrinoN Geographical Number of Country/Date Survey Name Executing Agenoy Coverage Households Argentina Encuesta Permanente Instituto Nacional do Metropolitan Ara 3,400 October 1980 de Hogares (EPH) Estadistica y Censos Argentina Encuesta Permanent. Intituto Nacional de Metropotitan Area 16,759 May 1989 do Hogares (EPH) Estadistica y Censos Bolivia Encuests Permanent. Instituto Nacional de La Paz, Coohabamba, 12,226 1986 de Hogare (EPH) Estadistica (INS) Cruro, y Santa Cruz Bolivia Encuesta Integrada Instituto Nacional de 17 urban centers with 37,864 November 1989 de Hogarp (EIH) Estadistica (INE) 10,000 or mor inhabitants 8razil Pesquisa Nacional por Fundacao Istituto Brashiro Naional 88,975 November 1979 Amostra de Domicilios de Geografia y Estadistica (PNAD) Brazil Pesquisa Nacional por Fundacao Instituto Bnuieiro National 70,777 Fourth quarter 1989 Amostra de Domicilios de Geografia y Eatadistics (PNAD) Chile Encuesta Nacional del Instituto Nacional de National 32,456 Fourth quarter 1989 Empleo (PIDEH) Estadistica y Censos Colombia Encuesta Nacional de Departamento Barranquilla, Bogota, 7,473 September 1980 Hogares - Fuerza de Administraivo Nacional Bucaramanga, Call, Trabajo (ENH) de Estadstica Manizales, Medellin y pato Colombia Encuesta Nacional de Deparumento Barranquilla, Bogota, 17,949 September 1989 Hogares - Fuerza de Administraivo Nacional Bucaramanga, Ca}i, Trabajo (ENH) de Estadistica Catagena, Manizales, Medetlin y Pasto Costa Rica Encuesta Nacional de Direccion General de National 6,604 July 1981 Hogars- Empleo y Estadistica y Censos Desempleo (ENH) Costa Rica Encueta de Hogares Direecion General de National 7,637 July 1989 de Propositos Estadisdca y Censos Muldples (EHPM) Dom. Republic Encuesta de Gasto Banco Central de la National 799 March 1989 Social de las Familias Republica Dominicas Ecuador Encuesta Peiodica Instituto Nacional Nadonal 5,558 November 1987 sobro Empleo y do Empleo Desempleo Continued - -42- ANNX 1 continued - Goographical Number of Country/Date Survey Name Execouting Agency Coverage Houscholds El Salvador Encuesta de Hogamos Ministerio do Planificacion Urban 23,773 October 1990 de Proposizos y Coordinacion del Multiples (EHPM) Desarrolo Eoonomico y Social Guatemala Encuesta Nacional Instituto Nacional de National 9,660 Oct 1986-Aug 1987 Soci-Detmografica Estadistica (ENSD) Guatemala Encuesta Nacional Instituto Nacional do National 10,934 Apr 4-July 24, 1989 Socio-Demografica Estadistica (ENSD) Honduras Encuesta Continua Direccion General do 16 major cities 8,650 September 1986 Sobre Fucrza Estadstica y Censos do Trbajo (ECSFT) Honduras Encues Pormanente do Direccion General de National 8,648 September 1989 Hogares do Propositos Estadistica y Ccnsos Multipls (EPHPM) Jamaica Jamlaica Survey of Statistidcal htitute National 2,725 July 1989 Living Conditions of Jamaica Mexico Encuesta Nacional do Diroccion de Estadistica National 4,708 Third quartwr 1984 Ingreso- Gasto de de Corto Plaza los Hogarps (ENIGH) Panama Encueta do Hogares, Direcocion de EstAdistica National 8,593 Sep 19-Oct 28. 1979 Mano de Obra (EMO) y Conso P4nama Encuesta de Hogares, Diroocion de Estadistica National 8,817 August 1989 Mano de Obra (EMO) y Censos Parguay Encuesta do Hogaes, Direcion General de Metropolitan Area 1,002 June-August 1983 Mano de Obra (EMO) Estadistica y Coms Paraguay Encuesta d Hoepros, Direccion General do Metopoltan Ar 1,000 June-August 1990 Mane do Obra (EMO) Estadistica y Censos Peru Peru LSMS Instituto Nacional de National 4,981 July 1985-July 1986 Estica Informatica Peru Peru LSMS Insdtuto Cuanto Lima 1,385 June-July 1990 Uruguay Encuest Nacional de Direccion Generald Urban 9,506 Second half 1981 Hogas (ENH) Estadistica y Caaos Continued - -43 - continued - Geogrphial Number of Country/Date, Survey Name Execudng Agoney Covegp Households Uruguay Encuesta Nacional de Direccion Goneral de Urban 21,473 Second half 1989 Hogarm (NH) Estadistica y Consos Venezuela Encuosta do Hogares Oficina Centrl do National 4S,421 Second half 1981 por Muesta (EHM) Estadisdca e Informatica Venezuela Encuasa do Hogares Oficina Cental do Nadonal 61,385 Second half 1989 por Muestra (EHM) Estadistica e Informatica - 44 - ANNEX 2. VARLABLE DEFINIONS All country data sets refer to individuals age 15 to 65, inclusive. Observations with missing values for education variables have been dropped from the analysis. All individuals have positive earnings from employment. 1. Education The education variables are of two types. One is continuous in terms of years of schooling (S). The other is a series of educational dummy variables: NOSCHOOL No education. PRIMDROP Primary education incomplete. PRIM Primary education completed. SECDROP Secondary education, either general or vocational, incomplete SECGEN Secondary general education completed. In cases where information on the general/vocational split of secondary education is not available, this variable refers to both types of the curriculum. SECVOC Secondary vocational education completed. SECTEAC Teachers' college graduate. NOUNI Higher non-university education such as post-secondary education or technical institute. UNIVDROP University education incomplete. UNIV University education completed. In the case of the Paraguay data sets (1983 and 1990), the sample size of those with no- education (NOSCHOOL) is very small and hence we grouped this category with the less-than- primary category ,PRIMDROP). In Peru's 1985 and 1990 data sets, the two education groups are defined in a different way: NOSCHOOL No education or primary education incomplete. PRIM Primary education completed or secondary education incomplete. - 45 - 2. Eamings The earnings variable used in the study is the sum of monthly wage earnings and self- employment income in the primary job in local currency with a few exceptions. In the 1990 El Salvador data, bonus earnings are included. Quarterly wage income is used for Mexico while income from the main job for the last week is used in the Peru 1985 data set. 3. Hours Worked According to the over table information in the country data sets, there are three different time periods to which the hours worked variable refers to -- daily, weekly or yearly. In the 1984 Mexico data set, the hours worked information is not available. Daily Daily hours worked in Bolivia 1989 primary job Jamaica 1989 Weekly Total hours worked per week Argentina 1980, 1989 Panama 1979 Venezuela 1981 Weekly hours worked in Bolivia 1986 primary job Brazil 1979, 1989 Costa Rica 1981, 1989 Guatemala 1986, 1989 Honduras 1986 Panama i989 Paraguay 1983, 1990 Uruguay 1981, 1989 Total hours worked last week Dominican 1989 Republic Ecuador 1987 El Salvador 1990 Peru 1990 Normal hours worked per week Chile 1989 Colombia 1980, 1989 Honduras 1989 Venezuela 1989 Yearly Yearly hours worked Peru 1985 -46- 4. Sector of Employment Most of the country data sets, except data for the Dominican Republic (1989), provide information on the sector of employment for each individual. Each sample was split into "public" and "private" sub-samples using the following rule: PUBLIC Public sector employees. PRIVATE Private sector employees, self-employed individuals, employers and family workers. Of course we had to adapt the above general rule depending on the availability of information in the respective country surveys: Argentina 1980, 1989 PUBLIC Industry of natural gas and petroleum, manufacturing industry related to petroleum and minerals, electricity, gas and water supply industry, water and aerial transportation industry, communication industry, social services, public and defense administration, and drainage services. PRIVATE Manufacturing industry not related to petroleum refining, rubber, mineral, machinery and equipments, construction industry, commercial and services industries, ground transporation industry, finance and real estate, cleaning and laundry services. Bolivia 1986, 1989 PUBLIC Public administration and public employees or mixed. PRIVATE Employees of private sector and cooperative. Brazil 1989 PUBLIC Social services and public administration. PRIVATE Self-employed. Mexico 1984 PUBLIC Industries of oil, electricity and natural gas, public administration, education and research. PRIVATE Industries of food processing, textile, furniture, printing, chemical industry, mineral, metal and machinery industry, manufacturing and construction industries, wholesales and retail, hotel industry, transportation industry, real estate and services. - 47 - Peru 1985 PUBLIC Wage earners. PRIVATE Self-employed. -48- ANNE[X a BASIC EARNINGs FUNCIONS Argentina 1980 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.093 0.080 0.098 0.078 0.097 Experience (EX) 0.030 0.087 0.017 0.026 0.050 Experience-squared (EX2) -0.0004 -0.0004 -0.0002 -0.0004 -0.0007 Log Hours (H) Worked 2.278 1.584 2.228 0.642 0.614 Constant Term -3.191 -0.942 -3.096 3.231 3.056 R2 0.66 0.45 0.65 0.06 0.19w N 6,156 2,745 3,411 2,030 -737 Means| Earnings (Y) 735 1,234 333 1,207 1,309 S 7.9 8.1 7.8 7.9 9.5 EX 22 21 23 22 .21 H 31 43 22 47 40 Var (Ln Y) 3.621 2.554 2.673 1.543 1.024 Source: Encuesta Permanente de Hogares (EPH), CEPAL Notes: The earnings variable (Y) is in thousands of pesos per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level or better. -49 - ANNEx 3. BASIC EARNINGs FUNeCoNs Argentina 1989 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.103 0.107 0.112 0.010 0.089 Experience (EX) 0.045 0.052 0.039 0.046 0.048 Experience-squared (EX2) -0.0006 -0.0007 -0.0006 -0.0007 -0.0007 Log Hours (H) Worked 0.613 0.355 0.590 0.38t 0.647 Constant Term 4.856 5.843 4.719 5.767 4.847 R2 0.35 0.32 0.40 0.26 0.35 N 4,760 2,965 1,795 2,463 1,097 Mens Earnings (Y) v 7,456 8,563 5,629 7,413 8,463. S 9.1 8.7 9.8 8.7 11.0 EX 22 23 21 22 21 H 42 46 36 45 39 Var (Ln Y) 0.656 0.546 0.696 0.557 0.610 Source: Encuesta Permanente de Hogares (EPH), CEPAL. Notes: The earnings variable (Y) is in australes per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level or better. -50 - ANIx 3L BASc EARNINGS FuNcrIoNs BoUvia 1989 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.071 0.073 0.077 0.087 0.06i Experience (EX) 0.040 0.046 0.028 0.053 0.032 Experience-squared (EX2) -0.0005 -0.0006 -0.0004 -0.0007 -0.0003 Log Hours (H) Worked 0.514 0.301 0.594 0.234 0.726 Constant Term 3.278 3.726 2.994 3.656 2.919 R2 0.17 0.18 0.18 0.19 0.19 N 5,356 3,823 1,533 2,989 2,367 Mans Earnings (Y) 364 402 270 361 369 S 10.1 9.5 11.5 8.7 11.7 EX 18 19 16 17 20 H 8.2 8.7 7.1 8.7 7.6 Var (Ln Y) 0.645 0.659 0.539 0.697 0.573 Source: Encuesta Integrada de Hogares (EIH), CEPAL. Notes: The earnings variable (Y) is in bolivianos per month. H is the daily hours worked. All coefficients are statistically significant at the 5% level or better. -51 - ANNEx 3.L BASC EARNIGS FuNCIONS Brazil 1979 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.114 0.118 0.089 n.a. n.a. Experience (EX) 0.071 OD70 0.053 n.a. n.a. Experience-squared (EX2) -0.0011 -0.0011 -0.0009 n.a. n.a. Log Hours (H) Worked -0.174 -0.270 -0.301 n.a. n.a. Constant Term 8.066 8.510 8.605 n.a. n.a. R2 0.34 0.37 0.28 n.a. n.a. N 6,655 5,529 1,126 n.a. n.a. Means Earnings (Y) 10,244 10,943 6,813 n.a. n.a. S 5.3 5.2 5.5 n.a. n.a. EX 21 21 18 n.a. n.a. H 52 53 47 n.a. n.a. Var (Ln Y) 0.651 0.632 0.578 n.a. n.a. Source: Pesquisa Nacional por Amostra de Domicillos. Notes: The earnings variable (Y) is in cruzeiros per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level or better. n.a. = Not available. -52 - ANEX 3 BASIC EARNIGS FUNWCIONS Brazil 1989 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.147 0.154 0.142 0.150 0.114 Experience (EX) 0.064 0.073 0.051 0.038 0.054 Experience-squared (EX2) -0.0009 -0.0010 -0.0008 -0.0005 -0.0008 Log Hours (H) Worked 0.724 0.310 0.595 0.936 0.829 Constant Term 1.954 3.567 2.314 1.454 1.915 R2 0.29 0.30 0.29 0.26 0.26 N 108,527 69,773 38,754 24,690 17,428 MeanS Earnings (Y) 6,969 7,151 6,640 9,979 7,746 S 5.3 5.0 5.9 4.1 8.2 EX 21 22 20 28 20 H 43 46 39 43 36 Var (Ln Y) 1.631 1.474 1.680 2.051 1.608 Source: Pesquisa Nacional por Amostra de Domicillos, CEPAL. Notes: The earnings variable (Y) is in nuevos cruzados per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level or better. -53 - ANNx 3. BASIC EARNNGS FUNCTIONS ChIle 1989 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.120 0.121 0.132 0.114 0.112 Experience (EX) 0.042 0.048 0.029 0.041 0.029 Experience-squared (EX2) -0.0004 -0.0005 -0.0002 -0.0004 -0.0002 Log Hours (H) Worked 0.885 0.768 0.753 0.918 0.660 Constant Term 5.189 5.652 5.487 5.104 6.418 R2 0.40 0.39 0.45 0.37 0.29 N 37,679 26,823 10,856 33,794 3,885 Means Earnings (Y) 40,275 43,878 31,373 38,232 58,044 S 8.5 8.2 9.4 8.1 12.3 EX 21 22 20 22 20 H 47 48 44 48 43 Var (Ln Y) 0.638 0.591 0.692 0.629 0.423 Source: Programa Integrado de Encuestas de Hogares (PIDEH) Encuesta Nacional del Empleo, IV Trimestre, 1989 Notes: The earnings variable (Y) is in pesos per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level or better. -54 - AN 3. BASIC EARNNGS FUNCTONS Colombia 1980 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.186 0.186 0.173 0.167 0.140 Experience (EX) 0.066 0.081 0.042 0.060 0.060 Experience-squared (EX2) -0.0008 -0.0010 -0.0005 -0.0008 -0.0009 Log Hours (H) Worked 0.584 0.395 0.577 0.690 0.434 Constant Term 4.020 4.668 4.299 4.000 4.665 1R2 0.34 0.33 0.35 0.35 0.10 N 11,373 7,017 4,356 8,136 3,237 Means Eamings (Y) 8,401 10,124 5,626 10,374 3,442 S 6.9 7.0 6.8 7.7 5.0 EX 20 21 18 21 17 H 48 50 46 47 51 Var (Ln Y) 1.479 1.610 1.169 1.295 1.225 Source: Encuesta Nacional de Hogares, CEPAL. Notes: The eamings variable (Y) is in pesos per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level or better. -55 - ANwx 3.1 BAsic EARNiNGS FuCTIONS Colombia 1989 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.140 0.145 0.129 0.137 0.119 Experience (EX) 0.047 0.059 0.035 0.046 0.035 Experience-squared (EX2) -0.0005 -0.0006 -0.0004 -.OOOS -0.0003 Log Hours (H) Worked 0.645 0.428 0.719 0.664 0.326 Constant Term 6.190 6.897 6.108 6.140 7.980 R2 0.33 0.32 0.36 0.30 0.38 N 27,021 16,272 10,749 23,974 3,047 MM Earnings (Y) 53,643 60,592 43,124 50,279 80,116 S 8.2 8.1 8.3 7.8 11.2 EX 20 21 18 19 20 H 48 50 46 48 45 Var (Ln Y) 0.947 1.010 0.815 0.956 0.458 Source: Encuesta Nacional de Hogares, CEPAL. Notes: The earnings variable (Y) is in pesos per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level or better. 56 - ANNEX I BASIC EARNINGS FUNCIONS Costa Rica 1981 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.168 0.156 0.206 0.148 0.104 Experience (EX) 0.095 0.101 0.083 0.099 0.039 Experience-squared (EX2) -0.0011 -0.0012 -0.0011 -0.0012 -0.0005 Log Hours (H) Worked 0.698 0.695 0.598 0.699 0.584 Constant Term 2.164 2.236 2.257 2.148 4.260 R2 0.44 0.44 0.51 0.38 0.37 N 8,220 6,033 2,187 6,454 1,766 Means Earnings (Y) 1,925 1,990 1,744 1,539 3,334 S 6.7 6.3 7.7 5.9 9.5 EX 20 21 17 20 19 H 46 47 43 46 45 Var (Ln Y) 1.100 1.055 1.195 1.057 0.362 Source: Encuesta Nacional de Hogares (ENA), Empleo y Desempleo. CEPAL. Notes: The earnings variable (Y) is in colones per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level or better. -57 - ANNEX 3 BAC EARNNGS FUNCTONS Costa Rica 1989 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.109 0.105 0.135 0.093 0.085 Experience (EX) 0.039 0.042 0.033 0.035 0.030 Experience-squared (EX2) -0.0005 -0.0005 -0.0004 -0.0004 -0.0003 Log Hours (H) Worked 0.745 0.620 0.725 0.747 0.393 Constant Term 5.345 5.896 5.064 5.443 7.248 R2 0.41 0.35 0.54 0.36 0.33 N 8,882 6,400 2,482 7,305 1,577 Means Earnings (Y) 16,346 17,283 13,928 14,245 26,079 S 6.9 6.4 8.1 6.2 10.1 EX 21 22 18 21 19 H 45 47 41 45 45 Var (Ln Y) 0.692 0.576 0.922 0.677 0.268 Source: Encuesta Nacional de Hogares (ENH) Empleo y Desempleo, CEPAL. Notes: The earnings variable (Y) is in colones per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level or better. -58 - ANEX 3. BASIC EARNIGS FUNCTIONS Dominican Republic 1989 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.094 0.078 0.120 n.a. n.a. Experience (EX) 0.045 0.055 0 032 n.a. n.a. Experience-squared (EX2) -0.0005 -0.0008 -0.0004 n.a. n.a. Log Hours (H) Worked 0.338 0.331 0.261 n.a. n.a. Constant Term 3.578 3.801 3.558 n.a. n.a. R2 0.30 0.30 0.39 n.a. n.a. N 736 436 300 n.a. n.a. Earnings (Y) 652 722 552 n.a. n.a. S 8.8 8.4 9.5 n.a. n.a. EX 17 19 15 n.a. n.a. H 46 47 45 n.a. n.a. Var (Ln Y) 0.573 0.479 0.659 n.a. n.a. Source: Encuesta Nacional de Gasto Social de las Famiias. Notes: The earnings variable (Y) is in sucres per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level or better. n.a. - Not Available. - 59 - x 3. BASIC EARNINGS FuNcToNS Ecuador 1987 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.108 0.098 0.115 0.113 0.071 Experience (EX) 0.048 0.054 0.037 0.051 0.030 Experience-squared (EX2) -0.0007 -0.0008 -0.0005 -0.0007 -0.0004 Log Hours (H; Worked 0.376 0.273 0.305 0.391 0.206 Constant Term 6.864 7.434 6.938 6.730 8.234 R2 0.39 0.40 0.40 0.37 0.33 N 8,941 5,604 3,337 7,364 1,577 Means Eamings (Y) 27,313 32,049 19,360 26,254 32,258 S 9.6 9.7 9.5 8.9 12.8 EX 19 19 18 20 18, H 43 45 40 43 40 Var (Ln Y) 0.634 0.531 0.646 0.679 0.242 Source: Encuesta Periodica Sobre Empleo y Desempleo en el Area Urbana del Ecuador. Notes: Quito, Cuenca, and Guayaquil only. The earnings variable (Y) is in sucres per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level or better. - 60 - ANNEx 3. BASIC EARNiNGS FuNCTIoNs El Salvador 1990 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.097 0.096 0.098 0.094 0.062 Experience (EX) 0.037 0.041 0.034 0.038 0.015 Experience-squared (EX2) -0.0005 -0.0005 -0.0004 -0.0005 -0.0007* Log Hours (H) Worked 0.556 0.499 0.561 0.595 0.319 Constant Term 3.239 3.513 3.132 3.083 4.887 R2 0.33 0.32 0.35 0.30 0.29 N 6,903 4,094 2,809 5,785 1,009 Means Earnings (Y) 899 989 766 835 1,215 S 6.9 7.0 6.7 6.1 10.9 EX 22 22 23 23 20 H 47 47 46 48 41 Var (Ln Y) 0.656 0.619 0.669 0.677 0.224 Source: Encuesta de Hogares de Propositos Multiples. Notes: The earnings variable (Y) is in colones per month. H is the weeldy hours worked. All coefficients are statistically significant at the 5% level or better, except those with a *. -61 - ANNEx 3. BASIC EARNINGS FUNCTIONS Guatemala 1989 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.149 0.142 0.163 0.141 0.087 Experience (EX) 0.043 0.044 0.041 0.041 0.025 Experience-squared (EX2) -0.0006 -0.0006 -0.0006 -0.0006 -0.0002 Log Hours (H) Worked 0.514 0.313 0.467 0.556 0.153 Constant Term 1.822 2.698 1.750 1.692 4.252 R2 0.35 0.29 0.50 0.29 0.39 N 11,708 8,476 3,232 10,554 1,154 Means Earnings (Y) 242 256 207 219 455 S 4.3 4.0 4.8 3.7 9.1 EX 23 24 21 24 20 H 47 48 43 47 42 Var (Ln Y) 1.044 0.996 1.103 1.002 0.304 Source: Encuesta Nacional Socto-Demografica (ENSO), CEPAL. Notes: The earnings variable (Y) is in quetzales per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level or better. -62 - A,rx 3. BASIC EARNINGS FUNCTIONS Honduras 1989 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.176 0.172 0.198 0.174 0.123 Experience (EX) 0.054 0.058 0.049 0.055 0.035 Experience-squared (EX2) -0.0006 -0.0007 -0.0006 -0.0007 -0.0004 Log Hours (H) Worked 0.474 0.260 0.475 0.505 0.185 Constant Term 1.913 2.856 1.548 1.763 3.956 R2 0.43 0.42 0.51 0.37 0.49 N 9,945 6,575 3,370 8,442 1,503 Means Eanings (Y) 453 488 384 406 714 S 6.5 6.1 7.1 5.9 9.9 EX 20 20 18 20 19 H 47 48 46 48 43 Var (Ln Y) 0.990 0.937 1.042 0.964 0.428 Source: Encuesta Penranente de Hogares de Propositos Multiples (EPHPM), CEPAL. Notes: The earnings variable (Y) is in lempiras per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level or better. -63- ANNEx 3. BAsc EARNIGS FUNCTIoNs Jamaica 1989 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.288 0.280 0.317 0.249 0.160 Experience (EX) 0.052 0.083 0.039 0.041 0.018* Experience-squared (EX2) -0.0008 -0.0011 -0.0007 -0.0005 -0.0004*| Log Hours (H) Worked 0.834 0.135* 0.781 0.767 1.834 Constant Term 1.638 2.760 1.445 1.980 2.432 R2 0.21 0.22 0.28 0.15 0.18 N 2,127 1,172 955 1,768 359 Means Earnings (Y) 5,886 9,829 1,047 6,443 3,140 S 7.2 7.0 7.4 6.9 8.5 EX 20 19 20 19 21 H 5.4 5.5 5.2 5.4 5.3 Var (Ln Y) 1.940 1.982 1.761 1.628 1.690 Source: 1989 Jamaica Labor Force Survey, second round. Notes: The earnings variable (Y) is in Jamaica dollars per year. H is the daily hours worked. All coefficients are statistically significant at the 5% level or better, except those with a '. - 64 - ANNEx 3. BASIc EARNIGS FUNCTIONS Mexico 1984 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.141 0.141 0.150 0.154 0.080 Experience (EX) 0.079 0.084 0.065 0.086 0.051 Experience-squared (EX2) -0.0010 -0.0010 -0.0010 -0.0010 -0.0007 Constant Term 9.132 9.110 9.101 8.959 10.077 R2 0.29 0.31 0.29 0.26 0.22 N 4,684 3,425 1,259 3,671 1,013 Means Earnings (Y) 81,029 84,520 71,533 73,448 108,503 S 6.6 6.3 7.5 5.7 9.7 EX 20 21 17 20 18 Var (Ln Y) 0.978 0.920 1.117 1.042 0.446 Source: Encuesta Nacional de Ingreso-Gasto de los Hogares. Notes: The earnings variable (Y) is in pesos for the 3rd quarter. H is the not available hours worked. All coefficients are statistically significant at the 5% level or better. - 65 - ANNEx 3. BASIc EARNNGS FuNCTIoNs Panama 1979 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.130 0.123 0.157 0.134 0.105 Experience (EX) 0.050 0.047 0.052 0.059 0.031 Experience-squared (EX2) -0.0006 -0.0006 -0.0007 -0.0008 -0.0003 Log Hours (H) Worked 0.423 0.646 0.058* 0.525 0.419 Constant Term 1.847 1.248 2.721 1.286 2.430 R2 0.45 0.49 0.56 0.42 0.40 N 7,673 4,844 2,829 4,412 3,261 Means Earnings (Y) 231 250 198 193 281 S 8.5 7.8 9.6 7.3 10.0 EX 19 20 16 19 19 H 43 43 42 45 40 Var (Ln Y) 0.539 0.469 0.616 0.572 0.355 Source: Encuesta de Hogares - Mamo de Obra (EMO), CEPAL. Notes: The earnings variable (Y) is in balboas per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level or better, except those with a . -66 - ANNEX 3L BASIC EARNNGS FUNCTIoNS Panama 1989 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.137 0.126 0.171 0.122 0.110 Experience (EX) 0.063 0.066 0.061 0.060 0.036 Experience-squared (EX2) -0.0008 -0.0008 -0.0007 -0.0008 -0.0004 Log Hours (H) Worked 0.749 0.701 0.684 0.750 0.591 Constant Term 0.442 0.800 0. 148* 0.504 1.891 R2 0.51 0.48 0.61 0.44 0.46 N 8,616 5,436 3,180 6,041 2,575 Means Eamings (Y) 292 312 258 232 434 S 9.2 8.6 10.1 8.2 11.5 EX 20 21 19 20 20 H 42 43 40 42 40 Var (Ln Y) 0.935 0.817 1.098 0.935 0.388 Source: Encuesta Hogares-Mano de Obra (EMO), CEPAL. Notes: The earnings variable (Y) is in balboas per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level or better, except those with a *. - 67 - ANNEX 3. BASIC EARNIGS FUNCTIONS Paraguay 1983 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.116 0.105 0.117 0.120 0.09 | Experience (EX) 0.047 0.052 0.032 0.049 0.040 Experience-squared (EX2) -0.0006 -0.0008 -0.0004 -0.0007 -0.0006 Log Hours (H) Worked 0.326 0.275 0.345 0.324 0.346 Constant Term 7.561 8.007 7.336 7.515 7.859 R2 0.36 0.37 0.35 0.34 0.40 N 1,723 1,042 681 1,501 222 | Means Earnings (Y) 42,203 51,043 28,678 40,880 51,151 S 8.2 8.4 7.7 7.6 11.9 EX 19 19 18 19 17 H 49 48 49 50 39 Var (Ln Y) 0.642 0.543 0.585 0.661 0.415 Source: Encuesta de Hogares (Mano de Obra). Notes: The earnings variable (Y) is in guaranies per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level or better. -68 - ANNEX 3L BASIC EARNINGS FUNCTIONS Paraguay 1990 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.115 0.103 0.121 0.119 0.083 Experience (EX) 0.049 0.058 0.036 0.052 0.031 Experience-squared (EX2) -0.0006 -0.0009 -0.0003 -0.0007 -0.0004 Log Hours (H) Worked 0.401 0.319 0.370 0.399 0.504 Constant Term 8.873 9.467 8.763 8.808 9.117 R2 0.38 0.43 0.37 0.38 0.43 N 1,825 1,084 741 1,599 226 Means Earnings (Y) 239,861 290,496 165,787 236,360 264,629 S 9.1 9.1 8.9 8.6 12.6 EX 19 20 18 20 16 H 49 50 48 51 38 Var (Ln Y) 0.624 0.514 0.590 0.651 0.362 Source: Encuesta de Hogares (Mano de Obra). Notes: The earnings variable (Y) is in guaranies per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level or better. -69 - ANNEX 3. BAsC EARNmIGS FuNCTIONS Peru 1985 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.182 0.173 0.189 0.203 0.135 Experience (EX) 0.058 0.057 0.060 0.068 0.058 Experience-squared (EX2) -0.0007 -0.0007 -0.0008 -0.0008 -0.0007 Log Hours (H) Worked 0.896 0.892 0.860 0.781 1.013 Constant Term -0.373 -0.176 -0.335 -0.080 -0.618 R2 0.54 0.51 0.53 0.40 0.73 N 6,393 4,165 2,228 3,201 3,192 Men Earnings (Y) 9,278 11,142 5,794 7,349 11,212 S 6.7 7.1 6.1 5.1 8.4 EX 24 24 24 29 19 H 1,854 792 1,564 1,914 1,793 Var (Ln Y) 2.689 2.468 2.755 2.829 2.271 Source: 1985 Peru Survey of Living Conditions. Notes: The earnings variable (Y) is in intis per year. H is the yearly hours worked. All coefficients are statistically significant at the 5% level or better. -70- AM= 3. BAsIc EARNINGs FUNCIIONS Peru 1990 Gender Sector Variable Entire Males Females Private Publiq Sample Years of Schooling (S) 0.081 0.085 0.065 0.090 0.090 Experience (EX) 0.053 0.053 0.053 0.058 0.036 Experience-squared (EX2) -0.0007 -0.0007 -0.0008 -0.0008 -0.0005 Log Hours (H) Worked 0.519 0.355 0.473 0.491 0.766 Constant Term 6.060 6.467 6.176 6.002 5.489 R2 0.18 0.18 0.13 0.19 0.23 N 2,476 1,621 855 2,063 413 Means Earnings (Y) 9,912 11,482 6,937 10,295 8,002 S 10.1 10.2 9.8 9.6 12.5 EX 19 19 18 19 18 H 8.0 8.5 7.1 8.0 7.9 Var (Ln Y) 0.859 0.778 0.878 0.908 0.613 Source: 1990 Peru Survey of Living Conditions, Lima. Notes: The earnings variable (Y) is in thousands of intis per month. H is the daily hours worked. All coefficients are statistically significant at the 5% level or better. -71 - Nmx 3. BASIc EARNIGS FuNCnIONS Uruguay 1981 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.103 0.091 0.119 0.073 0.105 Experience (EX) 0.051 0.061 0.038 0.045 0.051 Experience-squared (EX2) -0.0007 -0.0009 -0.0005 -0.0006 -0.0007 Log Hours (H) Worked 0.724 0.449 0.571 0.334 0.79Z Constant Term 3.753 4.994 4.015 5.701 3.439 R2 0.34 0.31 0.37 0.29 0.35 N 10,587 6,666 3,921 2,599 7,988 Means Eamings (Y) 4,375 5,331 2,748 4,549 4,318 S 8.5 8.3 8.7 9.9 8.0 EX 23 24 22 21 24 H 46 50 38 44 46 Var (Ln Y) 0.771 0.582 0.764 0.318 0.893 Source: Encuesta Naclonal de Hogares (ENH), CEPAL. Notes: The eanmings variable (Y) is in pesos per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level or better. - 72 - ANNx 3. BASIC EARNNGS FuNCIONS Uruguay 1989 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.097 0.090 0.106 0.105 0.057 Experience (EX) 0.044 0.051 0.042 0.045 0.030 Experience-squared (EX2) -0.0005 -0.0007 -0.0006 -0.0006 -0.0003 Log Hours (H) Worked 0.828 0.596 0.708 0.860 0.447 Constant Term 6.998 8.029 7.164 6.779 9.051 R2 0.40 0.35 0.42 0.41 0.28 N 10,981 6,567 4,414 8,434 2,547 MeansI Earnings (Y) 145,840 178,086 97,865 146,073 145,069 S 9.0 8.7 9.3 8.6 10.2 EX 24 24 22 24 24 H 44 49 37 47 42 Var (Ln Y) 0.743 0.545 0.774 0.885 0.205 Source: Encuesta Continua de Hogares, CEPAL. Notes: The earnings variable (Y) is in pesos per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level or better. -73 - ANNX 3 BASC EARNINGS FuNCTIoNs Venezuela 1981 Gender Sector Variable Entire Males Females Private Publiq Sample Years of Schooling (S) 0.118 0.112 0.140 0.121 0.109 Experience (EX) 0.054 0.060 0.042 0.063 0.032 Experience-squared (EX2) -0.0007 -0.0008 -0.0005 -0.0008 -0.0004 Log Hours (H) Worked 0.655 0.496 0.382 0.685 0.519 Constant Term 3.614 4.305 4.314 3.382 4.467 R2 0.37 0.40 0.40 0.36 0.40 N 57,112 41,303 15,809 40,629 16,483 Means Earnings (Y) 2,619 2,895 1,898 2,545 2,799 S 7.3 7.1 7.8 6.7 8.7 EX 21 22 19 21 21 H 43 45 40 44 42 Var (Ln Y) 0.445 0.391 0.446 0.500 0.284 Source: Encuesta de Hogares por Muestra, CEPAL. Notes: The earnings variable (Y) is in bolfvares per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level or better. - 74. ANNX 3 BASIC EARNINGS FUNCTIONS Venezuela 1989 Gender Sector Variable Entire Males Females Private Public Sample Years of Schooling (S) 0.084 0.084 0.080 0.097 0.066 Experience (EX) 0.022 0.031 0.019 0.027 0.017 Experience-squared (EX2) -0.0002 -0.0003 -0.0003 -0.0002 -0.0002 Log Hours (H) Worked 0.669 0.330 0.671 0.738 0.577 Constant Term 5.103 6.311 5.153 4.626 5.746 R2 0.37 0.27 0.50 0.37 0.35 N 2,902 1,340 1,562 1,228 1,674 Means Earnings (Y) 6,894 7,858 6,067 6,700 7,037 S 9.1 7.9 10.2 7.3 10.5 EX 22 25 21 23 22 H 41 46 35 46 37 Var (Ln Y) 0.305 0.315 0.281 0.468 0.167 Source: Encuesta de Hogares por Muestra, CEPAL. Notes: The earnings variable (Y) is in bolfvares per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level or better. - 75 - ANNEx 4. ExTENDED EARNINGS FuNcTIONs Argentina 1989 Variable Sample Gender Sector Males Females Private Public No schooling -0.358 -0.351 -0.341 -0.302 -0.035* Prim. dropout -0.204 -0.216 -0.122 -0.205 -0.182 Sec. dropout 0.197 0.179 0.276 0.195 0.122* Sec. general 0.615 0.621 0.717 0.567 0.453 Sec. vocational 0.549 0.537 0.688 0.414 0.535 Teacher training 0.430 0.679 0.705 0.533 0.303 Univ. dropout 0.891 0.833 1.041 0.856 0.714 Tertiary non-univ. 0.694 0.807 0.863 0.602 0.628 University 1.182 1.248 1.265 1.255 0.949 Experience 0.046 0.052 0.041 0.045 0.052 Exp-squared -0.0007 -0.0008 -0.0006 -0.0007 -0.0008 Log hours worked 0.617 0.370 0.592 0.409 0.626 Constant 5.532 6.524 5.394 6.363 5.501 R2 0.37 0.34 0.42 0.29 0.37. N 4,760 2,965 1,795 2,463 1,097 M-M~~~~~~~~~~~~~~~ Mean Y (Local Curr.) 7,456 8,563 5,629 7,413 8,463 No schooling (%) 1.4 4.5 1.3 1.2 1.2 Prim. dropout (%) 13.6 14.0 13.0 14.0 7.5 Primary (%) 32.1 35.8 25.9 35.6 19.2 Sec. dropout (%) 20.0 21.3 17.7 21.8 17.5 Sec. general (%) 3.6 3.3 4.1 4.1 2.9 Sec. vocational (%) 10.4 9.7 11.6 10.0 11.9 Teacher training (%) 1.2 0.2 2.8 0.4 4.0 Univ. dropout (%) 7.1 7.0 7.1 6.5 9.3 Tertiary non-univ. (%) 3.9 1.8 7.5 1.9 10.9 University (%) 6.8 5.4 9.0 4.5 15.5 Experience (Years) 22 23 21 22 21 Hours worked (Hours) 42 46 36 45 39 VAR (Ln Y) 0.656 0.546 0.696 0.557 0.610 Source: Encuesta Permanente de Hogares (EPH), CEPAL. Notes: The earnings variable (Y) is in australes per month. H is the weekly hours worked. * Not statistically significant at the 5% level. - 76 - ANEX 4. EXTEDED EARNNGS FuNCToNs Bolivia 1989 Variable Sample Gender Sector Males Females Private Public No schooling -0.388 -0.259 -0.452 -0.458 -0.079* Prim. dropout -0.128 -0.099* -0.306 -0.147 -0.098* Sec. dropout 0.147 0.147 0.070* 0.118 0.212 Sec. general 0.265 0.289 0.200 0.294 0.249 Sec. vocational 0.417 0.516 0.419 0.492 0.346 Teacher training 0.139* 0.192* 0.149* 0.342* 0.120* Univ. dropout 0.299 0.309 0.358 0.487 0.279 University 1.000 1.055 0.832 1.109 0.967 Experience 0.041 0.044 0.034 0.049 0.037 Exp-squared -0.0005 -0.0006 -0.0005 -0.0007 -0.0004 Log hours worked 0.421 0.254 0.505 0.237 0.561 Constant 4.001 4.372 3.800 4.337 3.710 R2 0.21 0.22 0.20 0.20 0.26 N 5,356 3,823 1,533 2,989 2,367 M-aa Y (Local Curr.) 364 402 270 361 369 No schooling (%) 2.1 1.9 2.5 3.0 0.9 Prim. dropout (%) 26.9 31.7 14.9 35.3 16.3 Primary (%) 5.4 6.1 3.8 0.7 3.4 Sec. dropout(%) 16.4 18.6 11.0 19.7 12.3 Sec. general (%) 13.3 13.5 12.9 13.5 13.1 Sec. vocational (%) 4.5 3.0 8.3 4.2 4.9 Teacher training (%) 0.5 0.4 0.8 0.3 0.8 Univ. dropout (%) 20.3 14.3 35.2 10.4 32.7 University (%) 10.5 10.5 10.6 6.5 15.5 Experience (Years) 18 19 16 17 20 Hours worked (Hours) 8.2 8.7 7.1 8.7 7.6 VAR (Ln Y) 0.645 0.659 0.539 0.697 0.573 Source: Encuesta Integrada de Hogares (EIH), CEPTAL Notes: The earnings variable (Y) is in bolivianos per month. H is the daily hours worked. * Not statistically significant at the 5% level. - 77 - ANNEX 4. EXTEDED EARNNGS FuNcTIoNs Brazil 1989 Variable Sample Gender Sector Males Females Private Public No Schooling -0.911 -1.022 -0.718 -1.117 -0.280 Prim. dropout -0.577 -0.580 -0.602 -0.589 -0.506 Sec. dropout 0.205 0.189 0.209 0.131 0.128 Sec. general 0.492 0.544 0.540 0.433 0.372 Univ. diopout 1.136 1.153 1.199 0.963 1.001 Univ. dropout 1.522 1.516 1.561 1.516 1.424 Experience 0.064 0.070 0.054 0.035 0.055 Exp-squared -0.0010 -0.0010 -0.0009 -0.0005 -0.0008 Log hours worked 0.768 0.366 0.631 0.944 0.927 Constant 2.903 4.554 3.165 2.658 2.268 R2 0.29 0.30 0.31 0.25 0.33 N * 108,527 69,773 38,754 24,690 17,428 Mean Y (Local Curr.) 6,969 7,151 6,640 9,979 7,746 No Schooling (%) 22.7 22.9 22.3 25.6 15.8 Prim. dropout 46.0 49.2 40.2 55.0 24.8 Primary (%) 7.7 7.8 7.5 6.5 7.6 Sec. dropout (%) 3.2 3.3 3.1 2.5 4.0 Sec. general (%) 12.4 10.1 16.5 6.7 24.4 Univ. dropout 1.7 1.4 2.3 0.7. 4.1 University (%) 6.3 5.3 8.1 2.9. 19.3 Experience 21 22 20 28 20 Hours Worked 43 46 39 43 36 VAR (Ln Y) 1.631 1.474 1.680 2.051 1.608 Source: Pesquisa Nacional por Amostra de Domicilios, CEPAL. Notes: The earnings variable (Y) is in nuevos cruzados per month. H is the weekly hours worked. All Coefficients are statistically significant at the 5% level. - 78 - ANNEx-4. EXTEDED EARNINGS FucnrIoNS Chile 1989 Variable Sample Gender Sector Males Females Private Public No schooling -0.333 -0.350 -0.339 -0.329 -0.084* Prim. dropout -0.171 -0.188 -0.141 -0.164 -0.171 Sec. dropout 0.287 0.280 0.347 0.267 0.326 Sec. general 0.566 0.606 0.611 0.544 0.469 Sec. vocational 0.785 0.883 0.753 0.760 0.796 Teacher training 1.025 0.915 1.292 0.801 0.767 Univ. dropout 1.120 1.110 1.263 1.136 0.799 University 1.736 1.811 1.687 1.847 1.283 Experience 0.038 0.044 0.026 0.037 0.032 Exp-squared -0.0005 -0.0006 -0.0003 -0.0005 -0.0004 Log hours worked 0.941 0.835 0.805 0.954 0.706 Constant 5.847 6.278 6.241 5.802 7.069 -R2 0.42 0.42 0.47 0.40 0.29 N 37,679 26,823 10,856 33,794 3,885 Mean Y (Local Curr.) 40,275 43,878 31,373 38,232 58,044 No schooling (%) 5.2 5.8 3.9 5.7 0.9 Prim. dropout (%) 23.3 25.4 18.2 25.6 3.2 Primary (%) 17.3 18.4 14.6 18.5 7.4 Sec. dropout(%) 24.9 25.5 23.6 25.3 21.5 Sec. general (%) 19.1 17.0 24.3 18.1 27.6 Sec. vocational(%) 0.1 0.1 0.1 0.1 0.1 Teacher training (%) 0.6 0.3 1.1 0.1 4.2 Univ. dropout (%) 5.6 4.3 9.0 4.1 19.0 University (%) 4.3 3.8 5.6 2.9 16.6 Expe :ence (Years) 21 22 20 22 20 Hours worked (Hours) 47 48 44 48 43 VAR (Ln Y) 0.638 0.591 0.692 0.629 0.423 Source: Programa Integrado de Encuestas de Hogares (PIDEH), Encuesta Nacional del Empleo, IV Trimatre, 1989. Notes: The earnings variable (Y) is in pesos per month. H is the weekly hours worked. * Not statistically significant at the 5% level. - 79 - ANNEX 4. EXTEDED EARNNGS FUNCTIONS Colombia 1989 Variable Sample Gender Sector Males Females Private Public No Schooling -0.567 -0.557 -0.461 -0.565 -0.053* Prim. dropout -0.245 -0.247 -0.224 -0.243 -0.179 Sec. dropout 0.291 0.309 0.256 0.271 0.380 Sec. general 0.733 0.746 0.720 0.703 0.595 Univ. dropout 1.143 1.146 1.109 1.106 0.899 University 1.729 1.798 1.567 1.736 1.373 Experience 0.046 0.057 0.037 0.045 0.035 Exp-squared -0.0005 -0.0006 -0.0005 -0.0005 -0.0004 Log hours worked 0.639 0.430 0.708 0.659 0.272 Constant 6.981 7.690 6.822 6.915 8.845 R2 0.33 0.33 0.36 0.30 0.38 N 27,021 16,272 10,749 23,974 3,047 Mean Y (Local Curr.) 53,643 60,592 43,124 50,279 80,116 No Schooling (%) 2.4 2.0 3.0 2.6 0.4 Prim. dropout (%) 14.0 13.9 14.3 15.2 5.1 Primary (%) 19.3 20.0 18.3 20.7 8.8 Sec. dropout (%) 28.8 30.6 26.1 30.0 19.0 Sec. general (%) 19.5 17.9 21.9 18.3 28.5 Univ. dropout (%) 6.8 6.2 7.7 5.9 13.7 University (%) 9.2 9.5 8.7 7.2 24.5 Experience (Years) 20 21 18 19 20 Hours Worked (Hours) 48 50 46 48 45 VAR (Ln Y) 0.947 1.010 0.815 0.956 0.458 Source: Encuesta Nacional de Hogares, CEPAL. Notes: The earnings variable (Y) is in pesos per month.. H is the weekly hours worked. * Not statistically significant at the 5% level. - 80 - AtwX 4. EXMiDED EARNINGS FUNCrIONS Costa Rica 1989 Variable Sample Gender Sector Males Females Private Public No schooling -0.341 -0.220 -0.468 -0.309 -0.067* Prim. dropout -0.199 -0.219 -0.209 -0.179 -0.037* Sec. dropout 0.283 0.285 0.330 0.266 0.217 Sec. general 0.589 0.552 0.782 0.511 0.402 Sec. vocational 0.735 0.684 0.921 C.619 0.541 Univ. dropout 0.872 0.850 1.036 0.730 0.614 Tertiary non-univ. 0.914 0.953 0.943 0.768 0.658 University 1.293 1.276 1.451 1.244 0.923 Experience 0.040 0.040 0.036 0.036 0.034 Exp-squared -0.0005 -0.0006 -0.0005 -0.0005 -0.0004 Log hours worked 0.748 0.627 0.726 0.747 0.402 Constant 5.942 6.466 5.808 5.960 7.696 R2 0.41 0.35 0.54 0.36 0.32 N 8,882 6,400 2,482 7,305 1,577 Y (Local Curr.) 16,346 17,283 13,928 14,245 26,079 No schooling (%) 5.5 6.6 2.6 6.3 1.6 Prim. dropout(%) 22.4 25.0 15.9 25.4 8.7 Primary (%) 34.7 36.0 31.5 37.9 20.0 Sec. dropout(%) 15.4 15.0 16.2 16.0 12.5 Sec. general (%) 10.5 8.3 16.1 8.2 21.0 Sec. vocational (%) 1.7 1.5 2.2 1.3 3.8 Univ. dropout (%) 4.2 3.3 6.6 2.4 12.7 Tertiary non-univ. (%) 0.7 0.6 0.8 0.4 1.8 University (%) 5.0 3.8 8.1 2.1 17.9 Experience (Years) 21 22 18 21 19 Hours worked (Hours) 45 47 41 45 45 VAR (Ln Y) 0.692 0.576 0.922 0.677 0.268 Source: Encuesta Nacional de Hogares (ENH) Ernpleo y Desempleo, CEPAL. Notes: The earnings variable (Y) is in colones per month. H is the weekly hours worked. * Not statistically significant at the 5% level. - 81 - ANNEX 4. EXrEDED EARNIGS FUNCIONS Dominican Republic 1989 Variable Sample Gender Sector Males Females Private Public No schooling -0.490 40.272* -0.913 n.a. n.a. Prim. dropout -0.171 -0.052* -0.358 n.a. n.a. Sec. dropout 0.339 0.316 0.415 n.a. n.a. Sec. general 0.433 0.491 0.347 n.a. n.a. Sec. vocational 0.411* -0.109* 0.655 n.a. n.a. Univ. dropout 0.826 0.846 0.863 n.a. n.a. University 1.131 0.955 1.410 n.a. n.a. Experience 0.045 0.055 0.030 n.a. n.a. Exp-squared -0.0006 -0.0008 -0.0003* n.a. n.a. Log hours worked 0.341 0.352 0.250 n.a. n.a. Constant 4.193 4.169 4.518 n.a. n.a. R2 0.31 0.31 0.42 n.a. n.a. N 736 436 300 n.a. n.a. Y (Local Curr.) 652 722 552 n.a. n.a. No schooling (%) 5.6 6.4 4.3 n.a. n.a. Prim. dropout (%) 33.6 37.2 28.3 n.a. n.a. Primary (%) 9.6 11.2 7.3 n.a. n.a. Sec. dropout (%) 15.6 14.0 18.0 n.a. n.a. Sec. general (%) 14.7 14.7 14.7 n.a. n.a. Sec. vocational (%) 1.2 0.2 2.7 n.a. n.a. Univ. dropout(%) 12.4 8.5 18.0 n.a. n.a. University (%) 7.1 7.6 6.3 n.a. n.a. Experience (Years) 17 19 15 n.a. n.a. Hours worked (Hours) 46 47 45 n.a. n.a. VAR (Ln Y) 0.573 0.479 0.659 n.a. n.a. Source: Encuesta Nacionall de Gasto Social de las Famlias. Notes: The earnings variable (Y) is in sucres per monthi. H is the weekly hours worked. * Not stadstically significant at the 5% level. - 82 - ANNEX 4. EXTEDED EARNIGS FUNCnONS Ecuador 1987 Variable Sample Gender Sector Males Females Private Public No Schooling -0.545 -0.319 -0.408 -0.532 -0.485 Prim. dropout -0.244 -0.129 -0.258 -0.254 0.007* Sec. dropout 0.295 0.234 0.333 0.298 0.160 Sec. general 0.682 0.594 0.889 0.689 0.409 Univ. dropout 0.983 0.875 1.142 0.9J9 0.621 University 1.366 1.305 1.377 1.467 0.885 Experience 0.049 0.055 0.039 0.052 0.031 Exp-squared -0.0007 -0.0008 -0.0005 -0.0007 -0.0004 Log hours worked 0.374 0.269 0.305 0.389 0.195 Constant 7.508 8.039 7.536 7.406 8.711 R2 0.39 0.39 0.40 0.36 0.33 N 8,941 5,604 3,337 7,364 1,577 Mean Y (ocal Curr.) 27,313 32,049 19,360 26,254 32,258 No Schooling (%) 2.8 1.6 4.7 3.3 0.5 Prim. dropout (%) 8.8 8.0 10.3 10.1 2.9 Primary (%) 27.9 29.6 25.1 31.2 12.2 Sec. dropout (%) 19.9 22.3 15.9 21.3 13.1 Sec. general(%) 17.7 15.1 22.1 16.5 23.5 Univ. dropout (%) 13.5 13.1 14.3 10.9 25.7 University (%) 9.4 10.4 7.7 6.6 22.1 Experience (Years) 19 19 18 19 18 Hours Worked (Hours) 43 45 40 43 40 VAR (Ln Y) 0.634 0.531 0.646 0.679 0.242 Source: Encuesta Periodica Sobre Enpleo y Desempleo en el Area Urbana del Ecuador in Quito, Cuenca, and Guayaquil. Notes: (Y) is the earning variable in sucres per month. (H) is the weekly hours worked. * Not statistically significant at the 5% level. - 83 - ANNX 4. EXMEDED EARNINGS FUNerIONS El S'lvador 1990 Variable Sample Gender Sector Males Females Private Public No schooling -0.478 -0.552 -0.293 -0.437 -0.231 Prim. dropout -0.188 -0.194 -0.135 -0.162 -0.164 Sec. dropout 0.249 0.246 0.232 0.243 0.202 Sec. general 0.685 0.664 0.785 0.677 0.401 Univ. dropout 1.089 1.040 1.179 1.092 0.691 Tertiary non-univ. 0.963 0.896 1.130 0.869 0.593 University 1.478 1.366 1.699 1.609 0.950 Experience 0.038 0.041 0.037 0.039 0.016 Exp-squared -0.0005 -0.0006 -0.0006 -0.0006 40.0001* Log hours worked 0.573 0.511 0.588 0.607 0.341 Constant 3.711 4.017 3.484 3.545 5.136 R2 0.33 0.32 0.37 0.30 0.29 N 6,903 4,094 2,809 5,785 1,009 men Y (Local Curr.) 899 989 766 835 1,215 No schooling (%) 12.6 10.1 16.2 14.4 3.0 Prim. dropout (%) 26.5 26.6 26.2 29.6 10.1 Primary (%) 16.2 17.6 14.1 17.1 11.5 Sec. dropout(%) 20.5 23.7 15.9 21.4 15.0 Sec. general (%) 14.8 13.0 17.4 12.4 27.7 Univ. dropout (%) 3.8 4.1 3.2 2.8 8.6 Tertiary non-univ. (%) 3.6 2.2 5.7 1.1 18.6 University (%) 2.1 2.6 1.3 2.8 6.1 Experience (Years) 22 22 23 23 20 Hours worked (Hours) 47 47 46 48 41 VAR (Ln Y) 0.656 0.619 0.569 0.667 0.224 Source: Encuesta de Hogares de Propositos Muldples Notes: The earnings variable (Y) is in colones per month. H is the weekly hours worked. * Not statistically significant at the 5% level. - 84 - A X 4. ExTEDED EARNNGS FucnCTONs Guatemala 1989 Variable Sample Gender Sector Males Females Private Public No Schooling -0.931 -0.902 -0.948 -0.864 -0.391 Prim. dropout -0.436 -0.424 -0.529 -0.394 -0.173 Sec. dropout 0.382 0.371 0.449 0.345 0.339 Sec. general 0.901 0.796 1.107 0.792 0.571 Univ. dropout 1.153 1.059 1.336 1.110 0.702 University 1.636 1.557 1.775 1.694 1.098 Experience 0.041 0.042 0.041 0.037 0.026 Exp-squared -0.0006 -0.0006 -0.0006 -0.0005 -0.0003 Log hours worked 0.500 0.302 0.466 0.546 0.138 Constant 2.805 3.643 2.738 2.616 4.783 R2 0.34 0.28 0.50 0.28 0.39 N 11,708 8,476 3,232 10,554 1,154 kqean No Schooling (%) 31.0 30.4 32.4 33.7 6.5 Prim. dropout 32.6 35.5 25.2 34.7 13.5 Primary (%) 15.5 16.0 14.4 15.1 19.5 Sec. dropout (%) 9.9 9.2 11.8 9.1 17.0 Sec. general (%) 6.1 4.5 10.3 4.1 24.4 Univ. dropout 2.5 2.0 3.6 1.6 10.1 University (%) 2.4 2.4 2.3 1.6 9.1 Experience 23 24 21 24 20 Hours Worked 47 48 43 47 42 VAR (Ln Y) 1.044 0.996 1.103 1.002 0.304 Source: Encuesta Nacional Socio-Demografica (ENSO), CEPAL. Notes: The earnings variable (Y) is in quetzales per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level. - 85 - ANEx 4. ExTEDED EARNINGS FuNCTIONS Honduras 1989 Variable Sample Gender Sector Males Females Private Public Prim. dropout -0.466 -0.525 -0.423 -0.438 -0.387 Sec. dropout 0.412 0.374 0.486 0.402 0.172 Sec, general 0.990 0.898 1.231 0.973 0.547 Sec. vocational 1.405 1.200 2.315 1.449 0.923 Univ. dropout 1.357 1.173 1.684 1.357 0.817 Tertiary non-univ. 1.310 1.111 1.659 1.304 0.811 University 1.992 1.879 2.173 2.102 1.372 Experience 0.054 0.057 0.052 0.054 0.035 Exp-squared -0.0007 -0.0008 -0.0007 -0.0007 -0.0004 Log hours worked 0.477 0.256 0.491 0.511 0.136 Constant 2.963 3.951 2.620 2.790 4.972 R2 0.42 0.41 0.51 0.36 0.51 N 9,945 6,575 3,370 8,442 1,503 Mean Y (Local Curr.) 453 488 384 406 714 No schooling (%) 0.0 0.0 0.0 0.0 0.0 Prim. dropout (%) 41.1 44.9 33.5 45.9 13.8 Primary (%) 28.1 28.1 9.7 29.9 17.6 Sec. dropout (%) 9.5 9.4 28.0 9.3 10.9 Sec. general (%) 14.6 10.6 22.4 10.5 37.6 Sec. vocational (%) 0.3 0.4 0.0 0.2 0.5 Univ. dropout (%) 1.6 1.6 1.6 1.1 4.2 Tertiary non-univ. (%) 0.9 0.7 1.2 0.4 3.5 University (%) 4.1 4.3 3.6 2.7 11.8 Experience (Years) 20 20 18 20 19 Hours worked (Hours) 47 48 46 48 43 VAR (Ln Y) 0.990 0.937 1.042 0.964 0.428 Source: Encuesta Permanete de Hogares de Propositos Multiples (EPHPM), CEPAL. Notes: The earnings variable (Y) is in lempiras per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level. - 86 - AxNNE 4. EXTEDED EARNGS FVNCfONS Jamaica 1989 Variable Sample Gender Sector Males Females Private Public No Schooling -0.469* -0.748 -0.168* -0.544 -0.600* Prim. dropout -0.093* -0.254* 0.022* .0.093* -0.217* Sec. dropout 1.618 1.570 1.785 1.288 1.009 Sec. general 2.296 2.050 2.608 2.363 1.182 University 2.877 2.973 2.657 3.322 1.441 Experience 0.063 0.089 0.058 0.055 0.018* Exp-squared -0.0009 -0.0013 -0.0010 -0.0008 -0.0004* Log hours worked 0.985 0.286* 0.945 0.874 2.000 Constant 3.046 4.213 2.878 3.236 2.937 R2 0.30 0.28 0.42 0.22 0.24 N 2,127 1,172 955 1,768 359 Mean Y (Local Cuff) 5,886 9,829 1,047 6,443 3,140 No Schooling(%) 1.1 1.3 0.9 1.1 1.1 Prim. dropout(%) 6.3 7.1 5.3 6.8 3.9 Primary (%) 74.7 77.1 71.6 81.2 42.6 Sec. dropout (%) 12.0 9.0 15.6 7.1 36.2 Sec. general (%) 5.0 4.3 5.9 3.3 13.4 University (%) 1.0 1.2 0.7 0.6 3.1 Experience (Years) 20 19 20 19 21 Hours Worked (Hours) 5.4 5.5 5.2 5.4 5.3 VAR (Ln Y) 1.940 1.982 1.761 1.628 1.690 Source: 1989 Jamaica Labor Force Survey, second round. Notes: The earnings variable (Y) is in Jamaica dollars per year. H is the daily hours worked. * Not statistically significant at the 5% level. - 87- ANxA 4. ExrENDED EARNNGS FvNcIONS Mexico 1984 Variable Sample Gender ' Sector Males Females Private Public No schooling -1.037 -1.069 -1.049 -1.027 -0.393 Prim, dropout -0.552 -0.565 -0.671 -0.561 -0.284 Sec. dropout 0.345 0.291 0.485 0.391 0.073* Sec. general 0.745 0.720 0.856 0.809 0.379 Sec. vocational 0.740 0.776 0.851 0.929 0.306 Univ. dropout 0.890 0.839 0.982 0.934 0.464 University 1.262 1.269 1.212 1.498 0.786 Experience 0.077 0.081 0.065 0.084 0.048 Exp-squared -0.001 -0.001 -0.001 -0.001 -0.0007 Constant 10.074 10.094 10.040 9.953 10.697 R2 0.29 0.32 0.30 0.26 0.22 N 4,684 3,425 1,259 3,671 1,013 Y (Local Curr.) 81,029 84,520 71,533 73,448 108,503 No schooling (96) 9.2 10.3 6.1 11.3 1.6 Prim. dropout (%) 26.8 30.0 18.0 31.2 10.8 Primary (%) 23.0 22.4 24.5 24.7 16.8 Sec. dropout (%) 25.9 23.9 31.3 24.9 29.5 Sec. general (%) 5.4 3.8 9.8 2.3 16.9 Sec. vocational (%) 0.7 0.4 1.7 0.4 2.0 Univ. dropout (9) 3.7 3.9 3.2 2.6 7.8 University (%) 5.4 5.4 5.3 '2.8 14.7 Experience (Years) 20 21 17 20 18 VAR (Ln Y) 0.978 0.920 1.117 1.042 0.446 Source: Encuesta Nacional de Ingreso - Gasto de los Hogares. Notes: The earnings variable (Y) is in pesos for the 3rd quarter. H is the Hours of work is not available. hours worked. * Not statistically significant at the 5% level. - 88 - ANNEX 4 ExrEDED EARNGS FuNcTIoNs Panama 1989 Variable Sample Gender Sector Males Females Private Public No schooling -0.236 -0.238 -0.426 -0.152 -0.272 Prim. dropout -0.251 -0.243 -0.348 -0.218 -0.161 Sec. dropout 0.395 0.359 0.516 0.353 0.309 Sec. general 0.901 0.794 1.190 0.800 0.676 Sec. vocational 0.493 0.467 0.600 0.406 0.540 Univ. dropout 1.239 1.107 1.572 1.170 0.870 University 1.764 1.713 1.993 1.767 1.310 Experience 0.068 0.070 0.068 0.066 0.039 Exp-squared -0.0009 -0.0009 -0.0009 -0.0009 -0.0004 Log hours worked 0.747 0.696 0.690 0.745 0.601 Constant 1.182 1.511 1.045 1.159 2.506 R2 0.52 0.49 0.61 0.46 0.45 N 8,616 5,436 3,180 6,041 2,575 Mew Y (Local Curr.) 292 312 258 232 434 No schooling (%) 3.4 4.2 2.1 4.5 0.9 Prim. dropout (%) 11.0 12.6 8.4 13.8 4.5 Primary (%) 25.2 27.4 21.3 29.4 15.1 Sec. dropout (%) 21.4 22.3 19.9 22.9 18.0 Sec. general (%) 18.9 16.9 22.3 15.9 25.9 Sec. vocational (%) 2.2 2.3 2.1 2.3 2.0 Univ. dropout (%) 8.7 6.5 12.4 6.5 13.8 University (%) 9.2 7.9 11.6 4.7 19.8 E7xperience (Years) 20 21 19 20 20 Hours worked (Hours) 42 43 40 42 40 VAR (Ln Y) 0.935 0.817 1.098 0.935 0.388 Source: Encuesta Hogares - Mano de Obra (EMO), CEPAL. Notes: The earnings variable (Y) is in balboas per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level. - 89 - AMEX 4. EXTENDED EARNPGS FUNCTIONS Paraguay 1983 Variable Sample Gender Sector Males Females Private Public Prim. dropout -0.213 -0.222 -0.146 -0.163* -0.145* Sec. dropout 0.317 0.189 0.373 0.330 -0.110* Sec. general 0.679 0.547 0.798 0.739 0.075* Univ. dropout 1.029 0.898 1.130 1.159 0.294 University 1.532 1.390 1.550 1.551 1.054 Experience 0.048 0.050 0.034 0.051 0.036 Exp-squared -0.0007 -0.0008 -0.0005 -0.0008 -0.0006 Log hours worked 0.328 0.280 0.353 0.338 0.3001 Constant 8.240 8.681 7.932 8.544 8.979 R2 0.35 0.37 0.35 0.33 0.49 N 1,723 1,042 681 1,501 222 Mean Y (Local Curr.) 42,203 50,143 28,678 40,880 51,151 Prim. dropout (%) 23.9 21.9 26.9 26.7 4.5 Pi mnary (%) 27.9 26.3 30.2 30.6 9.5 Sec. dropout (%) 20.5 22.7 17.2 20.5 20.7 Sec. general (%) 14.9 15.3 14.4 12.4 32.0 Univ. dropout (%) 6.9 7.0 6.8 5.4 17.1 University (%) 5.9 6.8 4.6 4.4 16.2 Experience (Years) 19 19 18 19 17 Hours worked (Hours) 49 48 49 50 39 VAR (Ln Y) 0.642 0.543 0.585 0.661 0.415 Source: Encuesta de Hogares (Mano de Obra). Notes: The earnings variable (Y) is in guaranies per month. H is the weeldy hours wor.ced. * Not statistically significant at the 5 % level. -90-. ANX 4. EXTnED EARNGS FUNCTIONS Paraguay 1990 Variable Sample Gender Sector Males Females Private Public No schooling Prim. dropout -0.216 -0.226 -0.230 -0.217 0.012* Sec. dropout 0.322 0.192 0.257 0.323 0.130* Sec. general 0.709 0.569 0.748 0.736 0.323 Univ. dropout 0.986 0.797 1.118 1.027 0.547 University 1.535 1.394 1.498 1.612 0.988 Experience 0.051 0.057 0.040 0.054 0.035 Exp-squared -0.0007 -0.0009 -0.0005 -0.0007 -0.0005 Log hours worked 0.414 0.343 0.380 0.417 0.514 Constant 9.484 10.042 9.427 9.647 9.682 R2 0.39 0.44 0.36 0.38 0.44 N 1,825 1,084 741 1,599 226 Mqean Y (Local Curr.) 239,861 290,496 165,787 236,360 264,629 Prim. dropout(%) 15.0 14.9 15.0 16.8 1.8 Primary (%) 25.3 22.3 29.7 28.1 5.8 Sec. dropout (%) 22.0 25.1 17.4 23.1 14.2 Sec. general (%) 23.5 23.8 22.9 31.1 39.8 Univ. dropout (%) 7.9 7.0 9.2 5.7 23.5 University (%) 6.4 6.8 5.8 5.2 15.0 Experience (Years) 19 20 18 20 16 Hours worked (Hours) 49 50 48 51 38 VAR (Ln Y) 0.624 0.514 0.590 0.651 0.362 Source: Encuesta de Hogares (Mano de Obra). Notes: The earnings variable (Y) is in guaranies per month.. H is the weekly hours worked. * Not statistically significant at the 5% level. - 91 - ANNEX 4. ExTENDED EARNINGS FuNCTiONS Peru 1990 Variable Sample Gender Sector Males Females Private Public No schooling -0.198 -0.172 -0.074* -0.213 -0.193 Sec. general 0.202 0.174 0.260 0.223 0.206 Sec. vocational 0.318 0.276* 0.510 0.342 0.237* Univ. dropout 0.543 0.507 0.553 0.587 0.562 Tertiary non-univ. 0.381 0.467 0.392 0.435 0.428 University 0.871 0.918 0.792 1.072 0.786 Experience 0.053 0.051 0.055 0.057 0.040 Exp-squared -0.0008 -0.0007 -0.0009 -0.0008 -0.0006 Log hours worked 0.527 0.362 0.465 0.495 0.789 Constant 6.716 7.182 6.616 6.747 6.162 R2 0.19 0.19 0.14 0.19 C.23 N 2,476 1,621 855 2,063 413 Mean Y (Local Curr.) 9,912 11,482 6,937 10,295 8,002 No schooling (%) 19.4 17.1 23.6 21.8 7.5 Primary (%) 20.2 21.4 17.9 22.6 8.2 Sec. general (%) 35.0 37.1 31.0 35.4 32.9 Sec. vocational (%) 1.3 1.1 1.5 1.3 1.2 Univ. dropout (%) 7.1 7.5 6.5 6.4 10.9 Tertiary non-univ. (%) 7.1 5.7 .9.6 5.9 13.1 University (%) 10.0 10.1 9.8 6.7 26.2 Experience (Years) 19 19 18 19 18 Hours worked (Hours) 8.0 8.5 7.1 8.0 7.9 VAR (Ln Y) 0.859 0.778 0.878 0.908 0.613 Source: 1990 Peru Survey of Living Conditions, Lima. Notes: The earnings variable (Y) is in thousands of intis per month. H is the daily hours worked. * Not statistically significant at the 5% level. -92 f ANNEX 4. ExrEDED EARNNGS FUNCTIONS Uruguay 1989 Variable Sample Gender Sector Males Females Private Public No schooling -0.611 -0.398 -0.538 -0.560 -0.412 Prim. dropout -0.346 -0.333 -0.415 -0.360 -0.186 Sec. dropout 0.253 0.199 0.212 0.283 0.100 Sec. general 0.489 0.520 0.571 0.533 0.235 Sec. vocational 0.609 0.437 0.830 0.536 0.412 Univ. dropout 0.706 0.642 0.768 0.815 0.290 University 1.101 1.059 1.130 1.255 0.588 Experience 0.042 0.049 0.040 0.043 0.029 Exp-squared -0.0006 -0.0007 -0.0006 -0.0006 -0.0003 Log hours worked 0.832 0.602 0.715 0.876 0.428 Constant 7.780 8.761 8.000 7.574 9.624 R2 0.38 0.32 0.40 0.39 0.24 N 10,981 6,567 4,414 8,434 2,547 Mean Y (Local Curr.) 145,840 178,086 97,865 146,073 145,069 No schooling (%) 0.9 0.7 1.2 1.1 0.2 Prim. dropout (%) 13.0 14.3 11.2 14.1 9.4 Primary (%) 51.6 52.1 50.8 53.5 45.1 Sec. dropout (%) 12.2 14.4 8.9 12.5 11.1 Sec. general (%) 7.6 5.5 10.7 7.0 9.5 Sec. vocational (%) 5.4 5.0 6.2 3.8 10.8 Univ. dropout (%) 3.6 3.3 4.1 3.2 4.9 University (%) 5.7 4.9 6.9 4.7 8.9 Experience (Years) 24 24 22 24 24 Hours worked (Hours) 44 49 37 47 42 VAR (Ln Y) 0.743 0.545 0.774 0.885 0.205 Source: Encuesta Continua de Hogares, CEPAL. Notes: The earnings variable (Y) is in pesos per month. H is the weekly hours worked. All coefficients are statistically significant at the 5% level. -93 - ANm=N 4. EXTNDED EARNNGS FuNcToNs Venezuela 1989 Variable Sample Gender Sector Males Females Private Public No schooling -0.351 -0.357 -0.272 -0.696 0.053* Prim. dropout -0.100 -0.147* -0.183 -0.205 0.001* Sec. dropout 0.356 0.517 0.251 0.432 0.257 Sec. general 0.447 0.408 0.428 0.445 0.358 Sec. vocational 0.655 0.748 0.268 0.582 0.581 Teacher training 0.625 0.540 0.615 0.415 0.505 Univ. dropout 0.675 0.735 0.615 0.646 0.584 University 0.886 0.908 0.814 0.990 0.760 Experience 0.025 0.037 0.022 0.027 0.021 Exp-squared -0.0003 -0.0004 -0.0004 -0.0002 -0.0003 Log hours worked 0.687 0.409 0.675 0.744 0.578 Constant 5.445 6.340 5.569 5.132 6.013 R2 0.37 0.30 0.50 0.38 0.35 N 2,902 1,340 1,562 1,228 1,674 Men Y (Local Curr.) 6,968 7,962 6,067 6,700 7,036 No schooling (%) 2.8 3.2 2.4 4.1 1.9 Prim. dropout (%) 8.8 11.7 6.3 11.6 6.8 Primary (%) 25.6 41.1 12.3 43.5 12.5 Sec. dropout (%) 23.3 19.4 26.6 23.3 23.3 Sec. general(%) 8.3 6.0 10.4 5.3 10.6 Sec. vocational (%) 1.7 2.5 0.9 0.6 2.4 Teacher training (%) 8.6 2.0 14.2 0.7 14.3 Univ. dropout (%) 7.8 3.4 11.5 5.4 9.6 University (%) 13.1 10.6 15.3 5.5 18.7 Experience (Years) 22 25 21 23 22 Hours worked (Hours) 41 46 35 46 37 VAR (Ln Y) 0.305 0.315 0.281 0.468 0.167 Source: Encuesta de Hogares por Muestra, CEPAL. 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