1. Education and Wages Pedro Telhado Pereira May 2004 Part 3

2. Universidade da Madeira2 We have arrived in part 1 to the following formula – at the time the individual finish his studies

3. Universidade da Madeira3 But the wage profile is

4. Universidade da Madeira4 Mincer (1974) suggested Individuals at time t will devote a certain percentage of his time to acquire human capital – h t

5. Universidade da Madeira5 And therefore

6. Universidade da Madeira6 The equation we estimate is Where: x – is the work experience after school – generally age- years of education – age of start of education X – other variables r - rate of return of Education To be correct the wage should be a % as individuals are devoting part of their time to acquire human capital.

7. Universidade da Madeira7 Problems with the estimation of the equation Problem 1 - Endogeneity of Education Assume that an individual chooses education and maximises a utility function of the type: subject to the individual’s opportunity set summarised by w=g(E),

8. Universidade da Madeira8 The first order condition for optimal education requires that: For the sake of simplicity, it is assumed that the marginal costs are increasing functions of the amount invested in education, and that the marginal returns do not vary with education (the latter assumption is only a matter of simplicity and can be discarded without changing the main implication)

9. Universidade da Madeira9 Since the individual invests in education until the point where marginal costs equal marginal benefits, his optimal amount of education is given by:

10. Universidade da Madeira10 Integration of the marginal benefits leads to a log-linear wage equation for individual i of the type:

11. Universidade da Madeira11 The model identifies two sources of heterogeneity in the population: variation in marginal rates of return to education at each level of schooling (loosely known as differences in ability) and variation in the marginal costs of investment in schooling (loosely known as differences in access to funds or tastes for education).

12. Universidade da Madeira12 The general econometric problem

13. Universidade da Madeira13 We have to use instrumental variables Z – instrumental variables Z must be correlated with X and is a full rank matrix and

14. Universidade da Madeira14 Instruments used (Harmon, Walker and Westergaard-Nielsen (2001)): Variation of Compulsory school law Month of birth Years of war – Vietnam, II WW Distance to college Family variables Abolition of fees Age (Barceinas, Oliver, Raymond and Roig(2001))

15. Universidade da Madeira15 In Barceinas, Oliver, Raymond and Roig(2001) paper “… in the Spanish case the ability bias seems to be not very important and that differences between the OLS and IV estimates do not follow a clearly identifiable pattern…”

16. Universidade da Madeira16 The common finding of the literature The IV estimates are higher than the OLS estimates – Card 1999. Possible explanation: IV estimators do not represent sample average returns to education but the marginal returns to education of certain subgroups of the population.

17. Universidade da Madeira17 The use of fixed effects to handle ability The problem is that we can not observe a individual with and without education simultaneously as most individuals don’t get more education after they start working. Use of data on twins (or family members) – the IV estimates are higher than the OLS estimates.

18. Universidade da Madeira18 Problem 2 - The return by level of education in Portugal

19. Universidade da Madeira19

20. Universidade da Madeira20

21. Universidade da Madeira21 There is not a constant return to education - it depends on the level of education Similar results were obtained using Spanish data (Barceinas-Paredes, F., J. Oliver-Afonso, J. L. Raymond-Bara, J. L. Roig-Sabaté (2001))

22. Universidade da Madeira22 Problem 3 - The OLS assumes a paralel shifting of the distribution W 0 W ed

23. Universidade da Madeira23 If there is not a paralel shift “there may be information gains from estimating and comparing several conditional location measures for the dependent variable, even after controlling for a large set of observed individual and job characteristics” (Hartog, Pereira and Vieira,1999).

24. Universidade da Madeira24 Rates of return to education (%)

25. Universidade da Madeira25 This result appears for other european countries and the USA.

26. Universidade da Madeira26 Results for European Countries - Martins and Pereira (2004)

27. Universidade da Madeira27 Table 1 - Data-sets description CountryData-setYear N. Obs. AustriaMikrozensus19937175 DenmarkLongitudinal Labour Market Register19954416 FinlandLabour Force Survey19931175 France Training and Professional Qualifications + Employment Survey19934606 GermanySocio-Economic Panel1995? GreeceHousehold Budget Survey19942096 IrelandESRI Household Survey19941903 ItalySurvey of Household Income and Wealth19953441 Netherland sStructure of Earnings Survey199649805 NorwayLevel of Living Survey1995870 PortugalPersonnel Records199528055 SpainWage Structure Survey1995118005 SwedenLevel of Living Surveys19911508 SwitzerlandLabour Force Survey19956334 UKFamily Expenditures Survey19952183 USACurrent Population Survey199542347

28. Universidade da Madeira28 Table 4 - Summary of results CountryOLS1st dec.9th dec.Diff. Austria9.7%7.2%12.8%5.6% Denmark6.6%6.3%7.1%0.8% Finland8.9%6.8%10.1%3.3% France7.6%5.9%9.3%3.4% Germany8.0%8.5%7.5%-1.0% Greece6.5%7.5%5.6%-1.9% Italy6.4%6.7%7.1%0.4% Ireland8.9%7.8%10.4%2.6% Netherlands7.0%5.3%8.3%3.0% Norway6.0%5.5%7.5%2.1% Portugal12.6%6.7%15.6%8.9% Spain8.6%6.7%9.1%2.4% Sweden4.1%2.4%6.2%3.8% Switzerland9.5%8.7%10.6%1.9% UK8.6%4.9%9.7%4.8% USA6.3%3.9%7.9%4.0% Means7,9%6,5%9,1%2,7% St. Dev.2,0%1,6%2,6%2,7% Coeff. Var.0,250,240,291,00

29. Universidade da Madeira29 In a graph

30. Universidade da Madeira30 The highest rate is in Portugal – 12.6% The lowest one is Sweden – 4.1% The value for Spain is 8.6%

31. Universidade da Madeira31 In the majority of countries we observe The return is higher in the top decile than it is at the lower decile.

32. Universidade da Madeira32 Can we say that Portugal has a high rate of return to Education? We should take, at least, two points in consideration Support from the State to the Families Risk of the investment

33. Universidade da Madeira33 In Asplund and Pereira (1999) we showed that there is a negative relationship between State Support and Returns to Education

34. Universidade da Madeira34

35. Universidade da Madeira35 In Pereira and Martins (2002), we showed that there is a negative relationship between return and risk as in all assets.

36. Universidade da Madeira36

37. Universidade da Madeira37 We used the difference between the coefficient of education at the last decile and the first decile[1] as the measure of the risk [1] The significance of the difference was tested for several countries and it showed to be significantly different from zero, provided the sample was large enough.[1]

38. Universidade da Madeira38 we construct dummy variables for years (yeari=1 if year=i, zero otherwise), type of wage (net=1, if net wages were used, zero otherwise). dif stands for the difference in returns between the last and first decile, absdif for its absolute value and ols for the OLS Mincer equation coefficient corrected.

39. Universidade da Madeira39 Table 2 Regression with robust standard errors Number of obs = 16 F( 5, 9) = 1957.53 Prob > F = 0.0000 R-squared = 0.9831 Root MSE = 1.3989 | Robust ols | Coef. Std. Err. t P>|t| [95% Conf. Interval] ---------+-------------------------------------------------------------------- net | -.0594735.4831846 -0.123 0.905 -1.152513 1.033566 dif |.5565127.169201 3.289 0.009.1737533.939272 year91 | 1.985252.642964 3.088 0.013.5307662 3.439737 year93 | 6.471456.9839524 6.577 0.000 4.245601 8.697311 year94 | 7.534957.2900354 25.979 0.000 6.878851 8.191063 year95 | 6.490306.7973708 8.140 0.000 4.686527 8.294084 year96 | 5.330462.5076031 10.501 0.000 4.182184 6.47874

40. Universidade da Madeira40 Table 3 Regression with robust standard errors Number of obs = 16 F( 5, 9) = 51.57 Prob > F = 0.0000 R-squared = 0.9818 Root MSE = 1.4512 | Robust ols | Coef. Std. Err. t P>|t| [95% Conf. Interval] ---------+-------------------------------------------------------------------- net | -.5700131.5674445 -1.005 0.341 -1.853662.7136356 absdif |.56264.1762516 3.192 0.011.1639312.9613489 year91 | 1.961968.6697562 2.929 0.017.446874 3.477062 year93 | 6.616513.9744813 6.790 0.000 4.412083 8.820943 year94 | 6.719066.86393 7.777 0.000 4.764721 8.673412 year95 | 6.529603.7854792 8.313 0.000 4.752726 8.306481 year96 | 5.31208.5287549 10.046 0.000 4.115953 6.508207

41. Universidade da Madeira41 The main finding is the positive relationship between return and risk. There seems to be a positive compensation to “be received” to face the risk of the investment in education.

42. Universidade da Madeira42 And what about signalling? Workers acquire costly education in order to signal their higher ability to employers – who would otherwise know little about their prospective workers skills. Education per se plays no role in enhancing a worker’s productivity and is almost entirely wasteful from the public or social point of view. One way to test this idea involves comparing the returns to education between employees and the self-employed. The intuition behind this results is whereas the former may benefit from education as a signal, the others will not, given that they are their own employers and have no informational asymmetries problems to deal with. The results for Portugal suggest that returns to education for the self-employed are at least as high as those for employees, therefore there is no sign of signalling.

43. Universidade da Madeira43

44. Universidade da Madeira44 Barceinas-Paredes, F., J. Oliver-Afonso, J. L. Raymond-Bara, J. L. Roig-Sabaté and A. Skalli (2001) Use Spanish and French Data Use –Private and Public Sector Public sector is more prone to signalling –No evidence for the screening hypothesis –Number of years of education and relative position in attainment Years=Human Capital, relative position=screening –Education is likely to serve as a signalling device but only to a rather limited extent.

45. Universidade da Madeira45 –Experience eearnings profile of higly educated individuals More tenure = less signalling –None of the predictions of the screening hypothesis could be strongly confirmed –Sheepskin effects More years to attain a degree less signal –Even if the results show that there are many (human capital) reasons to obtain the same result

46. Universidade da Madeira46 Their conclusions: “…our results suggest unanimously that the effect of education is primarily due to its impact in individual’ productivity…” “… our findings confirm the idea that although there might be some elements of truth in the screening hypothesis, the returns to education are to the greatest extent due to human capital accumulation…”

47. Universidade da Madeira47 References Asplund, R. and P. T. Pereira. (1999), ‘Introduction’, in (eds), Returns to human capital in Europe: a literature review, Helsinki, Finland: ETLA/Taloustieto Oy., pp 259-278. Barceinas-Paredes, F., J. Oliver-Afonso, J. L. Raymond-Bara, J. L. Roig-Sabaté and A. Skalli (2001), Does Education Improve Productivity or Earnings Only, in: R. Asplund,eds, Education and Earnings – Further Evidence from Europe, ETLA, Helsinki. Barceinas-Paredes, F., J. Oliver-Afonso, J. L. Raymond-Bara, J. L. Roig-Sabaté (2001), Spain, in: C. Harmon, I. Walker and N. W. Nielsen, eds, Education and Earnings in Europe – a Cross Country Analysis of Returns to Education, Edward Elgar, Cheltenham, UK. Bosworth, D., P. Dawkins and T. Stromback (1996), The Economics of the Labour Market, Longman, Singapore. Card, D. (1999), The Causal Impact of Education on Earnings, in: O. Ashenfelter and D. Card, eds, Handbook of Labor Economics, North Holland, Amsterdam and New York. Harmon C., I. Walker and N. W. Nielsen, (2001), Introduction, in: C. Harmon, I. Walker and N. W. Nielsen, eds, Education and Earnings in Europe – a Cross Country Analysis of Returns to Education, Edward Elgar, Cheltenham, UK. Hartog, J., P.T. Pereira, J. C. Vieira (1999) "Changing Returns to Education in Portugal During the 1980s and Early 1990s: OLS and Quantile Regression Analysis", Applied Economics, 33/8, 2001, 1021- 1037. Martins, P.S. and P.T. Pereira (2004) "Does Education Reduce Wage Inequality? Quantile Regressions Evidence from Fifteen European Countries and the USA" (forthcoming Labour Economics. Mincer, J. (1974). Schooling, Experience and Earnings. New York: National Bureau of Economic Research. Pereira, P. T. and P. S. Martins (2001), Portugal, in: C. Harmon, I. Walker and N. W. Nielsen, eds, Education and Earnings in Europe – a Cross Country Analysis of Returns to Education, Edward Elgar, Cheltenham, UK. Pereira, P. T. and P. S. Martins (2002), "Is there a Return-Risk Link in Education", Economic Letters, 75, 31-37, (2002).