Estimating the long-term impact of Adult Education using Data on Siblings

1. Estimating the long-term impact of Adult Education using Data on Siblings

2. Plan of this seminar • Background • Purpose of this study • Related studies • AE in the Swedish educational system • Descriptive data. • Estimations and results. • Summary and conclusion.

3. Background • The demand for flexibility in competence raises with globally competing markets and faster technological development. • Incentives to improve the human capital of the workforce. • Adult education mainly seems to concern vocational, or specific, training. • Remarkably few studies of comprehensive, or general, education (e.g. 1st and 2nd language, mathematics) acquired in adulthood.

4. Purpose of this study Is adult education in Sweden associated with long-term beneficial earnings effects? - In Sweden, AE is an integral part of the educational system. - Data on course credits available from 1979. - Earnings data available 1982 - 2004.

5. Why is this interesting? • AE is used very differently across countries, potential efficiency gains appear likely. • Human capital theory would predict a positive return to another year of schooling. • In the long-run; general education should compare more favourably with specific education as it is less sensitive to structural changes. Sidetracks: • Evens out educational differences between demographic groups. • Improves democracy and social justice.

6. Related studies • AE in Sweden and its effects on earnings? • Ekström (2003) No. • Albrecht, van den Bergh and Vroman (2004) Maybe. • Stenberg and Westerlund (2007) Yes (LTU). LTU Males +14% LTU Females +23% Drawback – AE is measured as 0/1. • Stenberg (2007) uses completed course credits. m/f born 1970 + 5% (Ekström o Albrecht et al. reconciled)

7. Related studies cont. • Returns to schooling literature in Sweden (for youths) - app 3.5 – 4.5 % Isacsson 1999, Kjellström 1999, Meghir and Palme, 2005 • Returns to a year of adult schooling Evaluations of community college (US & Canada) • Jacobson, Sullivan, Lalonde (2005) – laid off workers • Males: 9 % Females: 13 % • Marcotte (2006) – nationally representative sample App. 5 % • Zhang and Palameta (2006) [Canada] • Aged 17-34: males 9 %, females 15 % (p-value .07) • Aged 35-59: no effects.

8. Contribution • Longer time horizon than any earlier study. • The study with the strongest identification strategy yet (family fixed effects). • First Swedish study to evaluate the earnings effects of course credits for individuals above 30.

9. Educational system in Sweden • 9 year compulsory school • Upper secondary school; 2 or 3 years - 2 year programs mainly vocational - 3 year programs mainly theoretical (since 1996 all programs are 3 years) • Higher studies ---- • AE at municipal education centers komvux; • upper secondary level (85%) • compulsory level (10%) • supplementary courses (5%, vocational, post-secondary)

10. Number of participants in upper secondary komvux 1970 - 2001

11. Data and descriptives • First time AE enrollees in 1986-87 or in 1994-95 • One group enrolled in boom period and one in recession • Sample, individuals aged 24-43 in 1986 or 1994, low skilled (with two year upp sec school or less). • 26500 ind (1986-87) and 31000 ind (1994-95).

12. Evaluation design • a) First time AE enrolees 1986-87, possibly later also in higher education. b) No AE before 1988; possibly later enrolled in AE and/or higher education. 2. a) First time AE enrolees 1994-95, possibly later also in higher education. b) No AE before 1996; possibly later enrolled in AE and/or higher education.

13. Male and female annual earnings; AE enrolees 1986-87 and control groups

14. Percentage earnings change; AE 1986-87

15. Male and female annual earnings; AE enrolees 1994-95 and control groups.

16. Percentage earnings change; AE 1994-95

17. Sample means of participants in AE and control groups.

19. Contents of AE; course credits • Each course is attached to a number of credits. • Credits are accumulated for each individual; 500 credits “equal” a schooling year. • Course credits are not counted if a course is reported as “interrupted”. However, we do not know if these courses really were completed (e.g. with a grade ‘pass’)

20. Registered AE course credits among enrollees 1986-87

21. Registered AE course credits among enrollees 1994-95

22. Completed AE course credits among enrollees 1994-95

23. AE 1986-87 25% registered in less than 100 course credits. AE 1994-95 18% registered in less than 100 course credits. 11% completed zero credits. 30% completed less than 100 credits.

24. Shares with further education by 2004 Sample 1986-87 - Among AE; 8.5 % completed at least one year of HE. - Of control group; 21.4 % later enrolled in AE and 3.0 % completed at least one year of HE. Sample 1994-95 - Among AE; 21.3 % completed at least one year of HE. - Of control group; 22.6 % later enrolled in AE and 3.6 % completed at least one year of HE. - suggests long-term is helpful for an evaluation

25. Sample means of AE course credits and higher education.

26. AE may influence earnings… • Directly – AE courses has a beneficial impact on productivity and earnings. • Indirectly – AE leads to further education at university which in turn leads to an earnings increase.

27. Methodological remarks • Average treatment effect of the treated (ATT) - propensity score matching (PSM) vs OLS. • Difference-in-differences (DiD). • Counterfactual state. • Regression specification – direct and indirect effects.

28. PSM vs OLS • Propensity score matching (PSM) attaches weights to control group members which are proportional to their (statistical) resemblance to an AE participant. • In the presence of heterogeneous effects, PSM allows for an estimate of ATT (unlike OLS). • Disadvantage: standard PSM estimates are designed for binary variables.

29. Assume a conventional OLS regression: Yit = α + βXit-1 + γDit-1 • In the estimate of γ, the implicit weights are proportional to how often a value of Xit-1 occurs and to the variation in Dit-1 for this value. 2. The coefficient estimate of γ reflects ATT only if the impact of AE is homogenous across individuals. 3. If “family-ID” is included in Xit-1. ATT is identified if effects of AE are homogenous across siblings (cfr PSM). 4. Returns to a year of AE is reflected by OLS coefficient in front of variable (years of AE).

30. DiD is ambiguous in the literature • To clarify; let earnings be denoted Yit Yit = α + βYit-1 + γDit-1

31. Yit = α + βYit-1 + γDit-1; γreflects C – B’

32. The specification can be improved: Let ΔYit = Yit – Yit-1 and ΔYit-1 = Yit-1 – Yit-2 : ΔYit = α + β ΔYit-1 + γDit-1 1) ΔYit is not truncated at zero. 2) The coefficient γ better reflects a treatment effect.

33. ΔYit = α + β ΔYit-1 + γDit-1; γreflects D – C’

34. The counterfactual outcome of individuals enrolled in AE • The outcome of the control group is a weighted average of non-enrollees and later enrollees in AE. • Given the expansion of AE in Sweden in the 1990s, any positive effect of AE is expected to be diluted by AE among control group members. - To a policy maker outside Sweden, the relevance of such an estimate is doubtful.

35. Four versions of the regression model • ΔYit = βXit-1 + γDit-1 + εi • ΔYit = βXit-1+ γDit-1•totit-1 + εi where totit-1 = cit-1 + HEdit-1 (the sum of AE (in years) and subsequent higher education). • ΔYit = βXit-1 + Dit-1γ•totit-1 + (1-Dit-1)θ•totit-1 + εi • ΔYit = βXit-1 + Dit-1•[γ1cit-1 + γ2HEdit-1] + (1-Dit-1)•[θ1cit-1 +θ2HEdit-1]+εi

37. Descriptive estimates look positive and according to theory. • OLS generates negative direct effects. • Direct effects increase somewhat when siblings data are introduced (attenuating negative selection?) and indirect effects become more moderate (attenuating positive selection?).

39. AE 1986-87 are associated with weaker effects on earnings; in line with that the boom period attracts a weaker selection (and heterogeneous effects). • The indirect effects are diluted, possibly as higher education went through a large expansion during the 1990’s.

42. Summary of the results • Effects of AE for total sample are significantly positive throughout, but strongly heterogeneous and on average relatively small. • Indirect effects of AE (higher education) are never below 8.0 per cent. • The direct effects of registered AE credits are significantly negative for males (- 3.0% and - 2.2%). Female estimates 2004-1984 are insignificant and positive (3.5%) 2004-1992. • The direct effects of completed AE credits (only 2004-1992) are insignificant for males and significantly positive (7.5%) for females.

43. Concluding remarks