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

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

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

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  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.

  18. 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’)

  19. Registered AE course credits among enrollees 1986-87

  20. Registered AE course credits among enrollees 1994-95

  21. Completed AE course credits among enrollees 1994-95

  22. 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.

  23. 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

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

  25. 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.

  26. 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.

  27. 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.

  28. 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).

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

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

  31. 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.

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

  33. 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.

  34. 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

  35. 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?).

  36. 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.

  37. 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.

  38. Concluding remarks

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