Ismayilov Ilgar Konorev Alexey

1. Can adult education delay retirement from the labor market? (2010)Xavier de LunaAnders StenbergOlleWesterlund Ismayilov Ilgar Konorev Alexey

2. Intro • Motivation: increasing shares of population are entering retirement rather than engaging in productive work. • Concept of “active aging” by OECD (1998): retraining of old workers. • Purpose of paper: to study whether AE at compulsory or upper secondary level that takes place at the age of 42 or above affects the timing of the transition.

3. Human Capital Theory (Becker, 1962) • Decision about investment: • where T1-T0 is period of training, T2 is an age of retirement, W(0) is a scholarship, Kt is direct costs per period. • Decision about retirement: shape of utility function, subjective time preferences, link between income and pension

4. Program Description • Since 1969 municipalities offer adult education free of charge, scholarship 780 euro • Data: Swedish register data of AE transcripts, 1979-2004 Labor earnings, 1982-2004 • Treatment group: first-time AE enrollees (at least 125 credits) between 1986 and 1989 • Control group: those who were not registered or those who took less than 125 credits • Sample of study: who were born from 1931 to 1944, i.e. aged 42 to 55 in 1986 and 60 to 73 years old in 2004.

5. Program Description (cont.) • Outcome of interest: timing of the transition from productive work to dependence on pension transfers where pit is annual pension, eit is annual labor earnings. • rit ≤ 1 individuals are active in the labor market; • rit > 1 pensioners.

6. Sample means of treated (AE enrollees) and untreated in 1985

8. Figures 1-2: • Duration in labor force for treated and unmatched groups using KMSF (where rit<1) • S(t)=Pr(T>t) • Not reflect causal effect • The average age is slightly lower in treated groups Figure 1 males Figure 2 females

9. How age influence being in active labor force: Table 3

10. Empirical method • Nearest-neighbour matching on the propensity score and by selecting 4 untreated individuals with propensity scores closest to those each participants given in AE • PS are estimated probabilities of being among treated using probit models • Causal effect of interest is the difference in KMSF estimates of AE and comparison groups

11. Empirical method • Assumptions: • Choice of enrolling or not does not affect outcomes of others • conditional on covariates, probability of treatment is 0< pr<1 • COC, mechanism of enrollment is independent of the potential outcomes • COC, different censoring mechanisms are independent of outcomes

12. Empirical method To identify causal effect it is crucial that (C) is not violated by unobservable factors Ability or/and motivation- earnings during period 1982-85 Leisure activity-threshold (125) Geographical variations - residents in Stockholm

13. Results Table 3 males matched group Table 4 females matched group

14. To check stability • Alternative subsamples(no upper secondary schooling, year of birth 1935-1939, some upper secondary schooling) • Alternative definition of treatment group(250 cts) • Alternative definition of outcome rit=0.8; 1.2

15. Evaluation Do we believe the results? - Yes. • Relevant data • Good matching • Assumptions are likely to hold • Robustness of the results was checked in different ways But we believe that these results are appropriate for Sweden economy only. One may find significant evidence in other countries.

16. Thank you for your attention! Any questions?