1. The Effects of Life-long Learning on Earnings and Employment Richard Dorsett, Silvia Lui and Martin Weale

2. The Role of Life-long Learning Educational attainment is strongly dependent on socio-economic background. It is unlikely that capacity to benefit from education is as dependent on background as is attainment It follows that there is plenty of scope for making up for lost time

3. The Spread of Life-long Learning 1994. 31% of 451,000 UK students starting undergraduate courses aged twenty-five or over. 2007, 43% of 706,000 UK students A similar pattern elsewhere –Forty per cent of those starting university in Sweden were had left school at least five years earlier –Thirty-five per cent of male school leavers in the United States between 1979 and 1988 resumed their education by 1989. What are the benefits of qualifications gained through life-long learning

4. Doubts about the Benefits Jenkins et al. (2002). Wage growth after life-long learning was not significantly faster than for those who did not do it. Egerton and Parry (2001). Substantial penalties for late learners. Purcell et al (2007). Case studies suggest mature graduates have difficulty finding appropriate employment. Blanden et al. (2008). Little benefit for men; some for women aged thirty-five to forty-nine

5. A Mover-stayer Framework People have to take a wage from a stationary distribution (Movers) OR The wage rate is closely related to the wage in the previous period (Stayers) Expected earnings depend on –i) the nature of the stationary distribution –ii) the speed with which people move up the ladder –iii) the chance of falling off

6. Employment Prospects People have to be employed to have earnings. Previous unemployment may damage earnings potential at least in the short run. These effects need to be allowed for along with earnings dynamics.

7. Life-long Learning Consider qualifications acquired when age 25 or older. BHPS provides information on qualification level (NVQ) from 1991 or when subject joins survey. And each year on i)whether qualifications have been obtained and ii) whether educational status has been upgraded.

8. Separate effects of qualifications in each of last five years from ever acquiring qualifications.

9. Average Transitions (Men) Qualification in Previous Year 01234 Qualification00.98450000 Level10.00290.9837000 in Current20.00720.00830.983200 Year30.0040.00520.00890.99030 40.00140.00290.00790.00971 Upgrading 0.01550.01630.01680.00970 Life-long Learning 0.04410.07450.11890.09930.0969

10. Average Transitions (Women) Qualification in Previous Year 01234 Qualification00.98850000 Level10.00590.9824000 in Current20.00310.00940.985400 Year30.00220.00470.01090.98090 40.00030.0036 0.01911 Upgrading 0.01150.01760.01460.01910 Life-long Learning 0.02990.06780.10870.11080.1285

11. Non-employment Rates Life-long Learning QualNeverNot in last yearIn last year MenWomenMenWomenMenWomen 040.1%55.7%11.2%21.6%2.7%13.1% 118.3%32.4%8.5%18.3%7.7%18.0% 214.4%41.1%14.2%16.2%8.6%15.2% 39.6%28.2%11.1%19.5%11.3%17.5% 49.4%28.3%9.1%15.3%7.8%15.3%

12. Earnings Life-long Learning QualNeverNot in last yearIn last year MenWomenMenWomenMenWomen 0£8.17£6.47£9.49£6.78£9.56£6.55 1£9.82£7.94£10.48£8.09£10.33£7.87 2£10.14£7.72£10.17£7.76£9.72£7.63 3£12.27£9.72£11.78£8.90£11.66£8.17 4£15.79£13.17£15.15£13.04£13.52£11.94

13. Sample structure Consider only people aged 25-60. Leave out self-employed (who may have negative earnings) and drop from sample if people become self-employed.

14. Equation Structure

15. Estimation Strategy Consider covariance structure of residuals Note that for identification

16. Estimation Strategy Apply a Cholesky decomposition to the co-variance matrix with the life- long learning equation at the top of the diagonal. Estimate the life-long learning equation as an ordered probit Compute the generalised residuals from this and introduce these as extra variables into the other four equations estimated as a system.

17. Movers: Men: Selected Coefficients UnrestrictedRestricted Coeffz-statCoeffz-stat Ever Acquired 25-340.0070.11 Ever Acquired 35-49-0.001-0.02 Ever Acquired 50-600.0340.38 Ever Upgraded 25-340.0870.880.092.21 Ever Upgraded 35-490.1211.360.092.21 Ever Upgraded 50-600.1250.960.092.21 Orig Qual 10.1242.720.122.65 Orig Qual 20.2344.670.234.64 Orig Qual 30.2584.270.2564.23 Orig Qual 40.4636.590.4696.88

18. Stayers: Men: Selected Coefficients UnrestrictedRestricted Coeffz-statCoeffz-stat Upgraded (t-1)0.0592.260.0642.85 Orig Qual 10.0030.490.0010.29 Orig Qual 2-0.005-0.88-0.006-1.03 Orig Qual 30.0071.450.0061.24 Orig Qual 40.0152.880.0142.75 High Qual Academic0.0051.540.0051.57

19. Switching: Men: Selected Coefficients UnrestrictedRestricted Coeffz-statCoeffz-stat Ever Upgraded 25-34-0.623-2.19-0.348-1.78 Ever Upgraded 35-490.2681.05 Ever Upgraded 50-60-0.491-1.9 Orig Qual 10.1941.560.1881.54 Orig Qual 20.4143.160.4233.27 Orig Qual 30.5924.80.5984.86 Orig Qual 40.9836.830.9857.26

20. Employment: Men: Selected Coefficients UnrestrictedRestricted Coeffz-statCoeffz-stat Upgraded(t)-0.565-2-0.542-2.91 Upgraded(t-1)-0.585-2.37-0.427-2.8 Upgraded(t-2)-0.327-1.41-0.275-1.84 Ever Acquired 25-340.1120.67 Ever Acquired 35-490.261.880.2782.64 Ever Acquired 50-600.4472.40.4043.1 Orig Qual 10.1110.920.1060.88 Orig Qual 20.2931.940.2851.91 Orig Qual 30.3793.10.3733.09 Orig Qual 40.3272.550.3122.45

21. Movers: Women: Selected Coefficients UnrestrictedRestricted Coeffz-statCoeffz-stat Acquired(t-2)-0.176-3.2-0.171-3.77 Acquired(t-3)-0.129-2.47-0.122-2.99 Ever Acquired 25-340.0491.040.0792.72 Ever Acquired 35-490.0942.210.0792.72 Ever Acquired 50-600.1271.860.0792.72 Ever Upgraded 25-340.2683.090.1132.99 Ever Upgraded 35-490.121.870.1132.99 Ever Upgraded 50-600.0760.810.1132.99 Orig Qual 10.0310.780.0340.87 Orig Qual 20.0931.940.0941.98 Orig Qual 30.1853.420.1863.45 Orig Qual 40.45710.010.45610.11

22. Stayers: Women: Selected Coefficients UnrestrictedRestricted Coeffz-statCoeffz-stat Acquired(t-2)0.0131.40.0071.65 Orig Qual 10.0010.180-0.03 Orig Qual 20-0.04-0.001-0.2 Orig Qual 30.0081.080.0071.03 Orig Qual 40.011.740.0091.65

23. Switching: Women: Selected Coefficients UnrestrictedRestricted Coeffz-statCoeffz-stat Orig Qual 10.0460.440.0440.42 Orig Qual 20.0090.06-0.003-0.02 Orig Qual 30.4082.790.4062.82 Orig Qual 40.5154.360.4954.44

24. Employment: Women: Selected Coefficients UnrestrictedRestricted Coeffz-statCoeffz-stat Upgraded(t)-0.577-3.16-0.404-3.05 Ever Acquired 25-340.2281.860.2743.05 Ever Acquired 35-490.4324.070.4615.8 Ever Acquired 50-600.5294.280.5215.38 Ever Upgraded 25-340.2581.1 Ever Upgraded 35-490.1420.84 Ever Upgraded 50-60-0.005-0.02 Orig Qual 10.2723 3.01 Orig Qual 20.1551.210.1541.21 Orig Qual 30.1321.180.1331.19 Orig Qual 40.1741.810.1711.84

25. Employment Effects in the Model UnrestrictedRestricted Coeffz-statCoeffz-stat Movers Men: Newly Employed-0.306-2.14-0.307-2.36 Women: Newly Employed-0.214-3.78-0.206-3.69 Employment Employed 19911.83620.591.82320.68 Employed 19911.34122.791.33722.75

26. Wage Rate Profiles: Men

27. Wage Rate Profiles: Women

28. Average Returns to Life-long Learning: Men Man Aged 25Man Aged 40 Prior Education Level Full Effect Wages only Full Effect Wages only No upgrading08.74%1.73%17.47%2.87% 15.73%1.88%11.98%3.60% 24.37%1.59%9.31%3.06% 34.65%2.16%9.73%4.21% 46.62%4.34%11.99%7.06% Upgrading016.68%11.06%23.52%11.35% 112.92%9.97%18.57%11.26% 211.62%9.45%16.17%10.54% 310.12%8.25%15.90%11.02%

29. Average Returns to Life-Long Learning: Women Woman aged 25Woman aged 40 Education Levels Full Effect Wages only Full Effect Wages only No upgrading037.46%7.81%45.67%6.87% 120.36%8.12%23.32%6.71% 220.11%7.73%23.22%6.34% 320.67%9.43%23.14%7.65% 420.29%10.19%22.47%8.38% Upgrading051.62%20.21%58.99%18.71% 132.03%19.41%33.66%16.58% 232.29%19.38%34.24%16.76% 331.26%19.78%31.76%16.08%

30. Conclusions We find significant average impacts of life-long learning on the wage rates of both men and women, with the effects larger for women. However people with life-long qualifications are more likely to be employed than those without. This effect sharply increases the returns to life-long education.