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

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Presentation on theme: "The Effects of Life-long Learning on Earnings and Employment Richard Dorsett, Silvia Lui and Martin Weale."— Presentation transcript:

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 % 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 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 Qualification Level in Current Year Upgrading Life-long Learning

10 Average Transitions (Women) Qualification in Previous Year Qualification Level in Current Year Upgrading Life-long Learning

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 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 Ever Acquired Ever Acquired Ever Upgraded Ever Upgraded Ever Upgraded Orig Qual Orig Qual Orig Qual Orig Qual

18 Stayers: Men: Selected Coefficients UnrestrictedRestricted Coeffz-statCoeffz-stat Upgraded (t-1) Orig Qual Orig Qual Orig Qual Orig Qual High Qual Academic

19 Switching: Men: Selected Coefficients UnrestrictedRestricted Coeffz-statCoeffz-stat Ever Upgraded Ever Upgraded Ever Upgraded Orig Qual Orig Qual Orig Qual Orig Qual

20 Employment: Men: Selected Coefficients UnrestrictedRestricted Coeffz-statCoeffz-stat Upgraded(t) Upgraded(t-1) Upgraded(t-2) Ever Acquired Ever Acquired Ever Acquired Orig Qual Orig Qual Orig Qual Orig Qual

21 Movers: Women: Selected Coefficients UnrestrictedRestricted Coeffz-statCoeffz-stat Acquired(t-2) Acquired(t-3) Ever Acquired Ever Acquired Ever Acquired Ever Upgraded Ever Upgraded Ever Upgraded Orig Qual Orig Qual Orig Qual Orig Qual

22 Stayers: Women: Selected Coefficients UnrestrictedRestricted Coeffz-statCoeffz-stat Acquired(t-2) Orig Qual Orig Qual Orig Qual Orig Qual

23 Switching: Women: Selected Coefficients UnrestrictedRestricted Coeffz-statCoeffz-stat Orig Qual Orig Qual Orig Qual Orig Qual

24 Employment: Women: Selected Coefficients UnrestrictedRestricted Coeffz-statCoeffz-stat Upgraded(t) Ever Acquired Ever Acquired Ever Acquired Ever Upgraded Ever Upgraded Ever Upgraded Orig Qual Orig Qual Orig Qual Orig Qual

25 Employment Effects in the Model UnrestrictedRestricted Coeffz-statCoeffz-stat Movers Men: Newly Employed Women: Newly Employed Employment Employed Employed

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% %9.97%18.57%11.26% %9.45%16.17%10.54% %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% %8.12%23.32%6.71% %7.73%23.22%6.34% %9.43%23.14%7.65% %10.19%22.47%8.38% Upgrading051.62%20.21%58.99%18.71% %19.41%33.66%16.58% %19.38%34.24%16.76% %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.


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