1. The Decision to take up Adult Education: a Dynamic Programming Analysis Justin van de Ven and Martin Weale National Institute of Economic and Social Research

2. Why don’t more people participate in life- long learning? Educational upgrading leads to higher pay and better employment prospects. We consider men upgrading from level 2 (qualifications above GSCE) to level 4 (higher education).

3. The Low Prevalence of Lifelong Learning BHPS dataInitial Qualifications UpgradeLevel 2Level 3Total Pooled Panel Data No1,5772,8154,392 Yes82188270 Total1,6593,0034,662 Percentage upgraded4.90%6.20%5.80% Individual Time Series No232382614 Yes113142 Total243413656 Percentage upgraded4.50%7.50%6.40% Probability upgrade over life-time5.40%18.60%

4. Earnings are Unpredictable Qualification LevelMedianMeanSt. DevNumber 2£385£419£1791577 2 with Upgrade£514£519£16082 3£445£493£2292815 3 with Upgrade£479£512£238188 Full Sample£425£469£2164662 Are the uncertain benefits from upgrading a deterrent?

5. The increase in earnings associated with upgrading is not statistically significant at a 5% level. But the uncertainty surrounding the effects of upgrading suggest that 90% confidence limits for its individual effects in multiplying up earnings are 0.52 to 1.92. A high chance of upgrading going wrong.

6. A Structural Analysis (i) Welfare comes from consumption and leisure Assume people maximise their expected life- time welfare but are risk-averse £1 is better than equal chances of getting 50p or £1.50. Life-long learning has costs in terms of fees and leisure time given up. It yields uncertainty benefits in terms of better pay and employment prospects. Is this uncertainty enough of a deterrent.

7. A Structural Analysis (ii) Choose parameters to define welfare function so as to match observed consumption and labour supply decisions over the life-course as closely as possible. Implies a reasonably strong degree of risk- aversion. Earnings rise sharply for people in their 20s and more slowly to about 45; then fall off But there is a strong random element.

8. A Structural Analysis (iii) Simulate a panel of 10000 people moving through the life course. At each age they can decide how much to spend and whether to work full-time, part-time or not at all. They can also decide whether to upgrade their qualifications or not. Upgrading is possible only once. Observe the number of people deciding to upgrade by age.

9. Costs of Education University fees introduced at £1000 in 1998/9; currently £9000 Many higher education sub-degree courses are much cheaper and take one or two years. Full-time education makes full-time work impossible but does allow part-time work. Part-time study is compatible with full-time work but leaves little spare time. Assumed two years of full-time study or three years of part-time study.

10. Drop-out Rates 15-17% of mature students drop out after the first year Resumption rates are under 20% 37% of part-time students under 30 dropped out and 34% of those aged 30+ No information on failure; we explore the role of a subjective risk of failure.

11. Simulated Life-time Probabilities of Upgrading from Level 2 to Level 4 Risk of Failure Cost of full-time course (£ p.a.)0%20%40%60%80% 08175644611 500807361438 1000797160395 3000736451280 900059452710 The observed probability is 5%

12. Simulated Life-time Probability of Upgrading from Level 3 to Level 4 Risk of Failure Cost of full-time course (£ p.a.)0%20%40%60%80% 0716252377 500696050345 1000675948313 3000625442230 900050392530 The observed probability of upgrading is 18%

13. The Simulated Participation Profile 60% chance of failure; fees of £1000 p.a.

14. Conclusions Risk is a factor affecting the take-up of life- long learning. But both uncertainty about earnings and fees go only a part of the way to explaining low participation. High subjective risks of failure are needed to account for observed participation rates.