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

• 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).

The Low Prevalence of Lifelong Learning

BHPS data Initial Qualifications

Upgrade Level 2 Level 3 Total

Pooled Panel Data

No 1,577 2,815 4,392

Yes 82 188 270

Total 1,659 3,003 4,662

Percentage upgraded 4.90% 6.20% 5.80%

Individual Time Series

No 232 382 614

Yes 11 31 42

Total 243 413 656

Percentage upgraded 4.50% 7.50% 6.40%

Probability upgrade over life-time 5.40% 18.60%

Earnings are Unpredictable

Qualification Level Median Mean St. Dev Number

2 £385 £419 £179 1577

2 with Upgrade £514 £519 £160 82

3 £445 £493 £229 2815

3 with Upgrade £479 £512 £238 188

Full Sample £425 £469 £216 4662

Are the uncertain benefits from upgrading a deterrent?

• 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.

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.

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.

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.

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.

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.

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%

0 81 75 64 46 11

500 80 73 61 43 8

1000 79 71 60 39 5

3000 73 64 51 28 0

9000 59 45 27 1 0

The observed probability is 5%

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%

0 71 62 52 37 7

500 69 60 50 34 5

1000 67 59 48 31 3

3000 62 54 42 23 0

9000 50 39 25 3 0

The observed probability of upgrading is 18%

The Simulated Participation Profile

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54

Age

Inci

den

ce o

f U

pgr

adin

g

Level 2 Level 3

60% chance of failure; fees of £1000 p.a.

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.