Over-education

1. Over-education Amanda Gosling and Yu Zhu GES Summer School, Kent, 30th June 2010

2. Structure • Introduction and Motivation • Background (literature, some trends and data • A bit of theory • Estimating the extent of over-education and discussion of some evidence • Tea Break • Discussion

3. Why look at over-education? • Over-education is a very active research field: • Google Scholar keyword search returns 2000+ papers in Business, Administration, Finance, and Economics; and another 12000+ papers in Social Sciences, Arts and Humanities • Policy • Controversy over 50% target of cohort in further or higher education • Debate over the level and mechanisms for funding and subsidy • Current (25% help!) funding cuts • Skills and Concepts • Controversy over over-education is a good way to understand what labour economics are concerned about, the models and concepts used and the key areas of disagreement • Right way to model the labour market • How to estimate the return to education? • How to think about policy interventions

4. Workshop should not be considered a summary of everything there is to know about over-education but an illustration of current thinking about labour markets through this particular question

5. Definitions • Micro • Over-education refers to the situation when a job-holder has an achieved qualification above that which would currently be required for someone to get the job (rather than to do the job). • As such, it represents graduate labour market disequilibrium: workers possess excess educational qualifications relative to those their jobs require. • Macro • Labour market has “too many” graduates • Credentialism • Again represent disequilibrium • Examples • Slacker • Philosophy PhD • SAHM • Mother with small children unable to find suitable jobs with flexible/part time hours • Russian Labour market • Early labour market experiences • Long run graduates “trapped” in low status jobs

6. Background • Emphasis on education expansion • Third way (emphasis on equality of ops. rather than of outcomes) • Becoming more controversial • Academic • Freeman (the over-educated American) • Research on demand and supply of skills • Research on large (and growing) returns to education • Micro led research on over-education (and its criticisms) • Factual • Changes in “return” to education • Participation in education • Long series on education by occupation and gender

7. Academic background (1) Cobweb-model Graduate wage supply Wage associated with zero rents demand Graduate employment

8. Card and Lemieux (QJE 2001) • Look at changes over time in relative wage of graduates • Hypothesis that part of the changes can be explain by changes in relative supply • Idea that demand and supply are always racing to keep up with each other • Strong support using US micro data • BUT • Identification problems • Identification relies on non-substitutability of workers of different ages • Estimate is “raw”

9. What do we know about the return to education? • Early work (e.g. Dennison 1962, 1967) on growth accounting • But is education a consumption or investment good? • Mincer, Becker Human Capital Wage regressions • Rate of return (like on any other asset) • High but fluctuating • Sheepskin effects • Later (Ashenfelter, Angrist, Kruegar, Walker) on solving the “ability bias” problem • Use of instrumental variables to relate differences in wages to differences in education that are not a result of differences in ability (e.g. Twin studies, Vietnam draft, Compulsory School Leaving laws) • Measured returns appear to RISE • Measurement error • Heterogeneity in Returns (marginal entrant different from the average, suggestion of credit constraints)

10. What do we know about the return to education? • Changes in the return to education over time (Card, Gosling et al. Schmitt). • Sharp rise over 80s and early 90s • Evidence (Green and Zhu) that return to education for younger cohorts has flattened or even fallen • Growing focus on the distribution of returns using techniques like quantile regressions • Starts off with Buschinsky (1996) • Key difficulty is that the distribution of returns is NOT the same as the distribution of differences • Treatment effect literature • Consensus that all changes to the structure of wages cannot be explained by differences in the demand and supply of education and skills

11. Over–education literature • Consequences (wages, job satisfaction • Causes (race, gender, discrimination, ability) • Measurement • Changes over time • Long versus short run • Implications for human capital model • Is this a meaningful avenue for research?

12. Now some data on background trends Own calculations using FES and BHPS data

13. Supply of Education (Men)

14. Supply of Education (Women)

15. Men

16. Women

17. men

18. women

20. Quantile estimates of Ed diff (Men)

21. Quantile estimates of Ed diff (Women)

22. Summary • Dramatic increase in relative supply of educated workers over last 30 years • Some weak evidence that the return has declined • For younger cohorts • Distribution of returns • Picture becomes less clear cut when we look at employment • More graduates doing non-graduate jobs but • Less of these jobs • Numbers are small • Not clear that over-education is a growing problem • Might think it should be more of an issue for women but this is not apparent in the data

23. Now for some economics!

24. Some key economic concepts to understand and think about • Production functions • Education as screening/signalling device • Labour market models • Incentives to acquire education. If education is a choice, how can a worker have too much? • Investment under uncertainty

25. Production functions • Can we write a production function with labour quality in which the concept of over-education “makes sense”? • Need the marginal product of extra education to be zero • Firm production with labour of different types • Technology of human capital production • Part of explanation of why this topic is so controversial

26. Education as screening/signalling device • Dog-bone economy (Sattinger) • Variations in costs of education are correlated with variation in unobserved ability. • Sheepskin effects • Plausibility of models depend on other available strategies to separate workers

27. Labour market • Assume there ARE some firms for which MP of education is zero • Will we then get over-education? • Argue that only in presence of labour market imperfections

28. W Supply of graduates Supply of non graduates L Q

29. W Supply of graduates Supply of non graduates L Q Non graduate firm ONLY employs non graduates

30. So in classic model of labour market will get specialisation rather than over-education • If we do see “over-education” then it must be to do with technology of human capital rather than production • If graduate were in non graduate jobs they would have to get a graduate wage • So specialisation and no wage diffs

31. What about market with frictions? • Much applied theory of the labour market (Burdett, Shimer, Mortensen, Coles, Manning) works on the idea that workers are not able to see or to move to all potential jobs • Search or mobility costs • Non wage differences in jobs (Bhaskar and To) • See idea with simple discriminating monopsony model (but note this analysis is partial)

32. Supply non graduates W Supply graduates Constant marginal product for simplicity N

33. W Marginal cost of hiring non graduate Marginal cost of hiring graduate Supply graduates Supply non graduates demand N

34. W Marginal cost of hiring non graduate Marginal cost of hiring graduate Supply graduates Supply non graduates demand Small wage premium here and large diff in employment N

35. W Marginal cost of hiring non graduate Marginal cost of hiring graduate Supply graduates Supply non graduates demand Note that could have drawn graph to get a NEGATIVE or zero premium N

36. So • Simple monopsony model does predict incidence of over-education • Model is ambivalent about relative wage for graduates in non graduate firms • If labour supply is very inelastic then may get zero or negative differences • Costs too much for the firm to try and get more graduates by paying them more • Key thing is the relative wage depends on outside option NOT on relative productivity • What about industries with more than one firm?

37. This analysis is partial, as if each firm follows this strategy the supply curves will look very different • General equilibrium search models,(Diamond (1971) , Burdett and Mortensen (1998) can be easily used to show how the relative wage and employment of graduates will evolve in the non graduate sector in equilibrium • Manning shows that key findings are similar to those in the partial equilibrium model BUT • Get wage dispersion amongst workers of each type • Association of education and wages across firms (higher wage firm attract more educated workers) but this does not relate to productivity • May get higher graduate unemployment

38. What about incentives to acquire human capital? • Assume • There exist firms for which MP of education is zero • Labour market frictions exist • private returns are lower than social returns • returns are risky

39. Earnings B Stays at school until E A Leaves school at F O G + E F Age 65 - C D

40. So if individuals are undertaking investments with low return • Are the costs also low • Open to the floor! • Temporary versus permanent effects • Is the low return predictable ex ante? • If so then mean return may be large but the outcome small or zero • Finding from investment literature is that this typically results in under-investment as agents are risk averse • Case for MORE subsidy not less • Govt. should act as insurer (graduate tax?)

41. Estimating the Extent of Over-Education

42. Background • Focus on graduate over-education • Better measured than other types of over-education • important policy implications • HE expansion over the past two decades • Government policy to increase HE participation rate to 50% • Destinations of Leavers from Higher Education (DLHE) survey: snapshot of graduates 6 months after graduation • Latest figure on the 2008 cohort of graduates: • 61.4% entering employment, 14.1% entering further study or training, 8.1% entering working & studying, 7.9% unemployed and 8.5% other

43. What types of work did graduates go into? • Of those who were working ft or pt or combine work with further study, 32.3% (last 5 rows) might be classified as over-educated • But this is only 6 months after graduation

44. Earnings of new graduates by occupations • salary of full-time, first degree leavers who entered full-time employment in the UK • Graduates in professional jobs earn more than their counterparts in non-graduate occupations • Associate professionals in between

45. Trend in over-education: DLHE 2004-8 • Graduate job classifications were developed by Professors Peter Elias and Kate Purcell for their study Seven Years On: Graduates in the Changing Labour Market.

46. Measurement of over-education • Typologies of over-education: • Objective measures of over-education • Required education determined on the basis of job title according to the SOC system (job title inflation will lead to under-estimation of over-education!) • Comparing individual’s education with the mean education level of his/her occupation • Subjective measures of over-education • Self-assessed (by the respondent) minimum requirements of the job (to be contrasted with individual’s acquired education) • Directly asking the respondent whether they are overeducated • Distinction between overqualification and skill underutilization • Respondent’s satisfaction with the match between qualification and job

47. Empirical evidence • Use the Green & Zhu 2010 OEP paper as a case study • Based on up-to-date data from the UK Quarterly Labour Force Survey 1994-2007 and recent UK Skills Surveys (1992, 1997, 2001 and 2006) Theme: use of “overqualification” to help understand trends in the returns to graduate education after the surge in HE participation • Trends in the dispersion of returns to graduate education: quantile regressions • Definition and decomposition of overqualification • Trends in overqualification • Trends in the costs of overqualification • Linking the trends

48. Motivation • Figure shows proportion of 25-59 year olds who record having a first degree in UK QLFS 1994–2006, by birth cohorts (by year when aged 19) (Walker & Zhu, SJoE 2008 Fig 1) • huge increases in HE participation over a short period of time • More than 50% increase for men • Doubling for women

49. Measure of stock of graduates • Figure updated with two additional years of data (up to Dec 2009) • It shows share of graduates in the labour force (proportion of 25-60 year olds with NVQ 4+) • Rapid rise throughout period. • For women an apparent acceleration after 2002

50. Returns to graduate education • Key research question: If the increased participation persists, when if ever will there be a decline in the returns to graduate education? • General stability or rise over 1980s and 1990s: • Machin, 2003 • Elias and Purcell, 2004; Mason, 2002 • Some hints of falling returns from: • Purcell et al., 2005 • Sloane, 2005 • Walker and Zhu, 2008