Presentation on theme: "Amanda Gosling and Yu Zhu GES Summer School, Kent, 30th June 2010"— Presentation transcript:
1 Amanda Gosling and Yu Zhu GES Summer School, Kent, 30th June 2010 Over-educationAmanda GoslingandYu ZhuGES Summer School, Kent, 30th June 2010
2 Structure Introduction and Motivation Background (literature, some trends and dataA bit of theoryEstimating the extent of over-education and discussion of some evidenceTea BreakDiscussion
3 Why look at over-education? Over-education is a very active research field:Google Scholar keyword search returns papers in Business, Administration, Finance, and Economics; and another papers in Social Sciences, Arts and HumanitiesPolicyControversy over 50% target of cohort in further or higher educationDebate over the level and mechanisms for funding and subsidyCurrent (25% help!) funding cutsSkills and ConceptsControversy 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 disagreementRight way to model the labour marketHow 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 Macro Examples 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.MacroLabour market has “too many” graduatesCredentialismAgain represent disequilibriumExamplesSlackerPhilosophy PhDSAHMMother with small children unable to find suitable jobs with flexible/part time hoursRussian Labour marketEarly labour market experiencesLong run graduates “trapped” in low status jobs
6 Background Emphasis on education expansion Academic Factual Third way (emphasis on equality of ops. rather than of outcomes)Becoming more controversialAcademicFreeman (the over-educated American)Research on demand and supply of skillsResearch on large (and growing) returns to educationMicro led research on over-education (and its criticisms)FactualChanges in “return” to educationParticipation in educationLong series on education by occupation and gender
7 Academic background (1) Cobweb-model Graduate wagesupplyWage associated with zero rentsdemandGraduate employment
8 Card and Lemieux (QJE 2001)Look at changes over time in relative wage of graduatesHypothesis that part of the changes can be explain by changes in relative supplyIdea that demand and supply are always racing to keep up with each otherStrong support using US micro dataBUTIdentification problemsIdentification relies on non-substitutability of workers of different agesEstimate is “raw”
9 What do we know about the return to education? Early work (e.g. Dennison 1962, 1967) on growth accountingBut is education a consumption or investment good?Mincer, Becker Human Capital Wage regressionsRate of return (like on any other asset)High but fluctuatingSheepskin effectsLater (Ashenfelter, Angrist, Kruegar, Walker) on solving the “ability bias” problemUse 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 RISEMeasurement errorHeterogeneity 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 90sEvidence (Green and Zhu) that return to education for younger cohorts has flattened or even fallenGrowing focus on the distribution of returns using techniques like quantile regressionsStarts off with Buschinsky (1996)Key difficulty is that the distribution of returns is NOT the same as the distribution of differencesTreatment effect literatureConsensus 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 satisfactionCauses (race, gender, discrimination, ability)MeasurementChanges over timeLong versus short runImplications for human capital modelIs this a meaningful avenue for research?
12 Now some data on background trends Own calculations using FES and BHPS data
22 SummaryDramatic increase in relative supply of educated workers over last 30 yearsSome weak evidence that the return has declinedFor younger cohortsDistribution of returnsPicture becomes less clear cut when we look at employmentMore graduates doing non-graduate jobs butLess of these jobsNumbers are smallNot clear that over-education is a growing problemMight think it should be more of an issue for women but this is not apparent in the data
24 Some key economic concepts to understand and think about Production functionsEducation as screening/signalling deviceLabour market modelsIncentives to acquire education. If education is a choice, how can a worker have too much?Investment under uncertainty
25 Production functionsCan 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 zeroFirm production with labour of different typesTechnology of human capital productionPart 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 effectsPlausibility of models depend on other available strategies to separate workers
27 Labour marketAssume there ARE some firms for which MP of education is zeroWill we then get over-education?Argue that only in presence of labour market imperfections
29 WSupply of graduatesSupply of non graduatesLQNon 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 productionIf graduate were in non graduate jobs they would have to get a graduate wageSo 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 jobsSearch or mobility costsNon wage differences in jobs (Bhaskar and To)See idea with simple discriminating monopsony model (but note this analysis is partial)
32 Supply non graduatesWSupply graduatesConstant marginal product for simplicityN
33 WMarginal cost of hiring non graduateMarginal cost of hiring graduateSupply graduatesSupply non graduatesdemandN
34 WMarginal cost of hiring non graduateMarginal cost of hiring graduateSupply graduatesSupply non graduatesdemandSmall wage premium here and large diff in employmentN
35 WMarginal cost of hiring non graduateMarginal cost of hiring graduateSupply graduatesSupply non graduatesdemandNote that could have drawn graph to get a NEGATIVE or zero premiumN
36 So Simple monopsony model does predict incidence of over-education Model is ambivalent about relative wage for graduates in non graduate firmsIf labour supply is very inelastic then may get zero or negative differencesCosts too much for the firm to try and get more graduates by paying them moreKey thing is the relative wage depends on outside option NOT on relative productivityWhat 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 differentGeneral 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 equilibriumManning shows that key findings are similar to those in the partial equilibrium model BUTGet wage dispersion amongst workers of each typeAssociation of education and wages across firms (higher wage firm attract more educated workers) but this does not relate to productivityMay get higher graduate unemployment
38 What about incentives to acquire human capital? AssumeThere exist firms for which MP of education is zeroLabour market frictions existprivate returns are lower than social returnsreturns are risky
39 Earnings B A O G + E F Age 65 - C D Stays at school until E Leaves school at FOG+EFAge65-CD
40 So if individuals are undertaking investments with low return Are the costs also lowOpen to the floor!Temporary versus permanent effectsIs the low return predictable ex ante?If so then mean return may be large but the outcome small or zeroFinding from investment literature is that this typically results in under-investment as agents are risk averseCase for MORE subsidy not lessGovt. should act as insurer (graduate tax?)
42 Background Focus on graduate over-education Better measured than other types of over-educationimportant policy implicationsHE expansion over the past two decadesGovernment policy to increase HE participation rate to 50%Destinations of Leavers from Higher Education (DLHE) survey: snapshot of graduates 6 months after graduationLatest 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-educatedBut this is only 6 months after graduationOccupationsShareArts, design, culture, media and sports professionals6.20%Business and financial professionals and associate professionals7.50%Commercial, industrial and public sector managers9.30%Education professionals7.10%Engineering professionals3.20%Health professionals and associate professionals14.60%Information technology professionalsLegal professionals0.60%Marketing, sales and advertising professionals4.10%Scientific professionals1.20%Social and welfare professionals4.70%Other professionals, associate professionals and technical occupations5.20%Numerical clerks and cashiers2.00%Other clerical and secretarial occupations8.90%Retail, catering, waiting and bar staff10.60%Other occupations11.60%Unknown occupations0.20%
44 Earnings of new graduates by occupations salary of full-time, first degree leavers who entered full-time employment in the UKGraduates in professional jobs earn more than their counterparts in non-graduate occupationsAssociate professionals in betweenTypes of jobsAverage salary for a new graduate (£)Health professionals (eg doctors, dentists and pharmacists) 25,362Functional managers (eg financial managers, marketing and sales managers)23,976Engineering professionals23,651Business and statistical professionals (eg accountants, management consultants, economists)23,208Information and communication technology professionals22,941Architects, town planners, surveyors21,567Teaching professionals (eg secondary and primary school teachers) 19,989Science professionals19,972Legal professionals (eg solictors and lawyers)19,765Sales and related associate professionals19,134Design associate professionals (eg designers, including web designers) 17,829Artistic and literary occupations (eg artists, writers, actors, musicians, producers and directors)17,334Social welfare associate professionals (eg youth and community workers, housing officers) 17,317Legal assocaite professionals (eg legal executives and paralegals)16,931Sports and fitness occupations16,443General administrative occupations 15,374Customer service occupations 14,543All occupations19,677
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.Types of job Examples20042005200620072008Traditional graduate occupationsSolicitors, research scientists, architects, medical practitioners11.1%11.2%11.5%11.7%12.4%Modern graduate occupationsSoftware programmers, journalists, primary school teachers12.3%12.6%13.1%13.8%13.7%New graduate occupationsMarketing, management accountants, therapists and many forms of engineer14.9%15.5%16.0%17.2%16.6%Niche graduate occupationsNursing, retail managers, graphic designers22.7%23.3%23.7%23.8%23.0%Non-graduate occupationsAny jobs that do not fall into the above categories39.1%37.5% 35.6%33.5%34.3%Total in graduate occupations 60.9% 62.5%64.4%66.5%65.7%
46 Measurement of over-education Typologies of over-education:Objective measures of over-educationRequired 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 occupationSubjective measures of over-educationSelf-assessed (by the respondent) minimum requirements of the job (to be contrasted with individual’s acquired education)Directly asking the respondent whether they are overeducatedDistinction between overqualification and skill underutilizationRespondent’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 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 participationTrends in the dispersion of returns to graduate education: quantile regressionsDefinition and decomposition of overqualificationTrends in overqualificationTrends in the costs of overqualificationLinking the trends
48 MotivationFigure shows proportion of 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 timeMore than 50% increase for menDoubling 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 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, 2003Elias and Purcell, 2004; Mason, 2002Some hints of falling returns from:Purcell et al., 2005Sloane, 2005Walker and Zhu, 2008Machin covered to the end of the 1990s.Mason: three sectors in : graduate skills being utilised in traditionally non-graduate jobsElias and Purcell: new and niche jobs, using some of the skills normally associated with graduatesChevalier and Lindley: no increase in penalty for overeducation for 1995 graduates in 2002, compared with earlier cohort.Covering up toA few hints from these studies, nothing definitive.
51 QR/OLS est. of the college premium for women Returns are for Level 4 relative to Level 2.Dispersion between high and low percentiles, attributable to either: education complementary with unobserved skill; heterogeneous school quality or over-education (as found by Pereira and Martins for both sexes together).Dispersion has become more pronounced over time: 0.17 to 0.27 log points; significant.Another way of seeing this: the returns have increased, slightly, at higher quantiles, but have decreased somewhat at lower quantiles.
52 QR/OLS est. of the college premium for men Increasing dispersion over time with higher returns for high residual quartiles and slightly lower returns for low quartiles at end of period; gap increased significantly from to 0.11.Put another way, there are significant increases at the top end, but not at bottom end: new finding.Our story is that this is evidence of persistently increasing demand at the high end; but that returns at the lower end have fallen or remained steady because more people at this end are failing to obtain graduate-level jobs (with associated pay). Those who are overeducated are not in effective competition with successful graduates; hence the falling returns at the lower end can co-exist with stable or rising returns to more successful graduates.
53 Changing composit. of the lowest quintile of the residual wage dist. In lowest quintile of the residual pay distribution we have:No rise in proportion of graduate jobs being heldRise in the proportion of graduates.
54 Previous evidence on overeducation Overqualification, according to earlier studiesHas a pay penaltyLowers job satisfactionFor some is persistent/permanentIs more likely for less able personsChevalier (2003): splits into “genuine” and “apparent” overeducation, according to whether satisfied with match.Little/nothing known about (our research questions):change over time,whether cohorts shake it off as they get older,changing penalties over time;plus little or no attempt to relate to changing returns to education.
55 Definitions and decomposition Overqualification (OQ) dummy:OQ = 1 if RQi < Qi, OQ = 0 if RQi >= QiOverskilling (OS) dummy, defined from:“How much of your past experience, skill and abilities can you make use of in your present job?”, (“very little”/ “a little”/ “quite a lot”/ “almost all”). Top two points.“Real Overqualification”: OS and OQ“Formal Overqualification”: OQ but not OS.Skills Fully UtilisedSkills UnderutilisedIn Graduate JobsMatchedQualification Matched and Skills UnderutilisedIn Non-Graduate JobsFormalOverqualificationRealTwo definitions of overskilling used in paper for robustness.
56 Data Employment in Britain (1992) 1997 Skills Survey UK-wide, but here restricted to employees, in England, Scotland and Wales; some regions over-sampled5224 employees, weighted analyses, representative
57 Validation of classification of overqualification (% of graduate employees)Learning Time Over 2 YearsLearning Time Under 1 MonthRequirement to Learn New ThingsInfluence Skills RequirementComplex/Advanced Computing Skills RequirementIn SOC Major Groups1-3RealOverqualification8.038.019.55.011.330.9Formal26.313.136.725.725.058.0Qualification Matched and Skills Underutilised126.96.36.1996.234.279.4Qualification Matched and Skills Utilised6.749.950.130.889.7Point is: more skilled jobs for less overqualified, better matched, graduates.
58 Prevalence of Graduate Overqualification by Education Characteristics (Row percentages summing to 100%)RealOver-qualificationFormalQualification-Matched and Skills UnderutilisedQualification-Matched and Skills UtilisedMaths Level **Below A-Level9.424.94.761.1A-Level or above5.313.76.474.6University TypeOxbridge0.010.60.489.0Pre-1992 University8.914.36.070.9Other UK8.821.465.2Non-UK14.83.760.1Degree Grade*Below Upper Second12.820.03.563.7Upper Second or First9.315.64.670.4Some connection to ability/achievement; not at all perfect correlation.
59 Education/job matching for graduates 1992199720012006MEN:Matched78.377.073.066.8Overskilled15.4-12.8Overqualified, of which21.723.027.033.2Real Overqualification188.8.131.52Formal Overqualification14.019.823.4WOMEN:76.274.876.668.012.212.012.723.8184.108.40.206.416.117.523.7Rise in overqualified. No rise in overskilling. Main increase in Formal Overqualification.Similar story for both genders.
60 Cond. association of overqualification with log hourly wage, Men 19921997200120061. Estimates including graduate overqualification (see below for other variables included)Overqualified-0.276-0.330-0.246-0.404(0.050)(0.061)(0.048)Observations117288816572126R-squared0.430.400.452. Estimates including types of mismatch (see below for other variables included)Real overqualification-0.401--0.488-0.619(0.085)(0.081)(0.099)Formal overqualification-0.240-0.175-0.322(0.055)(0.042)Qualification Matched but Skills Underutilised-0.229-0.189-0.046(0.069)(0.092)(0.056)116321250.440.410.46Sharp increases in the overqualification penalty; as highlighted in red.
61 Cond. association of overqualification with log hourly wage, Women 19921997200120061. Estimates including graduate overqualification (see below for other variables included)Overqualified-0.316-0.257-0.392-0.454(0.048)(0.063)(0.040)(0.033)Observations114488616432308R-squared0.490.580.570.552. Estimates including types of mismatch (see below for other variables included)Real overqualification-0.441--0.430-0.642(0.060)(0.056)Formal overqualification-0.250-0.386-0.407(0.062)(0.047)Qualification Matched but Skills Underutilised0.109-0.076-0.196(0.058)(0.088)1134164023060.56Same story, with slight variation in the timing.
62 Cond. association of overqualification with job satisfaction 199220012006MenReal Overqualification-0.429(0.461)(0.317)(0.238)Formal Overqualification-0.196(0.347)-0.340(0.184)-0.199(0.175)Qualification Matched & Skills Underutilised-0.784(0.387)0.195(0.406)-0.505(0.430)Mean job satisfaction of graduates4.3254.1144.310Women(0.459)(0.420)(0.358)0.160(0.278)0.389(0.195)-0.294(0.177)-0.750(0.557)-0.545(0.315)-0.341(0.281)4.5154.2314.472Only real over-qualification has a significant effect on job dissatisfaction, as highlighted in blue.Formal over-qualification has no significant effect.For men, the satisfaction penalty has significantly increased since 1992; for women, it has always been quite high.Same story using a compound job satisfaction measure.
63 Returns to graduate education at 10th/90th percentiles for men Fanning out of 90th and 10th percentiles, as with QLFS data; increase at top end; decrease at lower end more pronounced than with the QLFS data.But, no fanning out of the matched graduates.
64 Returns to graduate education at 10th/90th percentiles for women Same story for women.
65 Summary of new findings Increasing dispersion in returnsRising “formal”, stable or slowly rising “real” overqualification till 2006Rising pay and satisfaction costs of overqualificationStable dispersion of returns for those matched to jobs
67 Why does over-education happen? The simple story (Human Capital Theory):Human Capital Theory: education determines worker’s stock of HC which in turn determines marginal product; wages equate worker’s marginal product; firms adapt production technology in response to changes in the supply of skilled labour.over-education as a result of too many graduates over-flooding the labour market arising from HE expansion, oras a temporary blip while new graduates get their foot on the career ladder (life-cycle perspective) , oromitted variable problem: over-educated workers may be compensating for a lack of work-related capital (assuming education and less formal measures of HC are substitutes)
68 Alternative explanations Supply-side mechanisms:worker skill heterogeneity: perhaps a university education only benefits the more able students, oreducation is an inherently risky investment?Demand-side mechanisms:labour market frictions preventing possible efficient matches between educated workers and employers that need skills;some type of graduates might be more constrained in the way they can look for jobs, e.g. women with partners, e.g. Frank (1978)Does the evidence give support to the view that education is merely a signaling mechanism (rather than enhancing your productivity)?
69 Some things to think about Is the concept of “over-education” a useful one for economists?What does the evidence on over-education suggest about the rationale for reducing the number of state funded university places?Is there anything that policy makers can (or should) do to improve outcomes for those graduates (both past and future) who are or will perform less well in the labour market?Are there too many people going to university who would be better off going straight into the labour market or into another form of training.
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