The Economics of Imperfect Labor Markets - @let@token Tito Boeri del... · 2012-12-10 · Source:...

Source: Tito Boeri and Jan van Ours (2008), The Economics of Imperfect Labor Markets, Princeton University Press.

The Economics of Imperfect Labor MarketsTito Boeri

November 2010

Tito Boeri and Jan van Ours (2008)The Economics of Imperfect Labor Markets

Princeton University Press

Chapter 8. Education and training

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Education and Training – What Are We Talking About?

What are we talking about?

Schooling and training: investments by individuals and firms → costsare paid in exchange for expected future benefit

Formal schooling usually before individual enters the labor market

Training usually after entrance into the labor market:

GeneralFirm-specific

Focus literature on schooling: choice of educational attainment

Focus literature on training: who pays?

Market failures education and training:1 Incomplete capital markets2 Private rates of return ⇐⇒ social rates of return3 Long time lag between decision and outcome4 Holdup problem: training agreements are non-contractible

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Education and Training – What Are We Talking About?

Overlaps with other institutions

Payroll taxes: incentives to extend schooling & to attend training

Unions: training

Employment protection:

if not – no trainingif too much – no training

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Measures and Cross-Country Comparisons

Measures

Organization formal education very country-specific

Educational expenditures as % of GDP

Training: difficult to measure

Participation rateAnnual volume

PISA scores

Program for International Student AssessmentSurvey of student knowledge and skills of 15-year-oldsMathematics, science and reading

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Educational expenditures & attainments

Educational Years of formal education PISAexpenditures Men Women Math score

Denmark 7.1 13.6 13.7 106France 6.1 11.7 11.4 106Germany 5.3 13.7 13.1 104Italy 4.9 10.2 9.9 96Netherlands 5.1 13.1 12.7 111Spain 4.9 10.6 10.4 100UK 5.9 12.8 12.6 –US 7.2 13.8 13.9 100

Educational expenditures: % of GDP (2002)Years of formal education: population 25-64 years (2003)

PISA: normalized to US score (2003)

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Cross-country comparison schooling

Substantial differences in spending level:4.9% (Italy, Spain) ↔ 7.2% (US)

Educational attainment wide variation:9.9–10.2 (Italy) ↔ 13.8–13.9 (US)

Positive but imperfect correlation between spending and educationalattainment

PISA math score (15 year olds):Italy lowest score (96) ↔ Netherlands highest score (111)

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Employment rates by education (2006)

Men Women1 2 3 1 2 3

Denmark 70.5 84.3 87.9 54.7 74.3 85.2France 68.0 81.4 85.6 52.0 68.5 78.3Germany 59.7 74.6 85.6 41.4 64.3 78.4Italy 70.8 83.5 87.9 32.6 63.7 77.1Netherlands 75.1 84.2 88.4 46.1 70.9 82.2Spain 77.1 84.7 87.3 37.8 61.0 76.5UK 60.1 84.9 89.4 46.9 73.9 85.6US 68.1 78.6 87.3 43.5 67.4 77.5

1 = Less than upper secondary education2 = Upper secondary education

3 = Tertiary education

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Relative earnings – if income from employment (2005)

Men Women1 2 3 1 2 3

Denmark 87 100 131 90 100 123France 88 100 159 81 100 146Germany 90 100 150 81 100 145Italy 74 100 162 78 100 147Netherlands 84 100 143 72 100 155Spain 79 100 138 64 100 125UK 73 100 151 70 100 180US 67 100 189 70 100 177

1 = Less than upper secondary education2 = Upper secondary education

3 = Tertiary education

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Empirical evidence effect of education

Strong relationship between educational attainment and labor marketstatus and earnings

Wide cross-country variation in employment rates of low-educatedmen59.7 (Germany) ↔ 77.1 (Spain)

Less variation among higher-educated men85.6 (France, Germany) ↔ 89.4 (Denmark)

Wide range in relationship between earnings and education; men67–189 (US) ↔ 87–131 (Denmark)

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Cross-country comparison employer sponsored training

IALS data ECVTS dataParticipation Annual Participation Annual

rate (%) volume rate (%) volumeDenmark 45 36 53 22France – – 46 17Germany – – 31 9Italy 14 8 26 8Netherlands 24 21 41 15Spain – – 25 11UK 44 22 49 13US 33 18 – –

IALS = International Adult Literacy Survey – 1994–96ECVTS = European Continuing Vocational Training Survey – 1999

Annual volume = hours per employed worker

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Education and Training – Theory

Theory – schooling

Basic assumption human capital model:

1 More education −→ higher productivity

2 Higher productivity −→ higher wage

3 Individuals’ choice is based on financial considerations

Investment decision:

Costs: direct expenses & forgone earnings

Benefits: higher wage (and employment rate)

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0

-C

W0

Ws

Monetary benefits

Forgone earnings

Direct costs

0 sYears of schooling and age

T

Earnings and costs

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The Wage-Schooling Locus

The wage-schooling locus gives the salary that a particular worker wouldearn if he completed a particular level of schooling.

12 13 14 18

20,000

23,00025,000

30,000

Dollars

Years ofschooling

δw

δs= MRR

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The Wage-Schooling Locus II

12 13 14 18

20,000

23,00025,000

30,000

Dollars

Years ofschooling

δw

δs= MRR

from 12 to 13 years of schooling: $ 3000 extra: MRR = $ 3000 = 15% / yearfrom 14 to 18 years of schooling: $ 5000 extra: MRR = $ 1250 / year = 5% / year

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Optimal level of schooling

MRR r MRR: marginal benefits

r=marginal costs

Years of SchoolingS*

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Schooling and earnings when workers have differentdiscount rates

11 12

Rate of Interest

Years ofSchooling

race

rbob

MRR

race

rbob

Wage

Years ofSchooling

Ace and Bob have the same ability but face different discount ratesAce is from a poor family, Bob from a rich familyAce has fewer years of schooling

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Schooling and earnings when workers have differentabilities

MRRace

MRRbob

r

Rate of Interest

11 12

wace

wbob

wdrop

ZDollars

Years of Schooling

11 12

Bob

Ace

Ace and Bob have the same discount rate (r), but each worker faces adifferent wage-schooling locus.

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Education and the wage gap

Observed data on earnings and schooling does not allow us toestimate returns to schooling

In theory, a more able person gets more from an additional year ofeducation

Ability bias - the extent to which unobserved ability differences existaffects estimates on returns to schooling (since the ability differencemay be the true source of the wage differential)

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Schooling as a signal

Education reveals a level of attainment which signals a worker’squalifications to potential employers

Education → wage (but not via productivity)

Information that is used to allocate a workers in the labor market iscalled a signal

There could be a separating equilibrium

Low-productivity workers choose not to obtain y years of education,voluntarily signaling their low productivityHigh-productivity workers choose to get at least y years of schoolingand separate themselves from the pack

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Education as a Signal

B

Costs

D

C

AYears of Schooling

Dollars

200,000

25,001

300,000

Slope = 25,001

ӯ

(a) Low – Productivity Workers

Dollars

B

Costs

D

C

AYears of Schooling

200,000

20,000

300,000

Slope = 20,000

ӯ

(b) High – Productivity Workers

1 AB > CD −→ 0 years of schooling

2 AB < CD −→ y years of schooling

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Theory – training I

Human capital theory → main issue: who pays for training?

Traditional: workers pays general training – firm pays firm-specifictraining

General training:

Increases productivity but diminishing returnsTraining costs increase more than proportionallyWorker is paid according to productivity and chooses the optimal levelof training maximizing revenue

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Theory – training I

ττ*

c(τ)

v(τ)=w(τ)

v(τ)c(τ)w(τ)

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Theory – training II

Alternative theory general training: non-competitive markets

Employers have monopsony power: worker is paid below productivity

Wage compression: gap between wage and productivity increases withtraining

Employers chooses the optimal level of training maximizing revenue

Monopsony power: moving costs due to matching and searchfrictions, asymmetric information

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Theory – training II

τ

c(τ)

v(τ)v(τ)c(τ)w(τ)Δ(τ)

w(τ)

Δ(τ)=v(τ)-w(τ)

τf

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Education and Training – Empirical Evidence

Box 8.1 Returns to schooling & identical twins

Ashenfelter and Rouse (1998)

Correct for ability bias – sample of twins

Annual Twinsburg Twins Festival (Ohio) → interviews 1991, 1992,1993

Sample: identical twins both of whom have held a job at some pointin the previous 2 years

Schooling difference: each twin reported on own schooling andsibling’s schooling

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Box 8.1 Returns to schooling & identical twins

Ashenfelter and Rouse (1998)

Returns to schooling → percentage increase in wage due to 1additional year of schooling

Account for differences in ability (more able → more education)US sample of 340 twinsDirect estimate 10.2%Twins: 8.8%Ability bias: 1.4%

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Alternative ways to correct for ability bias

Distance to school

Season of birth −→ variation in compulsory schooling age

Vietnam War lottery: each day of the year → random number; lownumbers were drafted for the war ↔ high number not. Throughgoing to college avoid having to go to war. Low numbers had thisincentive ↔ high numbers not. Low numbers more schooling thanhigh numbers (same ability)

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Box 8.2 On-the-job training in Germany

Training in imperfect labor markets

Germany: firms voluntarily offer apprenticeships to workers enteringthe labor market

Firms that train have to follow prescribed curriculum

Apprentices take rigorous outside exam at the end of theirapprenticeship

Training is monitored by worker councils

Most of the skills acquired = general training

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Acemoglu and Pischke (1998)

Why do German firms do this → do they have monopsony power?

Mobility of workers is restricted

No direct investigation of training – in stead: focus on presence ofadverse selection – informational monopsony power

3 cross-sections (1979, 1985-86, 1991-92) German Qualification andCareer Survey

Gross monthly wages

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Acemoglu and Pischke (1998)

Quits or layoffs signal low quality – exogenous separations can breakinformational monopsony power

Military quitter: left apprenticeship firm immediately & mentionmilitary service as reason – unrelated to ability

Relative to voluntary quitters wage increase

Stayers: 1.2%Military quitters: 4.5%

Military quitters earn more because they are separated for anexogenous reasons and therefore must be of higher quality

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Education and Training – Policy Issues

Policy issue 1 – Should governments subsidize in-companytraining?

Is it optimal from a welfare point of view?

Deadweight loss?

Answer depends on market power of firms

Competitive market – employers reluctant to invest in training – ifproductivity goes up: social returns to training

Social returns – based on gross wage; private returns – based on netwage

If social returns > private returns: governments may step in andsubsidize

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Education and Training – Policy Issues

Policy issue 2 – Should there be a compulsory schoolingage?

All OECD countries compulsory schooling age

Is it welfare improving?

Individuals may be shortsighted – too high discount rate – ignorefuture benefits (higher wages, lower unemployment)

If social returns > private returns: governments may step in andsubsidize → scholarships are welfare improving

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Why Do Governments Provide Education and Training?

Why do governments provide education and training?

Having a higher educated population and a well-trained workforce haspositive externalities – competitive asset

Capital market imperfections → impossible or difficult to borrow →sub-optimal investments in human capital

Investment in schooling and training → national income goes up

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Education and Training – Review Questions

Review questions

1 Why do firms pay for general training even though trained workers arevaluable for other firms as well?

2 Why is it difficult to measure returns to schooling?

3 Why should not all students try to achieve an academic degree?

4 Does it matter for the schooling decisions of the individual to whatdegree schooling is a signal of innate productivity?

5 Should the state subsidize on-the-job training?

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The Economics of Imperfect Labor Markets - @let@token Tito Boeri del... · 2012-12-10 · Source:...

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