labor economics - crest

Labor EconomicsLabor Market Policies.

Pierre Cahuc/Sebastien Roux

ENSAE-Cours MTPE

December 12th 2007

Pierre Cahuc/Sebastien Roux (ENSAE) Labor Market Policies December 12th 2007 1 / 45

Introduction

Introduction

Justification of Intervention of State :

Political objectivesMarket failures

Two forms of State intervention1 Active policies : Increase employment and wages of persons who have

difficulties to enter the Labour MarketExamples : Job Search assistance, Training, Employment subsidies...

2 Passive policies : Increase the welfare of disadvantaged populationswithout trying to improve their Labour Market performancesExamples : Unemployment Insurance, provisions for early retirement


Introduction

Effects of Labour Market Policies

Obvious Incentive problems with passive policies.

But Active policies are not always“good”and passive policies “bad”

Some active policies may be counterproductive :

Creation of public sector jobs can, because of cost and low efficiency,lead to a decline in the total number of jobs.Subsidies to promote some employment types can introduceunexpected distortions.

Some passive policies may be efficient :

Increase in unemployment benefits may reduce the number ofunemployed when not all workers are eligible.Financial compensation for unemployment may improve efficiency byimproving the quality of matches, letting more time for unemployed toget better jobs.


Introduction

Outline

1 Definition of Labor Market Policies2 Theoretical Analyses

1 Manpower Services2 Subsidizing low wage jobs

3 Evaluation of Labor Market Policies1 Baseline framework2 Evaluation of low-wage payroll reduction


Definition of Labor Market Policies


OECD Classification of Active Policies :

Public Employment Services : ANPE

Labor Market training,1 Training for unemployed adults (or similar...)2 Training for employed adults

Youth employment and training measures1 For the unemployed and disadvantaged2 Apprenticeship or Youth training

Subsidized Employment1 Subsidies for private sector Employment2 Helps for unemployed persons in launching new firms3 Direct Job creation in the public sector



Employment programs for the disabled1 Professional rehabilitation2 Jobs oriented to disabled

Passive Policies :

1 Unemployment Insurance

2 Early retirement for reasons connected to the labour market



Improving the Labor Market

Public Employment Services : Reduction of the search costs.

US Employment service or ANPE. Also private agencies in somecountries. All Job Search Assistance programs (JSA)

Labor Market Training : Increasing“Employability” (see Denmark orGermany)

Classroom training : brief duration, industry or firm-specific, mayimprove general human capital.

Youth Employment and training.

Apprenticeship, programs helping young people who leave school early(Ex : Job corps in the USA)Other measures : On-the-job training. Incentives for firms to train theiremployees with general human capital.



Reduction of Labor Cost or Direct Creation of jobs

Transfers to firms that hire members of particular groupsExamples : Reduced payroll taxes for low wage jobs, Public serviceemployment.

Some remarks

Subsidized employment non-existent in the US.Distinguish between temporary and permanent Civil Service jobs.One individual can enter in different programs.Distinguish between active and passive labor market policies issometimes difficult (cf. Netherlands with Disabled)



Public expenditure on labor market policies

Total Passive Active Passive/Country Year Expenditure Expenditure Expenditure ActiveAustralia 2000-01 1.43 0.98 0.46 2.13Canada 2000-01 1.13 0.72 0.41 1.76Denmark 2000 4.56 3 1.56 1.92France 2000 2.96 1.65 1.31 1.26Germany 2001 3.13 1.92 1.2 1.60Japan 2000-01 0.86 0.55 0.31 1.77Netherlands 2001 3.44 1.86 1.58 1.18Norway 2001 1.23 0.44 0.79 0.56Sweden 2001 2.28 1.19 1.09 1.09United Kingdom 1999-2000 0.92 0.56 0.36 1.56United States 2000-01 0.45 0.3 0.15 2.00

Source : OECD



Structure of expenditures

YouthPublic Labor employment Employment

Employment Market and training Subsidized programs forCountry Year Service Training measures employment the disabledAustralia 2000-01 44.4 4.4 15.5 24.4 11.1Canada 2000-01 41.5 41.5 4.9 7.3 4.9Denmark 2000 7.6 54.1 6.4 10.8 21France 2000 13.7 19.1 32.1 28.2 6.9Germany 2001 19.2 28.3 7.5 20.8 24.2Japan 2000-01 62.5 9.4 - 25 3.1Netherlands 2001 16.5 19.7 2.5 24.2 36.9Norway 2001 15.2 7.6 1.3 1.3 74.7Sweden 2001 20.9 27.3 1.8 21.8 28.2United Kingdom 1999-2000 36.1 13.9 41.7 2.8 5.5United States 2000-01 26.7 26.7 20 6.7 20

Source : OECD


Theoretical Analyses of Active Policies

Theoretical Analysis : Manpower services

Equilibrium model accounting for Labor demand, wages and possibleMarket unefficiencies : the Matching model

Note that, most often, the way the reforme is financed and how itaffects the outcome is not examined : we want to focus on the directeffect of the reform.

Here, example of manpower services. Double mission :

Registering unemployed and checking whether they are indeed lookingfor a job.Gathering job offers and job demands and thus reduce search costs

Hence their existence is justified by moral hazard and the reduction ofsearch inefficiencies

Its being public may be justified by its fixed cost and its relying onlarge networks (externalities).



A matching model with Placement Agencies, Yavas(1994)

Idea : An placement agency ensures a better match-up betweenunemployed and vacant jobs.

Alternative matching technology with increasing returns (networkeffect) and a specific cost.

Formalization :

Let x ∈ [0; 1] the share of unemployed persons resorting to placementagencies.

i ∈ [0, a] continuum of agencies. a is the number of agencies.Simplifying assumptions :

Agencies are uniformly distributedThey are instantaneously able to locate vacancies

c (xi ) is the cost attached to the placement of xi individuals byagency i

c (xi ) = c0 (a) + cv (xi ) where c0() is a fixed cost (c0(0) ≤ 0 c ′′0 > 0,

congestion) and cv () is a variable cost (cv (0) = 0, c ′′v > 0)



Adapted Beveridge Curve

Unemployed u ∈ [0, 1] are the ones who do not resort to agencies

Matching function M (u, v), v are vacancies

θ = v/u is the labor market tightness, such as θm (θ) is the exit rateout of unemployment.

q is the exogenous destruction rate of jobs

At steady-state, flows balance

q (1− u) = x + θm (θ) u

where x =∫ a0 xidi .

Hence, x = q (1− u)− θm (θ) u, Beveridge curve.



Social Optimum in the presence of placement agencies

To simplify, we consider r → 0

y is the productivity of employed

z is the domestic production of unemployed

Instantaneous aggregate production : (1− u) y + zu

Total relevant cost : huθ +∫ a0 c (xi ) di where h is the cost of a vacant

job.

Total profit : ω = (1− u) y + zu − huθ −∫ a0 c (xi ) di

Using the Beveridge Curve, we get :

ω = −∫ a

0[c0(a) + cv (xi )] di + y −

(q −

∫ a0 xidi

)(y − z + hθ)

q + θm (θ)



Planner’s problem : maxxi ,a,θ

ω

Can be solved in two steps :1 V ∗ = min

θ

y−z+hθq+θm(θ)

2 maxxi ,a

(−

∫ a

0[c0(a) + cv (xi )] di + y −

(q −

∫ a

0xidi

)V ∗)

The first step brings :

(y − z) (1− η (θ))

q + η (θ) m (θ) θ=

h

m (θ)

with η (θ) = − θm′(θ)m(θ)

The second step brings

c ′v (xi ) =

y − z + hθ

q + θm (θ)=

h

(1− η (θ))m (θ)

and

ac ′0 (a) + c0 (a) + cv (xa) = xa

y − z + hθ

q + θm (θ)



Decentralized Equilibrium with Private Agencies

Let pv the price for firms and pu the price for unemployed whenresorting to these agencies.

Hence a firm turns to an agency if its gain exceeds Πe − pv . Atequilibrium, Πv = Πe − pv . At free entry, Πv = 0. Hence Πe = pv .

Same reasoning for Unemployed : Vu = Ve − pu, i-e pu = Ve − Vu

Wage bargaining such that employees get a share γ ∈ [0; 1] of thesurplus S = Πe − Πv + Ve − Vu.

Free entry condition leads to Πe = hm(θ) and the sharing rule to

(1− γ) (Ve − Vu) = γΠe . Hence

pv =1− γ

γpu =

h

m (θ)

Perfect competition between agencies : take pu and pv as given.Decentralized choice of xi , solution of max

xi

(pu + pv ) xi − c (xi )



Hence, c ′v (xi ) = pv + pu = h

(1−γ)m(θ)

Free Entry for agencies lead to :

(pu + pv )− [c0 (a) + cv (xi )] = 0

Firms do not account for congestion effects ! !

Remark : γ = η (θ) (Hosios condition) not enough for thedecentralized equilibrium to be efficient. But the labour tightness θ isat its efficient level :

(1− γ) (y − z)

r + q + γθm (θ)=

h

m (θ)



Theoretical Analysis : Subsidies to low-wage employment,Salanie, 1999

No friction framework.

Three production inputs : capital K , skilled labor LS and unskilledlabor LNS

Y =

(aA

σ−1σ + bL

σ−1σ

NQ

) σσ−1

where A is an aggregate representing skilled labor and capital such as :

A = min (LS , γK )

Hence cA = cS + cKγ at equilibrium. Capital and skilled labor are fully

complementary.



Conditional demands of inputs

Firms maximize their profits. Conditional demand of inputs deducefrom the minimization of the cost function :

minA, LNScAA + cNSLNS , s.t. F (A, LNS) ≥ Y

This leads to

A = Y

(a

cA

)σ (aσc1−σ

A + bσc1−σNS

) σ1−σ = LS = γK

LNS = Y

(b

cNS

)σ (aσc1−σ

A + bσc1−σNS

) σ1−σ



Economic equilibrium

Under perfect competition, profits are nil. Hence, Y = cAA + cNSLNS .This leads to the inputs price frontier :

aσc1−σA + bσc1−σ

NS = 1

This simplifies the inputs quantities at economic equilibrium :

A = LS = γK = Y

(a

cA

)σ

LNS = Y

(b

cNS

)σ

Non-skilled labor cost depends exogenously on the minimum wage :

cNS = wNS (1 + τNS) = λw (1 + τNS)

Capital cost is supposed to be fixed. Hence, cS = cA − cKγ

Skilled Labor Market clears : LS = LSS

Non-skilled labor market fails : U = LSNS − LNS



Model’s resolution

9 unknown values : LS , LNS , K , A, Y , cS , cNS , cK , cA

9 equations

Resolution1 Unskilled Labor Cost cNS fixed by the State through the minimum wage2 cA is deduced from the inputs price frontier.3 Labor market equilibrium gives LS then A and Y .4 No profit condition brings LNS and U.

2 variables to consider :

Net skilled wage : cS = wS (1 + τS)Social contributions : T = TS + TNS − TU , where TS = τSwSLS ,TNS = τNSwNSLNS , and TU = ρwNSU. ρ is the remplacement rate.



Calibration

Figures taken for 1996.

13.3 millions of employees in the private sector

16% of unskilled workers

cNS = 141 200 F, cS = 231 900 F.

τNS = 0.64, wNS = 86 300 F, τS = 0.69

ρ = 0.38, ratio of average unemployment benefit on mean unskilledwage

Estimation of capital cost :

cA = cS +cK

γ=

cSLS + cKK

LS=

1− RNS

RScS

where RS , RNS and RK are the shares of skilled labor, unskilled laborand capital in global income.Hence RS + RNS + RK = 1 and RA = RS + RK = RNS



RNS = 0.06, share of wages in added value (CN)*share of unskilledwages in wages (DADS)

RS = 0.53, hence cAcS

= 1.76

Crucial parameter : Substitution elasticity σ between Aggregate A andunskilled labor LNS .Estimated on individual firm data : σ = 0.7.The model will also be estimated for σ = 2.5.



Effect of a decrease in the taxation of unskilled labor

Direct effect : a decrease of the cost of nonskilled labor.cNS = λw (1 + τNS) :

∂ ln cNS

∂τNS=

1

1 + τNS

Differentiating the price factor frontier leads to :

bσc1−σNS d log cNS + aσc1−σ

A d log cA

= RNSd log cNS + RAd log cA = 0

Hence,

∂ log cA

∂τNS=

∂ log cA

∂ log cNS

∂ log cNS

∂τNS= −RNS

RA

1

1 + τNS=

∂ log cS

∂τNS

An decrease in τNS leads to an increase in the cost of skilled labor,capital cost being fixed.



For the skilled labor market to be cleared, total output Y mustincrease to compensate for the increase of skilled labor force :

∂ log Y

∂τNS= σ

∂ log cA

∂τNS= −σ

RNS

RA

1

1 + τNS

We can deduce the effect on unskilled labor LNS

∂ log LNS

∂τNS=

∂ log Y

∂τNS− σ

∂ log cNS

∂τNS

= −σ

(1 +

RNS

RA

)1

1 + τNS= −σ

1

RA

1

1 + τNS

Consequences on social contributions∂TS

∂τNS= − τS

1+τSwNSLNS

∂TNS

∂τNS=

(1− σ

RA

τNS

1+τNS

)wNSLNS

∂TU

∂τNS= ρσ

RA

11+τNS

wNSLNS∂T

∂τNS=

(1

1+τNS− σ

RA

ρ+τNS

1+τNS

)wNSLNS

Laffer effect if σ > 2.4



Effect of a 10% decrease of τNS

Substitution Elasticity

σ 0.7 2.5cNS -6.1% -6.1%wS +0.7% +0.7%GDP +0.3% +1.1%Employment (thousands) +100 +390TNS (billions francs) -14 -0TS (billions francs) +8 +8TU (billions francs) -3 -13T (billions francs) -3 +21


Evaluation of Active Labor Market Policies


To assess the impact of active labor market policy, needs to assess theimpact on the agent who benefits and on the collective welfare

In practice, very difficult to assess the impact on the collectivewelfare : requires structural modeling.

To assess the impact on individual agents, Rubin-Roy framework.

Outline of the section :1 The Rubin-Roy model2 Evaluation of French low-wage subsidies



The Rubin-Roy Model

Notion of a potential gain : difference of the level of an indicator inthe presence and in the absence of the policy measure.

Main problem : we do not observe both ! !

Solution : Under some assumptions, available observations of someagents who have not benefitted from the measure can be used tomeasure to infer the behaviour of the agents who have benefitted, ifthey had not.

Formalisation : let tP the period over which the“treatment” is applied.There are two potential responses for the individual i

Y Cit is her outcome should she not be treated.

Y Tit is her outcome should she be treated.

Note that t can only be posterior to the“treatment” time tP .



Y Tit and Y T

it are potential results, for “to be treated”and“not to betreated”are two mutually exclusive states. It is not possible toobserve for the same individual at the same date both variables.

Let Di be a dummy indicating whether i has benefitted from themeasure at time t. The observed variable Yit = DiY

Tit + (1− Di ) Y C

it .

We are interested in the quantity ∆it = Y Tit − Y C

it , that cannot beobserved, by definition.

The unobserved result is named“counterfactual outcome”. For atreated individual i , it will be Y C

it , and for a non treated individual j ,it will be Y C

jt . This may be seen as a missing data problem.



Contrast Variables and Identifying Hypotheses

Choice of a Contrast Variable : Most often Average treatmenteffect on the treated

E (∆|D = 1) = E(Y T |D = 1

)− E

(Y C |D = 1

)Empirical counterpart of E

(Y T |D = 1

)easy. What about

E(Y C |D = 1

)? Need to make identifying hypothesis.

General principle : specify a“control group” that has not undergonethe treatment and is as nearly identical to the treated group aspossible.Identifying hypothesis : the observed responses of the control grouphave the same distribution of the treated group, would have they notbeen treated.



Indirect Effects : From partial equilibrium to Generalequilibrium

The Rubin-Roy model refers to a partial equilibrium. It can not assess theeffects of the measure on other agents than the treated or theenvironment : Indirect Effects

Displacement or crowding-out effects : the jobs created by a measuredestroy other jobs to which the measure does not apply.

Windfall effects : the impact of a measure differs hardly at all fromwhat would have been the case if it had not been applied.

Substitution effects : the jobs created flow to the beneficiaries of aparticular measure at the expense of those who are not targeted.

Tax effects : the taxes needed to finance a measure affect thedecisions of all agents.

Need of equilibrium models to asses the global impact of such policies.



Which Data ?

1 Observational data : a selection bias

Usually availability of survey or administrative data that giveinformation on treated and non-treated individuals (and the treatmentdummy).Do not allow to distinguish the specific impact of the measure from theimpact of individual initial differences.The treatment can be chosen by an individual, based on hercharacteristics (unobservable or not).If the choice of the treatment can fully be explained by observedcharacteristics Z , use of the“matching”estimator. It works if Y⊥D|Z ,which means a reason is required that justifies a random sampling at agiven stage.

2 Social Experiments

No selection bias : Data are collected such that individuals arerandomly assigned to the treated group or to the control group,randomization. Average differences reflect only programs effects.Would the effect be similar in the“real”world ?



Before-After Estimator

Compares the average responses of the persons treated before and aftertheir participation to the program.

Let Y TA be the realization of the treatment after (A). Y C

A is notobserved.The gain is defined as E

(Y T

A − Y CA |X ,D = 1

).

With individual data, we observe Y TB , the realization of the outcome

on the treated population before (B) the treatment.Identifying hypothesis : E

(Y C

A − Y CB |X ,D = 1

)= 0,

E�Y T

A − Y CA |X , D = 1

�= E

�Y T

A |X , D = 1�− E

�Y C

A |X , D = 1�

= E�Y T

A |X , D = 1�− E

�Y C

B |X , D = 1�

= E�Y T

A |X , D = 1�− E

�Y T

B |X , D = 1�

∆BA = Y TA − Y T

BIdentifying hypothesis failures :

No influence of unobserved heterogeneity.Global change of economy is not corrected forAshenfelter’s dip : behavioral change just before the treatments applies.Pierre Cahuc/Sebastien Roux (ENSAE) Labor Market Policies December 12th 2007 33 / 45


Differences-in-differences estimator

Identifying hypothesis :E

(Y C

A − Y CB |X ,D = 1

)= E

(Y C

A − Y CB |X ,D = 0

)Hence

E�Y T

A − Y CA |X , D = 1

�= E

�Y T

A − Y TB |X , D = 1

�− E

�Y C

A − Y CB |X , D = 1

�

= E�Y T

A − Y TB |X , D = 1

�− E

�Y C

A − Y CB |X , D = 0

�

Estimator : ∆DD =(Y T

A − Y TB

)−

(Y C

A − Y CB

)Advantage : insensitive to changes in the global state of the economy.

But assumes“the common-trend assumption”, i-e trends affectingparticipants and non-participants are identical. Ex : Ashenfelter’s dip,Ok if appears for treated and non-treated, but this is not always thecase...



Cross-section estimator

Identifying hypothesis : E(Y C

A |X ,D = 1)

= E(Y C

A |X ,D = 0)

The estimator simply deduces : ∆CC = Y TA − Y C

A

Does not require“common-trend assumption”, not sensitive toAshenfelter’s dip.

However, not satisfied if the selection of individuals does not respectthe randomization condition. Very few chances to be verified withnon-experimental data.

Very often used in social experiments.



Evaluation of the effects of payroll tax subsidies for lowwage workers

Crepon and Desplatz (Economie et Statistique, 2001)

Active labor policy : aims at decreasing the unemployment ofunskilled workers.

Unskilled workers are defined w.r.to their jobs. Automatic distinctionfor blue-collar workers, reconstructed for white-collar workers.

Some stylized facts :

In 2001, 22% or workers in the Private sector occupy unskilled jobs.60% are occupied by women.30% are part-time jobs.Over-representation of under-30 old workers.

Idea of the payroll tax subsidy : the decrease of the cost at low wagelevel should induce firms to create low-wage jobs, thus hire unskilledworkers, without diminishing the minimum wage.



Relative position of the minimum wage relative to medianwage

50 ,0 0 %

55,00 %

6 0 ,0 0 %

6 5,0 0 %

76 78 8 0 8 2 8 4 8 6 8 8 9 0 9 2 9 4 9 6 9 8

Co ût du SMIC/Coût du salaire méd ian SMIC net/Salaire net méd ian



Payroll tax subsidies from 1993 to 1998



Firms Heterogeneity

Treatment variable : level of subsidy.

Mandatory measure, all firms are“treated”.

But some are“more treated” than others

For instance firms with more low-wage workers have greater subsidies.From wages wi ,j ,94 observed for employee i in the firm j in 1994,reconstruction of the subsidy the firm would have been granted,should the measure had been applied in 1994. Let Tyear the taxscheme applied at year year

ci,j,94 (T94) =�1 + T94

�wi,j,94

��wi,j,94

ci,j,94 (T97) =�1 + T97

�wi,j,94

��wi,j,94

For all firms, ex ante cost reduction writes :

tj =

Pi∈j

��ci,j,94 (T97) − ci,j,94 (T94)��

Pi∈j

ci,j,94 (T94)



Heterogeneity of Cost Reductions between firms



Choice of the contrast variables

Basic framework : ∆yj = g (xj , tj) + uj

Causal effect of the measure applied to a firm j :ej = g (xj , tj)− g (xj , 0)

Effect of a marginal increase of cost reduction :

E1 =∑

j

ω∂g (xj , tj)

∂t

where ωj is the weight of firm j .

Global effect of the measure :

E2 =∑

j

ω (∆yj − g (xj , 0))



Estimation Method

Rosenbaum Rubin (1983) property : Instead of xj , effects can dependon the score s (xj) (dimensionality reduction).The score (interpreted as the predictive probability to be treated as afunction xj) can be estimated from the regression of h(t) on x whereh(.) is the logistic transformation.R2 around 0.5. It remains enough variability that will be interpretedas a“randomization”.

g (s, t) and ∂g∂t (s, t) are non-parametrically estimated. Projection on

orthonormal polynomials separately defined on t and s.



Data and Variables of interest

Data

DADS(individual wages, employment,...)Fiscal data (added value, capital,..)

Variables :

EmploymentMean labor costShare of unskilled workersCapital intensityAdded Value



Main Results

Marginal Effect Global EffectVariables Manufacturing Services Manufacturing ServicesEmployment 3,3 5,16 2,62 3,44

( 0,82 ) ( 0,68 ) ( 0,8 ) ( 0,78 )Mean labor cost -4,37 -6,4 -3,1 -4,36

( 0,69 ) ( 0,58 ) ( 0,48 ) ( 0,86 )Share of unskilled 0,71 0,73 0,69 0,69

( 0,49 ) ( 0,34 ) ( 0,3 ) ( 0,34 )Capital intensity -1,58 -2,21 -1,41 -1,61

( 1,08 ) ( 0,97 ) ( 0,66 ) ( 0,84 )Production unit cost -3,29 -5,37 -2,44 -3,48

( 0,63 ) ( 0,51 ) ( 0,43 ) ( 0,7 )Added value 2,61 4,65 1,94 3,19

( 1,01 ) ( 0,81 ) ( 0,63 ) ( 0,74 )



Summary of the results

Marginal increases give estimates of elasticities.

Applying the estimates of the global effects to the whole populationof firms, relative increase (or non-decrease) of 460 000 jobs in firmswho benefited from the payroll tax subsidies, half of themcorresponding to unskilled jobs.

Some limits :

Very imprecise measure.The estimation holds on a very selected sample of firms (90000).External validity ?Nothing about the effect of financing this measure.


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