Unemployment Insurance Eligibility and the Duration …...Introduction I Contribution1.a:WeestimatetheimpactofUIonon-the-jobbehaviours (OrtegaandRioux,2010;HopenhaynandNicolini,2009;Andersenetal.,

Unemployment Insurance Eligibility and the Duration ofEmployment

Laura Khoury, Clément Brébion, Simon Briole

31 mai 2019

Khoury, Brébion Unemployment Insurance Eligibility and the Duration of Employment 31 mai 2019 1 / 32

Motivation

Figure – Evolution of the share and length of fixed-term contracts

Source : DARES.


Introduction

Potential effect of UI on employment relationships :I Affects the labour supply decision of workers by changing their outside option

I Affects the value of short-term contracts for workers

In this paper :

→ Impact of the minimum employment history condition to be eligible to UIbenefits→ Use of the 2009 French reform which changed this condition.


Introduction

1 Do employers and employees respond to the increase in UI value byseparating more at the eligibility threshold ?

n Through increasing flows to unemploymentn Through shorter contracts after the reform

2 Does receiving UI benefits affect future employment prospects ?


Introduction

I Contribution 1.a : We estimate the impact of UI on on-the-job behaviours(Ortega and Rioux, 2010; Hopenhayn and Nicolini, 2009; Andersen et al.,2015)(Rebollo-Sanz, 2012; Van Doornik et al., 2018; Albanese et al., 2019;Martins, 2016)

I Contribution 1.b : Both at the micro and macro levels


Introduction

I Contribution 2 : extensive margin impact of UI benefits both on short- andlong-run outcomes(Landais, 2015; Lalive et al., 2006; Chetty, 2006; Schmieder andVon Wachter, 2016)(Davezies and Le Barbanchon, 2017)

I Contribution 3 : document the effect on job quality while still an on-goingdebate(Nekoei and Weber, 2017; Card et al., 2007; Schmieder et al., 2013; Lalive,2007; Van Ours and Vodopivec, 2008)

→ Comprehensive analysis of flows both in and out of employment


Institutional background and data

Table of Contents

1 Institutional background and data

2 Empirical evidence on employment outflowsSeparation responseContract duration

3 Empirical evidence on unemployment outflows

4 Conclusion



Institutional background

Contributory UI schemes characterised by :

I UI benefits and contributions proportional to past earnings

I Potential benefit duration (PBD) proportional to work history

I Eligibility depends on a minimum employment record → focus of the paper




Contributory UI schemes characterised by :

I UI benefits and contributions proportional to past earnings

I Potential benefit duration (PBD) proportional to work history

I Eligibility depends on a minimum employment record → focus of the paper




Reform on April, 1st , 2009 :

Table – Pre and Post reform rules

Minimum employment record Potential benefit durationPre-reform 6 months over the last 22 months Different categories according to work historyPost-reform 4 months over the last 28 months 1 to 1 relationship up to 2 years



Data

I FH-DADS : linked employer-employee dataset matched with UI data for apanel of individuals (1/12th) between 2003-2012

I DADS built at the individual × establishment × year level (’position’)

I FH only available for claimants

I Work history variable built from DADS→ 75% match between FH and DADS

I Sample restrictions : remove workers ever observed as a civil servant orhome-employed for a private employer

I 2,690,114 individuals accounting for 18,114,742 positions ending between2004 and 2012 and 3,071,283 corresponding UI spells


Empirical evidence on employment outflows

Table of Contents




4 Conclusion


Empirical evidence on employment outflows Separation response

Separation response - Unemployment inflows

I Analysis of the separation response at the micro level

I Definition of Panel 1 :n Random subsample of 100,000 individualsn Positions converted into biweekly spells starting from the 1st job after thereform over 2 years

n Measure of the transitions from employment to registered UI and tonon-employment




Figure – Probability to go from employment to registeredunemployment Reg

Source : FH-DADS.Khoury, Brébion Unemployment Insurance Eligibility and the Duration of Employment 31 mai 2019 13 / 32



Figure – Probability to go from employment to non-employment

Source : FH-DADS.




I Both graphs could be rationalised by a change in registration behaviour

I Yet :n Transitions E → UI small share of all transitions E → NEn Cannot distinguish layoffs from quitsn Evidence from other countries (Albanese et al., 2019; Rebollo-Sanz, 2012) andfrom France (Khoury, 2019) point to strategic separation behaviours

n Complementary findings on MMO




P(layoff )it = α+ β114monthsit + β2Postt + β314monthsit × Postt + uit

Probability of being laid-off Probability to end a fixed-term contract Probability to quit

Eligible=1 0.00012 0.00012 -0.00582*** -0.00598*** 0.00036* 0.00033*(0.000116) (0.000117) (0.000451) (0.000452) (0.000195) (0.000196)

Post=1 -0.00010 -0.00015 0.00179*** 0.00011 0.00054*** 0.00047(0.000116) (0.000215) (0.000451) (0.000829) (0.000195) (0.000360)

Eligible=1 × Post=1 0.00041** 0.00041** 0.00622*** 0.00798*** -0.00007 -0.00001(0.000171) (0.000173) (0.000664) (0.000670) (0.000288) (0.000291)

Month FE - yes - yes - yesConstant 0.00090*** 0.00075*** 0.01594*** 0.02096*** 0.00240*** 0.00195***

(0.000081) (0.000146) (0.000314) (0.000565) (0.000136) (0.000245)Observations 546535 546535 554500 554500 547528 547528* p<0.05, ** p<0.01, *** p<0.001. Standard errors in parentheses.The treatment (respectively control) group is made of individuals ending their contract between 4 and 5 months (resp. 3 and 4 months).The time window corresponds to 6 months before and after the reform.


Empirical evidence on employment outflows Contract duration

Contract duration

I Employers may internalise the jump in the value of unemployment at thetime of hiring

I Triple advantage of contracts scheduled to qualify workers for benefits :n They ease adjustments of the workforce to the variation in business activitywith a limited decrease in attractiveness of contracts

n Implicit contract theory : employers and employees may agree to share therent from UI through lower wages (Feldstein, 1976; Baily, 1977)

n If systematic enough, employers’ recalling behaviours can ensure investment infirm-specific human capital without bearing the cost of high employmentprotection



Contract duration

I We analyse the evolution of the duration of contracts at the aggregate level

I Data : the set of last contracts used to open UI entitlements.n From which we remove workers registering with a work history between 4 and6 months



Contract duration

Figure – Share of contracts among contracts of 1 year or less (allseparations) Reg

.02

.04

.06

.08

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2

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port

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ontr

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equal to

or

less than 1

year

2004 2006 2008 2010 2012 2014

1 to 2−monthcontracts






Contract duration

Figure – Share of contracts among contracts of 1 year or less (end offixed-term contract)

0.0

5.1

.15

Pro

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ontr

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equal to

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2004 2006 2008 2010 2012 2014







Contract duration

Figure – Share of contracts among contracts of 1 year or less (otherdismissals)

0.0

5.1

.15

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port

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ontr

acts

equal to

or

less than 1

year

2004 2006 2008 2010 2012 2014






Empirical evidence on unemployment outflows

Table of Contents




4 Conclusion



Impact on unemployment outflows - Methodology

I Qualifying for benefits 2 months sooner may affect decisions regardingemployment

I Separation response makes it hard to study the extensive margin impact of UIbenefits on U outcomes

I Further sample restrictions and use of the reformn Workers with 4months ≤ work history ≤ 6months before (controls) and after(treated) the reform

n Under a fixed-term contract that started before the reformn Fuzzy RDD around the time threshold of the reform on 23,559 observations



Impact on unemployment outflows - Methodology

Assumption to be checked :

I No disproportionately high number of contracts ≤ 4 months starting beforethe reform and ending right after Graphs

I McCrary test (McCrary, 2008) Graph

I Continuity of the covariates Graph



Impact on unemployment outflows - 1st stage

Figure – Probability of opening a UI right Reg

0.00

0.10

0.20

0.30

0.40

Bein

g r

egis

tere

d to U

I

−1.00 0.00 1.00

Ending date of the contract

Upper and Lower 95% interval Predicted Within−bin mean

Binsize: .03, Number of observation: 23559



Impact on employment probability

Figure – Impact of UI eligibility on employment probability 6 monthsafter Reg

0.30

0.40

0.50

0.60

0.70

Pro

babili

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f bein

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−1.00 0.00 1.00


Upper and Lower 95% interval Predicted Within−bin mean

Binsize: .03, Number of observation: 23559



Impact on employment path

Table – Impact of UI benefit receipt on the number ofemployment spells over the following two years

Number of employment spells over the following 2 yearsLinear Quadratic Cubic

RD_Estimate -9.795** -9.298* -9.336(4.076) (5.059) (6.296)

Observations 23559 23559 23559

* p<0.05, ** p<0.01, *** p<0.001. Standard errors in parentheses.The bandwidth has been computed using the MSE optimal bandwidth selector. Linear, quadratic andcubic specifications.The dependant variable corresponds to the number of employment spells over the two years followingthe end of the contract that defines the treatment status.



Impact on employment path

Table – Impact of UI benefit receipt on the total numberof days employed over the following two years

Total number of days employed over the following 2 yearsLinear Quadratic Cubic

RD_Estimate -1027.132* -737.503 -1084.775(566.452) (739.947) (837.905)

Observations 23559 23559 23559

* p<0.05, ** p<0.01, *** p<0.001. Standard errors in parentheses.The bandwidth has been computed using the MSE optimal bandwidth selector. Linear, quadratic andcubic specifications.The dependant variable corresponds to the total number of days employed over the two years followingthe end of the contract that defines the treatment status.



Impact on job quality

Table – Summary of the results on job quality

Unconditionally Conditionally Lee boundsShort-term Medium-term Long-term Next contract Short-term Medium-term Long-term

Permanent contract (-) - (-) (+) (+) n.s. n.s.Full-time - (-) n.s. (-) n.s. n.s. n.s.Wage n.s. (-) - - n.s. n.s. n.s.Duration - - - (-) n.s. n.s. n.s.Matching - n.s. n.s. n.s. n.s. n.s. n.s.

A single + or - means that the result is significant and of the indicated sign. A (+) or (-) in parentheses means that there is a strong pattern of the effectgoing in the indicated direction but coefficients are not significant.


Conclusion

Table of Contents




4 Conclusion


Conclusion

Conclusion

I Comprehensive evaluation of the 2009 reform affecting the eligibility criterionto UI benefits

I Suggestive evidence of :n A strategic separation response at the eligibility thresholdn May contribute to the increase in short-term contracts at the aggregate level

I One of the first empirical evidence on the effect of receiving any UI benefits :n Strong and long-lasting neg. impact on employment probabilityn Evidence of neg. impact on earningsn Less clear-cut results on job quality


Conclusion

Appendix


Table – Discontinuity in the transition rate fromemployment to registered unemployment Graph

Transition E → UI probabilityLocal Quadratic Cubic

RD_Estimate 0.008*** 0.007*** 0.010***(0.001) (0.001) (0.001)

Observations 1270880 1270880 1270880

* p<0.05, ** p<0.01, *** p<0.001. Standard errors in parentheses.The regression shows in a regression discontinuity design spirit the discontinuity in thebiweekly transition rate from employment to UI. The running variable is the work historyover the last 28 months and the cutoff value is 4 months. Bandwidth has been computedusing the mean squared error (MSE) optimal bandwidth selector with a linear specification.


Table – Post-reform evolution of 4 to 5-month contracts(6-month and 1 to 3-month control group) Graph

Proportion among contracts ≤1 year Proportion among contracts ≤1 yearPost=1 -0.00515*** -0.00500***

(0.0000395) (0.0000549)4 to 5-month contracts=1 -0.06441*** -0.06436***

(0.0000649) (0.0001418)Post=1 × 4 to 5-month contracts=1 0.01470*** 0.01451***

(0.0000811) (0.0001751)Constant 0.08778*** 0.08758***

(0.0000298) (0.0000414)Observations 122867 299939

* p<0.05, ** p<0.01, *** p<0.001. Standard errors in parentheses.The first specification shows the difference in the evolution of the shares of 4-month and 6-month contracts. Thesecond specification compares 4-month contracts to contracts between 1 and 3 months.


Figure – Share of 1 to 30-day contracts among contracts of 1 year orless Back

.1.2

.3.4

.5.6

Pro

port

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of 1 y

ear

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less

01jan2009 01mar2009 01may2009 01jul2009 01sep2009


2009 2010

2011

Source : FNA.


Figure – Share of 31 to 60-day contracts among contracts of 1 year orless

.05

.1.1

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of 1 y

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less



2009 2010

2011

Source : FNA.



.05

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2009 2010

2011

Source : FNA.



.05

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2009 2010

2011

Source : FNA.


Figure – Share of 121 to 150-days contracts among contracts of 1 yearor less

0.0

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.2.2

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2009 2010

2011

Source : FNA.


Figure – Mc Crary test contract ending date distribution Back

Source : FH-DADS.The running variable, ending date of the contract, has been normalised around the time threshold to beequal to be equal to 0 at the threshold, -1 six months before, and +1 six months after.


Figure – Mc Crary test contract ending date distribution

Source : FH-DADS.The running variable, ending date of the contract, has been normalised around the time threshold to beequal to be equal to 0 at the threshold, -1 six months before, and +1 six months after.


Figure – Histogram of the contract ending date frequencies

Source : FH-DADS.The running variable, ending date of the contract, has been normalised around the time threshold to beequal to be equal to 0 at the threshold, -1 six months before, and +1 six months after. The bin size isequal to 0.02.


Figure – Magnitude of the difference in covariates at the cutoff Back

−50 0 50 100

Gender Education

Wage Fulltime

Establishment size

The three levels of significance of the confidence intervals depicted are 5%, 1% and 0.1%.


Table – Impact of separating after the reform on UItakeup Back

Being registered to UILinear Quadratic Cubic

RD_Estimate 0.069*** 0.061** 0.058**(0.021) (0.024) (0.024)

F-stat 72.64 46.38 21.14Observations 23559 23559 23559

Bandwidth has been computed using the mean squared error (MSE) optimal bandwidthselector.Standard errors in parentheses.


Table – Impact of UI benefits receipt on employmentprobability (1-4 months) Back

Probability of beingemployed 1 months

after


after


after


afterRD_Estimate 0.023 0.019 -0.536 -0.902*

(0.556) (0.495) (0.426) (0.488)Observations 23559 23559 23559 23559

* p<0.05, ** p<0.01, *** p<0.001. Standard errors in parentheses.The bandwidth has been computed using the MSE optimal bandwidth selector. Linear specification.The dependant variable corresponds to the probability of being employed at different time horizons after the end ofthe contract that defines the treatment status.


Table – Impact of UI benefits receipt on employmentprobability (5-8 months)


after


after


after


afterRD_Estimate -0.895* -1.068** -1.020** -1.141***

(0.492) (0.494) (0.469) (0.342)Observations 23559 23559 23559 23559





after

Probability of beingemployed 10months after



RD_Estimate -0.376 -0.949** -0.978** -0.695(0.381) (0.453) (0.455) (0.438)

Observations 23559 23559 23559 23559








RD_Estimate -0.641 -0.719 -0.684 -0.772*(0.453) (0.446) (0.435) (0.438)

Observations 23559 23559 23559 23559








RD_Estimate -0.779* -0.979** -0.940** -1.064**(0.461) (0.480) (0.453) (0.486)

Observations 23559 23559 23559 23559








RD_Estimate -1.108** 0.069 0.079 0.048(0.444) (0.437) (0.428) (0.424)

Observations 23559 23559 23559 23559



Albanese, Andrea, Corinna Ghirelli, and Matteo Picchio, “Timed to saygoodbye : Does unemployment benefit eligibility affect worker layoffs ?,” 2019.

Andersen, Torben M, Mark S Kristoffersen, and Michael Svarer, “BenefitReentitlement Conditions in Unemployment Insurance Schemes,” 2015.

Baily, Martin Neil, “On the theory of layoffs and unemployment,”Econometrica : Journal of the Econometric Society, 1977, pp. 1043–1063.

Card, David, Raj Chetty, and Andrea Weber, “The spike at benefitexhaustion : Leaving the unemployment system or starting a new job ?,”American Economic Review, 2007, 97 (2), 113–118.

Chetty, Raj, “A general formula for the optimal level of social insurance,” Journalof Public Economics, 2006, 90 (10), 1879–1901.

Davezies, Laurent and Thomas Le Barbanchon, “Regression discontinuitydesign with continuous measurement error in the running variable,” Journal ofEconometrics, 2017, 200 (2), 260–281.

Doornik, Bernardus Nazar Van, David Schoenherr, and Janis Skrastins,“Unemployment Insurance, Strategic Unemployment, and Firm-WorkerCollusion,” 2018.

Feldstein, Martin, “Temporary layoffs in the theory of unemployment,” Journalof political economy, 1976, 84 (5), 937–957.

Hopenhayn, Hugo A and Juan Pablo Nicolini, “Optimal unemploymentinsurance and employment history,” The Review of Economic Studies, 2009, 76(3), 1049–1070.

Khoury, Laura, “Unemployment Benefits and the Timing of Redundancies :Evidence from Bunching,” 2019.

Lalive, Rafael, “Unemployment benefits, unemployment duration, andpost-unemployment jobs : A regression discontinuity approach,” AmericanEconomic Review, 2007, 97 (2), 108–112., Jan Van Ours, and Josef Zweimüller, “How changes in financial incentivesaffect the duration of unemployment,” The Review of Economic Studies, 2006,73 (4), 1009–1038.

Landais, Camille, “Assessing the welfare effects of unemployment benefits usingthe regression kink design,” American Economic Journal : Economic Policy,2015, 7 (4), 243–278.

Martins, Pedro S, “Working to get fired ? Regression discontinuity effects ofunemployment benefit eligibility on prior employment duration,” 2016.

McCrary, Justin, “Manipulation of the running variable in the regressiondiscontinuity design : A density test,” Journal of Econometrics, 2008, 142 (2),698–714.

Nekoei, Arash and Andrea Weber, “Does Extending Unemployment BenefitsImprove Job Quality ?,” American Economic Review, 2017, 107 (2), 527–61.

Ortega, Javier and Laurence Rioux, “On the extent of re-entitlement effects inunemployment compensation,” Labour Economics, 2010, 17 (2), 368–382.

Ours, Jan C Van and Milan Vodopivec, “Does reducing unemploymentinsurance generosity reduce job match quality ?,” Journal of Public Economics,2008, 92 (3), 684–695.

Rebollo-Sanz, Yolanda, “Unemployment insurance and job turnover in Spain,”Labour Economics, 2012, 19 (3), 403–426.

Schmieder, Johannes F and Till Von Wachter, “The effects of unemploymentinsurance benefits : New evidence and interpretation,” Annual Review ofEconomics, 2016, 8, 547–581., , and Stefan Bender, “The causal effect of unemployment duration onwages : Evidence from unemployment insurance extensions,” Technical Report,National Bureau of Economic Research 2013.


Documents

Unemployment Insurance Eligibility and the Duration …...Introduction I Contribution1.a:WeestimatetheimpactofUIonon-the-jobbehaviours (OrtegaandRioux,2010;HopenhaynandNicolini,2009;Andersenetal.,