Finance and Economics Discussion Series Divisions of Research & Statistics and Monetary Affairs Federal Reserve Board, Washington, D.C.

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1 Finance and Economics Discussion Series Divisions of Research & Saisics and Moneary Affairs Federal Reserve Board, Washingon, D.C. The Effecs of Unemploymen Benefis on Unemploymen and Labor Force Paricipaion: Evidence from 35 Years of Benefis Exensions Andrew Figura and Regis Barnichon NOTE: Saff working papers in he Finance and Economics Discussion Series (FEDS) are preliminary maerials circulaed o simulae discussion and criical commen. The analysis and conclusions se forh are hose of he auhors and do no indicae concurrence by oher members of he research saff or he Board of Governors. References in publicaions o he Finance and Economics Discussion Series (oher han acknowledgemen) should be cleared wih he auhor(s) o proec he enaive characer of hese papers.

2 The Effecs of Unemploymen Benefis on Unemploymen and Labor Force Paricipaion: Evidence from 35 Years of Benefis Exensions Regis Barnichon CREI, Universia Pompeu Fabra and CEPR Andrew Figura Federal Reserve Board Augus 2014 Absrac This paper presens esimaes of he effec of emergency and exended unemploymen benefis (EEB) on he unemploymen rae and he labor force paricipaion rae using a daa se conaining informaion on individuals likely eligible and ineligible for EEB back o he lae 1970s. To idenify hese esimaes, we examine how exi raes from unemploymen change across differen poins of he disribuion of unemploymen duraion when EEB is and is no available, conrolling for changes in labor demand and demographic characerisics. We find ha EEB increased he unemploymen rae by abou one-hird percenage poin in he mos recen recession bu did no affec he paricipaion rae. In previous recessions, he effec of EEB on he unemploymen rae was even smaller. JEL classificaions: J6, E24. *We hank Yanos Zylberberg for helpful commens. The views expressed here do no necessarily reflec hose of he Federal Reserve Board or of he Federal Reserve Sysem. We hank Devin Saiki for excellen research assisance. 1

3 1. Inroducion During he recession, U.S. unemploymen insurance (UI) benefis were exended o unprecedened levels, wih UI duraion increasing from 26 weeks he regular duraion o as much as 99 weeks in some saes, promping a lively debae in policy and academic circles abou he adverse effecs of such exensions on he search behavior of job seekers and hus on he unemploymen and labor force paricipaion raes. 1 While recen sudies have focused on he exension of UI benefis during he recen crisis, he exension of benefis is no specific o he recession. In fac, he duraion of UI benefis was increased in all recessions since he mid-70s. In his paper, we exploi daa on such UI benefis exensions going back o he mid-70s o esimae he effec of UI duraion exension, also called Emergency and Exended unemploymen Benefis (EEB), on he labor marke, and more specifically he unemploymen and paricipaion raes. We idenify he effecs of EEB from variaions in he exi raes ou of unemploymen across similar individuals as EEB availabiliy changes, conrolling for he sae of he business cycle. Imporanly, we allow individuals wih differen unemploymen duraion o reac differenly o he availabiliy of EEB. We hen develop a mapping of our esimaes of he effec of EEB on unemploymen exi raes ino esimaes of he effec of EEB on unemploymen and labor force paricipaion, and we find ha EEB increased he unemploymen rae by one-hird percenage poin in he mos recen episode and had hardly any effec on he paricipaion rae. To idenify he effecs of EEB, we consider individuals wih similar observable characerisics wih differen lenghs of unemploymen spells across periods and saes where EEB is and is no available. We find ha EEB reduces subsanially he Unemploymen o Employmen (U-E) ransiion rae of individuals receiving or abou o receive EEB by abou percen. The effecs of EEB on he Unemploymen o Nonparicipaion (U-N) ransiion rae are smaller and more uncerain, and only individuals receiving EEB benefis appear o be affeced, wih heir U- N rae falling by abou 7 percen. Imporanly however, we find ha EEB has lile adverse effec on exi raes for individuals wih less han 20 weeks of unemploymen or for individuals wih unemploymen duraion above he maximum duraion of EEB. To map our esimaes of he effec of EEB on unemploymen exi raes ino esimaes of he effec of EEB on unemploymen and labor force paricipaion, we use a firs order approximaion of seady sae unemploymen and labor force paricipaion raes (Shimer, 2012) o decompose he unemploymen and he labor force paricipaion raes ino linear funcions of hazard raes of ransiions across labor force saes. 1 See e.g., Farber and Vallea (2013), Rohsein (2011), Bradbury (2014), Mazumder (2010), Fujia (2011), and Nakajima (2012). 2

4 Despie sizable effecs of EEB on he exi rae of job seekers receiving or abou o receive EEB, we find ha EEB increased he unemploymen rae by only one-hird percenage poin in he mos recen episode and had hardly any effec on he paricipaion rae. The effecs in previous recessions were even smaller. Our ransparen mapping of he effecs of EEB on unemploymen, ogeher wih our esimaes of how EEB affecs differen individuals wih differen unemploymen duraions, enable us o undersand why he effecs of EEB are relaively modes. The main reason is ha EEB only affecs eligible individuals wih relaively long unemploymen duraions (greaer han 18 weeks), and such individuals represen a relaively small fracion of he unemploymen populaion (even in he recen recession where unemploymen duraion reached record highs, heir share sood only a abou 25 percen). In conras, mos of he unemployed are eiher simply ineligible for unemploymen insurance (around 40 percen of he unemployed in recessions are non job losers), or, if eligible (job losers), respond lile o he availabiliy of EEB because hey have eiher no been unemployed for very long (abou one-hird of he unemployed) or have duraions above he maximum duraion of EEB (a lile over 5 percen of he unemployed). Regarding he paricipaion rae, he effec is very small because (i) he average U-N rae is only modesly affeced by EEB, and (ii) he average UE rae (which is somewha affeced by EEB) has only an indirec (and hus modes) effec on he paricipaion rae. 2 Our paper relaes o a large lieraure on he effecs of Unemploymen Insurance on job seekers' unemploymen duraion. We conribue o he lieraure in several ways. Firs, our idenificaion sraegy allows us o clearly undersand why he effec of EEB on he aggregae unemploymen rae has been esimaed o be small (Fujia, 2011, Farber and Vallea 2013, Rohsein 2011), despie evidence ha exensions of unemploymen insurance do have a subsanial effec on individuals' exi rae (Meyer 1990). Our idenificaion sraegy is similar o sraegies used recenly in he lieraure Farber and Vallea (2013) and Rohsein (2011) and our esimaes of he effec of EEB on he unemploymen rae are consisen. However, we rely on a dimension of he daa (differences in effec by duraion) no fully exploied previously, which allows us o esimae he effec of EEB for individuals across he whole specrum of unemploymen duraions. As explained previously, we esimae ha benefis exensions do have a subsanial effec on an individual's exi rae, bu only on individuals receiving or abou o be receiving exended benefis. Tha laer esimae is he key o undersand he small aggregae effecs of EEB. Second, we consruc a daa se ha uses informaion on eligibiliy for exended and federal benefis across saes and ime and mach his wih individual CPS daa on labor force ransiions 2 Movemens in he job finding rae have an effec on he paricipaion rae because of a composiion effec: Unemployed workers are much more likely o leave he labor force han employed workers. By raising he number of unemployed workers relaive o he number of employed workers, a lower job finding rae increases he number of individuals who leave he labor force, and he paricipaion rae goes down. 3

5 back o Our daa se enables us o boh compare he effecs of EEB across differen episodes and show how EEB has affeced cyclical movemens in he unemploymen rae over ime. Because our daase spans several recessions, we can conras our findings wih hose of an earlier, influenial, lieraure which esimaed he effecs of EEB from recessions in he 1970s and 1980s, e.g. Meyer (1990) and Moffi and Nicholson (1982). Two conclusions sand ou. Firs, he effec of EEB on unemploymen exi raes has been generally sable over ime, allowing us o compare curren esimaes o sudies of EEB in he 1970s and 1980s. Second, while previous sudies sugges much larger effecs han we esimae Meyer (1990) and Moffi and Nicholson (1982), and Nakajima, (2011) we argue ha exrapolaing esimaes from sudies of previous episodes o calibrae EEB effecs in he mos recen episode can be misleading, because, unlike wha is ypically assumed, individuals nearing he exhausion of regular UI benefis behave very differenly from individuals who have exhaused heir benefis. As a resul, calibraions of EEB effecs based on esimaes such as hose in Meyer (1990) ha assume ha individuals abou o exhaus benefis are similar o hose who have exhaused heir benefis can subsanially overesimae he effec of EEB. Third, he paper proposes a mehod o easily and ransparenly map he effec of EEB on unemploymen hazard raes ino he effec of EEB on unemploymen. The ease and ransparency of our approach allows us o compare our resuls o oher esimaes and accoun for differences. Finally, we esimae he effec of EEB on he labor force paricipaion rae, a opic no addressed in previous papers. The nex secion describes our daa and mehod of idenificaion. The hird secion presens esimaion resuls. The fourh secion maps hese resuls o esimaes of he effec of EEB on he unemploymen and labor force paricipaion raes. The fifh secion compares resuls o ohers in he lieraure, and he sixh secion concludes. 2. Daa and Idenifying he Effec of EEB Daa To esimae he effec of EEB on unemploymen and labor force paricipaion, we combine wo daa ses; (i) a newly creaed daase conaining informaion on he maximum duraion of regular UI benefis and EEB benefis by sae and monh over , and (ii) he CPS conaining informaion on individuals characerisics and labor force saus across consecuive monhs as well as he unemploymen duraion of job seekers. To consruc daa on he maximum duraion of regular UI benefis and EEB by sae and monh, we compiled records published by he Employmen and Training Adminisraion (ETA). Our daa conain informaion on he maximum allowable duraion of combined EEB and regular UI benefis in a sae in each monh from 1976 hrough The appendix conains deails on UI laws ha have provided for emergency and exended unemploymen insurance benefis. 4

6 Specificaion We posi ha he probabiliy of ransiing from unemploymen o employmen (or o ou of he labor force) depends on he characerisics of an individual i a ime, X i, and on he person s eligibiliy for exended unemploymen benefis,. j i, i, i, y f X, ;, j U E, U N (1) UE where y i,, for example, equals 1 if an individual ransiions from unemploymen (U) o nonparicipaion (E) and 0 oherwise, and is a vecor of aggregae parameers, capuring for insance aggregae labor demand condiions. Equaion (1) can be derived from a simple model ha relaes he decision of wheher o search for employmen or no o he benefis and coss of searching versus no searching. 3 EEB, by providing a paymen o searchers, is generally prediced o increase search on he exensive margin (i.e. reduce he hazard from unemploymen o nonparicipaion), bu also o raise reservaion wages and, hus, reduce he hazard from unemploymen o employmen. When EEB benefis are available (ypically during and/or immediaely afer a recession), jobless individuals become eligible for EEB afer hey have exhaused heir regular UI benefis. Thus, o disinguish beween individuals who are eligible for EEB and individuals who are no, i.e, τ i =0 or τ i =1, we combine informaion on individuals unemploymen duraion wih informaion on he availabiliy of EEB in a given sae a ime. We se τ i =1 (EEB available) when he oal lengh of benefis duraion (including EEB and regular benefis) exceeds he unemploymen duraion of an individual. Idenificaion of he effec of EEB To esimae he effec of EEB on an individual s exi rae from unemploymen, we would ideally observe he same person under he same circumsances wice: once when he person is eligible for EEB and once when he person is no, and esimae he EEB effec as he difference in exi behavior i i,, i, 1; i,, i, 0; f X f X Because such daa are no available, we insead compare differen individuals, some who are eligible for EEB and ohers who are no, while also conrolling as bes we can for he effec of individuals characerisics (as well as aggregae labor demand condiions ) on heir probabiliy of exiing unemploymen. Specifically, we esimae (2) 3 See, for example, Morensen (1977) or Rohsein (2011). 5

7 i,, i, 1; i,, i, 0; f X f X in1 in2 (3) where N 1 denoes individuals for whom EEB are available and N 2 denoes individuals for whom EEB are no available. We conrol for individual characerisics and aggregae labor demand condiions in several ways. Firs, we only include permanen job losers in our sample, hus limiing i o a relaively homogenous group. We include only job losers because in mos saes, one mus have had a prior job and been laid off from ha job o be eligible for unemploymen benefis. 4 This excludes job quiers and enrans o he labor force. We also exclude individuals who are 20 years old or younger because, given he low employmen rae and high ransiions raes ou of employmen for his group, i is unlikely ha his group will have high eligibiliy raes for unemploymen insurance benefis. We also exclude emporary job losers. Because six monhs is he ypical maximum duraion of regular UI benefis, individuals on emporary layoff, who expec o be recalled o heir former job wihin 6 monhs, may be less likely o be affeced by he availabiliy of EEB han permanen job losers. 5 In he appendix, we presen esimaes of he effec of EEB on emporary job losers and show i is quie similar o he effec on permanen job losers. Second, we include several demographic variables in X i, including gender, marial saus, age, educaion, occupaion, former indusry of employmen, and sae of residence. Anoher crucial characerisic of individuals ha affecs he propensiy o exi is he duraion of unemploymen. Specifically, as a spell lengh increases, he propensiy o exi o employmen declines, and he propensiy o exi he labor force generally increases. 6 I is imporan o conrol for he endency for exi hazards o change wih duraion so as no o confuse his effec wih ha of EEB. We do his by allowing duraion o affec exi hazards non-paramerically. 4 Farber and Vallea (2013) mach individuals idenified as job losers in he monhly CPS wih he same individuals in he subsequen year s March CPS, which asks abou receip of unemploymen benefis. They find a srong correspondence beween job loser saus and subsequen reporing of receip of UI benefis. If job loser saus and eligibiliy for UI benefis are no perfecly correlaed, hen measuremen error may bias our esimaes of he effec of EEB downward if he exen of he discrepancy beween UI eligibiliy and job loser saus is relaed o he cycle, or more specifically o he implemenaion of EEB programs. 5 In addiion, Kaz and Meyer (1990) illusrae ha he evoluion of exi hazards ou of unemploymen can be quie differen for permanen and emporary job losers. 6 The effec of duraion on exi raes may be due o heerogeneiy in exi raes and individuals gradually learning abou heir rue reemploymen prospecs. Under his hypohesis, individuals wih low reemploymen prospecs become a higher fracion of he unemploymen pool a higher duraions, pushing down average exi raes o employmen. Also, if hese individuals learn abou heir relaively poor prospecs, exi raes o ou of he labor force should evenually increase. Alernaively, i could be ha ime spen unemployed, iself, lowers reemploymen prospecs so ha he longer an individual is unemployed, he less likely he will find a job. Realizing his, as an individual s spell of unemploymen increases in lengh, he evenually becomes more likely o drop ou. Finally, i could be ha many individuals who lose a job have very good job marke conacs and find a new job fairly easily. As duraion increases, his ype of individual becomes less prevalen, leading exi raes o employmen o decrease. 6

8 Finally, because EEB ypically becomes available during recessions and becomes unavailable once a recovery is firmly esablished, i is also imporan o conrol for he influence of changes in aggregae economic condiions on he propensiy o exi unemploymen. We do his using he raio of aggregae vacancies o aggregae unemploymen. 7 This measure has been shown by Barnichon and Figura (2013) o be a very good predicor of average exi raes o employmen. In addiion, we conrol for local labor marke condiions by including he unemploymen rae in an individual s labor marke segmen, defined as four broad occupaion groups (producion workers, service workers, sales workers or clerks, and professionals) wihin he 50 saes and he Disric of Columbia. 8 To summarize our idenificaion sraegy, our esimaor of he effec of EEB simply compares he behavior of individuals when EEB is available o he behavior of similar individuals when EEB is unavailable. In order for our esimae o correcly idenify he effec of EEB on unemploymen exi raes, i mus be ha our conrols for aggregae demand and demographic influences are sufficien, so ha he only reason exi raes for likely affeced job losers change beween periods when EEB is available and when i is no available, condiioning on an individual s duraion, is he influence of EEB. 3. Resuls This secion presens our resuls on he effecs of EEB. We find ha EEB reduces he U-E ransiion rae of job losers abou o exhaus regular UI benefis and of job losers receiving EEB benefis by a subsanial percen. The effecs of EEB on he U-N ransiion rae are smaller and more uncerain. Only individuals receiving EEB benefis (group 4) appear o be affeced, wih heir U-N rae falling by abou 7 percen. Preview of resuls Before presening he resuls of he complee specificaion wih conrols for individual characerisics, we firs illusrae he idea behind our idenificaion of he effec of EEB by comparing he unemploymen exi rae by unemploymen duraion when EEB are available wih he unemploymen exi rae when EEB are no available. 7 We use he adjused help waned index compued by Barnichon (2010) as our measure of aggregae vacancies. 8 In he appendix, Table A1 shows he number of observaions and he average characerisics of individuals in he 5 groups when EEB is and is no available. I suggess ha conrolling for demographic characerisics is necessary in order o avoid biasing esimaes of he effec of EEB, as some individual characerisics wihin groups vary across periods when EEB is and is no available. For insance, highly educaed individuals are a much larger share of he unemployed during periods when EEB is available. In addiion, males are more likely o have high duraion unemploymen and his is paricularly rue in periods when EEB is no available. 7

9 Table 1. Caegorizing Permanen Job Losers when EEB is available Characerisics Group Unemploymen duraion Affeced by EEB? 1 less han or equal o 8 weeks No, or small effec 2 3 greaer han 8 weeks, less han 18 weeks greaer han or equal o 18 weeks, less han he maximum allowable duraion of regular UI benefis Maybe Yes 4 Figures 1a and 1b: greaer han he maximum allowable duraion of regular UI benefis, less han 60 weeks. Yes Esimaion: greaer han he maximum allowable duraion of regular UI benefis, less han he maximum allowable duraion of EEB plus regular benefis 5 Figures 1a and 1b: greaer han 60 weeks. No Esimaion: greaer han he maximum allowable duraion of regular plus EEB benefis Figures 1a and 1b illusrae graphically our esimaor of he effec of EEB on job losers unemploymen o employmen ransiion rae, U-E, and on job losers unemploymen o nonparicipaion ransiion rae, U-N. As described in Table 1, we spli unemployed individuals ino 5 groups, deermined by he lengh of heir curren unemploymen spell. Groups 3 and 4 conain individuals who likely receive or may be abou o receive EEB benefis. 9 In conras, groups 1, 2 and 5 conain individuals who are less likely o be affeced by EEB, eiher because hey are early on in heir receip of regular UI benefis and hus unlikely o be significanly 9 Group 4 includes individuals wih unemploymen duraions greaer han he maximum allowable number of weeks of regular UI benefis and less han he maximum allowable duraion of regular plus EEB benefis. Individuals in his group are likely receiving EEB benefis. Group 3 includes individuals wih unemploymen duraions greaer han 18 weeks, i.e., individuals who are less han 8 weeks away from he expiraion of regular UI benefis. Individuals in his group are likely no ye eligible for EEB, bu because hey are nearing he erminaion of heir regular benefis, heir behavior may be affeced by he knowledge ha EEB will be available if heir regular benefis are exhaused. The 18 weeks hreshold is roughly consisen wih Meyer (1990), who finds ha a change in behavior among UI recipiens sars being noiceable six weeks prior o benefis expiraion. 8

10 affeced by he prospec of EEB (groups 1 and 2), 10 or because heir unemploymen duraion exceeds he maximum duraion of EEB (group 5). As noed in Table 1, o aid in he graphical exposiion, in Figures 1a and 1b we simplify he caegorizaion of individuals by using fixed unemploymen duraion cuoffs o place individuals in he five groups. Bu laer when we esimae he effec of EEB on exi raes, we will use cuoffs ha vary wih he maximum allowable duraion of boh regular benefis and EEB in a sae in a given monh. To consruc Figures 1a and 1b, we firs compue average U-E and U-N exi raes by week of unemploymen duraion for individuals when EEB is available in heir sae and for individuals when EEB is unavailable. These average exi raes are shown by he wo lines in he op panel of Figures 1a and 1b. The basis for our esimaor is he difference beween he solid EEB line and he dashed non EEB line. Wihou conrolling for demand, we can properly gauge he magniude of he effec, bu if EEB is affecing exis, hen he downward shif in exi hazards for groups 3 and 4 should be, and is, larger han for he groups ha should be less affeced or unaffeced by EEB. The boom panels of Figures 1a and 1b show he difference beween he wo lines in he op panel, and he horizonal bars show he average difference in exi raes for each group. In he boom panel, i is obvious ha he exi rae differences for groups 3 and 4 are larger han for he oher groups. In sum, preliminary resuls wihou demand or demographic conrols sugges ha he change in exi hazards across periods when EEB is and is no available is significanly more negaive for individuals likely receiving EEB benefis or abou o exhaus regular UI benefis. Specificaion and sample period We now urn o our full specificaion which conrols for a wide range of individual characerisics and changes in labor demand. In addiion, we esimae EEB availabiliy more rigorously by using sae and ime specific maximum allowable duraions of EEB (raher han he fixed duraion cuoffs used in Figures 1a and 1b) o deermine EEB eligibiliy. We esimae equaion (1) using a logi specificaion and cluser sandard errors for individuals in he same sae a he same ime. We use daa from 1976 hrough As noed a he boom of Table 2, our specificaion includes a measure of aggregae labor marke ighness, unemploymen raes for 204 sae/occupaion labor marke segmens, dummy variables for 10 age, 3 educaion, 13 indusry, 4 occupaion, and 100 unemploymen duraion classificaions, as well as dummy variables for gender, marial saus and sae of residence Boh Meyer (1990) and Rohsein (2011) illusrae ha job losers far removed from he expiraion of benefis are likely o respond lile o increases in he maximum duraion of benefis because he probabiliy of reaching he maximum duraion of regular UI benefis is relaively small a he beginning of an unemploymen spell. 11 We also considered specificaions ha allow for ineracions beween demographic conrols. For example, we included dummy variables consruced by ineracing 2 gender groups, 2 marial saus groups, 3 educaion groups, and 10 age groups. When we add hese 120 dummies o our main specificaion, our esimaes of he effec of EEB are lile changed. 9

11 Exi Hazard from Unemploymen o Employmen Saring wih he effec of EEB on he Unemploymen o Employmen (U-E) ransiion rae, Figure 2a shows panels illusraing he effec of observable characerisics (oher han eligibiliy for EEB) on he U-E rae. Exi raes decline as duraion increases, bu a a decreasing rae. Exi raes decrease in age, are higher for men and married individuals, increase in educaion and are highes for producion occupaions. Esimaion resuls (no shown) reveal ha, as expeced, greaer labor marke ighness, and lower labor-marke-segmen-level unemploymen, lead o higher ransiion raes o employmen. Esimaes of he effec of EEB on U-E exi raes are shown in he firs column of Table 2. Esimaes for boh group 3 and group 4 are negaive and significan and sugges ha EEB reduces exi raes o employmen by abou 17 percen for individuals abou o exhaus heir regular UI benefis and 16 percen for individuals receiving EEB benefis. 12 I also appears ha EEB has a small negaive effec on he U-E exi hazard of individuals a he beginning of heir unemploymen spells. Exi Hazard from Unemploymen o Nonparicipaion We now urn o he effec of EEB on he Unemploymen o Nonparicipaion (U-N) ransiion rae. Firs, he esimaed effecs of observable characerisics (oher han eligibiliy for EEB) on he U-N exi rae are shown in Figure 2b. As shown in he op panel, he U-N exi rae generally rises as duraion increases. As shown in he remaining panels, exi raes iniially decline in age before increasing around age 45. Exi raes are higher for females, unmarried individuals, and individuals wih less educaion and are lowes in professional occupaions, as one migh expec based on priors regarding he relaive labor force aachmen of hese groups. The second column of Table 2 shows esimaes of he percen change in exi hazards when EEB is in effec for our 5 groups. Group 4, conaining individuals likely receiving EEB, is he only group likely receiving UI or EEB benefis esimaed o be significanly negaively affeced by EEB. The esimae for group 4 suggess ha EEB decreases exi raes for individuals receiving EEB by close o 7 percen. Ineresingly, we also esimae ha EEB increases exi raes for groups 1 and 2, while reducing hem for group 5. Overall, his paern is difficul o inerpre. The posiive esimaed coefficiens for groups 1 and 2 sugges ha some oher facor may be increasing U-N raes in periods when EEB is available. If his facor affecs U-N raes for all unemployed workers, no jus hose who have experienced shor duraion unemploymen spells, hen he esimaed effec of 12 Theory would sugges ha he effec of EEB on individuals nearing he maximum duraion of heir regular UI benefis is smaller han he effec on individuals already having exhaused heir regular benefis. Thus, hese resuls sugges ha individuals nearing he erminaion of heir regular benefis may be differen han oher individuals, perhaps because hey having been waiing unil he end of heir benefi period o search for a job, see Kaz and Meyer (1990). 10

12 EEB on group 4 may be larger han he -7 percen we esimae. On he oher hand, he negaive esimaed coefficien for group 5 suggess ha some oher facor may be pushing down he U-N raes of long-duraion unemployed when EEB is available, implying ha he esimaed coefficien on group 4 may oversae he negaive effec of EEB. Thus, here is considerable uncerainy abou he effec of EEB on U-N raes. Neverheless, because he esimaed effec is relaively small under eiher of he above scenarios, and because, as we show laer, he effec of U-N raes on he unemploymen rae is also relaively small, he amoun of uncerainy abou he effec of EEB on U-N raes does no ranslae ino grea uncerainy abou he effec of EEB on he unemploymen rae. Separae esimaes by EEB episode Recen papers on he effec of EEB have used daa only for he mos recen recession. 13 However, as described in deail in he appendix, EEB benefis have been available during and afer each major recession since he early 1970s. This raises he quesion of wheher recen sudies esimaes of he effec of EEB are influenced by he unusual circumsances surrounding he Grea Recession of , or wheher, insead, hey are represenaive of earlier effecs. As described below, we find ha he esimaes are in line wih esimaes drawn from previous episodes. Table 3 shows esimaed effecs for four differen periods. Excep for he early 80s recession, he esimaed effecs of EEB on U-E ransiions are similar (and no saisically differen) across he pas hree recessions: individuals abou o exhaus regular UI benefis or receiving EEB see heir exi raes fall by abou 16 percen. The esimaed effec of EEB on U-N ransiions is also fairly similar across episodes. In general, EEB only has negaive effecs on individuals abou o exhaus regular UI benefis or individuals likely receiving EEB benefis, wih effecs esimaed o be larger for he laer group. Esimaed effecs range from 0 o 12 percen and end o be larger afer he mid-1980s. 4. Mapping Coefficien Esimaes o EEB Effecs on he Unemploymen Rae and Labor Force Paricipaion Rae We now urn o mapping our esimaes of he effec of EEB on exi raes ino esimaes of he effec of EEB on unemploymen and labor force paricipaion raes. Using a sock-flow accouning model of he labor marke, we show ha he effecs of EEB on unemploymen and paricipaion depend on hree facors: (1) he effec of EEB on workers' ransiion raes, (2) he disribuion of job seekers across unemploymen duraion bins (recall ha he effec of EEB on workers' ransiion raes is sronges for he unemployed receiving or abou o receive EEB), and (3) how changes in a given ransiion rae (say U-E or U-N) affec he unemploymen and paricipaion raes. 13 Farber and Vallea (2013) are an excepion as hey also use daa from he early 2000s. 11

13 We find ha EEB have a small overall effec on unemploymen. Imporanly, his is no because he ransiion raes are no affeced (on he conrary, recall ha EEB lowered he UE ransiion rae by abou 16 percen for job seekers receiving or abou o receive EEB), bu, insead because he groups who are affeced represen a small fracion of all unemployed. Indeed, he unemploymen pool includes mosly individuals wih shor unemploymen duraion, and EEB has lile effec on hese individuals. The following sysem of differenial equaions expresses changes in he socks of he hree labor IJ force saes as funcions of he insananeous hazard raes of moving beween saes, he s. U U E N N N U E E E U N UE UN EU NU NE NU UN EN EU EN UE NE One can solve for he seady sae value of each of he socks as funcions of he six hazard raes. The expressions for he unemploymen rae and he labor force paricipaion rae are (4) u ss s s f (5) lf s ss EU UN UE EN UN EN s f NU EU EN NU NE f NE UE UN NE NU s f (6) We consruc esimaes for he six hazard raes for each poin in ime by firs using daa on socks of individuals in unemploymen, employmen, and ou of he labor force and measures of ransiions beween hese socks o produce esimaed labor force ransiion raes over ime. We hen adjus hese ransiion raes for ime aggregaion bias using he mehod oulined by Shimer (2012). As noed by Shimer (2012), because of he relaively high ransiion raes beween labor force saes, he implied seady sae measures rack he acual levels of he unemploymen rae and labor force paricipaion rae quie closely. Nex, we ake a firs order approximaion of expressions (5) and (6) o relae he deviaion of he seady sae unemploymen rae and paricipaion rae from he values hey would have aken in 12

14 he absence of EEB o percen deviaions of labor force flows from he values hey would have aken absen EEB. We obain u lf UN, EEB UE, EEB EEB U U u UN log UE log UN UE UN, EEB UE, EEB EEB lf lf lf UN log UE log UN UE (7) (8), where IJ EEB is he hazard rae for ransiion I-J a ime afer aking ino accoun he effec of IJ EEB, is wha he hazard rae for ransiion I-J a ime would have been if EEB were unavailable, and he IJ s are he firs order coefficiens describing he effec of a percen change IJ in on he unemploymen rae or paricipaion rae. 14 To consruc an esimae of IJ, EEB IJ previously, and we esimae he raio, we decompose jobseekers ino 5 groups, as described IJ, EEB, i IJ, i for each of hese five groups i and hen sum hese esimaes weighing each group by heir unemploymen share. Using IJ o denoe he monhly ransiion probabiliy we observe in he micro daa and for which we esimae an effec of EEB, he hazard rae IJ is given by ln 1 IJ IJ IJ, EEB, i IJ. i, and we have ln 1 IJ * 1 ln 1IJ IJ, EEB, i IJ, EEB, i where is our esimae from secion 3 of he percen change in he ransiion rae I-J induced by EEB for individuals in group i. We hen use CPS daa on he number of permanen and emporary job losers by duraion o esimae i, i=1,...,4, he fracions of he unemployed accouned for by group i. 15 (In he appendix we show ha he effec of EEB on job losers on emporary layoff is similar o he effec of EEB on permanen job losers). Puing hese pieces IJ, EEB ogeher, we consruc as IJ 14 Theoreically, EEB may affec all six labor force flows, bu pracically we did no find any significan effec on flows ino he labor force or ou of employmen. 15 To check ha his esimae is reasonable, we compare he number of job losers wih duraions less han he maximum allowable duraion of regular and EEB benefis from he CPS o published daa on he number of UI and EEB beneficiaries published by he Deparmen of Labor. The numbers mach quie well. 13

15 IJ, EEB IJ, EEB, i IJ, EEB, i ln 1 * 1 * IJ i IJ IJ. i i i ln 1IJ i (9) Equaions (7), (8), and (9) provide a ransparen view of he facors ha influence he effec of EEB on he unemploymen and paricipaion raes. These facors include: (1) he size of each i IJ, EEB, i group, capured by (2) he percen change in ransiion I-J caused by EEB,, and (3) he firs order coefficien describing he effec on he unemploymen (paricipaion) rae of a percen change in hazard I-J, ( ). 16 u IJ lf IJ Table 4 shows he effec of EEB on he unemploymen rae decomposed ino he hree facors (1) o (3). Panel 1 of he able shows he shares of unemploymen accouned for by he five groups, i he s. 17 Panel 2 of he able shows esimaes of he effec of EEB on exi raes by group. To ge an upper bound of he adverse effecs of EEB on exi raes ou of unemploymen, we impose he resricion ha he effec of EEB on hazard raes is always less han or equal o Panel 3 of Table 4 shows he average value of he firs order coefficiens mapping he percen change in hazard I-J o he change in he unemploymen rae, he s, over periods when EEB is available. I is worh noing ha UE is nearly wice he level of UN. The effec of U-N raes on unemploymen is relaively small because he direc effec, in which an increase in U-N lowers he unemploymen rae, is compensaed by he fac ha a nonparicipan has a higher probabiliy o flow ino unemploymen han ino employmen, which raises unemploymen. Panel 4 combines he informaion in he firs 3 panels and repors he effec of EEB on he unemploymen and labor force paricipaion raes hrough he U-N channel, hrough he U-E channel, and hrough boh channels combined. In he recen recession, he maximum effec of EEB on he unemploymen rae is one-hird percenage poin, while he effec on he paricipaion rae is essenially 0, as a small boos from a reducion in U-N ransiions is more han offse by a small decline due o a reducion in U-E ransiions. 19 IJ 16 Our esimaes of he effec of EEB on he unemploymen and labor force paricipaion raes assume ha here is no secondary effec of EEB on exi hazards hrough he influence of EEB on firms' labor demand. Oher esimaes of he effec of EEB on unemploymen, such as Rohsein (2011), are based on a similar assumpion. 17 We assume coefficien values of 0 for he fifh group because our prior is ha EEB does no affec his group. Because his group is very small, using esimaed coefficiens for his group would no significanly change our esimaes. 18 Specifically, we se he posiive esimaes for he effec of EEB on U-N hazards for he firs wo groups o The negaive effec of a decrease in he U-E hazard on he paricipaion rae depends on he implici assumpion ha flows o ou of he labor force are more likely, condiional on an individual being unemployed han condiional on an individual being employed. If, counerfacually, hese probabiliies were he same, hen one could show using equaion (6) ha a change in he U-E hazard would have no effec on he paricipaion rae. 14

16 The op panel of Figure 3 shows he oal effec of EEB on he unemploymen rae over ime. In 2010 he esimaed effec of EEB on he unemploymen rae is one-hird percenage poin. The effec of EEB on he unemploymen rae in previous episodes, beween 0.1 and 0.2 percenage poin, is considerably smaller han in he curren episode. The lower panel of Figure 3 shows he esimaed effec of EEB on he paricipaion rae. I is quie small. Overall, we find ha EEB has a small effec on he unemploymen rae. The mos imporan reason is ha mos of job losers are relaively unaffeced by EEB: Mos of he unemployed eligible for EEB are concenraed in groups 1 and 2, for which EEB have lile effec (panel 1 of Table 4). In oher words, EEB could only have large effecs on he unemploymen rae if i had large effecs on he U-E and U-N flows of individuals early in heir unemploymen spells. Bu as shown in Table 4, his is no he case. Our resuls appears o conras wih earlier research (Moffi and Nicholson (1982) and Meyer (1990), whose esimaes seem o imply quie large effecs of EEB on he unemploymen rae, a poin which we address in secion 5 below. 5. Comparison wih he Lieraure We now pu our findings in he conex of oher research on he effecs of EEB on unemploymen. In doing so, we seek o answer wo quesions: (1) is our finding of a relaively moderae effec of EEB on U-E ransiion raes consisen wih earlier sudies, which appeared o find subsanial effecs, and if so, why or why no? and (2) why are our esimaes of he effec of EEB on he unemploymen rae differen from recen papers on he subjec? Meyer (1990) finds ha exi hazards from unemploymen increase dramaically as individuals approach he maximum duraion of benefis. Specifically, he finds ha exi hazards increase fourfold as an individual moves from 6 weeks prior o benefi expiraion o 1 week prior o expiraion, while changing relaively lile prior o 6 weeks before benefi expiraion. If exi hazards afer he expiraion of benefis are similar o hose jus prior o expiraion, hen Meyer s esimaes imply ha exi hazards afer expiraion are abou four imes greaer han exi hazards for individuals receiving benefis bu no ye near he expiraion poin. Thus, one way o exrapolae Meyer s resuls would be o assume ha EEB reduces exi hazards by 75 percen, he difference beween average hazards early on in unemploymen spells, when he effec is small, and he esimaed hazard rae righ before benefi exhausion. However, such an exrapolaion may be misleading. Figure 4 illusraes why. The hin solid line labeled EEB No Available shows how one would expec he exi hazard o change as an individual nears he period when benefis expire in he absence of EEB, see Meyer (1990). As he ime spen unemployed approaches 26 weeks, he exi rae increases unil he poin of benefi exhausion (26 weeks) is reached, afer which he hazard rae remains 15

17 unchanged. Meyer (1990) finds ha exi raes are relaively fla in he early porion of a benefi period, region A in he figure, bu hen rise seeply wih 1 o 2 monhs of benefis remaining, region B. As a resul, an increase in he maximum duraion of benefis would be prediced o reduce exi raes for individuals near he expiraion of regular benefis. This is illusraed by he difference beween he solid line in region B represening exi behavior when EEB benefis are no available and he dashed line, represening exi behavior when benefis are available. An exrapolaion of Meyer s (1990) resuls assumes ha he effec on individuals ha have already exhaused regular benefis, region C, is he same as he effec a 26 weeks or ha he hazard in he absence of EEB, is he horizonal line labeled Exrapolaion of Meyer (1990) in region C. However, his is likely no a good assumpion because we find ha he effec of EEB on exi hazards for individuals in region C is considerably smaller ha his exrapolaion would imply and similar o he average exi rae of individuals in region B. Our esimae is represened by he hick solid line labeled Our Esimaed Effec. The difference beween his line and he dashed line represens our esimaed effec of EEB on individuals in region C. Our esimaed effec in region C is well below he exrapolaed effec, he difference beween he dashed line and he solid line labeled Exrapolaion of Meyer (1990). Anoher earlier paper wih resuls seemingly in conras o ours is Moffi and Nicholson (1982). They find ha an exra week of benefis leads, on average across all individuals, o an increase of 0.1 week of unemploymen. Card and Levine (2000) esimae similar resuls for a one-ime increase in benefis in New Jersey in he 1990s. Applying his esimae o he mos recen episode of EEB would imply ha he average unemploymen duraion of individuals eligible for UI increased by nearly 6 weeks. While i is difficul o map his precisely ino he effec of EEB on exi hazards, given ha he mean duraion of unemploymen prior o he adven of EEB was around 17 weeks, i would seem o imply a reducion in he unemploymen exi hazard of a leas 35 percen (assuming ha unemploymen duraion equals 1 divided by he exi hazard), considerably larger han he effec we esimae, especially once one akes ino consideraion ha his esimae applies o all eligible unemployed workers. 20 However, Moffi and Nicholson (1982) cauion ha heir sample, composed of approximaely 1000 individuals observed over , who received federal supplemenal benefis, is unlikely represenaive of he universe of individuals eligible for UI, as i includes mainly individuals who have suffered relaively long periods of unemploymen. 21 For differen reasons, i is also likely misleading o exrapolae he Card and Levine (2000) esimae o he mos recen episode of EEB. This is because i is no 20 The rule of humb mapping from average unemploymen duraion o exi hazard ha we use requires daa on he average expeced duraion of all unemploymen spells. However, we only observe he average duraion of ongoing spells of unemploymen, which will be greaer han he duraion of all spells because individuals wih long duraion spells are more likely o be sampled. Thus, he reducion in exi hazards implied by a 6 week increase in he average duraion of a spell of unemploymen is likely greaer han 40 percen. 21 Moreover, i is no clear how robus he Moffi and Nicholson (1982) resul is o small changes in specificaion. For example, able 4 of heir paper suggess ha changes in he assumpion needed o empirically idenify individuals a he kink poin in he budge ses can lead o dramaic reducions in he esimaed effec of an exra week of benefis on mean unemploymen duraions. 16

18 clear ha he relaionship beween benefis and average duraions of unemploymen is linear. In paricular, he esimaes in Meyer (1990) and he esimaes in his paper, sugges ha individuals nearing he end of heir regular benefis respond srongly o an exra 6-8 weeks of benefis, bu would no respond very much o any furher increase in benefi duraions. Thus, applying esimaes of he effec of an exra week of benefis in a conex in which he maximum duraion of benefis was changed relaively lile o a highly unusual siuaion in which he lengh of benefis increased by over 60 weeks in many saes may be misleading. 22 Turning o more recen sudies, our paper relaes o he work of Fujia (2011), Rohsein (2011), Nakajima (2012), Farber and Vallea (2013) and Bradbury (2014). Similar o Rohsein (2011) and Farber and Vallea (2013), we find ha EEB does reduce exi hazards o nonparicipaion. Unlike hese sudies, however, we find ha EEB also has a sizable effec on exi hazards o employmen. Fujia (2011) esimaes a ¾ percenage poin effec of EEB on he unemploymen rae in he mos recen episode. He uses a regression disconinuiy approach o idenify he EEB effec as he sharp change in unemploymen exi behavior of prime-age males a 26 weeks during he period when EEB was available in he mos recen episode compared o prior o he recession. This is similar o our approach excep ha Fujia (2011) uses he abrup change in behavior a an unemploymen duraion of 26 weeks, whereas we compue he change in average exi raes for all individuals likely affeced by EEB o exi raes of similar individuals when EEB is no available. Also, while Fujia (2011) focuses on prime age men, we esimae effec for adul permanen (and emporary) job losers. Nakajima (2012) calibraes a model of search behavior and finds much larger effecs (1.4 percenage poins on he unemploymen rae) han we do. The discrepancy wih our findings likely owes o he paper s choice of calibraion. The paper uses he esimae of he effec of an exra week of UI benefis on he average duraion of unemploymen from Moffi and Nicholson (1982) and Card and Levine (2000) o calibrae he cos of search, he key parameer deermining he effec of EEB. Finally, comparing unemploymen in counies on borders beween saes having differen maximum duraions of EEB, Hagedorn, Karahan, Manovskii, and Miman (2013), HKMM, find ha EEB increased unemploymen by 3.6 percenage poins. They jusify his ousized effec by showing ha i is heoreically possible for higher wage demands from workers eligible for EEB o cause firms o drasically lower vacancies (or increase layoffs). This general equilibrium effec of EEB (operaing hrough job creaion raher han worker s search effor or reservaion wages) is no capured by our esimaes (which only reflec he influence of EEB on search and 22 Anoher reason o be wary of exrapolaing he Card and Levine (2000) resuls is ha New Jersey, where boh he UI benefi replacemen rae and he average benefi exhausion rae were near well above average levels in he Unied Saes, may no be represenaive of he Unied Saes. 17

19 reservaion wages), or oher empirical work discussed above. As a resul, heir resuls could be consisen wih ours if he effec of EEB on vacancies and job creaion is exremely large. 6. Conclusion We use differences in he behavior of unemployed individuals a differen unemploymen duraions o idenify and undersand he magniude of he effec of EEB on unemploymen. Because EEB has significan effecs on U-E hazard raes, we esimae ha i had non-negligible effecs on he unemploymen rae in recen years. A he same ime, because EEB has very lile effec on he behavior of he relaively large share of individuals who are a he beginning of heir unemploymen spells, he overall effec of EEB on he unemploymen rae is fairly modes; a is peak (in erms of he average number of benefi weeks provided) EEB boosed he unemploymen rae by one-hird percenage poin. Because he changes impared o U-E and U- N exi raes by EEB have offseing implicaions for he paricipaion rae, he effec of EEB on he paricipaion rae is esimaed o have been quie small. Using a daa se on EEB ha goes back o he 1970s, we are able o compare he effecs of EEB on unemploymen in he mos recen episode wih effecs in previous episodes. We find ha for he mos par, esimaed effecs of EEB on U-E and U-N hazards are quie similar over hisory o esimaed effecs in he mos recen episode. Because he number of individuals likely receiving EEB was much smaller, as a share of unemploymen, in hese episodes, he effec of EEB on he unemploymen rae is esimaed o have been quie modes. 18

20 Figure 1a. Permanen Job Loser U-E Exi Raes (wih and wihou EEB) U E Exi Raes by Unemploymen Duraion Rae Wih EEB Wihou EEB Weeks Differences in U E Exi Raes wih and wihou EEB, by Unemploymen Duraion Rae Weeks Noe. Raes are smoohed using a five-week cenered moving average wih weighs of.1,.2,.4,.2,.1. Daa adjused for poenial break in exi raes following he 1994 CPS redesign. 19

21 Figure 1b. Shif in Permanen Job Loser U-N Exi Raes (Across Periods wih and wihou EEB) U N Exi Raes by Unemploymen Duraion Rae Wih EEB Wihou EEB Weeks Differences in U N Exi Raes wih and wihou EEB, by Unemploymen Duraion Rae Weeks Noe. Raes are smoohed using a five-week cenered moving average wih he following weighs:.1,.2,.4,.2,.1. Daa adjused for poenial break in exi raes following he 1994 CPS redesign. 20

22 Figure 2a. Effec of Observable Characerisics on U-E Exi Raes (Permanen Job Losers) Panel A. By Duraion (relaive o 100+) Panel B. By Age (relaive o 65+) Weeks of Unemploymen Age Panel C. By Gender (relaive o female) Panel D. By Marial Saus (relaive o no married) Male Gender Female Married No married Marial Saus Panel E. By Educaion (relaive o college grad.) No Coll. Some Coll. Coll. Grad Educaion Panel F. By Occupaion (relaive o professional) Prof. Serv. Sales Prod. Occupaion Noe. Thick black lines represen poin esimaes. Red bars span poin esimae plus or minus wo sandard deviaions. 21

23 Figure 2b. Effec of Observable Characerisics on U-N Exi Raes (Permanen Job Losers) Panel A. By duraion (relaive o 100+) Panel B. By age (relaive o 65+) Weeks of unemploymen Age Panel C. By gender (relaive o female) Panel D. By marial saus (relaive o no married) Male Gender Female Married No married Marial saus Panel E. By educaion (relaive o college grad) Panel F. By occupaion (relaive o professional) No coll. Some coll. Coll. grad. Educaion Prof. Serv. Sales Prod. Occupaion Noe. Thick black lines represen poin esimaes. Red bars span poin esimae plus or minus wo sandard deviaions. 22

24 Figure 3. Effec of EEB on he Unemploymen Rae over Time Effec on Unemploymen Rae age poin Year Effec on Labor Force Paricipaion Rae age poin Year 23

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