Statistical Discrimination or Prejudice? A Large Sample Field Experiment

Transcription

1 DEPARTMENT OF ECONOMICS ISSN DISCUSSION PAPER 23/12 Statstcal Dscmnaton o Pejudce? A Lage Sample Feld Expement Mchael Ewens, yan Tomln, and Lang Choon ang * Abstact A model of acal dscmnaton povdes testable mplcatons fo two featues of statstcal dscmnatos: dffeental teatment of sgnals by ace and heteogeneous expeence that shapes pecepton. e constuct an expement n the U.S. ental apatment maket that dstngushes statstcal dscmnaton fom taste-based dscmnaton. Responses fom ove 14,000 ental nques wth vayng applcant qualty show that landlods teat dentcal nfomaton fom applcants wth Afcan-Amecan and whte soundng names dffeently. Ths dffeental teatment vaes by neghbohood acal composton and sgnal type n a way consstent wth statstcal dscmnaton and n contast to pattens pedcted by a model of taste-based dscmnaton. JEL Codes: J15, J70, J71, R3. * Mchael Ewens (mewens@cmu.edu), Teppe School of usness, Canege Mellon Unvesty; yan Tomln (bytomln@gmal.com), Loyola Unvesty, Depatment of Economcs; Lang Choon ang (lang.c.wang@monash.edu), Monash Unvesty, Depatment of Economcs. e benefted temendously fom the suggestons and comments of Kate Antonovcs, Godon Dahl, Pushka Mata, enda Ra, Zaha Sddque, and seveal anonymous efeees. e also thank El eman, Matn og, Vnce Cawfod, Jule Cullen, Jacob LaRvee, Mke Pce, Valee Ramey, en Gllen, and semna and confeence patcpants at IZA, Loyola Unvesty, Monash Unvesty, UC San Dego, Unvesty of Tennessee Knoxvlle, the 2010 esten Economc Assocaton Intenatonal Annual Confeence, the 2011 Illnos Economc Assocaton Annual Confeence, and the 2011 Intenatonal Economc Scence Assocaton Confeence. e acknowledge the fundng suppot fom the Insttute fo Appled Economcs at the UC San Dego Mchael Ewens, yan Tomln, and Lang Choon ang All ghts eseved. No pat of ths pape may be epoduced n any fom, o stoed n a eteval system, wthout the po wtten pemsson of the autho. 1

2 I. Intoducton Racal and ethnc dscmnaton contnues to pevade many makets n the US. Roughly half of the annual dscmnatoy cases epoted by fedeal agences nvolve ace o ethncty, and the numbe of new ncdents outpaced populaton gowth ove the past 10 yeas. 1 The economcs lteatue posts two majo souces of acal dscmnaton: taste-based and statstcal. Racal pejudce poduces taste-based dscmnaton, whle statstcal dscmnaton occus n an envonment of mpefect nfomaton whee agents fom expectatons based on lmted sgnals that coelate wth ace. 2 The esult of both types of dscmnaton, howeve, s the same: smla ndvduals who dffe only by the ace expeence dffeent outcomes. A smple examnaton of dffeental outcomes sheds lttle lght on the souce of dscmnaton. Employng an emal coespondence expement n the US ental apatment maket, ths pape tests whethe statstcal dscmnaton o taste-based dscmnaton s the pmay explanaton fo dffeental outcomes between whte and Afcan Amecan ental applcants. e extend the Agne and Can (1977) model of statstcal dscmnaton, whee landlods fom pedctons of qualty by ace, to test the key featue of statstcal dscmnatos: heteogeneous expeence. The statstcal dscmnaton model posts that landlods dffe n the peceptons of sgnals due to past expeence n the sceenng and ental pocess and n tun, ncopoate ace and sgnals nto decsons dffeently. In patcula, statstcally dscmnatng landlods place a geate weght on sgnals fom the famla goup than the unfamla goup. e contast the pedctons wth those of taste-based dscmnaton, whee pejudced landlods use nfomaton ndependent of ace to pedct qualty but deve lowe magnal utlty of pedcted qualty fom the out-goup. e show that lowe magnal etun to sgnal of qualty fo mnoty goups s 1

3 consstent wth both statstcal and taste-based dscmnaton, hghlghtng the empcal hudle to sepaate the two explanatons. The model gudes ou expemental desgn. Usng vacancy lstngs on Cagslst.og (Cagslst) acoss 34 US ctes and oughly 5,000 neghbohoods (census tacts), we send nquy emals wth two key components to 14,000 landlods. e use the common acal-soundng fst names of etand and Mullanathan (2004) to assocate applcants wth ace, and the nquy emal contans dffeng but lmted peces of nfomaton about the applcants: postve, negatve and no sgnals beyond ace. In the nosgnal nquy, we pesent emals to landlods wth acal soundng names as the only sgnal. In the postve nfomaton nquy, the fctonal applcant says he name and nfoms the landlod she s a non-smoke wth a espectable (and payng) job. In the negatve nfomaton nquy, the applcant states he name and tells the landlod she has below aveage cedt atng and smokes. Sendng negatve sgnals may seem unusual, howeve, we ague that applcants facng cedt check fees and landlods wth dffeng qualty thesholds may be easonably ncentvzed to dsclose negatve nfomaton. The dependent vaable codes landlods esponses to captue an nvtaton to the nquy fo futue contact. Although the outcome eflects only a postve esponse dung the ntal nquy phase of a sceenng pocess, any dffeental teatment n sceenng wll lkely nfluence fnal outcomes n the same decton. Snce esdental locatons ae closely ted to chaactestcs assocated wth welfae, such as the type of job held, cme levels, and school qualty, ou focus on the ental apatment maket s polcy elevant. As Cagslst s the domnant souce of onlne classfeds fo apatment lstngs n the US, and s fequented by one-thd of the whte and black US adult populaton, the fndngs ae epesentatve. 3 The gowng pevalence of onlne nteactons n eal estate, employment, fnance, and auctons, suggest the esults extend beyond the ental apatment maket. 2

4 The expement povdes fou majo esults. Fst, when no-sgnal nquy emals ae sent, applcants wth Afcan-Amecan soundng names ae 16 pecent less lkely to eceve a postve esponse fom a landlod than those wth whte soundng names. Second, usng a dffeence-ndffeences estmato, we show that the whte-black acal gap n the negatve nfomaton case wdens wth postve nfomaton. oth fndngs ae consstent wth statstcal dscmnaton and pejudce, as they can be the esults of landlods placng a heave weght on sgnals sent by whte applcants than black applcants o landlods ecevng a geate magnal utlty of pedcted qualty fom whte applcants than black applcants. Thus, the eseach desgn eques futhe efnement to sepaate the explanatons. Thd, the model defnes the noton of a supsng sgnal, whee the base case acts as a benchmak fo unnfomed expectatons and a means to quantfy supse elatve to the bettethan-expected (postve) and wose-than-expected (negatve) nfomaton. Ths noton of a supsng sgnal s dffcult to ntoduce n a job applcaton settng whee esumes ae equed, as t s mpossble to povde zeo nfomaton about educaton o expeence n a esume. In the pesence of dffeental weghtng of sgnals by ace, statstcal dscmnaton pedcts that a supsng postve sgnal wll not necessaly shnk the acal gap n the base case, but a negatve supse wll. In contast, the taste-based dscmnaton model shows that a supsng postve sgnal wll wden the acal gap. Ou empcal esults ae consstent wth statstcal dscmnaton. Fnally, we explot neghbohood acal composton as a souce of heteogenety n landlod expeences wth, o pefeences fo, dffeent acal goups. y allowng a sgnal s nose to depend on ace, the statstcal dscmnaton model pesents anothe testable hypothess: a landlod s elatve expeence wth a gven ace nceases the elatve weght she places on the 3

5 sgnals fom that goup. Convesely, taste-based dscmnaton pedcts that f landlods exhbt out-goup pejudce, as the shae of blacks n a neghbohood nceases, dscmnaton aganst black applcants n the base-case wll attenuate, whle supsng negatve nfomaton wll hut black applcants moe. The ental apatment maket s an deal settng fo ths test, snce a landlod s past expeence s closely ted to the neghbohood chaactestcs n whch she s entng. Smlaly, a landlod s ace and acal pefeences ae also lkely coelated wth the neghbohood acal composton. Usng a dffeence-n-dffeences estmato that combnes the expemental teatments and neghbohood acal composton, we show that as the shae of blacks n a neghbohood nceases, a supsng postve sgnal closes the acal gap obseved elatve to the base-case, whle a supsng negatve sgnal does lttle to close t. Moe mpotantly, the base-case acal gap pessts acoss all types of neghbohoods and contadcts the pedcton of taste-based dscmnaton. The theoetcal and empcal esults ae obust to a wde aay of specfcatons. Intoducng landlod sk aveson has no meanngful mpact on the mplcatons of the statstcal dscmnaton model. e also show that any possble coelaton between a neghbohood s acal shae and the sk pefeences of landlods s not a fst-ode empcal concen. The empcal esults ae also nsenstve to usng a subset of the moe common fst names and altenatve categozatons of landlod esponses. Ths pape fts nto and extends the lage body of eseach on acal dscmnaton. th the excepton of Lst (2004) and to some extent Levtt (2004), past evdence of statstcal dscmnaton s nconclusve. Fo example, ecent studes that examne the housng makets n the US o Euope, such as Ahmed et al. (2010), osch et al. (2010), and Hanson and Hawley (2011) fnd sgnfcant acal o ethnc dscmnaton aganst mnoty applcants, but do not 4

6 povde clea evdence on the souces of dscmnaton. Smlaly, Altonj and Peet (2001) and etand and Mullanathan (2004) found sgnfcant acal gaps n wages and job ntevew callback ates, espectvely, but weak suppot fo statstcal dscmnaton. 4 On the othe hand, the elated lteatue on acal poflng n the context of polce seaches, such as Knowles et al. (2001) and Antonovcs and Knght (2009), shows mxed evdence of acal pejudce. Ynge (1986), Page (1995), Roychoudhuy and Goodman (1996), Ondch et al. (1998, 1999), and Ondch et al. (2003) wee the ealest audt expemental studes to show dscmnaton aganst mnotes n the US housng makets. These esults may suffe fom the confoundng factos nheent n n-peson audt studes, as they ely on actos who often dffe n unobsevable dmensons. 5 In contast, Capuso and Loges (2006) and Ahmed and Hammastedt (2008) poneeed the use of emal coespondence desgn to study ethnc dscmnaton n ental housng makets. Moe ecently, Ahmed et al. (2010), osch et al. (2010), and Hanson and Hawley (2011) extend the methods by ncludng dffeent peces of nfomaton n emal nques to assess the effects of nfomaton on dffeental outcomes acoss acal o ethnc goups. Ou appoach dffes fom pevous studes and contbutes to the lteatue n seveal ways. e explctly model how and why statstcal and taste-based dscmnaton n the sceenng pocess can each pedct lowe magnal etun to sgnal fo the dscmnated goup, whch potentally esolves some contadctoy hypotheses and fndngs n the dscmnaton lteatue. In patcula, Ahmed et al. (2010) and osch et al. (2010) ague that statstcal dscmnaton mples educed dscmnaton aganst mnotes wth nceased postve nfomaton. Howeve, they show an unchangng acal gap n the lkelhood of postve esponses when postve nfomaton s ntoduced and ague that the fndng suppots taste-based 5

7 dscmnaton. etand and Mullanathan (2004), n contast, ague that the fndng of lowe o equal magnal etuns to cedentals fo mnotes s nconsstent wth taste-based dscmnaton. On the othe hand, Hanson and Hawley (2011) ague that smalle eply dffeences between whte and Afcan Amecan applcants n hgh-class (.e. hgh qualty pose n emals) nquy emals than low-class nquy emals ae evdence fo statstcal dscmnaton. Howeve, because eply ates decease wth class fo whte applcants, the esults may be dven by the hghe facton of negatve eples to low-class emals. Ou novel modelng and estmaton famewok demonstates the dffculty of sepaatng statstcal dscmnaton fom taste-based dscmnaton. e show that combnng neghbohood acal composton, vaous expemental teatments and supsng sgnals wth a dffeence-n-dffeences estmato s an mpotant peequste fo dstngushng statstcal dscmnaton fom taste-base dscmnaton. The evdence of statstcal dscmnaton yelds mpotant polcy mplcatons that may dffe fom those used to addess acal pejudce. Fo example, combatng acal pejudce may nvolve acceptance campagns and communty buldng, whle polces addessng statstcal dscmnaton would be most effectve f dected at equatng the manne n whch decson makes ncopoate new nfomaton sgnals acoss ace. II. Dscmnaton n Sceenng and Testable Implcatons e pesent a model that can explan dffeental sceenng outcomes by ace wth an applcaton to the ental apatment maket. Although the detals ae specfc to the ental apatment maket, the model should extend to othe stuatons of sem-fomal sceenng. Consde the followng fou-stage pocess of matchng potental tenants to apatments: 6

8 1. Inquy: An applcant selects publcly posted ental unts to send costless nques wth sgnal, x, to landlods. She knows that the pobablty of gettng a postve esponse s lkely nceasng n x. 2. Sceenng: th the set of sgnals X x,..., x } eceved fom T ndependent T { 1 T applcants, the landlod foms a set of pedcted qualtes ˆ,, ˆ } and esponds T { 1 T postvely to n of the applcants who maxmze he expected utlty of ntevew. 3. Intevew: Intevews, whch nclude cedt and efeence checkng, eveal the tue qualty of each ntevewee and cost applcants and landlods m and c, espectvely Decson: The canddate wth the hghest s offeed the apatment. Ou expement focuses on dstngushng statstcal and taste-based dscmnaton occung at stage 2 of the above pocess. A. Statstcal Dscmnaton Suppose that sgnal x poxes qualty nosly wth a ace-specfc eo e : 7 x, (1) 2 whee q ~ N ( m, s q ), E( e q ) = 0, va( 2 e q ) = s e,, E x ) (, and va( x ). 2 2, The assumptons mostly coespond to those n Agne and Can s (1977, pp ) model, except that we pemt the sgnal mean to vay by ace. Landlods have a sample of ntal nques x and applcant qualtes acqued dung past teatons of stages 2 and 3 outlned above. The lmted nfomaton avalable n the typcal nquy esults n the landlod fomng pedctons usng sgnals n the followng foecastng egesson fo each ace : ˆ ˆ ˆ x, (2) L 7

9 whee L mˆ s the Odnay Least Squaes (OLS) estmato of the ntecept tem; gˆ s the estmato of the magnal effect of sgnal x ; and s fo whtes, and fo blacks. It s sensble fo a sk-avese landlod to use the OLS estmato fo pedcton snce t mnmzes the condtonal vaance of the foecast eos. Estmates of because of the dffeng expeences. L mˆ and gˆ wll vay acoss landlods Now suppose a landlod obseves a new sgnal x ~ and ace fom an applcant n stage 2. The landlod wll pedct qualty as: ~ L ˆ ˆ ~ x. (3) Equatons (1), (2), and (3) coespond to Agne and Can s (1977) model of statstcally dscmnatng employes, and we call gˆ the nfomaton weghtng paamete fo ace snce t nfoms a landlod how much to weght a sgnal fom an applcant of ace. 8 It s also possble fo an applcant to only eveal he ace n an emal nquy. 9 The landlod can nfe qualty usng the aveage sgnal ( x ) obseved among ace n past emal nques n the followng foecastng egesson: ˆ ˆ x. (4) L Equaton (4) s equvalent to the landlod usng some aveage among to fom a pedcton. e dscuss the mplcatons when applcants stategcally eveal no nfomaton n Secton. Equatons (2), (3), and (4) defne a statstcal dscmnato who atonally esponds to mpefect nfomaton by ncopoatng past expeence nto an OLS estmato (.e., the best lnea pedcto) of applcant qualty by ace. 10 In the spt of Agne and Can (1977), we assume that the landlod may be sk avese and maxmzes expected utlty by choosng n ndependent applcants to espond postvely fo 8

10 ntevews (R = 1 n ou empcal specfcaton), gven a constant magnal cost of ntevew, c, and a capacty constant, M n. 11 Futhe, assume that the utlty functon belongs to a class of mean-vaance utlty functons, of whch the exponental utlty functon used by Agne and Can (1977) s an example. As applcants ae ndependent, f the total numbe of applcants T M, the landlod wll nvte any applcant fo whom the magnal utlty fom nvtng that applcant s geate than o equal to the cost of ntevewng that applcant: E[ U( ˆ )] c, whee U ˆ ) denotes the utlty ( deved fom ntevewng applcant wth pedcted qualty ˆ. If sot all applcants by E U( ˆ )] and nvte the best M of them. 12 [ A.1 Statstcal Dscmnaton unde Rsk Neutalty T M, then the landlod wll Consde the case when landlod s sk aveson s nsgnfcant, so we can focus solely on the effect of the mean of pedcted qualty, as expected utlty s monotoncally nceasng n pedcted qualty. As statstcal dscmnaton nfluences a landlod s decson though ˆ, dffeental outcomes by ace may ase though the OLS estmatos n equaton (2): côv, x ˆ (5) vâ x ˆ L ˆ x (6) Hee côv(, x ) s the sample covaance between qualty and sgnal, vâ( x ) s the sample vaance of the sgnal, and q and x ae the sample aveage of qualty and sgnal of applcants, espectvely. Gven the assumpton 2 E [côv(, x )] E[côv(, x )], equaton (5) shows that any dffeences n nose of sgnals, E [vâ( x )], can nduce dffeences n the weght placed 9

11 on the same sgnal fom dffeent aces. Fo example, landlods wth E[vâ( x )] E[vâ( x )] wll have. 13 Fo applcants wth objectvely dentcal sgnals except ace, the pedcted qualty s geate fo whte than fo black applcants. Note that we have not placed any estctons on the mean sgnals no nose acoss ace. Dffeences n mean sgnal o nose could stem fom fundamental acal dffeences n sgnals such as ncome o cedt scoes of the populaton o smply fom those obseved by landlods n the samples. The model offes seveal hypotheses that can be empcally tested. Although each L landlod s estmates of the ntecept tems ( ˆ ) and the nfomaton weghtng paametes ( ˆ ) ae unobsevable, we can expementally manpulate ace of applcants and sgnals sent by applcants to examne whethe landlod esponses ae consstent wth the model s pedctons. If we, the eseaches, could obseve each landlod s sample of and x, we could sepaately aveage the numeato and denomnato of the nfomaton weghtng paamete acoss the sample of landlods ( n l ) to obtan: l ) (1 nl ) côv(, x ) (7) (1 n vâ( x ) Smlaly, we have the aveage of the ntecept tem: L n ) ( x n ) (8) ( l l In a lage sample, equatons (7) and (8) yeld the means. A.1.1 Testable Implcaton 1 th andom assgnment of ace = {, } to a fctonal applcant and n the absence of addtonal sgnals, we can examne whethe landlod esponses ae consstent wth an aveage landlod havng,, o. Equatons (4) and (8) mply that: 10

12 E( ) (1 ) (9) Gven past fndngs of dscmnaton aganst black applcants, we expect: Hypothess 1 On aveage, a whte applcant s moe lkely to eceve a postve esponse than a black applcant n the no-sgnal base case. A.1.2 Testable Implcaton 2 If we andomly assgn a negatve sgnal ~ x 0 o a postve sgnal ~ x 0, and ace to dffeent applcants and pesent them to andomly selected landlods, we can use a dffeence-ndffeences appoach to test whethe,, o. Equaton (2) mples that the mean dffeence between black and whte applcants sendng a postve sgnal s: E( ˆ ~ ˆ ~ ) ~ L L x ) E( x ) ( ) ( x (10) Smlaly, the mean dffeence between black and whte applcants sendng a negatve sgnal s: E( ˆ ~ ˆ ~ ) ~ L L x ) E( x ) ( ) ( x (11) Takng the dffeence of equatons (11) and (10) yelds: ˆ ˆ ~ ˆ ˆ ~ ( ) ( ) ( )( ~ ~ E x E x x x ) (12) The extent of dependence acoss sgnals of tenant qualty whch landlods obtaned though the past expeence nfluences the aveage sample vaance of sgnal vâ( x ). 14 Massey and Denton s (1987) and Iceland et al. s (2002) descpton of esdental segegaton and neghbohood sotng mples that sgnals ae postvely coelated wthn a acal goup. Landlods entng n neghbohoods that ae pedomnantly whte ae elatvely moe expeenced wth whte tenants than wth black tenants. These landlods aveage sample 11

13 vaance of sgnals fom whte applcants wll be smalle than that fom black applcants because of neghbohood sotng. 15 Snce the aveage landlod n a natonal sample ents n a pedomnantly whte neghbohood, we expect. Ths pedcton s also consstent wth pevous studes (e.g., etand and Mullanathan [2004] and Ahmed et al. [2010]) that fnd smalle magnal etuns to sgnal fo blacks than fo whtes. Testable mplcaton 2 yelds: 16 Hypothess 2 On aveage, the postve esponse gap between whte and black applcants s lage wth postve sgnal sent than wth negatve sgnal sent. A.1.3 Testable Implcaton 3 If we andomly send a negatve sgnal that s below the mean sgnal of ace, ~ x E( ), o a postve sgnal that s above the mean, ~ x E( ), to landlods, we can futhe valdate whethe sgnals lead to dffeences n esponses that ae consstent wth. x Call the dffeence between the sgnal a landlod obseves and he expected sgnal fo the no-sgnal base case a supse n sgnal. th an dentcal postve sgnal fo black and whte applcants and E x ) E( x ), as evdent n past studes showng Afcan Amecans havng ( lowe aveage socal-economc backgounds than whte Amecans (Has 2010), we have ~ [ ( )] [ ~ x E x x E( x )]. The expementally manpulated negatve nfomaton wll be a geate supsng sgnal fo whtes than fo blacks: ~ ( )] [ ~ x E x x E( x )]. Dependng [ on the elatve sze of and, the pattens of landlod esponses wll dffe. x In case 1, whee, a supsng sgnal, whethe postve o negatve, wll be weghted equally fo blacks and whtes. As ~ ( )] [ ~ x E x x E( x )], the postve sgnal [ 12

14 benefts black applcants moe than whte applcants. As ~ ( )] [ ~ [( x E x x E( x )], the negatve sgnal huts whte applcants moe than black applcants. Hence, t follows that: ~ ( )] [ ~ x E x x E( x )] (13) [ ~ ( )] [ ~ x E x x E( x )] (14) [ That s, compang to the no-sgnal base case, the gap n expected qualty between the two acal goups closes n the pesence of ethe postve o negatve nfomaton (case 1 of Fgue 1). In case 2, whee, expesson (14) s unambguously satsfed, but the elatonshp n (13) may not be tue. Thus, when, negatve nfomaton wll shnk the gap n expected qualty between blacks and whtes, but postve nfomaton wll not necessaly naow the gap (case 2 of Fgue 1). Fnally, n case 3, whee, expesson (13) wll be satsfed, but expesson (14) wll not necessaly be. In ths case, the postve teatment wll naow the acal gap, but the negatve teatment may not (case 3 of Fgue 1). Theefoe, gven Hypothess 2, we have: Hypothess 3 On aveage, negatve nfomaton wll shnk the acal gap obseved n the base case, but postve nfomaton wll have an ambguous effect on the acal gap obseved n the base case. A.1.4 Testable Implcaton 4 Ou model and assumptons show that whethe,, o fo an aveage landlod depends on whethe vâ( x ) vâ( x ), vâ( x ) vâ( x ), o vâ( x ) vâ( x ) on aveage. If the elatve sze of ˆ vaes wth vâ( x ) n the decton pedcted by the model, t suggests that landlods behavos ae consstent wth ou model of statstcal dscmnaton. 13

15 Gven neghbohood sotng and postve covaance of sgnals, as the shae of black esdents n a neghbohood, S, nceases, we expect vâ( x ) to decease and vâ( x ) to ncease on aveage. As S nceases fom 0 to 1, t s nceasngly lkely that. The postve elatonshp between and S mples that the elatonshp between a supsng sgnal and shnkage n the acal gap (testable mplcaton 3) wll also vay wth S. As S 1, the effect of a supsng postve sgnal n naowng the acal gap n postve esponse ates wll become moe evdent (case 3 n Fgue 1). Theefoe, we have: Hypothess 4 Postve teatment should shnk the acal gap n postve esponse ates elatvely moe n pedomnantly black neghbohoods. Convesely, negatve teatment wll shnk the acal gap n pedomnantly whte neghbohoods, but not necessaly so n pedomnantly black neghbohoods. Pevous dscmnatoy behavo mght contbute to segegaton and vaaton n neghbohood acal composton. If pevous dscmnaton s statstcal, then usng neghbohood acal composton as the poxy fo landlods elatve expeences wth dffeent acal goups wll lead to stong esults, because landlods expeences enfoced themselves n the samples obseved. e now consde whethe landlod sk-aveson altes the hypotheses detaled above. A.2 hen Rsk-Aveson s Sgnfcant e have thus fa assumed away any sk aveson effects on landlod behavo, howeve the vaance of pedcted qualty could alte the hypotheses. ased on equaton (3), the vaance of pedcted qualty condtonal on a gven sgnal x ~ fom a ace- applcant s: ( ~ 2 ( ~ 2 ˆ ~ 1 ) 1 ) ) 2 x x 2 x x va( ˆ ˆ x N 2 (15) N ( x ) N N vâ( x ) j 1 j x whee N s the numbe of past ace- applcants that the landlods eve obseved. 14

16 Accodng to equaton (15), n the no-nfomaton base case, a landlod wll dscount the sgnal sent by applcants fom the goup that she has elatvely less expeence wth moe than the othe goup f she s sk avese than f she s sk neutal. Rsk aveson wll wden the esponse gap between whte and black applcants n hypothess 1. hen a black applcant ( x x ) sends a supsng postve (negatve) sgnal, the applcant s condtonal vaance of pedcted qualty s lage (smalle) than that of a smla whte applcant, holdng all else equal, as ~ 2 ( x x ) s lage (smalle) than ~ 2 ( x x ) n equaton (15). The lage s a postve (negatve) supsng sgnal, the moe (less) the black applcant s hut fom landlod sk aveson makng the effects of changng sgnal on acal gap moe ponounced. Thus, hypotheses 2 and 3 ae smla wth landlod sk aveson. Snce the effects of supsng sgnals on landlods postve esponses may vay dependng on the extent of landlod sk aveson, t s cucal that neghbohood acal composton only poxes landlods elatve expeence wth dffeent acal goups, but not the degee of sk aveson. Othewse, hypothess 4 wll only examne the extent of landlods sk aveson acoss neghbohoods unde statstcal dscmnaton, nstead of how elatve expeence wth a patcula ace shapes the nfomaton weghtng paamete. Futhemoe, as the shae of black esdents n a neghbohood (S ) nceases, N nceases and vâ( x ) deceases n equaton (15). Thee s a possblty fo postve esponses to black applcants supsng postve sgnals to ncease elatvely less than those to whte applcants as S 1. Hee, the extent of sk aveson and the effect fom shnkng vâ( x ) on vaance of pedcted qualty ae lage enough to offset the ncease n the nfomaton weghtng paamete. Although ou focus on the ntal sceenng of emal nques makes such an outcome mplausble, t s mpotant to ensue that sk aveson does not play any sgnfcant ole n pedctng esponses. 15

17 Oveall, statstcal dscmnaton unde sk aveson poduces pedctons that mmc those of statstcal dscmnaton unde sk neutalty. It s mpotant to note that we ae stll n a wold of statstcal dscmnatos. A landlod that s sk avese and ace-blnd wll not have esponse pattens smla to those of the sk-neutal o sk-avese settng.. Stategc Sgnalng and Tuth-tellng Ou model assumes a one-to-one mappng between applcant type and the sgnal sent. It s plausble that eal-wold applcants wll le and/o stategcally eveal nfomaton about the type. The landlod s expected sgnal x assumed to be the aveage sgnal eceved n the landlod s hstoy depends cucally on the applcants sgnal choce. If applcants nstead send sgnals not dectly ted to the type, the ntepetaton of dffeences n esponse ates may need to be alteed. e now dscuss f and how these sgnals ft nto ou modelng famewok. Let thee be thee applcant types hgh, aveage, and low fo each ace n the populaton of applcants. Suppose n stage 3 of the ental pocess that landlods obseve tue applcant type and eject any applcant that led n the fst stage. Hee, applcants wll neve fnd t advantageous to le about the type n the nquy stage. Tuth-tellng, howeve, s not dentcal to full evelaton as an applcant s not oblgated to eveal type. Applcants who do eveal the type wll do so tuthfully, but may stll decde to not sgnal type at all. 17 One possble sgnal stategy that satsfes tuth-tellng has an applcant nque about the apatment whle not sgnalng the type. Such an nquy mmcs ou "no nfomaton" case. Hgh-type applcants wll always fnd t advantageous to eveal the type to sepaate themselves, howeve, low-type applcants can ncease the esponse ate by non-evelaton and poolng wth the aveage applcant type. Such a poolng equlbum pesents two poblems fo ou analyss. Fst, the aveage sgnal x s no longe the analogue of the aveage type, but the mean of low 16

18 and aveage types. Ths lowe aveage sgnal lowes the pedcted esponse ate to no nfomaton and the ntepetaton of the gaps between t and othe sgnals. Ou model s obust to ths ntepetaton as we could magne the landlod uses the aveage of past no nfomaton nques and ntevews, nstead of usng the aveage sgnals of all past applcants, to foecast type. The mplcatons of dffeence-n-dffeences estmates eman unchanged. Second, unde poolng t s no longe optmal fo low-type applcants to send sgnals conguent wth the type and thus, the sgnals we send as eseaches do not ft nto the landlods decson-makng famewok. e beleve the combnaton of costs of ntevew fo applcants and landlods wth dffeent qualty thesholds geneates a sepaatng equlbum n sgnals. Recall that the model s ental pocess ncludes costs on both the landlod and successful applcant n stage 3. hat does the low-type applcant s non-evelaton stategy accomplsh? th a hghe expected esponse ate elatve to full evelaton, low type applcants have nceased the expected cost of ntevewng. Suppose that some landlods would have ejected the low-type applcant f the sgnal matched the type. If thee s a suffcent facton of such landlods, low-types wll sk payng fo ntevews they ae cetan to fal. Sendng a low-type emal benefts the low-type applcant though moe accuate nfeence of the landlod s lkelhood of entng the apatment. Poolng adds sgnfcant nose and hghe cost. e theefoe conclude that the low-type emals that we send n ou desgn wll be consdeed atonal fom the pespectve of the landlod. C. Taste-ased Dscmnaton Dffeental outcomes by ace may also ase fom pejudce. In ths secton, we pesent a model of taste-based dscmnaton that offes competng testable mplcatons. Any model o theoy of utlty that attempts to explan acal o ethnc pejudce should satsfy cetan ctea. Fst, all 17

19 aces exhbt out-goup pejudce, whch s a typcal assumpton made n most studes of dscmnaton (Ynge 1986). Second, f an ndvdual s pejudce and sk avese, sk aveson should not ncease utlty fom out-goups moe than n-goups. To contast wth statstcal dscmnaton, we assume that a pejudced landlod pedcts applcant qualty based on ace-ndependent sgnal usng a pooled OLS egesson: ˆ ˆ ˆ x (16) L The ntecept and slope n equaton (16) ae ace-nvaant. 18 Poolng by ace mples that the sample means and vaances estmated ae also ace ndependent. Agan, assume that the landlod s sk avese and maxmzes expected utlty by choosng n ndependent applcants to espond to postvely fo ntevews, gven a constant magnal cost of ntevew, c, and a capacty constant, n M. Futhe, assume that the utlty functon belongs to a class of mean-vaance utlty functons and the landlod deves geate expected (magnal) utlty of pedcted qualty fom an n-goup applcant than an out-goup applcant. ~ ~ ~ ~ Fo a gven pedcted qualty fomed ( ) usng equaton (16): E U( )] E[ U( )]. [ Consde, fo example, a pejudce paamete, k, whch dscounts the magnal utlty of pedcted qualty deved fom an out-goup applcant. Ths famewok contasts wth that of statstcal ~ ~ ~ ~ dscmnaton, whee E[ U( )] E[ U( )], f. The utlty specfcaton s agnostc about the undelyng eason fo pejudce: t can be the landlod s own pejudce aganst the outgoup o because of custome pejudce whee the landlod dscmnates aganst out-goup applcants fo fea of offendng pejudced n-goup tenants. Snce the vaance of pedcted qualty s ace nvaant, we focus solely on the mplcatons of sk-neutal landlods. 19 C.1 Testable Implcaton 5 18

20 Gven equaton (16) and geate magnal utlty of pedcted qualty fo n-goup applcants than fo out-goup applcants, f emal nques eveal only the aces of applcants, an aveage landlod who s whte wll be less lkely to espond to a black applcant than a whte applcant. Testable mplcaton 5 gves: Hypothess 1A On aveage, a whte applcant s moe lkely to eceve a postve esponse than a black applcant n the no-sgnal base case. Thus, hypotheses 1 and 1A ndcate that any dffeences n postve esponses fo the ace-only nques could stem fom ethe pefeence o statstcal dscmnaton. C.2 Testable Implcaton 6 As the magnal expected utlty of pedcted qualty s geate fo whte than fo black applcants fo an aveage landlod, an ncease n sgnal benefts the whte applcant moe than the black applcant. Testable mplcaton 6 yelds: Hypothess 2A On aveage, the esponse gap between whte and black applcants when postve sgnal s sent s lage than the esponse gap between whte and black applcants when negatve sgnal s sent. C.3 Testable Implcaton 7 hen a postve sgnal geate than the mean sgnal ( x ) s sent, equaton (16) combned wth pejudce pedct the landlod s esponse gap between whte and black applcants wll wden. hen a negatve sgnal below the expected sgnal fo applcants s sent, the landlod s esponse gap between whte and black applcants wll naow. Theefoe, the pedctons dffe slghtly fom those unde statstcal dscmnaton: 19

21 Hypothess 3A On aveage, negatve nfomaton wll unambguously naow the acal gap obseved n the no-sgnal base case, but postve nfomaton wll unambguously wden the acal gap obseved n the base case. C.4 Testable Implcaton 8 As the shae of black esdents n a neghbohood (S ) nceases, the pobablty that a landlod entng n that neghbohood s black also nceases. 20 Ths mples that the facton of landlods havng pejudce aganst black applcants deceases. Theefoe, Hypotheses 1A, 2A, and 3A wll swtch sgn o decton as we move fom a majoty whte neghbohood to a majoty black neghbohood, leadng to: Hypothess 4A As the shae of black esdents n a neghbohood S nceases, the esponse gap between whte and black applcants n the base case deceases. In a majoty black neghbohood, a supsng postve sgnal wll unambguously beneft a black applcant elatvely moe than a whte applcant, whle a supsng negatve sgnal wll unambguously hut a black applcant elatvely moe than a whte applcant. III. Expemental Desgn and Econometc Specfcatons To examne the eght hypotheses lsted n the pevous secton we expementally manpulate ace and sgnals pesented n emals to landlods who lsted ental apatments on Cagslst. 21 Emal s an excellent vehcle to test the model mplcatons and Cagslst seves as an deal expemental platfom wth ts focus on emal communcaton. Fst, Hypotheses 1 and 1A eque lmtng the nfomaton to agents to just ace, whch s staghtfowad n emal coespondence but dffcult n audt n-peson studes o othe coespondence expements. Next, Hypotheses 2, 3, 2A, and 3A demand clea sgnals that ae also unambguously dstnct 20

22 (.e. postve vs. negatve), whch can be flexbly ntoduced n emals. Fnally, the low cost of emal and the populaty of Cagslst n the U.S. povde us wth a lage sample of agents. 22 A. Expemental Subjects and Rental Maket Data e use landlods who posted lstngs on Cagslst, an onlne classfed ad webste of enomous populaty, patculaly amongst apatment seekes, as ou expemental subjects. As of 2009, 40 mllon unque ntenet vstos vew Cagslst each month and the ste s often consdeed one of the pncpal factos esponsble fo the shap fall of newspape classfed ad evenues. 23 Accodng to a study by ntenet eseach fm Htwse, about 95% of vsts to onlne classfed webstes ae to Cagslst. 24 Data fom Pew Intenet & Amecan Lfe Poject eveal that oughly 44% of black and 49% of whte ntenet uses have at some pont used onlne classfed ads lke Cagslst (Table 1). These Cagslst uses, whethe black o whte, epesent oughly one-thd of the adult populaton n the U.S. They ae slghtly younge and moe educated than non- Cagslst uses and non-ntenet uses, and they ae moe lkely to be hgh-ncome eanes, employed full-tme, and apatment entes. Howeve, black Cagslst uses ae younge and less educated, and moe lkely to be low-ncome eanes, sngle, and entng apatments than whte Cagslst uses. Thus, fndngs based on Cagslst wll be elevant fo a lage facton of black and whte adults, especally those usng ntenet and onlne classfed ads. Ou apatment selecton algothm attempted to elmnate scams, msplaced lstngs, epeated lstngs, and lstngs posted by ndvduals wth non-landlod ncentves. Those wth non-landlod ncentves nclude employees of lage copoatons managng dozens of apatments and pvate apatment fndes who make a lvng as mddlemen between landlods and entes. Sampled apatments nclude only one-bedoom and studo lstngs so as to avod concens of oommates, chlden, etc., and ensue compaable ents between any two unts wthn an aea. 21

23 Only one nquy pe lstng was sent, and numeous pecautons wee taken to avod sendng multple nques to the same landlod and/o the same lstng. 25 The seach algothm checked whethe a new postng had a phone numbe, emal o web addess aleady encounteed. thn each cty, the sample excludes unts wth ents below the 20 th and above the 90 th pecentle to avod sendng emals to stoage lockes, weekly entals o homes fo sale. Fnally, emals wee sent ove thee ntevals of tme afte the lstng was posted wth an uppe lmt of 48 hous. Table 2 lsts the ctes suveyed, the numbe of emals sent n each cty, the numbe of neghbohoods (census tacts) fom whch postngs wee souced, the shae of black populaton n each cty, and the aveage ents of apatments to whch we sent emal nques. 26 The aveage shae of black esdents acoss the sampled neghbohoods s smla to the actual shae of black populaton n the geate metopoltan aea n Census Emal Geneaton and Expemental Teatments As ths study focuses solely on emal coespondence, the only mechansm fo sgnalng the ace and gende of the applcant s a stated name. To maxmze the pobablty that landlods wll obseve ths sgnal, the full name of the fcttous applcant s pesented thee tmes n evey emal: fst n the emal addess, whch s always of the fom fst.last<andom numbe>@doman.com, second n the ntoductoy sentence of the emal text, and thd n the closng sgnatue of the emal. Fst names chosen ae those utlzed by etand and Mullanathan (2004), combned wth sunames souced fom the U.S. Census 2000 Famly Name Suvey. Names esultng fom ths combnaton nclude: Allson aue, Ebony ashngton, Matthew Klen, and Danell ooke. 27 Each emal text was geneated by andomly selectng the text fo each of the fve elements numeated n the sample emals n Illustaton 1. th the excepton of the statement of 22

24 qualty, all text was pulled fom the same pools. (1) s an ntoductoy hello statement. (2) s a statement of nteest n the apatment whch always ncludes the ent of the unt beng appled to (to avod confuson n case the landlod has posted multple lstngs). (3) s a statement of qualty whch s andomly ncluded (o not ncluded) to defne ou teatments. (4) s an nquy statement egadng the avalablty of the unt (e.g. s ths apatment stll avalable? ). Ths gves the landlod a specfc queston to espond to, allowng us to dentfy automated esponses and test fo dffeences n postve esponses between goups. (5) s a closng whch thanks the landlod and s always followed wth the applcant s full name. Element 3, the statement of qualty, s ncluded n appoxmately two-thds of all emals. The emal texts that do not nclude a statement of qualty ae sad to belong to the baselne teatment o base case. In ths teatment, landlods know nothng of the applcant except the name and the nteest n entng the apatment. The models detaled above assume that landlods smply take the aveage sgnals by ace o ndependent of ace as a poxy sgnal n ths baselne scenao. Statstcally dscmnatng landlods may expect ou fctonal black applcants to be less desable than ou fctonal whte applcants n the base case snce a typcal black Cagslst use has lowe soco-economc status than a typcal whte Cagslst use (Table 1). hen the statement of qualty s ncluded, t dscloses ethe postve o negatve nfomaton. Postve nfomaton always nfoms the landlod that the applcant has a good job and does not smoke. Negatve nfomaton always nfoms the landlod that the applcant smokes and has a bad cedt atng. These patcula peces of nfomaton wee selected because they ae unambguously postve o negatve. The pupose of ths methodology s not to detemne how any specfc pece of nfomaton affects outcomes, but nstead to test how postve o negatve nfomaton, n geneal, affects outcomes. 28 It s dffcult to magne a scenao n whch a 23

25 landlod would beneft fom a tenant who smokes o has bad cedt. Lkewse, t s dffcult to magne a landlod beng hamed because a tenant has a good job o does not smoke. Landlods typcally vefy chaactestcs such as cedt wothness and smokng habts n the ntevew stage and commonly ask applcants to pay fo cedt atng checks. As we dscussed n Secton II., t s atonal fo some low-type applcants to eveal the type n the emal nquy because full evelaton may educe the cost of gettng an apatment. 29 Futhemoe, ou focus on how landlods teat negatve sgnals dffeently by ace ensues that any peculaty n the sendng of negatve sgnals s dffeenced out. Last, gven the aveage chaactestcs of onlne classfed ad uses epoted n Table 1, the negatve nfomaton s lkely supsng to landlods, povdng a stong teatment effect. Ths pocess of nquy geneaton comes wth a sgnfcant beneft. y pullng all texts andomly fom the same pools and defnng the teatments entely by the statement of qualty alone we assue that any dffeences n landlod esponses ae the esult of ou teatments and not the ntoducton o nquy texts. Table 3 summazes the numbe of emals sent by each applcant type as defned by the ace, gende, and teatment. C. Categozng Outcomes The smplest esponse chaactestc s whethe o not a gven nquy eceves a esponse. Responses wee futhe classfed nto one of seveal categoes. To avod expemente bas n ths categozaton, all nstances of applcant names (fst and last, as well as emal addess) and ognal bodes of text sent wee automatcally emoved fom vew dung categozaton. oadly, esponses ae classfed as ethe postve o negatve. Postve esponses state that the unt s avalable and nvte futue contact n some manne. Negatve esponses nclude the nonesponse emals and those ethe statng that the unt s not-avalable, o statng that the unt s 24

26 avalable, but n a dscouagng manne. Each nquy sent ended wth a queston such as Is the apatment avalable? Some 95% of landlods that answeed Yes to that queston also asked fo futhe contact nfomaton (coded as a postve esponse). An emal esponse that smply ead Yes lacks any dect contact nfomaton o nteest and lkely meant the landlod was not encouagng the applcant fo futue vewng of the unt, and was classfed as Dsnteested. The categozaton pocess s cucal to ou esults as we ae pmaly nteested n the dffeental teatment of black and whte applcants by landlods. Dffeences n the lkelhood of smply ecevng a esponse may be msleadng, snce one goup may eceve a lage shae of negatve esponses than the othe. Ou caeful eadng and categozaton of all landlod esponses takes nto account the mpotance of the contents of a esponse. D. Econometc Specfcatons e estmate fou egesson equatons to test ou hypotheses. Fst, the empcal specfcaton to test hypotheses 1 and 1A s: R = a + a + u (17) R s 1 f the landlod ownng apatment esponded postvely, 0 othewse; s 1 fo an applcant wth an Afcan-Amecan soundng name, 0 othewse; and u s an eo tem. e expect < 0. ecause almost all ou empcal specfcatons nvolve dchotomous egessos, we use lnea pobablty model (OLS) to estmate all ou empcal specfcatons. 30 Second, the followng dffeence-n-dffeences specfcaton tests hypotheses 2 and 2A: R ( ) ( N ) ( N ) u. (18) P P N N N takes the value of 1 fo negatve nfomaton, 0 fo postve nfomaton. The omtted categoy s postve nfomaton fo whtes. If the aveage landlod weghts sgnals fom whte applcants moe heavly than those fom black applcants ( g > g ) o the magnal utlty of expected 25

27 qualty fo whtes s geate than fo blacks, we expect a N to be postve, esultng n a geate magnal etun to sgnal fo whte applcants. e estmate the followng dffeence-n-dffeences egesson to test hypotheses 3 and 3A, whch could sepaate the mplcatons of statstcal and taste-based dscmnaton: R ( ) ( P ) ( P ) ( N ) P P N N ( N ) u. (19) The omtted categoy s no nfomaton fo whtes. The coeffcents b and b N measue the extent of shnkage n the acal gap of postve esponse ates n the pesence of a (supsng) postve and negatve sgnal. If hypothess 3 s tue, we expect that N 0 and the sgn of P ambguous. If hypothess 3A s coect, we expect that 0 and the sgn of 0. Hence, falng to eject 0 wll cast doubt on taste-based dscmnaton. P Fnally, the followng empcal specfcaton tests hypotheses 4 and 4A: N P P R S SP ( S ) ( ) S( S ) P ( P ) SP ( S P ) P ( P ) ( S P ) N ( N ) SN ( S N ) N( N ) ( S N ) u (20) SN S measues the facton of black esdents n the neghbohood (%lack) n whch apatment s lsted and t anges between 0 and 1. The tems S and S allow the (unobseved) expected value of X n the statstcal dscmnaton model o pejudce paamete to vay acoss dffeent types of neghbohoods and ace. If landlods expeences wth black applcants ncease the sze of the nfomaton weghtng paamete as the statstcal dscmnaton model postulates, then we expect d > 0 and SN ambguously sgned. If landlods entng n a SP pedomnantly black neghbohood exhbt a pefeence fo black esdents elatve to landlods 26

28 entng n neghbohoods wth a lesse shae of black esdents, then we would expect d S to be postve. Moeove, f pejudce s dvng the obseved acal dffeentals, we would expect supsng postve nfomaton to help black applcants moe and supsng negatve nfomaton to hut black applcants moe as S nceases, such that 0 and 0. SP SN IV. Results Table 4 pesents summay statstcs of vaables geneated n ou expement, chaactestcs of the lsted apatments, and esponses fom landlods. Of the 14,237 nques sent, 9,229 (65 pecent) eceved a esponse. Of these esponses 6,597 (46 pecent) wee postve as defned n secton III. Fgue 2 shows the dstbuton of the shaes of black esdents n census tacts of lsted apatments ( S n equaton (20)). The measue anges fom 100 pecent whte to pecent black wth a mean of 12.4 pecent black esdents. Table 5 vefes that the chaactestcs of ou fcttous whte and black applcants ae statstcally smla and not coelated wth chaactestcs of lsted apatments by teatment types. A. Effectve Infomatonal Teatments Table 6 epots esponse ates fo postve and negatve teatment elatve to the baselne of no sgnal, poolng all applcants. Postve esponse ate s a less nosy measue of expected applcant qualty than esponse ate. Compang the ntecept tems n column (1) and column (3), whch measue esponse and postve esponse ates espectvely n the baselne teatment, eveals that oughly 18 pecent of esponses n the baselne wee negatve n some way. Ths means that the smple ate of esponse s lkely to msepesent whethe landlods encouaged futue contact. Futhemoe, the estmates n column (1) and column (3) show that landlods ae equally lkely to eply to an emal nquy 27

29 whethe o not the applcant has evealed somethng postve about heself, but landlods ae moe lkely to eply wth a ejecton f the tenant evealed nothng about he qualty. Theefoe, consdeng a no esponse as equvalent to a yes esponse s lkely to nvte eo nto ou data ntepetaton. As shown n column (3) of Table 6, applcants n the postve teatment goup eceve a sgnfcantly hghe postve esponse ate than baselne applcants (0.57 vs. 0.53). The effect of postve teatment s slghtly hghe fo females (0.04) than fo males (0.03). On the othe hand, column (4) shows that applcants n ou negatve teatment eceve a sgnfcantly lowe postve esponse ate than baselne applcants (0.32 vs. 0.53). The sgnfcant dffeences llustate that the teatments effectvely manpulated landlod nteest n the fctonal applcants. Fnally, the nsgnfcant dffeences n esponse ates acoss gende and ndependent of ace lead us to pool gendes heeafte.. Hypotheses 1 and 1A: lack Applcants eceve Lowe Response Rate Column (1) n Table 7 confms hypotheses 1and 1A that landlods, on aveage, ae moe lkely to espond to applcants wth whte soundng names than applcants wth Afcan-Amecan soundng names when no othe sgnal of qualty s dsclosed n an emal nquy. The estmated coeffcent on lack of s hghly sgnfcant and confms pevous fndngs of dscmnaton aganst Afcan Amecans o pesons wth Afcan-Amecan soundng names. Combned wth the ntecept estmate of 0.581, applcants wth Afcan-Amecan soundng names eceve about 84 postve esponses fo evey 100 eceved by applcants wth whte soundng names. The estmates ae consstent wth both the ntepetaton that aveage landlods expect aveage black applcants to have lowe qualty than aveage whte applcants and have pejudce aganst black applcants. 28

30 C. Hypotheses 2 and 2A: Postve Infomaton vesus Negatve Infomaton Column (2) n Table 7 pesents the dffeence-n-dffeences estmates fo equaton (18). It shows that the estmated coeffcent of the dffeence-n-dffeences effect of negatve teatment fo black s sgnfcantly postve (0.042). It s consstent wth hypothess 2 that on aveage, g > g, so sgnals fom whte applcants eceve elatvely moe weght n an aveage landlod s estmate of qualty. The estmates also confm hypothess 2A that pejudce aganst black applcants can geneate a lage esponse gap between whte and black applcants as sgnal nceases. Thus, the estmates ae consstent wth both statstcal and taste-based dscmnaton. D. Hypotheses 3 and 3A: The Effects of Supsng Sgnals If statstcal dscmnaton s the man explanaton fo the dffeental outcome, unde the hypotheszed elatve sgn of the nfomaton weghtng paamete, we expect supsng negatve nfomaton wll close the acal gap epoted n column (1) n Table 7, but supsng postve nfomaton wll not necessaly do so (hypothess 3). In contast, f pejudce s the pedomnant explanaton fo the dffeental outcome, then the acal gap wll unambguously amplfy wth postve nfomaton and unambguously close wth negatve nfomaton (hypothess 3A). In Table 7 column (3), the statstcally negatve coeffcent on negatve nfomaton and postve coeffcent on Negatve Infomaton x lack ae consstent wth both hypotheses 3 and 3A. It shows that dsclosng negatve nfomaton about an applcant s qualty leads to a geate educton n a whte applcant s pobablty of ecevng a postve esponse. In patcula, the negatve nfomaton almost halves the acal gap obseved n the baselne teatment. Table 7 column (3) also shows that the magnal etun to sgnalng a espectable occupaton and non-smokng behavo nceases postve esponse ate by 6.7 pecent (0.039/0.581) fo whtes. Howeve, the coeffcent on the nteacton tem lack x Postve 29

31 Infomaton s statstcally ndstngushable fom zeo. oth black and whte applcants beneft fom the ncluson of postve nfomaton, but the nfomaton does not wden o naow the acal gap obseved n the base case. Ths esult s consstent wth hypothess 3, athe than hypothess 3A, and confoms to the statstcal dscmnaton model s pedcton that g > g : the aveage landlod weghts dentcal nfomaton moe fom whte applcants. Although the postve nfomaton s much geate than the mean sgnal fo black applcants, the elatonshp g > g attenuates any mpovement n sgnal. Taste-based dscmnaton cannot geneate ths fndng as t pedcts that a postve supse wll unambguously wden the acal gap. E. Hypothess 4 and 4A: Dffeences by Infomaton Types acoss Neghbohoods The fnal model pedcton of statstcal dscmnaton states that the dffeence g -g s negatvely elated to the shae of blacks n a ental popety s neghbohood. A landlod n a pedomnantly black neghbohood pesumably has moe expeence sceenng and entng to black esdents, loweng the elatve nose of sgnals fom black applcants. So, the weghtng paametes fo black and whte applcants appoach each othe as the shae of black and whte esdents equalze. On the othe hand, f pejudce s dvng the obseved acal gap, then as the shae of black esdents and ownes nceases, taste-based dscmnaton wll lead to a shnkng acal gap n the baselne. Also, supsng postve nfomaton nceasngly benefts black applcants moe than whte applcants and supsng negatve nfomaton nceasngly huts black applcants moe than whte applcants. Column (4) of Table 7 pesents evdence that dffeental outcomes by ace vay wth the acal composton of an apatment s neghbohood (%lack) n a manne consstent wth statstcal dscmnaton. The statstcally sgnfcant and postve coeffcent on the nteacton tem Postve Infomaton x lack x %lack ndcates that as the shae of black esdents n a 30