Statistical Discrimination or Prejudice? A Large Sample Field Experiment. Michael Ewens, Bryan Tomlin, and Liang Choon Wang.

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1 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 manne consstent wth statstcal dscmnaton and n contast to pattens pedcted by a model of taste-based dscmnaton. JEL Codes: J15, J70, J71, R3. Afflatons: Teppe School of usness, Canege Mellon Unvesty; NERA Economc Consultng; Depatment of Economcs, Monash Unvesty. e benefted temendously fom the comments of Kate Antonovcs, Godon Dahl, Godon Hanson, Pushka Mata, enda Ra, Zaha Sddque, and seveal anonymous efeees. e also thank El eman, Matn og, Vnce Cawfod, Jule Cullen, en Gllen, Jacob LaRvee, Mke Pce, Valee Ramey, and Kunal Sengupta. e acknowledge the fundng suppot fom the Insttute fo Appled Economcs at the UC San Dego.

2 I. Intoducton Racal and ethnc dscmnaton pevades many makets n the U.S. Roughly half of the dscmnatoy cases epoted by fedeal agences nvolve ace o ethncty, and the numbe of epoted new ncdents outpaced populaton gowth ove the past 10 yeas. 1 The 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 n whch 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 U.S. ental apatment maket, we test whethe statstcal o taste-based dscmnaton can explan dffeental outcomes between whte and Afcan-Amecan ental applcants. e extend Agne and Can s (1977) and Mogan and Vady s (2009) models of statstcal dscmnaton to test the key featue of statstcal dscmnatos: heteogeneous expeence. 3 The model posts that landlods dffe n the peceptons of sgnals due to past expeence n the sceenng and ental pocess and place a geate weght on sgnals fom the famla goup than the unfamla goup n makng decsons. e contast the pedctons wth those of taste-based dscmnaton, n whch pejudced landlods use nfomaton ndependent of ace to pedct expected tenant qualty but deve lowe magnal utlty fom entng to the out-goup. e show that lowe magnal etun to sgnal of qualty fo mnoty goups s consstent wth both statstcal and taste-based dscmnaton, 1 Fo statstcs on dscmnaton chages epoted by the U.S. Equal Employment Oppotunty Commsson, see 2 Aow (1973) and Phelps (1972) fst dscuss statstcal dscmnaton and ecke (1957) detals pejudce. 3 Also see Conell and elch (1996) fo a model of statstcal dscmnaton whee agents can bette ntepet sgnals fom the own cultue, ace, o ethncty. 1

3 hghlghtng the empcal hudle nvolved n attemptng to sepaate the two explanatons. The model gudes ou expemental desgn. Usng vacancy lstngs on Cagslst.og (Cagslst), an onlne classfed ad webste, acoss 34 U.S. ctes, we send nquy emals wth two key components to 14,000 landlods. e use the common, acal-soundng fst names employed by 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, landlods eceve emals wth acal-soundng names as the only sgnal. In the postve nfomaton nquy, the fctonal applcant nfoms the landlod that she s a nonsmoke wth a espectable job. In the negatve nfomaton nquy, the applcant tells the landlod she has a below-aveage cedt atng and smokes. 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 nfluence fnal outcomes n the same decton. Snce esdental locatons ae ted closely 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 the domnant souce of onlne classfeds fo apatment lstngs n the U.S., Cagslst s fequented by one-thd of the whte and black U.S. adult populaton. The gowng pevalence of onlne nteactons n eal estate, employment, fnance, and auctons suggests the esults extend beyond the ental apatment maket. The expement yelds fou majo esults. Fst, when no-sgnal nquy emals ae sent, applcants wth Afcan-Amecan soundng names have a 9.3 pecentage pont lowe postve esponse than applcants wth whte soundng names. Second, usng a dffeence-n-dffeences 2

4 (heeafte DD) estmato, we show that the acal gap n esponse ates wdens n the swtch fom negatve to postve nfomaton. oth fndngs ae consstent wth statstcal dscmnaton and pejudce, as they follow fom landlods placng moe weght on sgnals sent by whte applcants than black applcants o landlods ecevng a geate magnal utlty of entng fom whte applcants than fom 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 no-sgnal base case acts as a benchmak fo unnfomed expectatons and as a means to quantfy supse elatve to the bette-than-expected (postve) and wose-than-expected (negatve) sgnals. Ths noton of a supsng sgnal s dffcult to ntoduce n a job applcaton settng n whch esumes ae equed, as t s mpossble to povde zeo nfomaton about educaton o expeence n a esume. th 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 that 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 sgnals fom that acal goup. Convesely, taste-based dscmnaton pedcts that f landlods exhbt out-goup pejudce and that f the ace and acal pefeences ae coelated wth neghbohood acal composton, as the shae of blacks n a neghbohood nceases, 3

5 dscmnaton aganst black applcants n the base-case wll attenuate. Supsng negatve nfomaton, n contast, wll hut black applcants moe. 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 basecase acal gap pessts acoss all types of neghbohoods and contadcts the pedcton of tastebased dscmnaton. Ths pape extends the lage body of eseach on acal dscmnaton. th the excepton of Lst (2004) and Levtt (2004), past evdence of statstcal dscmnaton s nconclusve. Altonj and Peet (2001) and etand and Mullanathan (2004) fnd 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. Audt studes, such as Ynge (1986) and Page (1995), show dscmnaton aganst mnotes n U.S. housng makets. These esults may suffe fom the confoundng factos nheent to n-peson audt studes, as they ely on actos who often dffe n many 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. Ou appoach dffes fom those of pevous studes and contbutes to the lteatue n seveal ways. e model explctly how and why statstcal and taste-based dscmnaton n the sceenng pocess can each pedct lowe magnal etun to sgnal fo the dscmnated-aganst goup, whch potentally esolves some contadctoy hypotheses and fndngs n the 4 Fo othe envonments, see Ayes and Segelman (1995) (automoble sales), Sddque (2011) (labo maket), Antonovcs et al. (2005) (game shows), and Doleac and Sten (2010) (onlne sales). 5 See Page and Shephed (2008) fo moe examples and Heckman (1998) fo a ctque on audt expements. 4

6 dscmnaton lteatue. e extend Agne and Can s (1977) and Mogan and Vady s (2009) non-pejudce dscmnaton famewok and juxtapose t wth a pejudce dscmnaton famewok to pemt a eseach desgn that sepaates statstcal and taste-based explanatons empcally. Ou famewok also allows fo landlod sk aveson and ou fndngs ae obust to ths specfcaton. In othe empcal wok, Ahmed et al. (2010) and osch et al. (2010) ague that statstcal dscmnaton mples educed dscmnaton aganst mnotes wth nceased postve nfomaton. They show, howeve, an unchangng acal gap n the lkelhood of postve esponses when postve nfomaton s ntoduced n ental emal nques and ague that the fndng suppots taste-based 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 deceased eply dffeences between whte and Afcan-Amecan ental applcants fom mpovng the pose qualty of emals suggest statstcal dscmnaton. ecause eply ates decease wth class fo whte applcants, howeve, 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 n most feld expements. II. Dscmnaton n Sceenng and Testable Implcatons e pesent a model to gude ou eseach desgn and to dstngush between statstcal and taste-based dscmnaton n the ental apatment maket. 6 A landlod seeks to maxmze the expected utlty of ntevewng each applcant, subject to a capacty constant of M ntevews 6 Although specfc to the ental maket, the model should extend to othe stuatons of sem-fomal sceenng. 5

7 and a constant magnal cost of ntevew c (.e., a budget constant of cm). The expected utlty deved fom each applcant depends on the steam of futue ental ncome (.e., tenant qualty) fom entng the apatment successfully. Ths qualty s summazed by. Although the ent s peannounced, may stll vay as a esult of default, lease enewal, and so on. Hence, the landlod foms a pedcted qualty ˆ (a andom vaable) fo each applcant and maxmzes the expected utlty E U( ˆ )]. [ Consde the followng fou-stage pocess of matchng potental tenants to apatments: 1. Inquy: An applcant wth qualty selects publcly posted ental unts to send costless nques wth sgnal x to landlods. 2. Sceenng: Gven sgnals X x,..., x } eceved fom T ndependent applcants, the T { 1 T landlod foms a set of pedcted qualtes ˆ,, ˆ } and esponds to n applcants. T { 1 T 3. Intevew: Intevews, whch nclude cedt and efeence checkng, eveal the tue qualty and cost of applcants and landlods m and c, espectvely. 4. Decson: The canddate wth the hghest tue qualty s offeed the apatment. Ths settng s smla to that of Mogan and Vady (2009), n whch employes have one vacancy, only want competent wokes, and eceve sgnals about the wokes types. That model has an addtonal stage n whch tue type s not evealed untl the he s complete. Ou expement can only dstngush statstcal and taste-based dscmnaton occung at stage 2 of the above pocess, and the esults ae consstent wth Mogan and Vady s (2009) patal equlbum, one-sded seach appoach. Nevetheless, we consde stages 2 though 4 n the model and dscuss the mplcatons of stategc sgnalng by applcants. A. Statstcal Dscmnaton 6

8 Suppose that sgnal x poxes the tue qualty nosly wth a ace-specfc eo : 7 x, (1) 2 whee ~ N (, ), E( ) 0, va( 2 ),, E x ) (, and va( x ). 2 2, The assumptons mostly coespond to those n Agne and Can s (1977) model, except that we pemt the sgnal mean to vay by ace. Landlods have a sample of nques x and applcants tue qualty acqued dung past teatons of stages 2 and 3 outlned above. Usng ths sample, a landlod can estmate the followng foecastng egesson fo each ace : ˆ ˆ ˆ x, (2) L whee L ˆ s the Odnay Least Squaes (OLS) estmato of the ntecept tem; ˆ s the estmato of the magnal effect of sgnal x ; and s fo whtes, and fo blacks. Estmates of L ˆ and ˆ wll vay acoss landlods because of the dffeng expeences. Equaton (2) s smla to the posteo belef n Mogan and Vady s (2009) o alsa and McGue s (2001) model. e assume, howeve, that landlods do not have po belefs about the tue means and vaances of qualty and sgnal but athe fom posteo belefs usng OLS estmates obtaned va past samples. Indeed, ayes s ule yelds the same L ˆ and ˆ unde a jont nomalty assumpton. 8 7 e may assume that x = + +, but t does not change the model s pedctons. 8 As landlods ae not nteested n the causal elatonshp between qualty and sgnal, but only pedctons that yeld the lowest vaance, OLS s sensble. It can be genealzed to a ayesan famewok. Fo nstance, landlods have po belefs that yeld the ntecept and slope of equaton (2) and update them as they obseve moe ealzatons of qualty and sgnal, as n Altonj and Peet s (2001) example of employe leanng. Ou focus on the ntal sceenng stage means that ths genealzaton s not necessay. 7

9 A landlod obseves sgnal x ~ and ace fom an applcant n stage 2 and pedcts the qualty by pluggng x ~ nto (2): ~ L ˆ ˆ ~ x. (3) e call ˆ the nfomaton weghtng paamete fo ace snce t nfoms a landlod how much to weght a sgnal fom an applcant of ace. 9 Some applcants may eveal only the ace n an emal nquy. 10 In ths case, the landlod nfes qualty usng the aveage sgnal ( nques n the followng foecastng egesson: x ) obseved among ace n past emal ˆ ˆ x. (4) L Equaton (4) s equvalent to the landlod usng some aveage among to fom a pedcton. 11 A.1 Statstcal Dscmnaton unde Rsk Neutalty and ts Implcatons Fo a sk-neutal landlod wth ace-nvaant utlty, f the total numbe of applcants s T M, the landlod esponds postvely to n of the T ndependent applcants, whee each yelds E[ U( ˆ )] c. If applcatons exceed capacty ( T M ), then the landlod wll sot all applcants by E U( ˆ )] and wll nvte the top M. As utlty and cost ae ace-nvaant, the decson ule s [ n lne wth Mogan and Vady s (2009) colo blnd theshold. Hee, the decson ule wll be some. As statstcal dscmnaton nfluences a landlod s decson though outcomes by ace ase though the OLS estmatos n equaton (2): ˆ, dffeental 9 Ths s not stctly a paamete, but a landlod s estmato of the paamete of the egesson model. 10 See secton III fo an example of such an nquy. 11 See subsecton fo the mplcatons when applcants stategcally eveal no nfomaton. 8

10 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 and x ae the sample aveage of qualty and sgnal of applcants, espectvely. Despte unobsevablty of L ˆ and ˆ, 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 each landlod s sample of and x wee obsevable, we could 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. Gven the assumpton 2 E [côv(, x )] E[côv(, x )], equaton (7) shows that any dffeences n nose of sgnals, E [vâ( x )], can nduce dffeences n the weght placed on the same sgnal fom dffeent aces. Fo example, landlods wth E[vâ( x )] E[vâ( x )] wll have. 12 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 o on nose acoss ace. Dffeences n mean sgnal o nose could stem fom 12 Hee, assumng qualty vaance ( 2 ) s the same acoss ace s cucal. Note that cov(, x ) = va( ) = 2, gven the assumpton that ~ N(, 2 ). e dscuss the obustness of ou esults to ths assumpton n secton V. 9

11 fundamental acal dffeences n sgnals such as ncome o cedt scoes of the populaton o smply fom those obseved by landlods n the samples. th andom assgnment of ace = {, } 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: 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. If we assgn a negatve sgnal ~ x 0 o a postve sgnal ~ x 0 and ace andomly to dffeent applcants and pesent them to andomly selected landlods, we can use a DD 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) 10

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 ). 13 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 dealng wth whte tenants than black tenants. These landlods aveage sample vaance of sgnals fom whte applcants wll be smalle than that fom black applcants because of neghbohood sotng. 14 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. So we have: 15 Hypothess 2 On aveage, the postve esponse gap between whte and black applcants s lage wth a postve sgnal sent than wth a negatve sgnal sent. 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 x valdate whethe sgnals lead to dffeences n esponses that ae consstent wth. 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 ), 16 we have ~ ( )] [ ~ x E x x E( x )]. The expementally ( x [ 13 The fact that sgnals ae not d has no beang on the landlod s decson to use OLS, snce the landlod caes only about gettng the best lnea pedcton. 14 Appendx A shows how dffeences n the vaance of sgnals acoss acal goups may ase. 15 e assume that applcants ae tuthful and that thee s a sepaatng equlbum n sgnals by type. 16 As evdent n past studes showng Afcan-Amecans havng lowe aveage socal-economc backgounds than whte Amecans (Has, 2010). 11

13 manpulated negatve nfomaton wll be a geate supsng sgnal fo whtes than fo blacks: ~ ( )] [ ~ [ x E x x E( x )]. Dependng on the elatve szes of and, the pattens of landlod esponses wll dffe. 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 [ 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, compaed 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 satsfed. 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. 12

14 The model mples 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 vaes wth E [vâ( x )] n the decton pedcted by the model, t suggests that landlods behavos ae consstent wth ou model of statstcal dscmnaton. 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 (hypothess 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). Thus: Hypothess 4 Postve teatment should shnk the acal gap n postve esponses 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. 17 A.2 Rsk Aveson and Implcatons To assess the mplcatons of landlod sk aveson, assume that the landlod s expected utlty takes a mean-vaance fom (e.g., exponental utlty). Hee, the vaance of the pedcted 17 Pevous dscmnatoy behavo mght contbute to segegaton and vaaton n neghbohood acal composton. If ths 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. 13

15 qualty geneates anothe souce of dffeental teatment by ace. 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 landlod eve obseved. In the no-nfomaton base case, equaton (15) shows that compaed to a sk-neutal landlod, a sk-avese landlod futhe dscounts applcant sgnals fom the goup wth whch she has elatvely less expeence. Rsk aveson wll thus wden the esponse gap between whte and black applcants n Hypothess 1. hen a black applcant 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 the 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, neghbohood acal composton must only poxy landlods elatve expeences wth dffeent acal goups and 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 dentfyng 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 14

16 sgnals to ncease elatvely less than postve esponses to whte applcants supsng postve sgnals as S 1. Hee, the extent of sk aveson and the effect fom shnkng vâ( x ) on the vaance of pedcted qualty ae lage enough to offset the ncease n the nfomaton-weghtng paamete. e assess whethe ou esults ae senstve to ths possblty n secton V.. Stategc Sgnalng and Tuth-tellng The landlod s expected sgnal x assumed to be the aveage sgnal eceved n the landlod s hstoy depends cucally on the applcants sgnal choces. If applcants nstead send sgnals not dectly ted to the type (e.g., stategcally le o not eveal), the ntepetaton of dffeences n esponse ates may need to be alteed. Let thee be thee applcant types: hgh, aveage, and low. Suppose n stage 3 of the ental pocess that applcants pay a cedt check fee, landlods obseve tue applcant type, and eject any applcant who led n the fst stage. Hee, applcants wll neve fnd t advantageous to le about the type n the nquy stage. Applcants who do eveal the type ae stll tuthful, but may stll decde to not sgnal type at all. 18 Non-evelaton of type mmcs ou no nfomaton case. Hgh-type applcants wll always fnd t advantageous to eveal the type to sepaate themselves, but low-type applcants can ncease the esponse ate by non-evelaton and by 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 athe the mean of low 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 pedctons ae obust to ths scenao f landlods use the aveage of past no-nfomaton nques and ntevew esults to foecast 18 The agument also apples to ace evelaton. If the aveage whte applcant s of hghe qualty than the aveage black applcant, then the fome wll always eveal the ace n nques. 15

17 qualty. 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 do not ft nto the landlods decsonmakng famewoks. 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 applcants f the sgnals matched the types. If thee s a suffcent facton of such landlods, low-type applcants wll sk payng fo ntevews they ae cetan to fal. Sendng a negatve nfomaton emal thus 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 conclude that landlods teat negatve nfomaton emals as comng fom low-type applcants. C. Taste-ased Dscmnaton Dffeental outcomes by ace may also ase fom pejudce. Let a pejudced landlod pedct applcant qualty based on a ace-ndependent sgnal usng a pooled OLS egesson: ˆ ˆ ˆ x (16) L The ntecept and slope n equaton (16) ae ace-nvaant, whch esults n smla nvaance fo sample means and vaances. 19 Pejudced landlods use the same decson ule fo selectng applcants as above, but the utlty s now ace-dependent. Assume that the landlod exhbts out-goup pejudce such that a pejudce paamete, k, dscounts the (magnal) utlty deved fom an out-goup applcant ~ ~ ~ ~ so that E[ U( )] E[ U( )] when. Ths famewok contasts wth that of statstcal 19 e thank an anonymous efeee fo ths suggeston. 16

18 ~ ~ ~ ~ dscmnaton, whee E[ U( )] E[ U( )] f. As the pedcted qualty has acenvaant vaance, we focus solely on the mplcatons of sk-neutal landlods. e ntoduce a pejudce paamete nto the landlod s utlty functon, whch s smla to Knowles et al. s (2001) ace-vayng magnal cost. 20 Although ou pooled OLS assumpton s moe estctve, t avods addtonal assumptons about how pejudced landlods ncopoate nfomaton dffeently by ace, whle smultaneously not dscmnatng statstcally. 21 If a pejudced landlod nstead ncopoates nfomaton dffeently fo each ace by penalzng the out-goup wth a smalle slope and a lowe o equal ntecept n equaton (16), testable hypotheses smla to the pooled OLS egessons wll stll emege. C.1 Taste-based Dscmnaton Testable Implcatons Gven equaton (16) and geate magnal utlty fo n-goup applcants than fo outgoup applcants, f emal nques eveal only the aces of applcants, then: 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. Next, geate magnal utlty fo whte than fo black applcants mples that an ncease n sgnal benefts the whte applcant moe than the black applcant: Hypothess 2A On aveage, the esponse gap between whte and black applcants when a postve sgnal s sent s lage than the esponse gap between whte and black applcants when a negatve sgnal s sent. 20 If we nstead assume ace-vayng magnal cost, the testable hypotheses eman the same. 21 In addton to havng a pejudce paamete on the magnal seach (ntevew) cost, Knowles et al. (2001) allow the polce s (landlods ) belefs about the pobablty of gult (pedcted qualty) of motosts (applcants) wth a cetan chaactestcs (x) to dffe by ace, but they do not specfy how landlods ncopoate nfomaton dffeently by ace, whle smultaneously not statstcally dscmnatng. e take the poston that pejudce s a utlty/pefeence assumpton and ncopoate t only nto the utlty functon. 17

19 hen a postve sgnal geate than the mean sgnal ( x ) s sent, equaton (16) combned wth pejudce pedcts that the aveage landlod s esponse gap between whte and black applcants wll wden elatve to the base case. 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: 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. As the shae of black esdents n a neghbohood ( S ) nceases, the pobablty that a landlod entng n that neghbohood s black also nceases. 22 Ths mples that the facton of landlods havng pejudce aganst black applcants deceases. Theefoe, hypotheses 1A, 2A, and 3A wll swtch sgns o dectons 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 22 The coelaton between the shae of black homeownes and the shae of black esdents acoss publc use mco aeas s 0.96 n the Amecan Communty Suvey

20 Cagslst seves as an deal expemental platfom to test the model mplcatons because of ts focus on emal communcaton. 23 Fst, hypothess 1(A) eques lmtng the nfomaton avalable 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(A) and 3(A) demand clea sgnals that ae also unambguously dstnct (.e., postve vs. negatve), whch can be ntoduced n emals n a flexble way. Fnally, the low cost of emal and the populaty of Cagslst n the U.S. povde us wth a lage sample of agents. 24 A. Expemental Subjects and Rental Maket Data e use landlods who posted lstngs on Cagslst as ou expemental subjects. As of 2009, 40 mllon unque Intenet vstos vew Cagslst each month and the ste s often consdeed one of the pncpal factos esponsble fo the shap fall n newspape classfed advetsement evenues. 25 Reseach fm Htwse found that Cagslst eceves 95% of vsts to onlne classfed webstes. 26 Data fom the Pew Intenet & Amecan Lfe Poject eveal that oughly 44% of black and 49% of whte Intenet uses have, at some pont, used onlne classfed advetsements lke Cagslst (table 1). These Cagslst uses, whethe black o whte, epesent oughly one-thd of the adult populaton n the U.S. Thus, fndngs based on Cagslst wll be elevant fo a lage facton of black and whte adults, especally those usng Intenet and onlne classfed advetsements. e elmnate scams, msplaced lstngs, epeated lstngs, and lstngs posted by ndvduals wth non-landlod ncentves. Those wth non-landlod ncentves 23 The expement was conducted between 9/2009 and 10/ The full (detaled) expemental desgn s avalable upon equest. 25 A epot by AIMGoup shows newspape classfed advetsement sales fell fom $16 mllon to $5mllon between 2005 and 2009, whle Cagslst s evenue gew fom $18 mllon to ove $100 mllon ove the same peod. 26 Appoxmately 2.5% of all U.S. Intenet vsts ae to Cagslst, whle othe classfed webstes combned account fo only 0.14% of U.S. Intenet vsts. 19

21 nclude employees of lage copoatons managng dozens of apatments and pvate apatment fndes who make a lvng as agents between landlods and entes. Sampled apatments nclude only one-bedoom apatments and studos to avod concens about oommates, chlden, etc., and to ensue compaable ents between any two unts wthn an aea. 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. 27 The sample excludes unts wth ents below the 20 th and above the 90 th pecentle wthn each cty to avod sendng emals to weekly entals o homes fo sale. Fnally, emals wee sent wthn 48 hous afte the lstng was posted. Table 2 lsts the ctes suveyed and the chaactestcs. 28 The aveage shae of black esdents acoss neghbohoods s smla to the actual shae of the black populaton n the geate metopoltan aea n Census Emal Geneaton and Expemental Teatments To maxmze the pobablty that landlods wll obseve the acal-soundng names, 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 used by etand and Mullanathan (2004). Sunames ae souced fom the U.S. Census 2000 Famly Name Suvey. Resultng name combnatons nclude: Allson aue, Ebony ashngton, Matthew Klen, and Danell ooke. 29 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 27 The Insttutonal Revew oad eques one nquy pe landlod so as to educe potental ham. Snce teatments ae andomly assgned, landlods ae, on aveage, dentcal acoss goups. 28 Roughly one-thd of postngs whch lack coss-steet nfomaton ae placed n the geate metopoltan aea. 29 hte female, black female, whte male, and black male, espectvely. A full lst of fst names and sunames used s n table 9. 20

22 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 (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 whch to espond, allowng us to dentfy automated esponses and to 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. Emals that do not nclude a statement of qualty belong to the baselne teatment o base case. In ths teatment, landlods only know the applcant s name and he nteest n entng the apatment. The model assumes that landlods take the aveage sgnals by ace o ndependent of ace as a poxy sgnal n the base case. hen the statement of qualty s ncluded, t dscloses ethe postve o negatve nfomaton. Postve nfomaton nfoms the landlod that the applcant has a good job and does not smoke. Negatve nfomaton nfoms the landlod that the applcant smokes and has a bad cedt atng. 30 oth types ae unambguously postve o negatve. Ths methodology does not am to detemne how any specfc pece of nfomaton affects outcomes, but nstead endeavos to test how postve o negatve nfomaton, n geneal, affects outcomes. 31 It s dffcult to magne a scenao n whch a 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 cedtwothness and smokng habts n the ntevew stage and commonly ask applcants 30 Revealng had-to-vefy chaactestcs such as habts and cleanlness s less ealstc. 31 e pooled two peces of nfomaton togethe to ncease the teatment effect. 21

23 to pay fo cedt atng checks. As we dscuss 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 entng an apatment. 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 advetsement uses epoted n table 1, the negatve nfomaton s lkely supsng to landlods, povdng a stong teatment effect. C. Categozng Outcomes The smplest dependent vaable dentfes a landlod esponse. Responses wee futhe classfed nto one of seveal categoes, naowed to ethe postve o negatve. 32 Postve esponses state that the unt s avalable and nvte futue contact n some manne. Negatve esponses nclude the non-esponse emals and those ethe statng that the unt s not avalable, o statng that the unt s avalable, but n a dscouagng manne. Each nquy sent ended wth a queston such as Is the apatment avalable? Some 95% of landlods who 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 beng dsnteested. Smple 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. D. Econometc Specfcatons e estmate fou egesson equatons to test ou hypotheses. Fst, the empcal specfcaton to test hypotheses 1 and 1A s: 32 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. 22

24 R 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 < Second, the followng DD specfcaton tests hypotheses 2 and 2A: R ( ) ( N ) ( N ) u. (18) P P N N N takes the value of 1 fo negatve nfomaton, and 0 fo postve nfomaton. The omtted categoy s postve nfomaton fo whtes. If the aveage landlod weghts sgnals fom whte applcants moe heavly than sgnals fom black applcants ( ) o f the magnal utlty fo whtes s geate than fo blacks, we expect N to be postve, esultng n a geate magnal etun to sgnal fo whte applcants. e estmate the followng DD egesson to test hypotheses 3 and 3A: R ( ) ( P ) ( P ) ( N ) P P N N ( N ) u. (19) The omtted categoy s no nfomaton fo whtes. The coeffcents P and 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 0 and that the sgn of N wll be ambguous. If hypothess 3A s coect, we expect that 0 and that 0. P N P Hence, falng to eject 0 wll cast doubt on taste-based dscmnaton. P Fnally, the followng empcal specfcaton tests hypotheses 4 and 4A: R S ( S ) ( ) S( S ) P ( P ) SP ( S P ) P ( P ) 33 th all dchotomous egessos, we use a lnea pobablty model (OLS) thoughout (see oolddge (2003, pp ) fo futhe dscusson). 23

25 SP ( 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) x n the statstcal dscmnaton model o the paamete k n the taste-based dscmnaton model to vay acoss dffeent types of neghbohoods. If landlods expeences wth black applcants ncease the sze of the nfomaton-weghtng paamete, then we expect SP and SN to be ambguously sgned. If landlods entng n a pedomnantly black neghbohood exhbt a pefeence fo black esdents elatve to landlods entng n neghbohoods wth a smalle shae of black esdents, then S should be postve. Moeove, f pejudce explans the obseved acal dffeentals, the supsng postve nfomaton helps black applcants moe and supsng negatve nfomaton huts black applcants moe as S nceases. So, 0 and 0. SP SN IV. Results Table 3 pesents summay statstcs of the expement and data collected. Of the 14,237 nques sent, 9,229 (65%) eceved a esponse. Of these esponses 6,597 (46%) 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% whte to 98.45% black wth a mean of 12.4% black esdents. Table 4 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 24

26 Table 5 epots esponse ates fo the postve and negatve teatments elatve to the baselne of no sgnal, poolng all applcants. Compang the ntecept tems n column (1) and column (3) n table 5, whch measue esponse and postve esponse ates espectvely n the baselne teatment, eveals that oughly 18% 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) n table 5 show that landlods ae equally lkely to eply to an emal nquy, whethe o not the applcant has evealed somethng postve about heself, but also that landlods ae moe lkely to eply wth a ejecton f the applcant 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. Column (3) n table 5 shows that 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 than fo males (0.04 vs. 0.03). Column (4) n table 5 shows that applcants n ou negatve teatment eceve a sgnfcantly lowe postve esponse ate than baselne applcants (0.32 vs. 0.53). The 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 Receve Lowe Response Rates Column (1) n table 6 confms hypotheses 1and 1A that landlods, on aveage and wthout a sgnal of qualty, ae moe lkely to espond to applcants wth whte soundng names than applcants wth Afcan-Amecan soundng names. The statstcally sgnfcant coeffcent on lack of confms pevous fndngs of dscmnaton aganst Afcan-Amecans o 25

27 pesons wth Afcan-Amecan soundng names. Combned wth the ntecept estmate of 0.581, applcants wth Afcan-Amecan soundng names eceve 16% fewe postve esponses. C. Hypotheses 2 and 2A: Postve Infomaton vesus Negatve Infomaton Column (2) n table 6 pesents the DD estmates fo equaton (18). It shows that the estmated effect of the negatve teatment on black elatve to whte s sgnfcantly postve (0.042). It s consstent wth hypothess 2 that, on aveage,, so sgnals fom whte applcants eceve elatvely moe weght n an aveage landlod s estmate of qualty. The estmates also fal to eject hypothess 2A that pejudce aganst black applcants can geneate a lage esponse gap between whte and black applcants as the sgnal swtches fom negatve to postve. D. Hypotheses 3 and 3A: The Effects of Supsng Sgnals If statstcal dscmnaton can explan dffeental outcomes fo the hypotheszed elatve sgn of the nfomaton-weghtng paamete, then the supsng negatve sgnal wll close the acal gap n column (1) n table 6. Convesely, supsng postve nfomaton wll not necessaly do so (hypothess 3). If pejudce nstead explans dffeental outcomes, then the acal gap wll amplfy wth postve nfomaton and wll close wth negatve nfomaton (hypothess 3A). In column (3) n table 6, the statstcally negatve coeffcent on negatve nfomaton and the statstcally postve coeffcent on Negatve Infomaton x lack ae consstent wth both hypotheses 3 and 3A. Column (3) n table 6 shows that dsclosng negatve nfomaton about an applcant s qualty leads to a 50% geate educton n a whte applcant s pobablty of ecevng a postve esponse. Column (3) n table 6 also shows that the magnal etun to sgnalng a espectable 26

28 occupaton and non-smokng behavo nceases the postve esponse ate by 6.7% (0.039/0.581) fo whtes. The coeffcent on the nteacton tem lack x Postve Infomaton s, howeve, statstcally ndstngushable fom zeo. oth applcant types 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. Although the postve nfomaton s much geate than the mean sgnal fo black applcants, the elatonshp attenuates any mpovement n sgnal. Taste-based dscmnaton cannot geneate ths fndng as t pedcts that a postve supse wll wden the acal gap unambguously. E. Hypothess 4 and 4A: Dffeences by Infomaton Types acoss Neghbohoods The fnal pedcton states that the dffeence s negatvely elated to the shae of blacks (%lack) n a ental popety s neghbohood. An ncease n ths facton equalzes the weghtng paametes fo black and whte applcants. If pejudce nstead explans the obseved acal gap, then as the shae of black esdents and landlods nceases, taste-based dscmnaton wll lead to a shnkng acal gap n the baselne. Column (4) n table 6 pesents evdence that dffeental outcomes by ace vay wth the acal composton of an apatment s neghbohood n a manne consstent wth statstcal dscmnaton. The postve coeffcent on the nteacton tem Postve Infomaton x lack x %lack ndcates that as the shae of black esdents n a neghbohood nceases, the supsng postve sgnal becomes moe effectve n closng the acal gap n postve esponse ates between whte and black applcants. The nsgnfcant postve coeffcent on the nteacton tem Negatve Infomaton x lack x %lack ndcates that n a pedomnantly black neghbohood, the negatve sgnal does not decease the acal gap between black and whte applcants 27

29 sgnfcantly when compaed wth the baselne teatment case. Thus, n neghbohoods n whch esdents ae pedomnantly black, a supsng postve sgnal leads to sgnfcantly geate mpovements n postve esponse ates. Although landlods n such a neghbohood ae moe lkely to be black, t does not eque that the landlod s black, but only that the landlod s moe famla wth black applcants. Ou estmates confm the key hypothess 4: landlods elatve past expeences wth dffeent acal goups shape the nfomaton paametes. In contast, column (4) n table 6 also eveals that the acal gap between whte and black applcants n the base case does not vay acoss dffeent neghbohoods. Futhemoe, as the shae of black esdents nceases, supsng negatve nfomaton does not hut black applcants moe than whte applcants, as ndcated by the postve coeffcent of Negatve Infomaton x lack x %lack. Ou esults contadct the pedctons of taste-based dscmnaton. Last, the esults n columns (2) (4) n table 6 show that postve nfomaton sgnfcantly nceases the lkelhood that applcants wth Afcan-Amecan soundng names eceve postve esponses, ulng out the pesence of lexcogaphc seach posted n etand and Mullanathan (2004). Oveall, the DD specfcatons and the sgnfcant coeffcent on Postve Infomaton x lack x %lack poduces dffeent conclusons about statstcal dscmnaton than those of pevous studes. th the sgnfcant teatment effect of postve nfomaton, ou estmato can dentfy dffeences n acoss ace and n tun llustates that the lack of expeence wth a patcula ace nfluences the behavo of agents. V. Robustness The esults ae obust to seveal altenatve specfcatons. Fst, ou fndngs do not contadct the theoetcal assumpton of ace-nvaant qualty vaance no do they suppot the 28

30 competng taste-based dscmnaton explanaton. Second, we assume that landlods exhbt ngoup favotsm and out-goup anmosty n the taste-based dscmnaton model. If black landlods ae nstead pejudced aganst black applcants, then, as the shae of black esdents/landlods nceases, the supsng postve sgnal should unambguously wden the acal gap favong whte applcants. Column (4) n table 6 ejects ths possblty. Landlod sk aveson pesents an ambguty that could lmt ou ablty to ule t out as the man souce of the esults. e explot dffeences n neghbohood acal composton to sepaate statstcal and taste-based explanatons, so acal composton must not be coelated wth landlod sk aveson. As sk aveson and wealth ae hghly coelated (Paavsn et al., 2010), neghbohood acal composton must not vay wth popety value. The hgh coelaton (0.544) between aveage ent and popety values of one-bedoom and studo non-fam unts n the Amecan Communty Suvey 2009 justfes ent as a poxy fo value. The coelaton between the shae of black esdents and the ent of the apatment s nsgnfcant. In unepoted estmates, we also fnd that the ncluson of both apatment ent (elatve to the neghbohood aveage) and ts polynomal have no sgnfcant effects on ou estmates pesented above. e conclude that sk aveson s not the man dve of ou esults. Table 7 pesents esults usng othe defntons of postve esponses. The estmates n columns (1) (3) n table 7 show that the estmated coeffcents vay lttle acoss all thee measues of postve esponses. The esults ae also obust to use of names. Column (4) n table 7 pesents the estmaton esults of equaton (20) wthout less common fst names. All eale conclusons about the testable mplcatons eman. 34 Fnally, the names chosen n ou study could convey an applcant s socal backgound 34 The esults ae also obust to the excluson of fou Muslm soundng fst names: Hakm, Jamal, Kaeem and Rasheed. 29

31 beyond ace. e follow etand and Mullanathan s (2004) appoach to examne whethe aveage postve esponse ates ae coelated wth the socal backgound of each name wthn each ace-gende goup, usng the facton of mothes of babes bon wth the names who have at least a hgh-school dploma as a poxy. The wthn ace-gende ank-ode coelaton test shows no evdence that postve esponse ate and socal backgound ae postvely elated (table 8). VI. Concluson Statstcal dscmnaton can explan the dffeental outcomes n ental apatment nquy sceenng by ace. e detal a model of statstcal dscmnaton that povdes testable mplcatons about a paamete that connects sgnals, expectatons, and ace and contast the model s pedctons wth those of an altenatve, taste-based model. e show some ovelap between the mplcatons of taste-based and statstcal dscmnaton and llustate that lowe magnal etun to sgnal o cedentals fo black applcants than fo whte applcants s consstent wth both statstcal and taste-based dscmnaton. hen no nfomaton othe than the ace of an applcant s evealed to landlods, applcants wth Afcan-Amecan soundng names eceve 9.3 pecentage ponts fewe postve esponses than applcants wth whte soundng names. The lack of a dffeental esponse to postve nfomaton casts doubt on taste-based dscmnaton as the domnant souce of dffeental teatment. Landlod esponse ates acoss neghbohood acal compostons confom to the statstcal dscmnaton model, n whch agents use past expeence to pedct applcant qualty by ace. Racal pejudce o lexcogaphc seach alone cannot explan these esults. The fndngs povde justfcaton fo polces amng to pomote clea nfomaton dssemnaton and to mpove communcaton between dffeent acal goups, as well as fo socal pogams 30

32 desgned to elmnate nequalty acoss acal goups. 31

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35 Knowles, John, Ncola Pesco, and Peta Todd, Racal as n Moto Vehcle Seaches: Theoy and Evdence, Jounal of Poltcal Economy 109 (2001), Lst, John A., The Natue and Extent of Dscmnaton n the Maketplace: Evdence fom the Feld, Quately Jounal of Economcs 119 (2004), Levtt, Steven D., Testng Theoes of Dscmnaton: Evdence fom eakest Lnk, Jounal of Law and Economcs 47 (2004), Massey, Douglas S., and Nancy A. Denton, Tends n the Resdental Segegaton of lacks, Hspancs, and Asans: , Amecan Socology Revew 52 (1987), Mogan, John, and Felx Vady, Dvesty n the okplace, Amecan Economc Revew 99 (2009), Page, Devah, and Hana Shephed, The Socology of Dscmnaton: Racal Dscmnaton n Employment, Housng, Cedt, and Consume Makets, Annual Revew of Socology 34 (2008), Page, Maanne, Racal and Ethnc Dscmnaton n Uban Housng Makets: Evdence fom a Recent Audt Study, Jounal of Uban Economcs 38 (1995), Paavsn, Danel, Veonca Rappopot, and Enchetta Ravna, Rsk Aveson and ealth: Evdence fom Peson-to-Peson Lendng Potfolos, NER wokng pape no (2010). Phelps, Edmund S., The Statstcal Theoy of Racsm and Sexsm, Amecan Economc Revew 62 (1972), Ruggles, Stephen, J. Tent Alexande, Kate Genadek, Ronald Geen, Matthew. Schoede, and Matthew Sobek, Integated Publc Use Mcodata Sees: Veson 5.0 [Machne-eadable database] (Mnneapols, MN: Unvesty of Mnnesota, 2010). 34

36 Sddque, Zaha, Evdence on Caste-ased Dscmnaton, Labou Economcs 18 (2011), S146 S159. US Census ueau, Census 2000 Summay Fle 1 (2000). oolddge, Jeffey M., Econometc Analyss of Coss Secton and Panel Data (Cambdge, MA: MIT Pess, 2002). Ynge, John, Measung Racal Dscmnaton wth Fa Housng Audts: Caught n the Act, Amecan Economc Revew 76 (1986),

37 Table 1: Compason of Cagslst Uses and Non-Cagslst Uses Full Sample Cagslst (g) Non-Cagslst Intenet (f) Non-ntenet Mean lack hte lack hte lack hte lack hte lack hte Age (yeas) Male College (a) Low ncome (b) Rente (c) Sngle (d) Full-tme job (e) Intenet use (f) Cagslst use (g) Sample sze Notes: Authos own calculatons based on the Pew Intenet & Amecan Lfe Poject s Apl 2009 Economy suvey data of the adult populaton. The sample ncludes non-hspanc whtes and blacks only. (a) Respondents wth at least some college educaton; (b) pesons eanng less than $50,000 pe yea; (c) pesons entng apatments/houses; (d) neve maed o sngle pesons; (e) pesons employed full tme; (f) pesons who use the Intenet at least occasonally; (g) Intenet uses who esponded yes to used onlne classfed ads o stes lke Cagslst. 36

38 Table 2: Ctes Suveyed Cty #Obs. #Neghbohoods Mean %lack acoss Neghbohoods %lack n Meto Mean Monthly Rent Atlanta % 29.4% Austn % 7.4% altmoe % 27.4% oston % 6.6% Chalotte % 20.3% Chcago % 18.7% Cleveland % 18.2% Dallas % 15.0% Denve % 5.6% Detot % 22.6% Dstct of Columba % 26.2% Houston % 17.4% Indanapols % 14.0% Jacksonvlle % 21.5% Kansas Cty % 12.8% Los Angeles % 9.4% Lousvlle % 15.2% Memphs % 44.1% Mlwaukee % 15.2% Mnneapols % 5.3% Nashvlle % 15.4% Oklahoma Cty % 11.3% Phladelpha % 19.5% Phoenx % 3.4% Potland % 2.7% Ralegh % 22.1% San Dego % 5.4% San Fancsco % 5.2% San Antono % 6.4% San Jose % 2.6% Santa abaa % 2.3% Seattle % 4.2% Tampa % 9.8% Tucson % 2.7% Total % 12.9% Notes: (a) a neghbohood s a Census tact f coss-steet nfomaton of the postng s avalable; othewse t s a metopoltan statstcal aea; (b) %lack s defned as the numbe of non-hspanc blacks dvded by all the populaton n the neghbohood; the mean s obtaned by aveagng %lack acoss neghbohoods wthn the same cty; (c) %lack n metopoltan statstcal aea based on the 5% publc use mco sample; (d) mean ent s calculated usng the ents of unts we suveyed. Populaton data souced fom Census 2000 Summay Fle 1 and the Integated Publc Use Mcodata Sees Census % sample (Ruggles et al., 2010). 37

39 Table 3: Summay Statstcs Vaable Obs. Mean Std. Dev. Mn Max Sent on weekend Monthly ent Negatve nfomaton aselne teatment Postve nfomaton Male lack % male n neghbohood % black n neghbohood Response Postve Response Notes: See defntons of monthly ent, % blacks n neghbohood, and neghbohood n the notes of table 2. lack and male efe to applcants wth Afcan-Amecan and male soundng names, espectvely. aselne teatment efes to emal text contanng no nfomaton about cedt atng, smokng, o occupaton of an applcant. Negatve teatment adds negatve nfomaton about bad cedt atng and smokng behavo to baselne emal text. Postve teatment adds postve nfomaton about espectable occupaton and non-smokng behavo to baselne emal text. Neghbohood demogaphc chaactestcs ae souced fom Census Response ndcates whethe a landlod esponded and a postve esponse ndcates whethe a landlod esponded postvely to the nquy. Postve esponse ncludes avalable and avalable + f. See onlne supplementay mateals fo esponse categoes. 38

40 Table 4: Vefcaton of Random Assgnment aselne Teatment Postve Infomaton Negatve Infomaton lack hte Dff. lack hte Dff. lack hte Dff. Pooled Gende Sent on weekend (.012) (0.012) (0.015) Monthly ent (10.76) (8.31) (9.44) % black n neghbohoods (.005) (0.004) (0.005) % male n neghbohoods (.0014) (0.001) (0.001) Notes: See defntons of vaables n notes of table 2 and table 3. Robust standad eos clusteed by neghbohood epoted n paentheses. *** p<0.01, ** p<0.05, * p<0.1 39

41 Table 5: Oveall Teatment Effects on Response Rate and Postve Response Rate (1) (2) (3) (4) Response Postve Response Gendes Pooled Postve Infomaton *** (0.011) (0.011) Negatve Infomaton *** *** (0.012) (0.013) Constant 0.710*** 0.710*** 0.534*** 0.534*** (0.010) (0.010) (0.011) (0.011) Obsevatons R-squaed Males Postve Infomaton ** (0.014) (0.015) Negatve Infomaton *** *** (0.017) (0.017) Constant 0.707*** 0.707*** 0.525*** 0.525*** (0.013) (0.013) (0.014) (0.014) Obsevatons R-squaed Females Postve Infomaton *** (0.013) (0.014) Negatve Infomaton *** *** (0.016) (0.016) Constant 0.713*** 0.713*** 0.544*** 0.544*** (0.012) (0.012) (0.012) (0.012) Obsevatons R-squaed Notes: The omtted categoy s the baselne (no-nfomaton) teatment. All samples pooled whte and black applcants. See defntons of vaables n notes of table 2 and table 3. Robust standad eos clusteed by neghbohood epoted n paentheses. *** p<0.01, ** p<0.05, * p<0.1 40

42 Table 6: Dffeental Teatment by Race and Infomatonal Sgnals (1) (2) (3) (4) lack *** *** *** *** (0.015) (0.012) (0.015) (0.019) Postve Infomaton 0.039*** 0.053*** (0.013) (0.017) Postve Infomaton x lack (0.019) (0.025) Negatve Infomaton *** *** *** (0.013) (0.016) (0.018) Negatve Infomaton x lack 0.044** 0.045** 0.044* (0.018) (0.020) (0.026) % lack (0.067) lack x %lack (0.099) Postve Infomaton x %lack (0.082) Postve Infomaton x lack x %lack 0.267** (0.125) Negatve Infomaton x %lack (0.093) Negatve Infomaton x lack x %lack (0.130) Constant 0.581*** 0.619*** 0.581*** 0.579*** (0.012) (0.009) (0.012) (0.014) Omtted categoy hte hte hte hte aselne Pos. Info. aselne aselne Obsevatons R-squaed Notes: See defntons of vaables n notes of table 2 and table 3. Robust standad eos clusteed by neghbohood epoted n paentheses. Columns (1), (2), (3), and (4) coespond to hypotheses 1&1A, 2&2A, 3&3A, and 4&4A, espectvely. *** p<0.01, ** p<0.05, * p<0.1 41

43 Table 7: Altenatve Measues of Postve Response and Excludng Rae Fst Names (1) (2) (3) (4) Altenatve Measues of Postve Response Rae Avalable + Ambguously leanng yes Avalable + Avalable f + Ambguously leanng yes Avalable + Avalable f + Ambguously leanng yes + Avalable & moe nfo Fst Names Excluded lack *** *** *** *** (0.019) (0.019) (0.019) (0.020) Postve Infomaton 0.064*** 0.054*** 0.041** 0.053*** (0.017) (0.017) (0.017) (0.017) Postve Infomaton x lack * (0.024) (0.024) (0.024) (0.025) Negatve Infomaton *** *** *** *** (0.019) (0.019) (0.020) (0.018) Negatve Infomaton x lack (0.026) (0.026) (0.027) (0.027) % lacks (0.067) (0.066) (0.066) (0.067) lack x %lacks (0.099) (0.099) (0.099) (0.103) Postve Infomaton x %lacks (0.082) (0.081) (0.082) (0.082) Postve Infomaton x lack x %lacks 0.273** 0.280** 0.230* 0.237* (0.124) (0.124) (0.124) (0.133) Negatve Infomaton x %lacks (0.093) (0.094) (0.096) (0.093) Negatve Infomaton x lack x %lacks (0.130) (0.131) (0.129) (0.137) Constant 0.556*** 0.587*** 0.619*** 0.579*** (0.015) (0.014) (0.014) (0.014) Obsevatons R-squaed Notes: The omtted categoy s the baselne (no nfomaton) teatment fo whte. See defntons of vaables n notes of table 2 and table 3. Column (4) excludes thee less common fst names, Hakm, Rasheed, and Temayne, whch have wthn-gende fequences below 0.005% n Census The esults ae smla f we exclude fou Muslm soundng fst names: Hakm, Jamal, Kaeem, and Rasheed. Robust standad eos clusteed by neghbohood epoted n paentheses. *** p<0.01, ** p<0.05, * p<0.1 42

44 Table 8: Postve Response Rate and Mothe s Educaton by Fst Name Name hte Female % Postve Response Mothe Educaton Name hte Male % Postve Response Mothe Educaton Jll Todd Cae Geg Emly Geoffey Ksten ett Laue Matthew Meedth endan Anne ad Saah Nel Allson Jay Coelaton (p = 0.194) Coelaton (p = 0.433) Name lack Female % Postve Response Mothe Educaton Name lack Male % Postve Response Mothe Educaton Latoya Jamal Tansha Temayne Ebony Rasheed Asha Hakm Tamka Kaeem Kesha Leoy Latonya Tyone Laksha Jemane Kenya Danell Coelaton (p= 0.798) Coelaton (p = 0.028) Notes: Fst names and mothe educaton ae souced fom etand and Mullanathan (2004). Mothe educaton s defned as the pecentage of babes bon wth that name n Massachusetts between 1970 and 1986 whose mothe had at least completed a hgh school dploma. Coelaton epots the Speaman ank ode coelaton between postve esponse ate and mothe educaton wthn each ace-gende goup, as well as the p-value fo the test of ndependence (null hypothess). The whte sunames used n ths study ae aue, ecke, Eckson, Klen, Kame, Muelle, Schmdt, Schnede, Schoede, and Schwatz. These ae sunames wth the hghest facton of whtes among the top 500 most common sunames n Census The black sunames used ae ashngton, Jeffeson, ooke, anks, and Mosley, because these names ae moe lkely belong to blacks among the 1,000 most common sunames n Census

45 Illustaton 1: Repesentatve Emal Samples Postve Teatment (1) Hello, (2) My name s [Full Name], and I am wtng n esponse to you lstng fo an apatment fo [apatment ent]/month. (3) In case you e nteested, I do not smoke and I wok full tme as an achtect. (4) Is ths unt stll avalable? (5) Thank you fo you tme, [Full Name] Negatve Teatment (1) H, (2) My name s [Full Name], I am espondng to you cagslst postng fo an apatment lsted at [apatment ent]/month. (3) Just so you know, I am a smoke and my cedt atng s below aveage. (4) I ealze places go fast sometmes, s ths unt stll avalable? (5) Thanks, [Full Name] 44

46 aselne Gap Neg. Info. Gap Pos. Info. Gap aselne Gap Neg. Info. Gap Pos. Info. Gap aselne Gap Neg. Info. Gap Pos. Info. Gap Fgue 1 Shnkage n Absolute Racal Gap and Infomaton eghtng Paametes E() Case 1: = hte lack -x E(x ) E(x ) x + x E() Case 2: > hte lack -x E(x ) E(x ) x + x E() Case 3: < hte lack -x E(x ) E(x ) x + x Notes: e assume nsgnfcant sk aveson to smplfy the llustaton. Case 1 shows shnkages n the acal gap fo both postve and negatve sgnals, compaed wth the baselne teatment. Case 2 shows shnkage n the acal gap fo a negatve sgnal only, compaed wth the baselne teatment. Case 3 shows shnkage n the acal gap fo a postve sgnal only, compaed wth the baselne teatment. The foecast equatons fo whte applcants ae placed abtaly above the foecast equaton fo black applcants to match stylzed facts. 45

47 Facton Fgue 2: The Dstbuton of Shaes of lack Resdents acoss Census Tacts mean = 0.124; std. dev. = Shae of lack Resdents Notes: Shae of black esdents s the numbe of non-hspanc black pesons dvded by all of the populaton esdng n the census tact. Fo postngs wth mssng addesses, we use metopoltan populaton fgues. Data souced fom Census

48 Appendx A Devaton of the Expected Value of Sample Vaance of Sgnal Equaton (7) states that the denomnato of n a sample of landlods s 1 n ) vâ( x ), ( l whee, fo a patcula landlod, the sample vaance of sgnal fo acal goup s vâ( x ). In a lage sample of landlods, the mean of the sample vaance of sgnal s: cov(, j ) va( ) E[vâ( )] va( ) cov(, ) x j cov(, j ) s the pa-wse covaance of qualty between ndvdual tenant and j fo all j; cov(, ) s the pa-wse covaance of the nose of the sgnal between the ndvdual tenant k k l and l fo all kl n acal goup. If ndvduals ae mutually ndependent, then cov(, ) s zeo. Neghbohood sotng means, howeve, that landlods ae lkely to meet smla ndvduals n neghbohoods n whch they own popetes and cov(, ) k l k k l s not zeo. k l cov( k, l ) s postve and lage fo f s the neghbohood majoty, as thee ae moe covaance tems. Thus, the majoty goup of a neghbohood wll have smalle E [vâ( x )]. hethe va( ) s small, lage, o constant acoss s not eally cucal to the elatonshp between neghbohood sotng, majoty goup, and the nfomaton-weghtng paametes. l k l 47