GENDER SELECTION DISCRIMINATION: EVIDENCE FROM A TRUST GAME* Robert Slonim Case Western Reserve University. September 7 th, 2004

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1 GENDER SELECTION DISCRIMINATION: EVIDENCE FROM A TRUST GAME* Robert Slonim Case Western Reserve University September 7 th, 2004 Abstract: Although discrimination remains prevalent, the reasons for its occurrence are still hotly debated. To disentangle vying explanations, researchers have begun using laboratory experiments. However, this research has not allowed, or studied, the effects of selection. In this paper, we examine discrimination in a Trust game where subjects can and cannot select partners. We find little evidence of discrimination without selection but significant evidence of discrimination with selection: specifically, subjects discriminate against their own gender in partner choice and levels of trust after partner selection. This pattern of discrimination is consistent with behavior documented in the social psychology literature on helping behavior. The discrimination cannot be explained by performance (trustworthiness), but is partially explained by tastes and beliefs towards each gender s trustworthiness. JEL: Key Words: J7, J15, C72, C91 Discrimination, Selection, Trust, Experimental Economics *Send correspondence to Robert Slonim, Department of Economics, Case Western Reserve University, Cleveland Ohio, 44106: rls18@case.edu. This research has been generously supported by the Russell Sage Foundation.

2 Many empirical studies and field experiments document discrimination in the selection process to establish relationships. 1 For example, Bendick, Jackson, and Reinoso [1994] use audit studies run by the Fair Employment Council to show whites are 10% more likely to get interviews and 50% more likely to get offers. Discrimination is mainly attributed to either (expected) performance differences (i.e., statistical discrimination) or tastes [Becker 1957; Arrow 1998, Heckman 1998]. Yet while policy may depend on whether discrimination is statistical or preferential, there are several reasons why the causes of discrimination remain an active debate. For instance, field studies cannot directly measure tastes, typically only proxies for expected performance, e.g., AFQT and NAEP, are observed, and these proxies are not perfectly correlated with performance and may reflect discrimination [Coleman 2003]. Further, even in controlled audit studies testers may inadvertently signal differences in performance that are correlated with race and/or gender. 2 To mitigate these concerns to better understand the causes of discrimination, researchers are turning to laboratory experiments (e.g., Fershtman and Gneezy 2001 and List 2004) since the lab allows researchers to control for difficult to observe information in field studies and measure tastes, performance and expectations of performance. However, lab studies have thus far only examined discrimination within random assignment (by the experimenter) relationships and have not examined discrimination within the selection process to determine relationships. This study compares discrimination in a lab setting in which participants can and cannot select relationship partners. There are many reasons to measure the selection into relationship form of discrimination apart from, and in addition to, discrimination within relationships. First, there is no a priori reason to assume the two types of discrimination are perfectly correlated, so measuring each type can provide different insights towards understanding discrimination. 1

3 Second, the welfare costs of selection discrimination may be greater than within relationship discrimination since selection discrimination prevents participation. Third, selection may affect behavior after relationships are formed in ways that magnify the total cost of discrimination. We examine discrimination in a trust game due to trust s importance as social capital. Trust lubricates economic activity [Arrow 1973], may be correlated with economic development (Fukuyama 1995 and Knack and Keefer 1997), and can facilitate business transactions by reducing contract and litigation costs [Grief 1993]. Since trustworthiness will be the only measure of performance and field evidence isolating trustworthiness is unobservable, the pattern of discrimination we observe in the lab may differ from some field evidence if trustworthiness is swamped by other considerations. For instance, field evidence in labor markets presented in the economics literature (see Altonji and Blank 1999 for a review) shows that gender discrimination, when it exists, is almost always directed against women (e.g., lower wages, fewer interviews and fewer job offers). Yet, if the only measure of performance is trustworthiness, men might be discriminated against if women are believed to be more trustworthy. For instance, Wright and Sharp [1979] find that subjects reveal greater trust towards women across a variety of situations. Shaub [1996] and survey data collected at the end of the current experiment show that both men and women believe women are significantly more trustworthy than men across a variety of contexts. 3 Furthermore, within the social psychology literature there is a substantial body of evidence showing that women are more likely than men to benefit from discrimination when decisions involve helping behavior (see Eagly and Crowley 1986 and Pearce and Amato 1980 for reviews). For instance, Geuguen and Fischer-Lokou [2004] report that women are more likely than men to get rides when hitchhiking, Rabinowitz et al. [1997] show that when tourists ask for directions, women are more likely than 2

4 men to get advice, Long et al. [1996] find that women are more likely than men to receive 37 cents when they ask strangers and Harris [1992] reports that the most recent courteous act reported by subjects were directed towards a woman rather than a man. This literature also documents many situations in which helping behavior favors recipient of the opposite gender. For instance, Dovidio [1982] finds that males are more likely to give 10 cents to women than men whiles females are more likely to give 10 cents to men than women. Whether men or women are more trustworthy is an empirical question that appears to be sensitive to context. Past research (without selection) presents mixed results on which gender is more trustworthy. For instance, some experimental studies find insignificant differences in the trustworthiness of males and females (e.g., Fershtman and Gneezy 2001 and Harbaugh, Krause, Liday and Vesterlund 2003). Some studies find that women are more trustworthy (Buchan, Croson and Solnick 2004, Chaudhuri and Gangadharan 2002, and Croson and Buchan 1999). Further, some studies find that subjects are more trustworthy to partners of the opposite gender (e.g., Sharlemann et al. 2001). 4 Thus, context likely moderates trustworthiness. Whether selection also affects the trustworthiness of men and women is an open question tested here. 5 Besides gender, ability may certainly moderate and/or mediate partner selection and behavior within relationship decisions (e.g., standard ability measures such as AFQT and NAEP often correlate with wages and employment). Thus, in the current experiment we also measure analytical ability. Ability may suggest greater trustworthiness for several reasons. First, there may be a halo effect [Thorndike 1920]: positive information on one trait (ability) may cause a belief in other positive traits including trustworthiness. Second, there may be desirability bias [Fisher 1993] where subjects prefer associating with talented people. Third, higher ability may be associated with greater education, which may imply greater socialization and trustworthiness. 3

5 These reasons predict that potential partners with greater ability will be selected more often. The first reason, a belief in statistical differences in trustworthiness, suggests that partners with higher ability will also receive more trust within relationships. Besides examining selection discrimination and comparing selection to non-selection discrimination, the current design increases the power to detect discrimination and understand its causes relative to some past studies. First, we collect multiple measures of trust per subject to obtain a more powerful estimate of discrimination. Second, with and without selection we use the strategy method to obtain a complete profile on trustworthiness for every subject. Third, we collect data on the same subjects for both trust and taste decisions so that we can measure within subject the contribution that tastes make towards discrimination. Finally, with the same subjects we collect survey data on trustworthiness beliefs to measure the extent to which participants believe men or women are relatively more trustworthy. We find almost no evidence of gender discrimination without selection, and the extent to which it exists is quantitatively small. In contrast, with selection we find gender discrimination in the partners that decision-makers select and in the amounts that decision-makers trust their selected partners. Among three potential sources of discrimination, tastes, beliefs and statistical differences in performance, we find that selection discrimination cannot be explained by differences in performance, but can be partially explained by tastes and beliefs. Finally, we show that the cost of discrimination against the discriminated group is much larger (sometimes more than fifteen times larger) with than without selection. Thus, the results will show that we draw different conclusions regarding the extent and costs of discrimination depending on whether decision-makers can or cannot select their partners. I. Research Design 4

6 Subjects participate in four financially motivated tasks followed by a survey. The tasks, always conducted in the same order, measure Ability, Trust-Trustworthiness, Altruism and Risk Aversion. All procedures are common knowledge. No selection and selection sessions are identical for the Ability and Risk Aversion tasks and vary across the Trust-Trustworthiness and Altruism tasks only in subject s ability to select partners. A. Ability Subjects had five minutes to add sets of five two-digit numbers. We privately told each subject how many sets they correctly summed. We refer to this number as the subject s ability (in the experiment we refer to this number as the subject s score). At the end of the experiment, one subject in each session was randomly selected and paid $1 times his/her ability. We find no difference in the mean ability of men (11.8) and women (11.9). The minimum and maximum score was 4 and 26, respectively, and one standard deviation was B. Trust-Trustworthiness This task modifies the two player game first studied by Berg, Dickhaut and McCabe [1995]. The first mover, the Trustor, has $30 and may send any amount in increments of $3 from $0 to $30 to the second mover, the Trustee. The Trustee receives three times the amount sent, and may return any proportion. The Trustee s payoff equals the amount received minus the amount returned. The Trustor s payoff equals $30 minus the amount sent plus the amount the Trustee returns. 7 Past studies, examining manipulations of this game (e.g., Berg et al. 1995, Croson and Buchan 1999 and Ortmann et al. 2000) find that most Trustors and Trustees send and return positive amounts. Procedures: In both conditions, all subjects first make four first-mover Trustor decisions sequentially. The appendix shows the decision sheet first-movers were given. For each decision, subjects are given the ability score from the first task and the gender of three possible second- 5

7 mover Trustees. We made partner gender explicit, consistent with Dufwenberg and Muren s [2003] approach. We agree with Dufwenberg and Muren s concern that using names (e.g., see Bertrand and Mullainathon 2004, Charness and Gneezy 2004, Fershtman and Gneezy 2001 and Holm 2000) may convey additional information such as ethnicity and/or cultural identity. We examine four orders to balance possible gender by order effects: (1) MMM, FFM, MMF, FFF; (2) FFF, MMF, FFM, MMM; (3) FFM MMM, FFF, MMF; and (4) MMF, FFF, MMM, FFM (M=male, F=female), and the triplets indicate the gender of the three potential second-movers for each decision. For instance, in Order 1 a subject is given information about three possible male partners in the first decision, two female and one male partner in the second decision, etc. Once subjects made the four decisions in the first-mover role, they then made decisions in the second-mover role. As second-mover, subjects indicated how much money they would return for each possible amount they could receive: subjects indicated how much they would return if the first-mover sent $3 (so they received $9), if the first-mover sent $6 (so they received $18), and so on. As second-mover, subjects were given no information about the first-mover. By not providing second-movers with information on first-movers, we eliminate first-mover motivation to send different amounts to second-movers on the expectation that second-mover s trustworthiness (amount second-movers return) may depend on first-mover s gender or ability. Treatments: In the control (no-selection), we randomly assigned one of the three possible partners to be the actual partner using two orders (M, F, M, F and F, M, F, M) so that subjects were paired with men twice and women twice. In the treatment (selection), subjects selected a partner from the three possible partners, thus subjects in two decisions selected between male and female partners and in two decisions selected between all men or all women. At the end of 6

8 every session, we randomly chose one of the four first-mover decision rounds and three subjects to be compensated as first-movers. We paid the selected first-movers and their second-mover partners according to the decisions they made. 8 C. Altruism The Altruism task modifies the dictator game first studied by Hoffman, McCabe and Smith [1996]. The procedures, matching protocols, selection of subjects to pay and task itself are identical to the Trust game task except that second-movers in this task do not get an opportunity to return any money. 9 Past studies (e.g., Fershtman and Gneezy 2001 and Hoffman et al. 1996), examining manipulations of this game find a non-trivial number of first-mover dictators send positive amounts. Subjects were paid for at most one decision made in tasks 2 and 3 (the trust and altruism tasks) but would not know which task or role they would be compensated for until the end of the session. D. Risk Aversion The risk aversion task Holt and Laury [2002] used was included to provide control for risk aversion that may affect trust (Eckel and Wilson 2004b use a similar approach). However, we find that the risk aversion measure has no significant effect to explain trust, trustworthiness or altruism decisions, nor does its inclusion qualitatively affect any of the results reported below, therefore we do not discuss the risk aversion task in any further detail. E. Survey We developed a survey to measure differences in subject beliefs regarding the trustworthiness of men and women. The questions are modified from those used in other studies (e.g., Glaeser et al and Eckel and Wilson 2004a,b,c) to examine beliefs regarding each gender s trustworthiness in general and specific to the subject population and trust experiment. The survey includes demographic questions and manipulation checks to test for the clarity of the 7

9 protocols. Subject responses indicate that they felt comfortable with the procedures. For instance, 92 percent of subjects agreed with the statement the instructions were clear and easy to follow. F. Sessions and Subjects We ran two control and three treatment sessions with a total of 56 and 76 subjects with 34% and 42% women, respectively. Subject characteristics and demographics are statistically identical in the control and treatment. 10 Each session took approximately 90 minutes. Subjects received on average $23.67 and $23.54 in the control and treatment sessions, respectively. II. Results A. Trust Descriptive Statistics: Table I provides descriptive statistics. Panels A-E present statistics for the Trust game and Panels F and G show results for the Dictator game. Panel A shows that decision-makers on average sent more to opposite sex partners regardless of whether they had selected their partners. For instance, men sent $6.00 more to women than to men and women sent $1.40 more to men than to women if they selected partners. Panel B shows that decision-makers, when selecting between male and female partners, selected opposite sex partners more often: men selected female partners 80% of the time and women selected male partners 65% of the time. From the second-mover s perspective, Panel C shows how often subjects were selected and received a positive amount. Panel C thus shows how often a potential partner could benefit from a transaction, and one minus this percentages indicates how often partners were excluded from any gains from trade. For instance, in the no selection (selection) treatment a male secondmover was selected by the experimenter (by the first-mover) and sent a positive amount by male decision-makers 24% (11%) of the time, and thus excluded from transactions 76% (89%) of the 8

10 time. Panel C shows that without selection male and female partners were almost equally likely to be sent a positive amount. This is not very surprising since all partners had an equal one-inthree chance to be randomly selected by the experimenter, and then most were sent a positive amount. Panel C also shows that with selection and male decision-makers, men were selected and sent positive amounts 11% of the time whereas women were selected and sent positive amounts 45% of the time. In contrast, with selection and female decision-makers, men were selected and sent a positive amount 37% of the time whereas women were selected and sent a positive amount 21% of the time. Thus, at least directionally, decision-makers send more to the opposite sex partners and also select opposite sex partners more often. 11 Panel D shows that on average decision-makers send more to partners who had the maximum rather than minimum ability of the three possible partners. For instance, decisionmakers with above median ability scores sent nearly twice as much to partners who had the highest rather than lowest ability. Further, Panel E shows that partners with the highest ability were more than twice as likely to be selected as partners with the lowest ability. Regression Analysis: Table II presents OLS regressions examining the determinants of amount sent (Columns 1-3) and probit regressions on the determinants of partner selected (Columns 4-7). We estimate regressions with multiple observations per subject and report robust standard errors (clustered on each subject) throughout the analyses. We estimate the following equation: (1) y = α + β PartnerAbility + β PartnerFem + β DMFem + β PartnerFembyDMFem + ε i PA i PF i DF i PFxDF i i where PartnerAbility is the number of questions answered correctly in the ability task, PartnerFem is 1 if a female partner and 0 otherwise, DMFem is 1 if a female decision-maker and 9

11 0 otherwise and PartnerFembyDMFem equals PartnerFem times DMFem. Since the omitted category in the 2x2 decision-maker gender by partner gender combination is male decisionmaker by male partner, β PF estimates the difference in behavior of men towards women relative to men towards men; thus β PF estimates male decision-maker discrimination favoring women. To estimate female decision-maker discrimination towards men rather than towards women, we subtract the estimates of β PF and β PFxDF. The row in Table II following the interaction parameter estimate shows this subtraction and the statistic testing whether - β PF - β PFxDF = 0 indicating whether female decision-maker discriminate in favor of men. 12 The first two columns of Table II show the OLS estimates for the amount sent (y i = amount sent) with and without selection. These regressions indicate different patterns of discrimination with and without selection for male but not female decision-makers. Without selection, men do not significantly discriminate based on gender (PartnerFem: β PF = 2.25, p>.10). However, with selection, men discriminate significantly in favor of women, sending $6.76 more to women than to men (p <.01). This estimate implies that women on average receive $20.28 more than men after the amount sent is tripled. For female decision-makers, the regressions indicate that women send more to men than to women (- β PF - β PFxDF = $1.25 without selection; - β PF - β PFxDF = $1.13 with selection), but neither is significant (p >.20). In sum, for amount sent decisions we only detect discrimination when subjects can select their partners but only by male decision-makers. Columns 1 and 2 also show that in both conditions higher ability partners are sent significantly more: for instance, with selection, a one-unit improvement in partner s ability is estimated to increase the amount sent by $0.43. Given one standard deviation was nearly 5 units 10

12 of ability and for each dollar sent a partner receives three dollars, the regression estimates that one standard deviation more in ability results in receiving an extra $6.45 ($3.00*5*$0.43). To examine partner selected decisions, we examine two definitions because the decision to select a partner but send nothing has ambiguous meaning. One possible meaning is that the decision-maker is indifferent between the possible partners and would have sent nothing to any of them. Another meaning is that the choice reflects weak preference for the selected partner. A third meaning is that the choice reflects an intentional insult. To proceed, we define partner selected a equal to 1 if the partner was selected and equal to 0 otherwise and we define partner selected b equal to 1 if partner selected and amount sent is positive, and equal to 0 otherwise. An advantage of the second definition is that it can be used to analyze the no selection treatment since decision-makers could have chosen to send nothing in this condition reflecting a partial ability to not select certain partners. 13 Columns 4-7 of Table II report the probit parameter estimates and the implied marginal effect on the probability of being selected. Columns 4 and 5 show that both definitions of partner selected produce qualitatively identical parameter estimates in the selection condition. The results show that ability has a positive and significant effect on being selected. For instance, using partner selected b, we find that one standard deviation in ability affects the chances of a partner being selected by 6.7% (=5*1.34%). Columns 4-7 show that male decision-makers discriminate significantly in favor of female partners: for instance, when males choose partners, a female partner was 35% more likely to be selected and sent a positive amount than a male partner (β PF = 1.12, p <.001). We also find that women discriminate in favor of men: when females choose partners, a male partner is almost 16% more likely to be selected and sent a positive amount than a female partner (-β PF - β PFxDF = 11

13 0.43, p <.01). We also find that without selection male decision-makers discriminate in favor of women, though by a small amount of 3.3% (p <.05), and female decision-makers do not discriminate (p >.20). In sum, for selection decisions we detect discrimination by men against men and by women against women. Thus, without and with selection we see the following significant patterns of discrimination: Pattern of Discrimination No Selection Selection Amount Men against men NO YES: $6.76 Sent Women against women NO NO Partner Men against men YES: 3.3% YES: 35.3% Selected Women against women NO YES: 15.6% Result 1: Without selection, there is no statistical evidence of discrimination in terms of amounts sent. There is evidence that male decision-makers discriminate against men in terms of sending nothing, though the magnitude of the effect is small. Result 2: With selection, male decision-makers discriminate against males in terms of amount sent and partners selected, and female decision-makers discriminate against females in terms of partners selected. Result 3: The pattern of discrimination differs depending on whether there is or is not partner selection: Without selection there is minimum evidence of discrimination, with selection there is substantial evidence of discrimination. Robustness: There are a number of possible concerns with the analysis presented in Table II. First, important covariates may be missing. For instance, decision-maker characteristics (including age, major, religiosity, GPA, ability, employment status and level of risk aversion from the fourth task) and interactions (e.g., decision-maker ability by partner ability and/or differences in ability) may explain some of the observed variance and affect the key parameter estimates and/or their significance. To address this concern, additional amount sent and partner selected regressions were run including the available decision-maker characteristics and possible 12

14 two- and three-way interactions. We do not report the large number of these regressions, but none provide results to change Results 1-3 reported above. 14 Second, parametric distribution assumptions in both the OLS and probit regressions may be suspect. For instance, in the OLS regressions, the linear assumption implies that an increase of $1 sent has the same marginal impact regardless of whether the base is sending $0 or sending $15 or $27. Further, the OLS regressions ignore possible censoring in which decision-makers are forced to send from $0 to $30. To address these concerns, we estimated the amount sent regressions with ordered probit and tobit models, with and without covariates and interaction terms. The results of these exercises are again consistent with the key Results 1-3. Last, although the main point is articulated in Result 3 (different conclusions regarding discrimination are drawn in the no selection and selection conditions), we can test whether there is a significant difference between the two conditions. Table II reports the results of this pooled analysis for the amount sent (third column) and for partner selected (last column). The estimates indicate that (1) men send marginally significantly more ($4.51) to women than men in the selection than no selection condition (p <.10), (2) men are significantly more likely to select women than men in the selection than no selection treatment (p <.001) and (3) women are marginally significantly more likely to select men than women in the selection than no selection treatment (p <.10). Thus, in addition to Result 3, we find that the level of discrimination is significantly greater with than without selection. Discussion: The pattern of discrimination in which first-movers discriminate in favor of selecting partners of the opposite gender is observed in some, but not all field contexts. In labor markets, almost all the evidence finds discrimination directionally favoring men. However, in the helping behavior literature, the evidence is mixed. Eagly and Crowley [1986] survey 99 13

15 studies of helping behavior and find that the two most common patterns are decision-makers helping partners of the opposite gender or helping women. The current evidence suggests that the Trust game may parallel helping behavior more closely than a job market situation. B. Why Discriminate? To understand the patterns of discrimination identified above, we test the reasons commonly presented in the literature: (1) statistical differences in performance: are women or men more trustworthy? (2) tastes: do decision-makers exhibit similar patterns of preference for partners of if there is no opportunity for reciprocation? and (3) beliefs: do decision-makers believe men or women are more trustworthy? B1. Statistical Justification for Discrimination We first examine whether the observed patterns of discrimination are justified on the basis of statistical differences in performance of trustworthiness. Figure 1 shows the trustworthiness, defined as the percent returned, by gender, amount received and selection. It shows that women return slightly more than men for most amounts sent, but the differences in amount returned by men and women are less than 5% for all amounts received and often less than 2%. Figure 1 also shows that the percent returned appears positively related to the amount received and selection. Table IIIA presents OLS regressions estimates of the determinants of percent returned. We show robust standard errors. 15 We only include explanatory variables observable to firstmovers since we want to test whether discrimination is justifiable based on the information available to the first movers. 16 We estimate the following model: (2) y = α + β Received + β 2 Received + β Female + β Ability + β ReceivedbyAbility + ε i R i R2 where y i is the percent returned and the other variables are self explanatory. i F i A i RxA i 14

16 The first two columns of Table IIIA show the results for the no selection and selection conditions alone. The estimate on Female indicates that with and without selection women return 2.4% and 0.7% more than men. The magnitudes are small and neither is significant (β F : p >.20). Thus, gender discrimination cannot be explained by differences in performance. 17 Result 4: Gender discrimination cannot be explained by differences in trustworthiness. Table IIIA also shows that with or without selection the amount received has a positive, significant effect (β R : p <.05), but at a decreasing rate (β R2 : p <.01). The regressions also show that greater ability has a negative effect on percent returned (β A < 0). The effect of ability is significant with selection (p <.01), but not significant without selection (p >.20). Given the similarity of the determinants of amount returned across the treatments, we pooled the data to get a more powerful measure of gender differences and to test whether there are any significant differences due to selection. Columns 3-5 of Table IIIA present regressions with the pooled data. These regressions include a dummy variable for the main effect of selection. Column 3 includes interaction terms for selection with all the other variables. This regression shows that no interaction terms are significant, confirming that the determinants of percent returned are statistically similar across treatments. Regarding gender, the pooled estimate shows that women return 1.8% more in selection than no selection, but this difference is insignificant (p>.50). Hence there is no significant difference in trustworthiness with or without selection. The same regression (Column 3) also shows that the main effect of selection is numerically large, suggesting that the amount returned is 15% greater with than without selection, yet the effect is not significant (p=.14). Selection most likely has no significant effect 15

17 on the amount returned in this specification due to the shared variance with the interaction terms. We further investigate the effect of selection and gender on amount returned by dropping all the insignificant interactions terms other than gender. Column 4 shows that in this case women are still estimated to return an insignificant amount (1.6%) more than men with than without selection. This regression also shows that the main effect of selection is now only 5.7%, more closely reflecting the levels shown in Figure 1. The effect of selection in this specification remains marginally insignificant (p=.12). Removing the insignificant gender variables, the last regression shows that selection has a significant effect: subjects who were selected by their partners return 6.5% more than subjects who were selected randomly (p <.05). Since this model includes only variables that have a significant effect, it is thus the most fully specified model. This result is consistent with other researchers who hypothesize that the percent returned reflects at least some element of reciprocity (e.g., Fehr and Gächter 2000). Comparing selection to no selection, we may expect that reciprocity will be greater with selection since decision-makers not only trust partners with some amount of money, but also select the partners. 18 Result 5: Selection significantly increases the percent returned. B2. Taste for Discrimination We now examine whether the patterns of discrimination can be explained by differences in preferences. We use Dictator game behavior to measure preferences (Fershtman and Gneezy 2001 and List 2004 follow a similar approach). If similar directional biases in behavior exist across the Trust and Dictator games, we then have evidence that discrimination in the Trust game may be explained by preferences. The bottom two panels of Table I show the amounts dictators send (Panel F) and the percent of dictators who select male and female partners. Panel F shows that male dictators send 16

18 more to females than males in both conditions and that male dictators are more likely to select female (58%) than male (42%) partners. These patterns are directionally the same as the behavior we observe in the Trust game. However, while female dictators send more to men than women in the selection treatment, also similar to the pattern we observe in the Trust game, they send more to women than men in the no selection condition and are equally likely to select male and female partners, patterns not observed in the Trust game. Table IIIB presents estimates of the incremental effects of the variables on the amount sent in the Trust game over the amounts sent in the Dictator game. 19 The regressions in Table IIIB pool the data from the two game. We estimate the following model: (3) yi = α + βpapartnerabilityi + βpf PartnerFemi + βdf DMFemi + βpfxdf PartnerFembyDMFemi + βttr + βtxpatrbypartnerabilityi + βtxpftrbypartnerfemi + β TxDFTRbyDMFemi + βtxpfxdftrbypartnerfembydmfemi + εi where TR is 1 for trust game observations and 0 otherwise, and the remaining terms were defined above or are the interaction between TR and each of the other variables. The estimates presented in Table IIIB in the first four variables indicate the effect of each variable in the Dictator game alone. The next variable, Trust, indicates the main effect difference in behavior between the Trust and Dictator games. The next four rows present the interaction terms that measure the incremental effect of each variable on behavior in the Trust game beyond its effect on behavior in the Dictator game. Note that a significant main effect indicates that the variable has an effect on behavior in the Dictator game while a significant interaction indicates that the variable has an incrementally different effect in the Trust than Dictator game. If preferences alone can explain discrimination in the Trust game, then we should observe an insignificant interaction effect. On the other hand, if preferences cannot 17

19 explain discrimination in the Trust game, then we should observe a significant interaction effect. Finally, if both preferences and other factors are driving behavior in the Trust game, then we should observe both a significant main effect and a significant interaction effect. 20 The first two columns of Table IIIB show estimates for the no selection and selection conditions for the amounts sent. Without selection (Column 1) male decision-makers do not send significantly different amounts to male and female partners in the Dictator game (β PF : p >.20) and though they send more to women than men in the Trust than Dictator game (β TxPF = $1.66), the difference is insignificant (p >.20). Without selection, we also find that female decision-makers do not send significantly different amounts to male and female partners in the Dictator game (-β PF -β PFxDF : p >.20) and though they send more to men than women in the Trust than Dictator game (-β TxPF -β PFxDF = $2.11), this difference is also insignificant (p >.15). These results are not surprising given we did not observe any discrimination in the amount sent in the Trust game. In sum, for the amount sent without selection, we have: Amount Sent No Selection Treatment Differential Behavior towards men and women Trust Game Discrimination In the Dictator Game In the Trust relative to the Dictator Game Men Against Men NONE None (p >.20) None (p >.20) Women Ag Women NONE None (p >.20) None (p >.15) With selection (Column 2), male decision-makers send significantly more to female than male partners in the Dictator game (β PF = $2.32: p <.05) and they also send marginally significantly more to women than men in the Trust than Dictator game (β TxPF = $4.44, p <.10). Thus, with selection, preferences can partially explain some, but not all, of the difference in the additional amounts that men send to women than men in the Trust game. With selection, we also find that female decision-makers send an insignificant amount more to male than female partners (-β PF - β PFxDF = $1.23, p >.20) and they send virtually the identical amount to men and women in the 18

20 Trust and Dictator games (-β TxPF -β PFxDF = -$0.09). The results for female decision makers in the selection treatment are not surprising given we did not observe any discrimination in the amount they sent in the Trust game. In sum: Amount Sent Selection Treatment Differential Behavior towards men and women Trust Game Discrimination In the Dictator Game In the Trust relative to the Dictator Game Men Against Men YES ($6.76) $2.32 (p <.05) $4.44 (p <.10) Women Against Women NONE None (p >.20) None (p >.20) The last two columns of Table IIIB show estimates for the no selection and selection conditions for the partner selection decision. We show results for the partner selected b defined as equal to 1 if partner selected and sent a positive amount and equal to 0 otherwise. Without selection (Column 3), male decision-makers marginally significantly send positive amounts more often to female than male partners in the Dictator game (β PF = 0.93 p <.10) and they are virtually equally likely to send a positive amount to women and men in the Trust and Dictator game (β TxPF = 0.01). Thus, the slight amount of male discrimination towards sending positive amounts more often to female partners with no selection that we observed in the Trust game can be entirely explained by tastes. In sum: Partner Selected and sent positive amount No Selection Treatment Differential Behavior towards men and women Trust Game Results In the Dictator Game In the Trust relative to the Dictator Game Men Against Men YES (3.3%) 0.9% (p <.10) None (p >.20) Women Against Women NO None (p >.20) None (p >.20) With selection (Column 4), male decision-makers selected female than male partners marginally significantly (9.8%) more often in the Dictator game (β PF =.314: p <.10) and they selected female than male partners significantly more often in the Trust than Dictator game (β TxPF = 19

21 0.807, 28%: p <.01). Thus, with selection preferences partially explains some, but not most, of the difference in the additional frequency that male decision-makers select men than women in the Trust game. With selection, we also find that female decision-makers selected male and female partners statistically the same amount of time (-β PF -β PFxDF = 0.00, p >.20) and though they selected men more often than women in the Trust than Dictator game (-β TxPF -β PFxDF = 0.37), the difference is not significant (p=.14). Thus, we cannot reject tastes as a motivation for the observed female discrimination in the Trust game since female decision-maker behavior across the two games is not significantly different; yet the evidence also does not suggest that tastes are the likely reason since women do not discriminate in the Dictator game. In sum: Partner Selected Selection Treatment Differential Behavior towards men and women Trust Game Results In the Dictator Game In the Trust relative to the Dictator Game Men Against Men YES (35.3%) 9.8% (p <.10) 28.0% (p <.01) Women Against Women YES (15.6%) None (p >.20) None (p =.14) Our main finding for whether tastes can explain discrimination is summarized as follows: Result 6: Male discrimination to select women in the Trust game can at least partially be justified by a taste for discrimination whereas female discrimination to select men cannot. B3: Beliefs Justification for Discrimination Although men and women are equally trustworthy (Result 4), it is possible that subjects expected otherwise. To explore beliefs, we conducted a survey at the completion of the experiment to examine beliefs towards male and female trustworthiness. These questions were modified from general trust attitude questions used by Glaeser et al [2000] and the National Opinion Research Center s General Social Survey (GSS). Table IIIC presents the survey questions and mean responses that address beliefs of the trustworthiness of each gender. The questions ask about (1) the likelihood of men and women 20

22 returning loans made by friends and strangers, (2) the trustworthiness, fairness and helpfulness of men and women within the student-subject population, and (3) the trustworthiness of the male and female students in the Trust game. The results indicate that women believe that females are more likely to return loans made by friends (p <. 01) and strangers (p<.001) and that female students at the university of the experiment can be trusted more (p <.01), are fairer (p<.04) and try to be more helpful (p<.09) than men. Men also directionally believe that females are more likely to return loans made by friends (p =.25) and strangers (p =.11) and that female students at the university of the experiment can be trusted significantly more (p <.04), are significantly more fair (p<.02) and directionally try to be more helpful (p =.16) than men. These responses suggest that both men and women believe women are generally more trustworthy than men. If decision-makers acted upon these beliefs, then they would select and send more to female than male partners, consistent with the male but not female decision-maker discrimination in the Trust game. Result 7: Male discrimination towards female partners in the Trust game can at least partially be justified by a general belief in women being more trustworthy than men. However, female discrimination towards male partners in the Trust game cannot be explained by general beliefs since women also generally believe women are more trustworthy than men. B4: Explaining Discrimination: Summary The following insert summarizes the main explanations for the patterns of discrimination that are consistent with the data and that we cannot reject: Outcome Pattern of Discrimination Condition Possible Justifications Amount Sent Men against men Selection Tastes, Beliefs Partner Selected Men against men No Selection Tastes, Beliefs Partner Selected Men against men Selection Tastes, Beliefs Partner Selected Women against women Selection Tastes 21

23 We do not list statistical discrimination as an explanation since the percent returned by men and women is not statistically different. However, women directionally return almost 2% more than men. Thus, men discriminating against men may at least partially be explained by tastes, beliefs and directional but insignificant differences in performance. In contrast, women s discrimination can only partially be explained by tastes. III. Discussion A. The costs of discrimination with and without selection In this section we explore the relative costs of discrimination with and without selection. To examine the costs of discrimination, we calculate the expected earnings of male and female recipients of trust. We define the conditional expected earnings, E pg,dg,c, that a partner (gender pg) receives from a decision-maker (gender dg) in condition c to equal the sum of the percent of time each amount i is sent, p i,pg,dg,c, times the average amount kept when i is sent, k i,pg,dg,c : $30, p $ 0 i, pg, dg, c * ki, pg, dg, c (4) E pg dg, c = i = For example, male decision-makers (dg=men) in the no selection treatment (c=no selection) sent $0, $3, $6, $9,, $30 to male recipients (pg=men) 28%, 0%, 1%, 7%, 7%, 9%, 7%, 3%, 4%, 1% and 32% of the time, respectively, and these male recipients on average kept $8.30, $16.30, $23.49, $29.08, $33.68, $39.27, $45.57, $52.32, $57.51, $ Thus, male recipients of male decision-makers in the no selection treatment expect to earn $33.49 (equals 0%*$ %*$ %*$ %*$60.89). 21 We calculate expected earnings for the two conditions: no selection and selection with a gender option. Recipients (unconditional) expected earnings E pg,c are a weighted average of the conditional expected earnings from male, E pg,m,c, and female, E pg,f,c, decision-makers, conditional on the proportion W f of female decision-makers and 22

24 the proportion P pg,dg,c of time decision-makers of gender dg select (or are paired with) partners of gender pg in condition c: (5) E pg, c = W f * Ppg, f, c * E pg, f, c + (1 W f ) * Ppg, m, c * E pg, m, c Table IV presents the expected earnings E pg,c results (ignore the decompositions for a moment). Given the differences in male and female decision-maker behavior, we show results by decisionmaker gender alone and then combined. Specifically, the top two panels show the expected earnings if all male (W f =0%) or all female (W f =100%) decision-makers, the third panel shows expected earnings assuming an equal number of male and female decision-makers (W F =50%) and the last panel shows the expected earnings assuming the proportion of female decisionmakers matches the proportion in the experiment (no selection: W f =34%; selection: W f =42%). Note also that with no selection, the proportion of time men and women are second-mover partners is 50% (i.e., P pg,m,c = 0.5), but with selection, men choose women 80% of the time (i.e., P f,m,c = 0.8) and women choose men 67% of the time (i.e., P f,f,c = 0.67). The first two panels of Table IV show that a large difference in expected earnings of male and female recipients exists between no selection and selection if decision-makers are all men rather than all women. With male decision-makers, expected earnings of women over men increases from 15% to 494% whereas with female decision-makers the expected earnings of men over women increases from only 12% to 59%. Without selection, the magnitude of male and female decision-maker discrimination mostly cancels each other out: females earn 15% more with male decision-makers and males earn 12% more with female decision-makers. However, selection increases the advantage to women if all decision-makers are male by 479% (15% to 494%) while it increases the advantage to men if all decision-maker are female by 47% (12% to 23

25 59%). Thus, selection disproportionately affects male decision-maker discrimination resulting in the larger cost of discrimination against men with than without selection. Without selection and using the actual proportion of men and women in the study (last panel), women recipients can expect to earn 8% more than men. Half of this advantage is due to more male decision-makers in the experiment: with an equal proportion of male and female decision-makers (third panel), women can only expect to earn 4% percent more than men. The remaining advantage to female recipients can be attributed to the generally larger amount that men rather than women sent to their partners. With selection, the advantage to women increases substantially: women can expect to earn 127% more than men assuming the same proportion of decision-makers as in the experiment, or 56% more than men with an equal proportion of male and female decision-makers. Thus, the advantage to women increases by more than fifteen-fold from 8% to 127% (or from 4% to 56%) if decision-makers have a gender option. We can isolate two effects to better understand why the cost of discrimination increases from no selection to selection: (1) exclusion (selection results in the discriminated groups being excluded from the transaction) and (2) change in amount sent (selection changes the amounts sent). To determine expected earnings isolating the exclusion aspect of selection discrimination (Decomposition Sel=Yes, Amt=No), we use the conditional expected earnings from no selection E pg,dg,c=no selection with the selection proportions P pg,dg,c=selection. To determine expected earnings isolating the change in amounts sent aspect of the selection discrimination (Decomposition Amt=Yes, Sel=No), we use the conditional expected earnings from selection E pg,dg,c=selection with the no selection proportions P pg,dg,c=no selection. 22 Table IV shows that either effect alone increases the cost of discrimination. However, the exclusion of partners from the transaction has a notably 24

26 larger effect. Thus, we may conclude that a major reason for the cost of discrimination increasing with selection is due to participants being excluded from the transaction. B. Does sending more without selection predict who decision-makers would select? One more reason the cost of discrimination may increase with selection is that the percent of decision-makers who, without selection, send more to opposite than same sex partners may underestimate the percent of decision-makers who select partners of the opposite sex. To test this hypothesis, Table V shows that without selection 31% (25/81) of male and 41% (21/51) of female decision-makers who discriminate (i.e., those who send different amounts to male and female partners) send more to opposite sex partners whereas only 18% of male decision-makers and 28% of female decision-makers send more to same gender partners. If we hypothesize the null effect that decision-makers select partner gender on the basis of which gender they send more to (and assume that the 51% (41/81) male and 31% (16/51) female decision-makers who send equal amounts to each gender would select partner gender with equal probability), then we predict that men select women and women select men 56 and 57 percent of the time respectively. However, recall that Table I shows that men select women 80% and women select men 67% of the time. We can thus easily reject the null hypothesis that men and women select partners with the same proportion that they send more to opposite sex partners (binomial test: p <.01 for both male and female decision-makers). Combining all decision-makers, the results suggest that selection exacerbates discrimination causing an additional 14% of the decision-makers to select partners of the opposite gender than they would have sent more to without selection. In sum, three reasons seem to account for the larger cost of discrimination when partner selection exists. First, and foremost, discrimination entirely excludes some participants from all 25