Economics Letters 117 (2012) 592–595

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Economics Letters

journal homepage: www.elsevier.com/locate/ecolet

The gender wage gap in experimental labor marketsChristiane Schwieren ∗

Department of Economics, University of Heidelberg, Bergheimer Straße 58, 69115 Heidelberg, Germany

a r t i c l e i n f o

Article history:Received 24 May 2012Received in revised form12 July 2012Accepted 19 July 2012Available online 24 July 2012

JEL classification:J31J71C91

Keywords:DiscriminationGenderGift exchangeExperiment

a b s t r a c t

Weanalyze the genderwage gap in experimentalmarkets.Women receive but donot request significantlylower wages than men. This hurts firms, as women react with low effort. Additionally, women tend toreact differently than men to wage levels.

© 2012 Elsevier B.V. All rights reserved.

1. Introduction

Despite the long awareness of the gender wage gap, it stillexists in all industrialized countries. The literature discusseshuman capital (see Weichselbaumer and Winter-Ebmer, 2005),institutional and situational variables, selection effects (Blauand Kahn, 2006; Olivetti and Petrongolo, 2008) as well asgender differences in negotiator behavior (Walters et al., 1998;Babcock and Laschever, 2003) as explanatory factors. Differentialbehavior in wage negotiations can be analyzed in a gift-exchangeframework. Firms could believe that women react differentlythan men to wages — either more ‘‘altruistic’’ or less reciprocal.This could be based on gender stereotypes describing womenas more cooperative (Croson and Buchan, 1999; Chaudhuri andGangadharan, 2007), less work-oriented and competitive (Crosonand Gneezy, 2009), or of lower status (Ball et al., 2001).

2. The experiment

2.1. Design

We use a ‘‘double auction with effort’’ (Fehr and Falk, 1999)with excess supply of workers (four firms and six workers), to test

∗ Tel.: +49 6221 542953; fax: +49 6221 543592.E-mail addresses: christiane.schwieren@awi.uni-heidelberg.de,

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whether we observe a gender wage gap in the lab and what theunderlyingmechanisms are. Each firm can contract oneworker perperiod. Workers and firms can make wage offers simultaneously.Each newwage request by a worker (firm) has to be lower (higher)than the last request made before (by any worker (firm)). Allstanding offers can always be accepted. This guarantees thatwagesare chosen consciously, among higher and lower offers. After threeminutes trading, workers with a contract select a (costly) effortlevel. Firms without contract do not earn any money. Workerswithout contract get twenty experimental guilders. Firms’ andworkers’ payoffs πF and πW are calculated using the followingprofit equations1 (see Table 1):

πF = 120∗percentage chosen by the worker – salary(between 20 and 120).

πW = salary – costs of percentage.

We ran four sessions (24 workers and 16 firms) for each gendercombination.2 160 students of various faculties participatedin the computerized experiment (z-tree (Fischbacher, 2007)).

1 Note that firms can incur losses!2 We analyze gender differences only for workers. An analysis of gender-pairing

effects (see also Sutter et al., 2009) is described in a longer version of this paper(Schwieren, 2003).

C. Schwieren / Economics Letters 117 (2012) 592–595 593

Table 1Effort costs.Source: Taken from Fehr et al. (1998).

Effort level (%) 10 20 30 40 50 60 70 80 90 100Cost 0 1 2 4 6 8 10 12 15 18

Table 2Regression explaining effort. 3

Regression type Tobit

Dependent variable EffortSex of worker −1.973

(12.764)Wage contracted .563***

(.204)Sex by wage .606**

(.26)Constant −21.140*

(12.587)# of observations 526

***=p < .01

**=p < .05

*=p < .10

Participants were divided into roles of firms and workers. Inthe gender-homogeneous sessions, this was done randomly. Inthe gender-heterogeneous sessions, the experimenter said loudlybefore participants entered the laboratory: ‘‘The women (men)come with me, you are firms (workers)!’’ After reading theinstructions and ensuring that subjects understood the payoff-structure, ten periods were played. Subjects were paid based ontheir earnings (1 experimental ‘‘guilder’’= 0.02e) plus a 5e show-up fee. Losses had to be covered with the show-up fee.

Assuming selfish money maximizing subjects, equilibriumpredictions are straightforward: Knowing that workers have noincentive to contribute more than the lowest effort level, nocontracts should be made, as any wage-payment would result ina loss for the firms. However, in related experiments firms do offercontracts with higher than minimal wages to motivate workers toexhibit higher than minimal effort (Fehr and Falk, 1999; Hannanet al., 2002; Charness, 2004).

2.2. Hypotheses

Based on the literature reviewed in the introduction,we test thefollowing hypotheses:

Hypothesis 1. Women (f ) receive lower wages (w) than men (m)(c.p.) : wf < wm.

Hypothesis 2. Women differ frommen in the reaction to wages: forany w either ef > em or ef < em.

Hypothesis 3. Women request lower wages: wrf (e) < wr

m(e).

3. Results and discussion

Hypotheses were first tested using data from period one, asbehavior in later periods is path-dependent. Using data from later

3 Robust standard error regression, clustered on session, using period dummies.

Fig. 1. Development of wage and effort.

Fig. 2. Wage requests by workers.

rounds we can differentiate between ‘‘fundamental’’ behavioraltendencies and reactions to market experience.

We confirm H1: Females earn significantly less than malesin the first period (average wf : 42.87, average wm : 59.13; t =

4.070, p = .000), and (at least marginally significantly) in all laterperiods, except the last two (see Fig. 1).

To test H2, we first calculate the correlation of wage with effortin period 1, which is highly significant (r = .50, p = .000). Splitby gender, it remains significant for men (r = .45, p = .01), butnot for women (r = .19, p = .3). Over all periods it is significantfor both sexes (male: r = .411, p = .000, female: r = .305, p =

.000). A regression (Table 2) reveals no main effect for gender, but

594 C. Schwieren / Economics Letters 117 (2012) 592–595

Table 3Wage and effort levels by wage categories.

Wage category Sex of worker Period 1 only All periods

N Mean Std. deviation N Mean Std. deviation

20–45 wage Male 4 32.25 5.188 140 31.34 7.974Female 18 34.56 7.898 152 27.54 7.392

Effort Male 4 32.50 28.723 140 22.57 18.364Female 18 16.11 13.346 152 16.84 12.471

46–65 wage Male 19 54.95 4.249 83 54.87 5.428Female 12 53.17 4.589 51 53.33 4.790

Effort Male 19 32.11 23.233 83 31.33 24.682Female 12 23.33 24.985 51 21.57 22.034

>66 wage Male 8 82.50 18.323 74 77.55 11.628Female 1 69.00 26 78.85 13.988

Effort Male 8 76.25 31.595 74 59.32 38.261Female 1 10.00 5.188 26 31.15 26.732

Fig. 3. Wage offers of firms.

both wage and the interaction of gender and wage are significantpredictors of effort.

To further analyze this, we use three wage categories (Fehr andFalk, 1999). C1 contains lowwages (20–45), C2 intermediatewages(46–65), and C3 high wages (>66). In period 1 we cannot comparemen and women in all categories, as only one woman is in C3 (seeTable 3). Over all periods, the distribution of men and women overthe categories differs significantly (Pearson Chi-Square = 22.765;as. Sig. = .000). We find (marginally) significant sex differences inwage within the lower two categories (category 1: t = 4.230, p =

.000, category 2: t = 1.660, p = .10, category 3: t = −.462, p =

.65) and significant sex differences in effort levels in all categories(category 1: t = 3.140, p = .004; category 2: t = 2.376, p = .038,category 3: t = 4.097, p = .000; see Table 3). Evidence on H2 isthus not conclusive.

To test H3, we take the average of all wage requests within onesession (per period), reducing our sample to N = 8 independentobservations per gender and period. There are no genderdifferences in the wages requested until period 3 (p1 : Z = −1.47,p. = .16). After that, wage requests differ (marginally) signifi-cantly by gender (p3 : Z = −1.785, p = .084). Fig. 2 shows that

women quickly adjust their requests downwards,whilemalewagerequests go down slowly. Rejecting H3 is consistent with Solnick’s(2001) findings and consistent with field evidence (Babcock andLaschever, 2003), if we think of ‘‘real world women’’ as being inlater periods of a ‘‘game’’.

Offers of firms are significantly lower when workers arefemale (Z = −2.94, p = .003, period 1; aggregated by session).The general downward trend in offers is smoother formen than forwomen, but the gender difference is only significant in periods 1–4,period 6 and period 10 (Fig. 3). In the last two periods male firmsstop tradingwith femaleworkers (on average 2.2 and 2.4 trades aremade with female workers, and 3.0 and 3.1 with male workers).

4. Conclusion

Caution is necessary when extrapolating from experimentalresults to real-world behavior. There seems to be a viciouscycle of reciprocity that reinforces the gender wage gap. Becker(1957–1971) proposed that paying women lower wages allowsnon-discriminating firms to make higher profits and drivediscriminating firms out of the market. He did however notconsider women’s reciprocity, which might lead to persistentdiscriminatory outcomes in wages or unemployment. As it seemsnot to bewomen’s negotiator behavior that negatively affects theirwages, anti-discrimination policies might actually be necessaryand useful (see Balafoutas and Sutter, 2012) — if they ensurewagesthat women perceive as fair.

Acknowledgments

We thank the University of Maastricht and the UniversitatPompeu Fabra for research funding, Armin Falk for the program,David Rodriguez for help with the experiments and Jordi Brandtsand Marc Vorsatz for translating the instructions.

Appendix A

Screen-shot trading screen workers4 (see Fig. A.1):

4 On the left, salary proposals are typed in. In the second (third) columnproposalsof workers (firms) are listed. The last column lists all contractsmade and below thatthe actual salary of the player.

C. Schwieren / Economics Letters 117 (2012) 592–595 595

Fig. A.1.

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