the impact of female sex hormones on …web.stanford.edu/~niederle/buser.stanfordpresentation.pdf1 /...

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The Impact of Female Sex Hormones on

Competitiveness

Thomas BuserUniversity of Amsterdam

The Impact of female sex hormones on competitiveness Thomas Buser

Introduction 2 / 25

Motivation

I Gender di�erences in competitiveness are a stable �nding oflab experiments:

I Niederle and Vesterlund (2007): when given a choice, 73percent of men but only 35 percent of women compete

I Datta Gupta et al. (2005): women, but not men, arein�uenced by risk aversion when deciding whether to compete

I Gneezy et al. (2003): men signi�cantly increase e�ort whenthe compensation scheme becomes more competitive whilewomen show no signi�cant reaction

I These gender di�erences are often thought to be a cause ofthe gender gap in the labour market

I What causes these gender di�erences in competitiveness is stilllargely an open question


Introduction 3 / 25

Nature vs. Nurture: Nurture

I Gender gap in competitiveness reversed in matrilineal society(Gneezy et al., 2008)

I Girls attending single-sex schools are signi�cantly more likelyto compete (Booth and Nolen, 2009)

I Gender gap in risk aversion disappears for girls being raised insingle-sex schools (Booth and Nolen, 2009)


Introduction 4 / 25

Nature vs. Nurture: Nature

I No study on tournament entry

I But mixed evidence on gender gap in other areas:

I Testosterone correlated with �nancial risk taking (Apicella etal., 2008) and a higher probability of rejection in theultimatum game (Burnham, 2007)

I Bidding in �rst price auctions �uctuates over the menstrualcycle (Chen et al., 2009; Pearson and Schipper, 2009); but noe�ect of 2D:4D ratio on bidding (Pearson and Schipper, 2009)

I Testosterone levels are positively correlated with risk seeking;gender gap for MBA students in seeking out �nance careerdisappears when controlling for current and prenataltestosterone levels (Sapienza et al., 2009)

I But no e�ect of testosterone and oestrogen injections given topost-menopausal women on risk aversion, altruism, reciprocalfairness, and trust (Zethraeus et al., 2009)


Introduction 5 / 25

This Paper

I Hormonal �uctuations - naturally occurring over the menstrualcycle or induced by contraceptives - provide exogenousvariation in oestrogen and progesterone levels

I Hypothesis: competitiveness �uctuates in sync with hormonelevels

I Hypothesis: women are more competitive when levels and/orchanges in hormone concentrations are low


Introduction 6 / 25

Summary of Results

I Likelihood of self-selecting into competition �uctuates stronglyand signi�cantly over the menstrual cycle and with the intakeof hormonal contraceptives

I Fluctuations follow the predicted pattern: subjects aresigni�cantly less competitive in times of high levels and rapidincreases of sex hormones in the body

I The results are consistent with an evolutionary hypothesisaccording to which women are more competitive during thefertile window when competition for genetically well-endowedmales occurs and less so after ovulation is over (and duringpregnancy)


Introduction 7 / 25

Summary of Results

I I consider three possible indirect pathways for the e�ect of sexhormones on competitiveness:

I via an impact on risk aversionI via an impact on mathematical performanceI via an impact on overcon�dence

I None of these hold up to the data


Menstrual Cycle and Hormonal Contraceptives 8 / 25

The Menstrual Cycle


Menstrual Cycle and Hormonal Contraceptives 9 / 25

Hormonal Contraceptives

I Constant doses of oestrogen and progestins

I 21-day intake phase and 7-day break

I Oestrogen secretion by the body is markedly reduced andprogesterone production ceases completely

I Wide range of progestins used

I Comparison between di�erent contraceptives and betweencontraceptive-takers and non-takers is impossible due toendogeneity issues


Experimental Design and Sample 10 / 25

Experimental Design

I Closely follows design by Niederle and Vesterlund (2007)

I Groups of fourI Subjects solve simple sums of �ve two-digit numbersI Round one: piece-rate; round two: tournamentI Subjects choose compensation scheme for third roundI Subjects estimate own rank

I Additionally, I conduct a simple objective probability lotterychoice experiment



Sample

Contraceptive Number of Subjects Percentage

Pill 47 43.9Condoms 31 29.0Other hormonal contraceptive 6 5.6Other method 1 0.9None 22 20.6Total 107 100.0



Sample

Menstrual Cycle or Pill Cycle Phase Number Expected Numberof Subjects of Subjects

Phase 1: Menstrual (5 days) 11 10Phase 2: Follicular (7 days) 15 13Phase 3: Peri-Ovulatory (3 days) 9 6Phase 4: Luteal (8 days) 15 15Phase 5: Premenstrual (5 days) 4 10

Pill Break (7 days) 13 13Pill Intake Phase (21 days) 40 40


Results 13 / 25

Basic Results

I I �nd signi�cant variations of competitiveness over themenstrual cycle

I One-way ANCOVA returns P-value of 0.03 for variation overthe menstrual cycle. Subjects are signi�cantly less competitiveduring the luteal phase compared to the rest of the cycle(P-value: 0.02).

I P-value of 0.04 for the null of equality between the 7-daypill-break and the rest of the 28-day pill-cycle

I Con�rmed by non-parametric tests and regression results

I Variations in competitiveness are signi�cantly correlated withvariations in both progesterone and oestrogen


Results 14 / 25

Regression Results

Competitiveness (1) (2) (3)

Cycle Phase 1 reference

Cycle Phase 2 -0.0121 -0.128 -0.147(0.208) (0.224) (0.231)

Cycle Phase 3 0.121 0.0658 0.0257(0.228) (0.241) (0.247)

Cycle Phase 4 -0.279 -0.432** -0.439**(0.198) (0.188) (0.194)

Cycle Phase 5 0.455*** 0.323* 0.305(0.158) (0.186) (0.192)

Controls for demographics no yes yes

Controls for risk aversion no no yesand maths scores (rounds 1 and 2)


Results 15 / 25

Regression Results


Oestrogen (level) 0.0041 0.0055 0.0045(0.0092) (0.0095) (0.0097)

Progesterone (level) -0.0116** -0.0145*** -0.0140***(0.0045) (0.0036) (0.0040)




Results 16 / 25

Regression Results

Competitiveness (4) (5) (6) (7)

Oestrogen (level) 0.0035(0.0085)

Progesterone (level) -0.0090*(0.0048)

Oestrogen (change) -0.0173* -0.0213** -0.0204** -0.0177(0.0103) (0.0100) (0.0100) (0.0107)

Progesterone (change) -0.0410** -0.0519*** -0.0529*** -0.0333**(0.0177) (0.0117) (0.0116) (0.0162)

Controls for demographics no yes yes yes

Controls for risk aversion no no yes noand maths scores


Results 17 / 25

Regression Results


Hormonal Contraceptives -0.315** -0.321* -0.258*(0.156) (0.166) (0.143)




Results 18 / 25

Evolutionary Background

I Progesterone has sedative and anti-anxiety e�ects and acts asa modulator of neurotransmitter receptors

I Evolutionary hypothesis: women are competitive during thefertile phase of their cycle when competition for geneticallystrong mates occurs and not competitive after ovulation isover (and during pregnancy) when commitment a long-termpartner is more important

I Women, who are in charge of taking care of the o�spring, facehigher costs of competitive behaviour compared to men, whospread their semen and run, because their death generallymeans the loss of their current o�spring (Campbell, 2002).This is especially true during pregnancy when hormonalconditions are similar to those in the luteal phase (Jones et al.,2005).


Results 19 / 25

Evolutionary Background

I Women's commitment to their romantic relationship andattraction to femininity in male faces are positively andsigni�cantly correlated with progesterone levels (Jones et al.,2005)

I During fertile phase women are more likely to engage inextra-pair copulations (Bellis and Baker, 1990) and moreattracted to testosterone-related masculine facial features(Penton-Voak and Perrett, 2000)


Pathways 20 / 25

Risk Aversion

I Is impact of sex hormones on competitiveness mediatedthrough impact on risk aversion?

I Chen et al. (2005) hypothesise that the impact of themenstrual cycle on auction bids is mediated via an impact onrisk aversion

I Datta Gupta et al. (2005) show that women are in�uenced bytheir degree of risk aversion when deciding whether to competeor not

I Majority of lab experiments show that women are more riskaverse than men (Croson and Gneezy, 2009)


Pathways 21 / 25

Risk Aversion

I Competitiveness signi�cantly varies with risk aversion

I Kruskal-Wallis P-value: 0.01I Linear probability model: the most risk seeking subjects are

around forty percent more likely to compete than the most riskaverse

I But sex hormones have no impact on risk aversion

I Kruskal-Wallis P-values: 0.79 for variation across themenstrual cycle and 0.18 for contraceptive-induced variation

I Regression results show no impact either


Pathways 22 / 25

Maths Scores

I Psychologists have found evidence of �uctuations of cognitiveabilities over the menstrual cycle

I Does not hold

I There is no signi�cant impact of sex hormones on averagemaths scores (Kruskal-Wallis P-value for variation over themenstrual cycle: 0.8281)

I Maths scores do not in�uence decision of whether or not tocompete


Pathways 23 / 25

Maths Scores


Mean Score (Rounds 1 and 2) 0.00365 0.0113 0.00671(0.0125) (0.0125) (0.0120)

Controls no yes yes

Controls for cycle and contraceptives no no yes


Pathways 24 / 25

Overcon�dence

I I �nd some evidence that (over)con�dence in�uencestournament entry

I Subjects who belief that they are amongst the two best in theirgroup are 16 percent more likely to enter the tournament(P-value: 0.0638; one-sided t-test)

I Subjects who overestimate their performance in round two are13 percent more likely to compete (P-value: 0.1006)

I But beliefs of individuals are not a�ected by sex hormones:Kruskal-Wallis P-values are 0.5931 for variation over themenstrual cycle and 0.3447 for contraceptive-induced variation


Pathways 25 / 25

Conclusions

I Female sex hormones are important for explaining genderdi�erences in competitiveness and potentially other economicbehaviours

I Part of gender di�erences in labour market decisions could becaused by biological factors


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