We present evidence of a direct social context effect on decision-making under uncertainty: the gender composition of those in the room when making individual risky decisions significantly alters choices even when the actions or presence of others are not payoff relevant. In our environment, decision makers do not know the choices made by others, nor can they be inferred from the experiment. We find that women become more risk taking as the proportion of men in the room increases, but the behavior of men is unaffected by who is present. We discuss some potential mechanisms for this result and conjecture it is driven by women being aware of the social context and imitating the expected behavior of others. Our results imply that the environment in which individual decisions are made can change expressed preferences and that aggregate behavior may be context dependent.
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See Eckel and Grossman (2001) for gender composition in ultimatum games, Gneezy et al. (2003) for tournaments, Bogan et al. (2013) for risk decisions of groups, Charness et al. (2007) for public and private decisions, Lindquist and Säve-Söderbergh (2011) for decisions in Jeopardy’s daily double, Cooper and Rege (2011) and Rohde and Rohde (2011) for peer effects in risky decisions, and Ambrus et al. (2015) for aggregation of individual risk preferences.
In Booth and Nolen (2012), adolescent boys and girls are randomly assigned to sit in 4-person groups in a large auditorium and complete five tasks in total, including a maze tournament with their group prior to choosing in a binary-choice lottery task.
This also speaks to Manski’s (2000) point that peer effects are difficult to identify because they are confounded by information and strategy.
At the first two sites, there are 21 8-person sessions and 14 6- and 7-person sessions. From the 8-person sessions, 6 of the 42 rooms are single-sex.
At the third site, there are 12 8-person sessions, with 6 rooms each of (4 w, 0 m), (3 w, 1 m), (1 w, 3 m) and (0 w, 4 m).
We find no evidence that room composition is correlated with either experimenter.
When we combine 6-, 7- and 8-person sessions, there are 356 participants, 47 sessions and 94 rooms (74 4-person rooms and 20 3-person rooms). In these pooled data, the distribution of gender composition of the rooms is: 9 all-women rooms, 24 rooms with one man, 18 of equal number of men and women, 27 rooms with one woman and 16 all-men rooms.
In the pooled 6-, 7- and 8-person sessions, 55.3% are male, 53.1% are White, 18.3% are Black, and 16.6% are Asian.
Manski (1999) would call this a contextual effect (e.g. the propensity of the individual to behave in some way varies with the distribution of background characteristics of the group).
Most participants (93.2%) are consistent, in that the average amount of money invested in lotteries with an expected payoff of $1 or more is at least as large as for those with an expected payoff of less than $1. On average, men are more consistent than women: 97% and 88% respectively.
All results hold if we instead specify gender composition with dummy variables for whether the participant is the minority sex in the room or the room is composed of all the same sex. Women put more money in the lottery when they are the minority sex in the room. Results in Table 1 also hold if lotteries are grouped by expected payoff of> $1, = $1 and< $1 (see Online Appendix).
An ordered logit is preferred in this setting because the investment decision may be nonlinear. The return of a dollar invested in the lottery is different across lotteries and the marginal utility of a dollar gained could be decreasing as gains increase (in the case of a risk averse individual). The coefficient associated with the proportion of men in the room is 1.68, the odds conditional on a 0.75 unit increase in this variable is \(exp(1.68\times 0.75) \sim 3.5\).
In a pooled regression with a dummy variable for being male and interaction terms with all the independent variables for the specification in Column 1, the coefficient on the interaction term on the proportion of males in the room is − 2.34 (p value of 0.088).
Without the all-female sessions, the coefficient on the proportion of males in the room is 1.65 (p value = 0.071) for women and − 0.77 (p value = 0.444) for men. Without the all-male sessions, these are 1.68 (p value = 0.074) and − 1.16 (p value = 0.284) respectively. Testing the gender difference in response yields a p value of 0.087 without the all-female sessions and 0.053 without the all-male sessions.
The total time to finish the task is the time it takes the participant to complete and submit all eight decisions. The correlation for women is − 0.333 (p value = 0.000) and for men is − 0.226 (p value = 0.006).
Kocher et al. (2013) find that risk aversion over gains is not affected by being rushed while risk aversion over pure losses actually increases.
There is no significant effect of the number of mouse clicks on the average risky investment. Coefficients on the average number of clicks by others on average risky investment are − 0.005 (p value = 0.209) for women and 0.004 (p value = 0.378) for men.
This procedure elicits a participant’s belief about the modal $3 interval for the average bet of others.
Ambrus, A., Greiner, B., & Pathak, P. A. (2015). How individual preferences are aggregated in groups: An experimental study. Journal of Public Economics, 129, 1–13.
Andreoni, J., & Bernheim, B. D. (2009). Social image and the 50–50 norm: A theoretical and experimental analysis of audience effects. Econometrica, 77(5), 1607–1636.
Asch, S. E., & Guetzkow, H. (1951). Effects of group pressure upon the modification and distortion of judgments. Groups, Leadership, and Men, 84, 222–236.
Baron-Cohen, S., Knickmeyer, R. C., & Belmonte, M. K. (2005). Sex differences in the brain: Implications for explaining autism. Science, 310(5749), 819–823.
Bertrand, M., Luttmer, E. F., & Mullainathan, S. (2000). Network effects and welfare cultures. The Quarterly Journal of Economics, 115(3), 1019–1055.
Bogan, V., Just, R. D., & Dev, C. S. (2013). Team gender diversity and investment decision-making behavior. Review of Behavioral Finance, 5(2), 134–152.
Bohnet, I., & Frey, B. S. (1999). Social distance and other-regarding behavior in dictator games: Comment. American Economic Review, 89(1), 335–339.
Bond, R., & Smith, P. B. (1996). Culture and conformity: A meta-analysis of studies using Asch’s (1952b, 1956) line judgment task. Psychological Bulletin, 119(1), 111.
Booth, A. L., Cardona-Sosa, L., & Nolen, P. (2014). Gender differences in risk aversion: Do single-sex environments affect their development? Journal of Economic Behavior and Organization, 99, 126–154.
Booth, A. L., & Nolen, P. (2012). Gender differences in risk behaviour: Does nurture matter? The Economic Journal, 122(558), F56–F78.
Buser, T., Niederle, M., & Oosterbeek, H. (2014). Gender, competitiveness, and career choices. The Quarterly Journal of Economics, 129(3), 1409–1447.
Charness, G., & Gneezy, U. (2012). Strong evidence for gender differences in risk taking. Journal of Economic Behavior Organization, 83(1), 50–58.
Charness, G., Gneezy, U., & Imas, A. (2013). Experimental methods: Eliciting risk preferences. Journal of Economic Behavior and Organization, 87, 43–51.
Charness, G., Rigotti, L., & Rustichini, A. (2007). Individual behavior and group membership. American Economic Review, 97(4), 1340–1352.
Conley, T. G., & Udry, C. R. (2010). Learning about a new technology: Pineapple in Ghana. American Economic Review, 100(1), 35–69.
Cooper, D. J., & Rege, M. (2011). Misery loves company: Social regret and social interaction effects in choices under risk and uncertainty. Games and Economic Behavior, 73(1), 91–110.
Cooper, H. M. (1979). Statistically combining independent studies: A meta-analysis of sex differences in conformity research. Journal of Personality and Social Psychology, 37(1), 131.
Croson, R., & Gneezy, U. (2009). Gender differences in preferences. Journal of Economic Literature, 47(2), 448–74.
Dohmen, T., & Falk, A. (2011). Performance pay and multidimensional sorting: Productivity, preferences, and gender. American Economic Review, 101(2), 556–90.
Duflo, E., & Saez, E. (2003). The role of information and social interactions in retirement plan decisions: Evidence from a randomized experiment. The Quarterly Journal of Economics, 118(3), 815–842.
Eagly, A. H., & Carli, L. L. (1981). Sex of researchers and sex-typed communications as determinants of sex differences in influenceability: A meta-analysis of social influence studies. Psychological Bulletin, 90(1), 1–20.
Eckel, C. C., & Grossman, P. J. (2001). Chivalry and solidarity in ultimatum games. Economic Inquiry, 39(2), 171–188.
Eckel, C. C., & Grossman, P. J. (2008a). Forecasting risk attitudes: An experimental study using actual and forecast gamble choices. Journal of Economic Behavior and Organization, 68(1), 1–17.
Eckel, C. C., & Grossman, P. J. (2008b). Men, women and risk aversion: Experimental evidence. Handbook of Experimental Economics Results, 1, 1061–1073.
Fisher, R. A. (1960). The design of experiments (7th ed.). Edinburgh: Oliver and Boyd.
Gneezy, U., Niederle, M., & Rustichini, A. (2003). Performance in competitive environments: Gender differences. The Quarterly Journal of Economics, 118(3), 1049–1074.
Gneezy, U., & Potters, J. (1997). An experiment on risk taking and evaluation periods. The Quarterly Journal of Economics, 112(2), 631–645.
Grossman, P. J. (2013). Holding fast: The persistence and dominance of gender stereotypes. Economic Inquiry, 51(1), 747–763.
Grossman, P. J., & Lugovskyy, O. (2011). An experimental test of the persistence of gender-based stereotypes. Economic Inquiry, 49(2), 598–611.
Heß, S. (2017). Randomization inference with Stata: A guide and software. The Stata Journal, 17(3), 630–651.
Kocher, M. G., Pahlke, J., & Trautmann, S. T. (2013). Tempus fugit: Time pressure in risky decisions. Management Science, 59(10), 2380–2391.
Levinger, G., & Schneider, D. J. (1969). Test of the “risk is a value” hypothesis. Journal of Personality and Social Psychology, 11(2), 165.
Lindquist, G. S., & Säve-Söderbergh, J. (2011). “Girls will be girls”, especially among boys: Risk-taking in the “daily double” on Jeopardy. Economics Letters, 112(2), 158–160.
Manski, C. F. (1999). Identification problems in the social sciences. Cambridge: Harvard University Press.
Manski, C. F. (2000). Economic analysis of social interactions. Journal of Economic Perspectives, 14(3), 115–136.
McClure, E. B. (2000). A meta-analytic review of sex differences in facial expression processing and their development in infants, children, and adolescents. Psychological Bulletin, 126(3), 424.
McGuire, W. J. (1984). Search for the self: Going beyond self-esteem and the reactive self. Personality and the Prediction of Behavior, 73, 120.
Niederle, M., & Vesterlund, L. (2007). Do women shy away from competition? Do men compete too much? The Quarterly Journal of Economics, 122(3), 1067–1101.
Rohde, I. M., & Rohde, K. I. (2011). Risk attitudes in a social context. Journal of Risk and Uncertainty, 43(3), 205–225.
Young, A. (2019). Channeling fisher: Randomization tests and the statistical insignificance of seemingly significant experimental results. The Quarterly Journal of Economics, 134(2), 557–598.
Zahn-Waxler, C., Shirtcliff, E. A., & Marceau, K. (2008). Disorders of childhood and adolescence: Gender and psychopathology. Annual Review of Clinical Psychology, 4, 275–303.
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Castillo, M., Leo, G. & Petrie, R. Room composition effects on risk taking by gender. Exp Econ 23, 895–911 (2020). https://doi.org/10.1007/s10683-019-09635-w
- Decision context effects
- Risk aversion