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It has become well-accepted that women are more risk averse than men. This research investigates when gender differences in risk aversion are likely to occur and when they are less likely to manifest. We find that gender differences in risk aversion are likely to occur in decisions under risk, where the probability of outcomes is known and objectiv...
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Context 1
... p 2 = .20. As shown in Figure 1, men are willing to pay about twice as much for each gamble; the gender difference is significant for all three winning probability levels (33%: F (1 Figure 1 illustrates that the gender difference in risk aversion grows as the probability of winning the gamble increases. These results replicate prior research noting a gender difference in risk aversion using incentive compatible payments (Croson & Gneezy, 2009;Eckel & Grossman, 2002, 2008Holt & Laury, 2002;Schubert et al., 1999). ...
Context 2
... p 2 = .20. As shown in Figure 1, men are willing to pay about twice as much for each gamble; the gender difference is significant for all three winning probability levels (33%: F (1 Figure 1 illustrates that the gender difference in risk aversion grows as the probability of winning the gamble increases. These results replicate prior research noting a gender difference in risk aversion using incentive compatible payments (Croson & Gneezy, 2009;Eckel & Grossman, 2002, 2008Holt & Laury, 2002;Schubert et al., 1999). ...
Context 3
... p 2 = .20. As shown in Figure 1, men are willing to pay about twice as much for each gamble; the gender difference is significant for all three winning probability levels (33%: F (1 Figure 1 illustrates that the gender difference in risk aversion grows as the probability of winning the gamble increases. These results replicate prior research noting a gender difference in risk aversion using incentive compatible payments (Croson & Gneezy, 2009;Eckel & Grossman, 2002, 2008Holt & Laury, 2002;Schubert et al., 1999). ...
Context 4
... p 2 = .20. As shown in Figure 1, men are willing to pay about twice as much for each gamble; the gender difference is significant for all three winning probability levels (33%: F (1 Figure 1 illustrates that the gender difference in risk aversion grows as the probability of winning the gamble increases. These results replicate prior research noting a gender difference in risk aversion using incentive compatible payments (Croson & Gneezy, 2009;Eckel & Grossman, 2002, 2008Holt & Laury, 2002;Schubert et al., 1999). ...
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... Finally, several authors have studied whether the gender and other characteristics of the creator influence the behavior of backers and the probabilities of success in crowdfunding (Rossi et al., 2021;Cumming et al., 2021;Letwin et al., 2023 andWang et al., 2023). Herding behavior may be related to risk aversion and to self-confidence, and these are characteristics that may be linked to gender (Eckel & Grossman, 2008;Sarin & Wieland, 2012). Thus, it can be interesting to study whether women contributors to crowdfunding campaigns are more prone to herd. ...
This paper investigates how signaling and herding behavior interact in crowdfunding markets to give raise to an information cascade, even when there are no identifiable experts, which is the typical case in reward-based crowdfunding. Using daily funding data for on all the projects launched on Kickstarter during one month, we find that during the initial phase of the campaign, the funding decisions of a reduced number of early backers are based on information and quality signals offered by the creator. However, during the second phase, signaling is substituted by the herding behavior of a large number of late backers, imitating early backers. The results suggest that, even in the absence of identifiable experts, backers self-select into early or late backers depending on their ability to process the information, so that herding after signaling generates an information cascade that ameliorates asymmetric information problems. The findings are relevant for (i) creators, that will obtain better results by targeting their crowdfunding campaigns at better informed potential contributors, and (ii) regulators, that can expect backers’ self-selection and herding to work together to protect uninformed backers from fraud and deception even when participation is not restricted.
... We start with the issue of gender, where there is a large literature suggesting that women are more risk averse than men (e.g., Bajtelsmit and Bernasek 1996;Barber and Odean 2001;Borghans et al. 2009;Croson and Gneezy, 2009;Dohmen et al. 2011;Finucane et al. 2000;Jianakoplos and Bernasek 1998;Powell and Ansic 1997;Schubert et al. 1999;Sarin and Wieland 2012;Scottish Friendly 2018;l'Haridon and Vieider, 2019). We observe that the male is above average, while the female is below average (with both below unity), and * indicates that the difference between men and women is statistically significant at the 5% level. ...
We quantify differences in attitudes to loss from individuals with different demographic, personal and socio-economic characteristics. Our data are based on responses from an online survey of a representative sample of over 4000 UK residents and allow us to produce the most comprehensive analysis of the heterogeneity of loss aversion measures to date. Using the canonical model proposed by Tversky and Kahneman (1992), we show that responses for the population as a whole differ substantially from those typically provided by students (who form the basis of many existing studies of loss aversion). The average aversion to a loss of £500 relative to a gain of the same amount is 2.41, but loss aversion correlates significantly with characteristics such as gender, age, education, financial knowledge, social class, employment status, management responsibility, income, savings and home ownership. Other related factors include marital status, number of children, ease of savings, rainy day fund, personality type, emotional state, newspaper and political party. However, once we condition on all the profiling characteristics of the respondents, some factors, in particular gender, cease to be significant, suggesting that gender differences in risk and loss attitudes might be due to other factors, such as income differences.
... According to them, some are risk neutral, some are risk averse, but few are risk loving. Moreover, Wieland and Sarin [4] study risk attitude focusing on gender. They propose that women tend to be more risk averse than men if the probability of the result is known. ...
This study focuses on using fee-charge video-on-demand services and reveals how people react when there are two uncertainties in decision making. Conducted economic experiments show that the choice rate of subscription video-on-demand service increases as the expected utility of watching videos grows. The experiments also show that the two uncertainties affect our decision making, but with a difference in degree.
... Importantly, such a heterogeneity of the gender pattern is not due to the fact that HL induces more noise than other tasks, something that, if true, would make it more difficult to detect the same differences in the underlying preferences. Observing a gender gap not only depends on the task being contextual or not (Eckel and Grossman 2008a), or on it having to do with risk or with uncertainty (Wieland and Sarin 2012), or on the choices being incentivised, self-reported, or observed (Byrnes et al. 1999). Even restricting the analysis to the narrow domain of incentivised lottery choice tasks currently used in experimental economics, gender differences depend on the details of the task. ...
This paper reconsiders the wide agreement that females are more risk averse than males. We survey the existing experimental literature, finding that significance and magnitude of gender differences are task specific. We gather data from 54 replications of the Holt and Laury risk elicitation method, involving about 7,000 subjects. Gender differences appear in less than 10% of the studies and are significant but negligible in magnitude once all the data are pooled. Results are confirmed by structural estimations, which also support a constant relative risk aversion representation of preferences. Gender differences correlate with the presence of a safe option and fixed probabilities in the elicitation method.
... Importantly, such a heterogeneity of the gender pattern is not due to the fact that HL induces more noise than other tasks, something that, if true, would make it more difficult to detect the same differences in the underlying preferences. Observing a gender gap not only depends on the task being contextual or not (Eckel and Grossman 2008a), or on it having to do with risk or with uncertainty (Wieland and Sarin 2012), or on the choices being incentivised, self-reported, or observed (Byrnes et al. 1999). Even restricting the analysis to the narrow domain of incentivised lottery choice tasks currently used in experimental economics, gender differences depend on the details of the task. ...
This paper reconsiders the wide agreement that females are more risk averse than males. We survey the existing experimental literature, finding that significance and magnitude of gender differences are task specific. We gather data from 54 replications of the Holt and Laury risk elicitation method, involving about 7,000 subjects. Gender differences appear in less than 10% of the studies and are significant but negligible in magnitude once all the data are pooled. Results are confirmed by structural estimations, which also support a constant relative risk aversion representation of preferences. Gender differences correlate with the presence of a safe option and fixed probabilities in the elicitation method.
This paper was accepted by John List, behavioral economics.
We estimate loss aversion using on an online survey of a representative sample of over 4,000 UK residents. The average aversion to a loss of £500 relative to a gain of the same amount is 2.41, but loss aversion varies significantly with characteristics such as gender, age, education, financial knowledge, social class, employment status, management responsibility, income, savings and home ownership. Other influencing factors include marital status, number of children, ease of savings, rainy day fund, personality type, emotional state, newspaper and political party. However, once we condition on all the profiling characteristics of the respondents, some factors, in particular gender, cease to be significant, suggesting that gender differences in risk and loss attitudes might be due to other factors, such as income differences.
