1. Gender and Economic Behavior: Insights from Experiments

2. Gender and Economic Behavior
Gender an important factor in many economic decisions and outcomes. Gender differences in wages, prospects for advancement, occupational choice (Blau and Kahn (2000), Blau, Ferber and Winkler (2010)). Bertrand & Hallock (2001): Only 2.5% of US executives are women, and they earn 45% less than male counterparts. Much fewer women in leadership positions in firms, in politics etc.

3. Gender Differences in:
Risk-taking
Altruism
Beliefs (e.g. overconfidence)
Competitiveness (in performance tasks, or negotiations/bargaining)
Leadership
Etc.

4. Experimental Literature on Gender
Documents differences
Explores the source of differences
Studies the role of institutions in influencing these differences (e.g. feedback, single-sex schooling etc.)

5. Different explanations: ability differences, family-career balance, discrimination… Another explanation: men and women might have different responses to and attitudes toward competition. Competitive career path for high-level positions, self-selection.

6. Gender and Competitiveness
1. Gender differences in the response to competition
Gneezy, Niederle & Rustichini (2003):
Men are more motivated by competition than women.
Piece-rate vs. tournament
Single-sex vs. mixed groups (results mixed)

7. Gneezy (2004), in Israel Physical ed. Class Running
When ran alone, no gender difference
Boys’ performance improves in competition

8. Self-Selection Gender differences in choice of incentive schemes:
Niederle & Vesterlund (2007):
Piece-rate, tournament, choice, submit to tournament.
Women shy away from competition. Piece-rate vs. tournament: 73% of males, only 35% of females.

9. Details of Niederle-Vesterlund’s Design (Used in Many Following Experimnets
Task I-PIECE-RATE
Subjects work on task, receive 50 cents per correct answer
Task II-TOURNAMENT
Subjects work on task, receive 2 dollars only if they win, winning means being the best performer in their group of 4 people.
Task III-CHOICE
Subjects choose the incentive scheme, and then work under their chosen incentive scheme
Task IV: SUBMIT PAST PERFORMANCE TO PIECE-RATE or TOURNAMENT
Subjects now do not have to do task again, but they make the following choice about their 1st period performance: either they want it rewarded by a piece-rate (50 c per correct) or a tournament (in this case it is compared to 3 other people and you get 2 dollars per correct only if you win)=> The reason they are doing this is to isolate the thrill or anxiety of actual competition from beliefs, risk-aversion etc.

10. Your Data

11. Your Beliefs
81% of people think they’re better than a randomly selected person!

12. Overconfidence
In surveys, “better-than-average” effect (93% of a sample of American drivers report that they were more skillful than the median driver in their own country (Svenson, 1981)).
Eliciting beliefs with incentives in experiments is not easy (problem with surveys? Problem if you pay beliefs?)

13. “Updating Beliefs” Ertac (2006): addition task, GRE verbal Do task
Assign probabilities to being in the top 20%, middle 60%, or bottom 20%
Then information comes (Top/Not Top, Bottom/Not Bottom)
Then you update your beliefs.
Control task: The same priors, but information is about state A, B, C (no ego-relevance).

15. Main Results
Overconfidence in addition, underconfidence in GRE verbal (difficult) When underconfident, use information pessimistically The overconfident ones use information optimistically (self-serving bias) Errors do not follow a clear pattern and are smaller in control task

16. Updating Beliefs
Eil & Rao (2011): IQ and BEAUTY IQ: Test, you get ranked BEAUTY: Speed-dating exercise, you get ranked You report prior beliefs (how likely are you to be the 1st, 2nd, 3rd,….., 10th person?) Then you get 4 pieces of information: Good news (you’re better than random person) Bad news (you’re worse than random person)

17. Main results
With good news: Less noisy processing, you act more rationally
With bad news: Self-serving bias—you discount it, do not incorporate it into your beliefs
Also: WTP for learning actual true rank:
Receive X and learn true rank
Receive 0 and not learn true rank
X ranges between $-7 and $7 (like a BDM mechanism)
Most optimistic people: Highest WTP
Most pessimistic people: Lowest WTP

18. Back to GENDER: Why do competitiveness differences exist?
Nature vs. Nurture:
Is it innate, or shaped by society?
“Sex vs. gender”?
Important for policy issues. Suppose you want to close the gap:
If nature, may need to make education system less competitive.
If nurture, socialize girls in a different way, keep education system competitive.

19. Gneezy, Leonard, List (2009):
Compare a matrilineal society (India) with an extremely patriarchal society (Tanzania).
“Men treat us like donkeys”
--A Maasai woman (Hodgson, 2001)
“We are sick of playing the roles of breeding bulls and baby-sitters.”
--A Khasi man (Ahmed, 1994)

20. Matrilineal society: Khasi in India

21. The Khasi Society Females are holders of property
Lineage descends through the mother (matrilineal)
Youngest daughter is the heir, and does not leave the mother’s home.
Men live in their mother’s or wife’s home.
Women more involved in economic activity.
“Men’s rights to property” movement in Shillong city.

23. Gneezy, Leonard & List (2009) Massai (Tanzania) vs. Khasi (India)
50% vs. 26% in Massai, 54% vs. 39% in Khasi.

24. 50% vs. 26% in Massai, 54% vs. 39% in Khasi.
The “men compete more” result is not universal, and societal factors can be important.
One interpretation: Khasi society may remove social barriers that prevent naturally competitive women from expressing their true personalities.
Or, the structure of the Khasi society may allow competitive women to earn greater rewards for their effort and to pass on wealth and competitive tendencies to their daughters, both of which increase the fecundity of competitive genes [gene-culture co-evolution]

25. Gender and Socialization
Data from adults do not tell us at what stage of the socialization process the difference starts.
Learning how competitiveness evolves through age can be important for policy.
=>Study kids of different ages.

26. Matrilineal (Khasi) vs. patriarchal (Kharbi)
=>Both in Northeast India
Very close in terms of location, so can keep other factors constant and have a cleaner comparison

27. Procedures
Use children aged 7-15, elicit information on age, grade in school.
Task: Throwing tennis balls into a bucket from a distance (Gneezy et al. find no significant difference in performance across gender).
Subject selects between two incentive schemes:
*Piece-rate: 10 Rupees per successful ball.
*Tournament: 30 Rupees per ball, only if you are better than opponent. 0 if worse, 10 if tie.
Opponent is randomly selected—subject never learns whom she is competing with.

28. Subjects

31. Data
Experiments conducted in 4 villages, 2 matrilineal and 2 patriarchal.
Matri
Patri
All
Boys 96 71
167
Girls 76 75
151
172
146
318

32. No gender difference in performance (mean performance is 1.6 balls).
Performance increases with age, although no gender-age interaction in either society.

34. Results: Across Gender, Within Society
Younger kids: No significant difference in matri, no significant difference in patri Older kids: Still no significant difference in matri, significant difference emerges in patri Girls compete less than boys (p<0.01)

35. Are Choices Ex-Post Optimal?
Risk-neutral subject should compete if 3Pr(win)+Pr(tie)>1
For each performance level, randomly draw 1000 opponents and calculate the win and tie probabilities
Check whether choices are optimal, given the empirical distribution of performance.

36. Types of Errors in Choices, Across Gender, Age and Society
7-12 Years old
13-15 Years old
All
Under
Over
Patriarchal Girls
47.46%
22.03%
62.50% 0%
50.67%
17.33%
Patriarchal Boys
32.14%
33.93%
26.67%
20%
30.99%
Matrilineal Girls
14.52%
35.48%
28.57%
17.11%
34.21%
Matrilineal Boys
12.66%
44.30%
11.76%
17.65%
12.50%
39.58% ]
25.38%
34.77%
32.26%
16.13%

37. Older girls in the patriarchal society under-enter 62
Older girls in the patriarchal society under-enter 62.5% of the time, never over-enter.
In contrast, older girls in the matrilineal society under-enter 28.6% of the time.

38. Hormones?

39. Discussion
Socialization might act along with biological forces to create the difference around puberty “Gender-intensification theory” in psychology (Hill and Lynch (1983))—with puberty, more pressure for sex-typed behavior (e.g. precarious manhood) An interesting question: Are the societies biologically different as well? Further dimensions: Self-confidence, response to performance feedback, self-selection in other domains.

40. What Kind of Policies? Single-sex schooling (Booth and Nolen (2011))
Students from ss & mixed schools brought to university for experiment
Random assignment to groups
All-girl, all-boy, mixed.
Girls from single-sex schools are more competitive and more risk-tolerant than girls in mixed schools
Problems?

41. What Kind of Policies?
An important institutional choice variable that might affect competition decisions: Performance feedback Competition choices usually dynamic in nature How much feedback to reveal in interim stages is a policy variable. In organizational and educational settings.

42. Performance Feedback Literature:
The effects of feedback policies on beliefs, performance and choices, under a variety of incentive schemes.
Ertac (2006, 2009)
Niehaus et al. (2010)
Ederer (2010), Azmat and Iriberri (2009, 2010)
Barankay (2010)
Gender and uncertainty: Ertac, Hortacsu, Roberts (2010)

43. The Effect of Performance Feedback on Gender Differences in Competitiveness (with Balazs Szentes, LSE)
If there is less uncertainty before the choice, how will the gender difference be affected? Original Niederle & Vesterlund experiment (2007): Piece-rate, tournament, then choice between piece-rate and tournament. Replicate the original Niederle & Vesterlund experiment except: Treatment: Vary the amount of uncertainty in the tournament environment (info vs. no info).

44. Design Task I-PIECE-RATE
Subjects work on task, receive 50 cents per correct answer
Task II-TOURNAMENT
Subjects receive 2 dollars only if they win, winning means being the best performer in their group of 4 people.
INFORMATION STAGE
Subjects learn the maximum performance of the other people in their group in the Task-2 Tournament.
Task III-CHOICE
Subjects choose the incentive scheme, and then work under their chosen incentive scheme
Survey (self-professed risk-loving, competitiveness)

45. Procedures
Task: Adding five 2-digit numbers e.g =? Solve as many as possible within 5 minutes, for each task. Experiments run at UCLA. 148 subjects in total, 74 male & 74 female. 108 of them in info treatment.

46. Results No performance difference between genders.
Competition percentages:
44% females, 48% males in information treatment.
30% females, 60% males in no information treatment.
=> No significant gender difference in the information treatment.
The effect between the two treatments seems to come from high-ability females entering more.

48. More Stuff on Competitiveness
*Highlighting family to women MBA’s (vs. professional life) (priming) Makes them less competitive, men more.

49. Gender and Bargaining
“Women don’t ask”—Starting salaries much lower because only 7% (vs. 57%) of women MBA’s negotiate=> Male starting salaries 7.6 % higher (Babcock and Laschever (2003))
Experiment with verbal task.
Regardless of performance, at end of experiment: “you earned $3, is that OK?” Much fewer women say no.

50. Gender and Leadership
Fewer women in leadership positions in business, politics, military etc.
(see Eagly and Karau (2002), Blau, Ferber and Winkler (2002)).
Usual explanations: ability differences, family-career balance, discrimination etc.
Propose an explanation based on self-selection.
Leadership involves risky decisions made on behalf of others.
Are women less willing to take such responsibility?

51. Design
Task: Allocating 10 TL into a risky and a riskless option (Gneezy and Potters (1997)).
Riskless option pays: Invested amount for sure.
Risky option pays:
p*(invested amount) with probability 0.5, p>1
0 with probability 0.5
Amount allocated to riskless option is a measure of risk-aversion.

52. Task 1: Individual decision-task. Allocate 10 TL for yourself
Task 1: Individual decision-task. Allocate 10 TL for yourself. 3 periods, with pє{1.5, 2, 2.5} Task 2: Group decision-task Allocate 10 TL on behalf of a group of 5. Before Task 2: Subjects state whether they would like to make the decision for their group.

53. How the Decision-Maker is Selected
If only one person willing, she is the decision-maker. If more than one person=>randomly chosen If noone=> randomly chosen. This is determined ex-post. Everyone makes decisions, in case they are selected as the decision-maker for their group.

54. Procedures
Experiments conducted at Koc U and TOBB ETU. 128 subjects. One of 6 decision tasks chosen randomly at the end. At the end, give subjects Neo-FF-TR personality inventory (“Big Five”: Openness, Agreeableness, Conscientiousness, Extroversion, Neuroticism).

55. Results: Individual Risk-Taking
People respond to changes in p, as expected.
Women individually more risk-averse than men: significantly lower average risk (Mann-Whitney test, p=0.002)

56. Main Result: Gender and the Willingness to Decide
86% of males are willing to make the decision for their group, but only 55% of the females (p = in a two-sample test of proportions). ***Does this correlate with individual risk-taking? No for females, yes for males.

57. Logit Regression of Leadership
Female
Male
Average
Individual
Risk
0.013
(0.044)
0.038**
(0.016)
Controls for session
Yes
0.047
0.1198 N 49 79

58. Group Decision-Making
General Results: Overall: 35%: “cautious shift”, 14%: “risky shift”, 51% same. Average risk taken for the group significantly lower than for self (Wilcoxon test, p<0.000)

59. Gender Results
Question 1: Are leader women as risk-taking as leader men? No (Mann-Whitney test, p=0.015) Question 2: How do leaders and non-leaders compare within gender? For females, no difference (Mann-Whitney test, p=0.832) Male leaders take more risk (Mann-Whitney test, p=0.013) Question 3: Tendency to “cautious-shift”: Strongest for non-leader males.

60. Gender and Risk-Taking, By Leadership

61. Leadership & Personality
Nothing significant for females
Male leaders more open, less agreeable.

62. Conclusions
Strong gender difference in the willingness to decide for others. Expect fewer female-led groups, and these groups to take less risk. Risk attitudes do not explain women’s leadership choices. Male leaders are more risk-taking than male non-leaders.

63. Some Field Experiments on Gender
A policy in India: 1/3 of all village councils have to be women Random assignment Results: Women voters’ policy choices are implemented more when the leader is a woman (e.g. better drinking water) At least as much public good provision Less bribery

64. Perceptions of Leaders
People less likely to be satisfied with public goods provision with female leaders
Bad prior beliefs? Unobservable characteristics playing into opinion?
Very low reelection probability

65. Women Leaders and Aspirations
Having a woman leader will increase the aspirations of families for girls’ education