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B. AFE: Gender and Competition

B. AFE: Gender and Competition . Recent work in experimental economics argues that men tend to be more competitively inclined than women (work due to Gneezy, Niederle, Rustichini, Vesterlund; of note is Niederle and Vesterlund’s wonderful new QJE study)

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B. AFE: Gender and Competition

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  1. B. AFE: Gender and Competition Recent work in experimental economics argues that men tend to be more competitively inclined than women (work due to Gneezy, Niederle, Rustichini, Vesterlund; of note is Niederle and Vesterlund’s wonderful new QJE study) One stylized result: Women shy away from competition

  2. Fraction who chose to be paid according to the winner-take-all scheme

  3. Exploring The Underpinnings • The literature and popular press are littered with potential explanations for these behavioral differences. • Is difference in competitiveness solely due to “sex” differences? • What role does “gender” play? • Straw-Man Hypothesis: on average (in every society), men are more competitively inclined than women. • One first step to begin to think about this straw-man is to visit two distinct societies: one matrilineal and one patriarchal

  4. Relative roles “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)

  5. Comparing Societies

  6. Comparing Societies

  7. One speculative interpretation (of many): Khasi society may remove social barriers that prevent naturally competitive women from expressing their true personalities. Khasi society may allow competitive women to earn greater rewards for their effort and to pass on wealth to their daughters, both of which increase the fecundity of their competitive genes. We can all agree that these results need to be replicated and that further treatments need to be carried out to detail the underlying structure at work.

  8. C. Using Natural Field Experiments in Partnerships with Firms • Outline: • I. Non-Profits • Giving Facts • Some Recent Work in the Economics of Charity • II. For Profits

  9. The Charitable Market Government Charity Donor / Solicitee

  10. What is at Stake?

  11. Why Study? • Theoretical: Unravel why people give to charities. What models best predict behavior? • Measure key parameters • Collect information to construct a theory

  12. Practical “There is an extraordinary amount of money available. The lack is of good ideas on how to get the basket under the apple tree” The Economist, July 31st, 2004, p. 57. Beyond the theoretical, policy, and practical import, the “demand side” of the economics of charity is ill-understood.

  13. Fundraising A. UCF experience Seed Money 1. Most capital campaigns do not kick off publicly until a substantial amount of seed money has been promised in a “quiet” period. UW’s Kohl Center ($27M of $72M) The Fundraising School (1999) recommends that “40% to 50% of the goal” be pledged before the public campaign begins. Other handbooks recommend figures between 20% and 50%. Refunds 2. There also exist examples of the use of refunds in case the fundraising campaign fails to reach the threshold. Manitoba’s New Democratic Party, 1985 - $250K Association of Oregon Faculties, 1979 - $30K

  14. 3x2 Experimental Idea Use a mail solicitation and split the campaign into several smaller capital campaigns (6 computers), randomizing households into treatment: 3 seed levels (10%, 33%, and 67%) crossed with refund/no refund. List and Lucking-Reiley (2002; JPE) found that seed money works well and refunds marginally increase contributions. Results were not entirely consistent with extant theory, rather more consistent with a signaling model.

  15. Other Uses of Upfront Money B. Conditional on having upfront money, should one use seed money or matching grants to raise funds? 4 treatment (2 controls, seed, matching) mail solicitation with the Sierra Club of Canada for a threshold public good. Contributions in the seed money and matching grant treatments are higher than those in the control treatments.

  16. Match Rates C. Dove (p. 15, 2000) warns that one should: “never underestimate the power of a challenge gift” and that “obviously, a 1:1 match—every dollar that the donor gives is matched by another dollar—is more appealing than a 1:2 challenge…..and a richer challenge (2:1) greatly adds to the match’s attractiveness.” A recent $50 million challenge grant gift to Drake University, which was among the forty largest gifts in U.S. history to an institution of higher education by an individual, was used to spur further gifts through 2:1 and 3:1 matching solicitations (Dove, 2000).

  17. Karlan and List (2007; AER) Basics • National liberal non-profit in the United States, political & socially oriented work • Sends letters regularly to prior donors (and acquisition mailers) • Anonymous donor with matching funds and desire to know how best to stir up further funding • 50,083 letters sent in August, 2005, following natural approach • 3 main treatments: • Match ratio: $3:1, $2:1, $1:1, no match • Maximum match amount: $100k, $50k, $25k, unstated • Example amount: Low, medium, or high

  18. Insert into Reply Card

  19. Results 19% more money raised per letter in the matching treatments The effect entirely occurs on the extensive, rather than intensive, margin: Response rate was 22% higher in matching treatments No additional response from higher ratios: 3-1, 2-1, and 1-1 perform similarly.

  20. Other Recent Work D. Lotteries—another use of up-front money (Landry et al, 2006 QJE; Lange et al., 2007 IER) E. Donor Gifts (Falk, 2008 ECTA, Landry et al., 2010 AER) F. What are the underpinnings for why people give in a door-to-door drive? (della Vigna et al., 2009)

  21. On-Going Field Experiments A. Give More Tomorrow B. Larger Donors; naming rights C. Phone-athons

  22. Lessons Learned 1. Smaller givers do not seem to be buying a private good when they donate 2. Upfront money is important; most effectively used as announced seed money. 3. Non-price incentives can have strong effects on givers: Use of a donor gift can substitute for a warm-list. 4. Long-run fundraising success depends on incentives used to attract first-time donors: Some types of incentives might crowd out reasons for giving later (incentives that signal charity quality seem to stick)

  23. Experiments with For-Profits Chrysler weight loss experiment—team incentive schemes can be quite useful in inducing weight loss. Chinese mfg. plant worker productivity experiment—simple frame manipulations matter. Ambassador’s Group—combining field experiments with naturally-occurring data can sharpen inference tremendously.

  24. Watch for an Experiment Near You! Major airline pricing experiment next Wednesday. Large insurance provider is now randomizing rate quotes. Busy website is using experimentation to increase shoe sales.

  25. Concluding Thoughts A. Field experiments take many shapes and forms and all might not fit neatly into the guideposts herein. http://www.fieldexperiments.com Their usage should continue to grow as we recognize and take advantage of settings where economic phenomena present themselves.

  26. Generation Next: Collaboration with private partners • Due to the historical outgrowth of field experiments from social experiments, it is unsurprising that most are done in partnerships with governments and NGOs • However, field experiments in the private sector are a largely untapped opportunity • Some low hanging fruit: • Optimal worker incentive schemes, hierarchal arrangements, social structures and networks relating to workplace design, firm compliance with rules and regulations, worker malfeasance, wellness and health programs.

  27. Concluding Thoughts B. Data, thus far, suggest that representativeness of the environment appears more important than representativeness of the population for some key economic games. We can learn a lot from doing more sampling of environments and stimuli that people actually encounter.

  28. An Example • A recent Govt. contingent valuation study explored whether men or women surveyors obtained higher stated values. • What did they do? • Spent gads of money to choose carefully a representative sample of respondents. • Had one man and one woman survey!

  29. $$$$ $0 $0 $$$$ Inference would be much different across these scenarios.

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