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09.19.2013 - Laura Schechter
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  • 1. Stability of Social, Risk, and Time Preferences over Multiple Years Yating Chuang UW Madison Laura Schechter UW Madison
  • 2. Main Question Theoretically, social, risk, and time preferences have an important impact on economic outcomes. For a couple of decades experimental economists have been perfecting methods to measure these preferences. More recently, a growing literature looks at how play in these experiments correlates with behavior in the real world. Underlying question: Do these experiments really measure preferences which are a fixed stable personal characteristic?
  • 3. Secondary Question Experimental economists often use university labs where students sign up to participate in experiments throughout the year. But, these researchers usually have no idea what type of experiences the participants have had in previous experiments. Secondary question: Do experiences in experiments impact play in subsequent experiments?
  • 4. Data Data on subsets of the same sample in 2002, 2007, 2009, and 2010. Data have incentivized and hypothetical risk, time, and social preference experiments, as well as social preference survey questions.
  • 5. Mixed results on stability • Risk preferences are not at all stable while time preferences are extremely stable. • Survey trust questions are quite stable. • Experimental measures of social preferences are not very stable.
  • 6. Little impact across experiments. • Some evidence that being unlucky in one experiment makes players more risk averse in later experiments. • Some evidence that being linked with a more generous partner causes players to be more generous in future experiments.
  • 7. Caveats and Contributions Take our results with a grain of salt because: • There is quite a bit of attrition over the years. • Some of our sample sizes for comparisons are quite small. • We didn’t play the same exact game twice. And yet! • We are the first study to have such a large sample, over such a long period of time, with measures of so many different preferences. • Other similar research may be a long time coming.
  • 8. Outline of Talk 1. Related Literature 2. Data • Sample Selection • Survey and Experimental Data 3. Results • Stability of Preferences over Time • Impact of Previous Experiments on Play in Later Experiments • Impact of Shocks on Play in Later Experiments 4. Conclusion
  • 9. Preference Stability Literature: Risk Correlations range from 0.13 to 0.63. Little systematic difference when measured across weeks, months, or years. Little systematic difference when incentivized or hypothetical.
  • 10. Preference Stability Literature: Risk Levin et al. (2007) 124 US children/parents 3 years 0.20 - 0.38 yes inc Guiso et al. (2011) 666 Italian investors 2 years 0.13 yes hyp Kimball et al. (2008) 700 older Americans 2 years 0.27 ? hyp Love & Robison (1984) 23 US farmers 2 years -0.38 - 0.23 no hyp Sahm (2007) 12000 older Americans multiple years 0.18 yes hyp Beauchamp et al. (2012) 489 Swedish twins 1 year 0.48 yes hyp Goldstein et al. (2008) 75 Americans 1 year 0.43 yes hyp L¨onnqvist et al. (2010) 43 German students 1 year 0.21 no inc Smidts (1997) 205 Dutch farmers 1 year 0.44 yes hyp Wehrung et al. (1984) 84 US businessmen 1 year 0.36 yes hyp Andersen et al. (2008) 97 Danes 3- 17 months ? yes inc Harrison et al. (2005) 31 US students 6 months ? yes inc Vlaev et al. (2009) 69 British students/adults 3 months 0.20-0.63 yes hyp Horowitz (1992) 66 US students & 23 PTA 2 months ? no inc Schoemaker & Hershey (1992) 109 US MBA students 3 weeks 0.55 yes hyp Hey (2001) 53 British students a few days ? yes inc
  • 11. Preference Stability Lit: Time and Social Less on time: Meier & Sprenger (2010) 250 US low-income 2 years 0.40 yes inc Krupka & Stephens Jr (2013) 1194 Americans 1 year ? ? hyp Harrison et al. (2006) 97 Danes 3- 17 months ? yes inc Or on social preferences: Carlsson et al. (2012) 196 Vietnamese 6 years 0.12 - 0.28 yes inc PG L¨onnqvist et al. (2010) 22 German students 1 year 0.69 yes inc trust Brosig et al. (2007) 40 German students 3 months 0.09-0.48 no/yes inc altruism Brosig et al. (2007) 40 German students 3 months -0.15-0.56 no/yes inc PD
  • 12. Extreme Events and Preferences • Natural disasters: – Less trustworthy: Fleming et al. (2011) – More trusting or no difference: Cassar et al (2011), Andrabi & Das (2010) – More or less risk averse: Cameron & Shah (2011), Cassar et al (2011), Eckel et al. (2009) – More or less impatient: Cassar et al (2011), Callen (2011) • Conflict: – Lower trust: Cassar et al (2011) – Increase altruism: Voors et al. (2012) – Increase egalitarianism: Bauer et al. (2011) – Decrease patience: Voors et al. (2012) – Decrease or increase risk aversion: Voors et al. (2012), Moya (2011), Callen et al. (2012)
  • 13. Economic Events and Preferences • Income, unemployment, and health shocks: – no change: Harrison et al (2005), Sahm (2007), and Meier & Sprenger (2010). – yes change: Krupka & Stephens Jr (2013) and Fisman et al. (2012).
  • 14. Sample Selection • 1991: 285 hhs in 15 villages of Paraguay. • 2002: 214 of the original hhs in survey and 188 participated in experiments. • 2007: 195 of the original hhs, plus added new for a total of 449 hhs. 371 participated in experiments. • 2009: Returned only to the 2 smallest villages. Found 52 of 59 hhs. Experiment conducted during survey. • 2010: Returned only to 10 villages. Interviewed 119 of the hhs chosen by the middlemen. Experiment conducted during survey. Sample sizes are even smaller because we only compare if the same individual participated in both years.
  • 15. Differential Attrition Our sample is: • sometimes significantly poorer • insignificantly older • insignificantly less educated • mixed results for household size and gender In addition, they: • play no differently in the games • are slight more trusting according to the survey
  • 16. Particular Trust more Stable than Generalized Trust Years Variable Correlation Regression Obs 02 v 07 trust world 0.0639 0.0677 123 07 v 09 0.2842** 0.339* 49 02 v 07 trust village 0.1365 0.162* 123 02 v 10 0.4401*** 0.425** 39 07 v 09 0.5250*** 0.525*** 49 07 v 10 0.2540*** 0.206** 119 02 v 07 trust neighbors 0.2728*** 0.275*** 123 07 v 09 0.4628*** 0.545*** 49 07 v 09 negative reciprocity 0.3219** 0.145 49 07 v 10 0.2116** 0.157* 119
  • 17. Risk and Time Experiments • 2002 Risk game: given 8,000 Gs and choose how much to bet on the roll of a die. • 2007 and 2009 Risk games: given a series of five hypothetical risky choices between a sure thing and a 50/50 gamble. • 2007 and 2009 Time preference: asked hypothetically the minimum we would have to offer them to wait one month instead of receiving 50,000 Gs today.
  • 18. Risk Preferences not Stable, but Time is Explanatory Dependent Correlation Regression # variable variable coefficient coefficient Obs. Bet in 2002 # risky choices in 2007 0.0695 0.0662 140 (0.0858) # risky choices in 2007 # risky choices in 2009 -0.0588 -0.0120 49 (0.127) Time preference in 2007 Time preference in 2009 0.4319*** 1.036** 49 (0.419)
  • 19. Social Preference Experiments • 2002 Trust Game: Trustor chooses how much (of 8,000 Gs) to send to anonymous trustee in village. Amount sent gets tripled. Trustee chooses how much to return to trustor. • 2007 Dictator Games: Dictator chooses how much (of 14,000 Gs) to send to anonymous recipient in village. Amount sent is doubled. Identity of dictator remains anonymous or is revealed. • 2009 Dictator Games: Dictator chooses how much (of 14,000 Gs) to send to anonymous recipient in village. Amount sent is doubled. Identity of dictator remains anonymous or is revealed. • 2010 Dictator Games: Dictator chooses how much (of 14,000 Gs) to hypothetically send to anonymous recipient in village. Amount sent is doubled. Dictator anonymous. • 2010 Reciprocity Games: Middleman chooses how much (of 12,000 Gs) to send to player. Player can pay 100 Gs to fine or reward middleman by 500 Gs.
  • 20. Little Stability in Social Preference Games Explanatory var Dependent var Correlation Regression Obs. ALTRUISM sent as trustor in 2002 sent as dictator in anonymous game in 2007 0.2970*** 0.298** 103 sent as trustor in 2002 sent as dictator in anonymous game in 2010 (hyp) -0.0837 0.106 43 TRUST sent as trustor in 2002 sent as dictator in revealed game in 2007 0.3544*** 0.513*** 103 RECIPROCITY share returned as trustee in 2002 accept 1 in ultimatum game in 2010 (hyp) -0.0966 -0.128 43 share returned as trustee in 2002 positive reciprocity in 2010 0.0085 0.473 43 share returned as trustee in 2002 negative reciprocity in 2010 0.1229 -0.430 43 ALTRUISM share returned as trustee in 2002 sent as dictator in anonymous game in 2007 0.1321 1.171 103 share returned as trustee in 2002 sent as dictator in anonymous game in 2010 (hyp) 0.1619 -0.383 43 TRUST share returned as trustee in 2002 sent as dictator in revealed game in 2007 0.2826*** 4.335*** 103 ALTRUISM sent as dictator in anonymous game in 2007 sent as dictator in anonymous game in 2009 -0.1068 -0.180 41 sent as dictator in anonymous game in 2007 sent as dictator in anonymous game in 2010 (hyp) 0.0925 0.121 81 sent as dictator in anonymous game in 2009 sent as dictator in anonymous game in 2010 (hyp) 0.1282 -0.0238 23 sent as dictator in chosen non-revealed game in 2007 sent as dictator in chosen non-revealed game in 2009 0.1378 0.126 33 TRUST sent as dictator in revealed game in 2007 sent as dictator in revealed game in 2009 0.0493 -0.0496 41 sent as dictator in chosen revealed game in 2007 sent as dictator in chosen revealed game in 2009 -0.1184 -0.236 33
  • 21. Normalized Correlations over Time risk time trustworld trustvillage trustneighbor buystolen takeadvantage negreciprocity trustor_Adict trustee_Adict Adict_Adict CNdict_CNdict trustor_Rdict trustee_Rdict Rdict_Rdict CRdict_CRdict trustee_posrec trustee_negrec Preference −.8 −.6 −.4 −.2 0 .2 .4 .6 .8 Coefficients and confidence interval 0207 0210 0709 0710
  • 22. Roll of Die in 2002 Weakly Increases Risk-Taking in 2007 Dependent Correlation Regression # variable coefficient coefficient Obs. # risky choices (2) in 2007 0.1189 0.187* 126 (0.108)
  • 23. Amt Received Back as Trustor in 2002 Increases Giving Dependent var Correlation Regression Obs. RECIPROCITY positive reciprocity in 2010 0.1745 0.0808 42 (0.128) negative reciprocity in 2010 0.4209*** 0.301*** 42 (0.104) ALTRUISM sent as dictator in anonymous game in 2007 0.2070** 0.848* 95 (0.502) sent as dictator in anonymous game (hyp) in 2010 0.0265 0.267 42 (0.563) TRUST sent as dictator in revealed game in 2007 0.1591 0.789 95 (0.537)
  • 24. Amount Received by Trustee Somewhat Increases Giving Dependent var Correlation Regression Obs. RECIPROCITY positive reciprocity in 2010 -0.094 0.00418 43 (0.0134) negative reciprocity in 2010 0.0319 -0.000116 43 (0.0125) ALTRUISM sent as dictator in anonymous game in 2007 0.2038** 0.0866 103 (0.0528) sent as dictator in anonymous game (hyp) in 2010 -0.3707** -0.121** 43 (0.0559) TRUST sent as dictator in revealed game in 2007 0.1790* 0.104* 103 (0.0586)
  • 25. No Impacts of Real-World Shocks • Income Shocks: Basically no impact. • Theft Shocks: Basically no impact. • Health Shocks: Very slight increase in survey trust.
  • 26. Middleman Data In 2010 we have data on how a person plays, and how a middleman predicts he will play. Dependent var Correlation Regression Obs. positive reciprocity 0.1750** 0.161** 177 (0.080) negative reciprocity 0.0136 -0.0616 177 (0.0906) sent as dictator in anonymous game (hyp) 0.1506*** 0.0266 428 (0.0411)
  • 27. Conclusions • Answers to survey questions are quite stable. Play in experiments is less so. • In experiments: time preferences are quite stable and altruism is a bit stable. • Some evidence that being unlucky in one experiment makes players more risk averse in later experiments. • Some evidence that being linked with a more generous partner causes players to be more generous in future experiments. • No discernible impact of health, income, or theft shocks on preferences.
  • 28. What does this mean? • In lab experiments don’t have to worry too much about past experimental experiences. • If social preferences from surveys are more stable than those from games, does this mean we should trust them more? • Play in games is not super correlated over time, but nor is it super correlated with shocks experienced. So, what do experiments actually measure?