Stability of Social, Risk, and Time Preferences over Multiple Years

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?