Stability of Social, Risk, and Time Preferencesover Multiple Years

Yating ChuangUW Madison

Laura SchechterUW Madison

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?

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?

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.

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.

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.

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.

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

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.

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

Lonnqvist 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

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

Lonnqvist 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

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)

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).

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.

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

Particular Trust more Stable than GeneralizedTrust

Years Variable Correlation Regression Obs

02 v 07trust 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 07trust neighbors

0.2728*** 0.275*** 123

07 v 09 0.4628*** 0.545*** 49

07 v 09negative reciprocity

0.3219** 0.145 49

07 v 10 0.2116** 0.157* 119

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.

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)

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.

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

Normalized Correlations over Time

risktime

trustworldtrustvillage

trustneighborbuystolen

takeadvantagenegreciprocity

trustor_Adicttrustee_Adict

Adict_AdictCNdict_CNdict

trustor_Rdicttrustee_Rdict

Rdict_RdictCRdict_CRdicttrustee_posrectrustee_negrec

Pre

fere

nce

−.8 −.6 −.4 −.2 0 .2 .4 .6 .8Coefficients and confidence interval

0207 02100709 0710

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)

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)

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)

No Impacts of Real-World Shocks

• Income Shocks: Basically no impact.

• Theft Shocks: Basically no impact.

• Health Shocks: Very slight increase in survey trust.

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)

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.

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?