Astrid Dannenberg*, Thomas Riechmann**,

Bodo Sturm*, and Carsten Vogt***

*Centre for European Economic Research (ZEW) Mannheim

**Otto-von-Guericke-University Magdeburg

***Leipzig University of Applied Sciences

Supported by the German Research Foundation

ESA 2007 World Meeting, Rome

Inequity Aversion and Individual Behavior in Public Good Games:

An Experimental Investigation

• Utility of subject i in a two-person game:

Objective of our study

• Low explanatory power of standard theory in social dilemmas

• to investigate the additional explanatory power of the Fehr

and Schmidt (1999) inequity aversion model

– αi ≥ 0 (aversion against disadvantageous inequality)

– βi ≥ 0 (aversion against advantageous inequality)

– βi < 1 and αi ≥ βi

• Assumptions:

Experimental Design I

Games A and B (N = 492)• Modified ultimatum and dictator games (similar to Blanco et al. ´06)• Pure allocation games, i.e. no strategic interaction

• in order to elicit parameters αi and βi

Game D (N = 160)• Stage 1: as in Game C• Stage 2: punishment option with constant marginal costs

Step 1

Step 2

Game C (N = 160)• certain αi-βi-types were matched in pairs

• Standard two-player Public-Good game, Partner design, 10 periods

Treatment βi, i = 1,2 Information Obs.

EGO βi < .3 yes 35

MIX β1 < .3 and β2 > .3 yes 13

FAIR βi > .3 yes 17

FAIR(ni) βi > .3 no 15

Treatment variables in Game C

• parameter βi

• information about co-player‘s type

Experimental Design II

Hypotheses for Game C according to Fehr and Schmidt:

1. No contributions in EGO and MIX treatments

2. In FAIR, cooperation should be observed more frequently

than in EGO and MIX.

3. In FAIR, cooperation should be observed more frequently

than in FAIR(ni).

Experimental Design III

Results: Games A&B

0 20 40 60 80percent

0(0;.1](.1;.2](.2;.3](.3;.4](.4;.5](.5;.6](.6;.7](.7;.8](.8;.9]

(.9;1.0)

0.2

.4.6

.81

be

ta

0 .5 1 1.5 2 2.5alfa

02

04

06

08

0p

erc

en

t

0(0

;.2]

(.2

;.4]

(.4

;.6]

(.6

;.8]

(.8

;1.0

](1

.0;1

.2]

(1.2

;1.4

](1

.4;1

.6]

(1.6

;1.8

](1

.8;2

.0]

(2.0

;2.2

](2

.2;2

.4]

(2.4

;2.6

]

• No dispersion of αi

• Only 12% fulfill αi ≥ βi.

• Small negative correlation between βi and

studying economics

(Spearman‘s ρ = -0.137, p = 0.015)

Results: Effect of βi in Game C

0

1

2

3

4

5

6

7

8

9

10

1 2 3 4 5 6 7 8 9 10periods

mea

n co

ntri

butio

ns

FAIR EGO MIX

Last period

• Contributions: GFAIR > GEGO (MW U, p < 10%) and GFAIR > GMIX (MW U, p < 5%)

• H0 that cooperation and defection (G < 3€) have the same probability, has to be rejected

for FAIR, but not for EGO and MIX (Chi2, p < 5%).

Results: Effect of Information in Game C

0

1

2

3

4

5

6

7

8

9

10

1 2 3 4 5 6 7 8 9 10periods

mea

n co

ntri

butio

ns

FAIR FAIR(ni) EGO

• Last period: Contributions in FAIR are significantly higher than in FAIR(ni) (MW U,

p < 5%). No difference between FAIR(ni) and EGO.

• No convergence between FAIR and FAIR(ni).

Conclusions

• Specific composition of groups significantly influences the

subjects' performance in the PG games.

• Only parameter βi matters.

• As long as subjects are informed about the co-player’s type,

“fair” groups contribute more than “egoistic” or “mixed” groups.

• This information cannot be extracted during the PG game.

Thank you for your attention!

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