Inequity Aversion and Individual Behavior in
Public Good Games:
An Experimental Investigation
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
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
• Utility of subject i in a two-person game:
Ui π i , π j   π i  αimax π j  πi ,0 βimax π i  π j ,0
• Assumptions:
– αi ≥ 0 (aversion against disadvantageous inequality)
– βi ≥ 0 (aversion against advantageous inequality)
– βi < 1 and αi ≥ βi
Experimental Design I
Games A and B (N = 492)
Step 1
• 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 C (N = 160)
• certain αi-βi-types were matched in pairs
• Standard two-player Public-Good game, Partner design, 10 periods
Step 2
Game D (N = 160)
• Stage 1: as in Game C
• Stage 2: punishment option with constant marginal costs
Experimental Design II
Treatment variables in Game C
• parameter βi
• information about co-player‘s type
Treatment
EGO
MIX
FAIR
FAIR(ni)
βi, i = 1,2
βi < .3
β1 < .3 and β2 > .3
βi > .3
βi > .3
Information
yes
yes
yes
no
Obs.
35
13
17
15
Experimental Design III
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).
0
.5
1
alfa
1.5
2
2.5
1
80
.8
(.9;1.0)
(.8;.9]
(.7;.8]
(.6;.7]
(.5;.6]
(.4;.5]
(.3;.4]
(.2;.3]
(.1;.2]
(0;.1]
0
.2
0
0
20
percent
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]
• Small negative correlation between βi and
studying economics
(Spearman‘s ρ = -0.137, p = 0.015)
80
• Only 12% fulfill αi ≥ βi.
60
• No dispersion of αi
percent
40
60
beta
.4
.6
Results: Games A&B
20
40
0
Results: Effect of βi in Game C
10
9
mean contributions
8
7
6
5
4
3
2
FAIR
EGO
MIX
1
0
1
2
3
4
5
6
periods
7
8
9
10
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
10
9
mean contributions
8
7
6
5
4
3
2
FAIR
FAIR(ni)
EGO
1
0
1
2
3
4
5
6
periods
7
8
9
10
• 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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