1. Take the lead! An experimental analysis of positive and negative leadership
ENRIQUE FATAS
(LINEEX-UTD)
SARA GODOY
(LINEEX-UV)
SAE Zaragoza December 2008

2. Two sides of Leadership:
1. Motivation (I)
The potential positive role of leadership has been detected in different economic domains
Two sides of Leadership:
Positive: Charitable fundraising
Leaders signal right behavior, inducing followers to act in the same way
Negative: Tax compliance
Non-exemplary behavior of publicly known evaders might promote dishonest behavior
Leadership in organizations
It might promote efficiency without the efficiency costs of other institutions (as group incentive contracts and monitoring, mutual monitoring and costly sanctions)

3. Two theoretical perspective on leading by example
1. Motivation (II)
Two theoretical perspective on leading by example
Exogenous (Hermalin, 1998)
Endogenous (Huck and Rey, 2006)
Experimental perspective:
Exogenous leadership
Asymmetric information:
Leaders move first (Meidinger and Villeval, 2002)
Asymmetric attributes:
Leaders have the chance to exclude free riders (Guth et al., 2004) or
Distribute earnings (Potters et al., 2006)
Endogenous leadership
Leaders are endogenously determined and move first
Gächter and Renner (2005)
Arbak and Villeval (2007)

4. 1. Motivation (III): Take the lead!
Our design:
The game: Linear public goods game (VCM)
Features:
Endogenous
Anyone can be the leader in any period
Symmetric and horizontal
Leaders and followers make the same decisions simultaneously
Leaders cannot sanction followers (a kind of low powered incentive system)
Becoming a leader is costless but (strategically) risky
A strong test for leading by example

5. 2. Experimental Design: The game
A standard linear public goods game based on the VCM
MPCR=0.5; group size =4; rounds (surprise restart game); endowment = 50 tokens; partners random matching
Treatment effects: after decisions are made subjects get back different social information
Good leader treatment (GL)
Unique available information: Highest contribution in their group
Bad leader treatment (BL)
Unique available information: Lowest contribution in their group
Baseline
Available information: Vector of contributions, no trace

6. 3. Experimental Procedures
Computerized experiments
LINEEX, Ztree
6/9 sessions per treatment
96 inexperienced undergraduate students
Background: business and economics
Subjects were asked to allocate the initial endowment
Partners random matching mechanism
Re-start effect

7. 4. Results (I): Descriptive Statistics
Table 1: Summary.
Treatment
Info
Groups Ss
Avg. contribution (%)
All
Original
Restart GL
Max ci 9 36
36.52
41.79
31.29 BL
Min ci
23.9
24.72
21.27
BSL
Vector 6 24
30.66
31.88
29.46

8. 4. Results (II): Having a Good leader matters

9. 4. Results (II): The usual decline holds

10. 4. Results (I & II): Treatment Effects (FGL vs FBL)
Table 2: Treatment Effect.
Random effects regression results (S.E); Dependent variable: Individual Contributions.
Model 1
(all rounds)
Model 2 OG RG
Constant
23.67***
(2.603)
22.89***
(2.96)
21.53***
(2.44)
Restart
-2.92***
(1.06)
--- --
Period
-1.250***
(0.13)
-1.26***
(0.14)
-1.24***
(0.17) GL
2.94(2.87)
4.96
(3.54)
0.92
(2.72) BL
-3.83(3.42)
-3.58
(3.77)
-4.09
(3.56)
GL vs. BL
6.77**(3.29)
8.54**
(3.43)
5.01
(3.52)
Nº Obs.
1920
960

11. 4. Results (III): Leadership & top contributors

12. 4. Results (III): Leadership & bottom contributors

13. 4. Results (III): Leadership and top/bottom performers
Table 3: Contribution by leaders.
Random effects regression results (S.E); Dependent variable: Highest/Lowest contributions
Dep. Var.
Highest Contribution
Lowest Contribution
Model 3
Model 4
Model 5
Model 6 OG RG
Constant
37***
(3.69)
34.03***
(3.49)
36.27***
(4.36)
10.11***
(2.27)
10.90***
(3.17)
8.24***
(1.64)
Restart
-3.70***
(1.34)
-1.07
(1.02)
Period
-1.68***
(0.24)
-1.38***
(0.31)
-1.98***
(0.28)
-0.59***
(0.12)
-0.65***
(0.16)
-0.53***
(0.14) GL
7.50*
(4.23)
9.88**
(4.50)
5.13
(4.66)
-2.37
(2.31)
-2.49
(3.51)
-2.25
(1.78) BL
-3.58
(4.71)
-2.41
(4.88)
-4.74
(5.08)
-2.18
(2.76)
-3.23
(3.52)
-1.13
(2.75)
GL-BL
11.08***
(3.75)
12.29***
(8.84)
9.87**
(4.21)
-0.19
(2.56)
0.74
(2.83)
-1.12
(2.68)
Nº Obs.
480
240

14. 4. Results (III): Followers’ contributions

15. 4. Results (III): Followers’ Contributions
Table 4: Contribution by followers.
Random effects regression results (S.E); Dependent variable: Individual Contributions.
Model 7
Data from Control & GL
Model 8
Data from Control & BL
Model 9
Data from GL & BL
Constant
19.93***
(2.89)
27.84***
(2.51)
25.84***
(2.90)
Period
-1.21***
(0.12)
-1.46***(0.14)
-1.22***(0.15)
Restart
-3.18**
(1.32)
-1.54(1.54)
-3.64***(1.31) GL
1.85
(2.84) --
-3.81(3.20) BL
-1.73(3.25)
Nº Obs.
843
716
903

16. 5. Results (IV): Who’s the leader?
Table 5: Probability of becoming a leader.
Random effects probit regression results;
Model 9
Data from GL
Model 10
Data from BL
Contri P1
0.031***
(0.007)
-0.025***
LagHig
-0.010**
(0.004) --
LagLow
-0.005
(0.011)
Nº Obs.
648

17. Leadership has a significant impact on contribution levels
5. Concluding remarks
Leadership has a significant impact on contribution levels
Depending on the dimension of leadership
Subjects who born leaders strongly react to the chance of becoming the right signal for the others, but
Bottom performers do not react.
The usual PGG decline holds
Positive leadership promotes (does not) higher contributions in top (bottom) performers
BUT Followers do not react in a significant way to leaders’ behavior
Subjects are born leaders
Becoming a leader depends on your initial contribution (type)

18. Thank you for your attention
“Don’t follow leaders, watch your parking meters”
“Subterranean Homesick Blues” Bob Dylan