performance incentives and the dynamics of voluntary cooperation simon gächter (university of...
Post on 22-Dec-2015
223 views
TRANSCRIPT
![Page 1: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/1.jpg)
Performance Incentives and the Dynamics of Voluntary
Cooperation
Simon Gächter (University of Nottingham)Esther Kessler (University College London)Manfred Königstein (University of Erfurt)
![Page 2: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/2.jpg)
2
Motivation
• Many employment contracts are incomplete
• “Voluntary cooperation” of the agent is important:
– “Managers claim that workers have so many opportunities to take advantage of employers that it is not wise to depend on coercion and financial incentives alone as motivators” (Bewley, 1999)
– “work morale”, “creativity”, “loyalty”, “initiative”, “Good will”, etc. (Williamson 1985; Simon 1997; Bewley 1999)
– “Organizational citizenship behaviour” (Organ 1988)
• Explicit performance incentives quite popular
![Page 3: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/3.jpg)
3
• A simple model: adapted from Fehr, Kirchsteiger & Riedl (QJE 1993)
• Participants are randomly assigned to the roles of “employer” and “worker”, respectively.
• Incomplete contract, because effort not specified• Worker payoffs: w – c(e) (costs increasing in effort)• Employer payoffs: ve – w (revenues increasing in effort)
1. Employer:
Wage offer [0,700]
2. Worker:
– Accept/reject offer– Choose costly effort [1, 2, …, 20]
3. Payoffs realised
Motivation (2)
![Page 4: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/4.jpg)
4 There is reciprocity-based voluntary cooperation
Fehr, Kirchsteiger & Riedl (QJE 1993):
Motivation (3)
![Page 5: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/5.jpg)
5
Motivation (4)
• Starting ideas for our experimental study:– Do explicit incentives crowd out voluntary cooperation?
– Can voluntary cooperation be re-established after experiencing incentive pay?
– Since we know from other experiments that framing of incentives and repeated game effects are also potentially relevant for behavior, these should be studied as well
![Page 6: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/6.jpg)
6
• We investigate in a unified framework:– 1. Existence of voluntary cooperation
– 2. Effectiveness of monetary incentives
– 3. Crowding out effects
– 4. Framing effects (Bonus vs Fine)
– 5. Repeated game effects
Motivation (5)
![Page 7: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/7.jpg)
7
• Principal-agent game:– Principal offers work contract– Agent can accept or reject– Agent chooses effort– Contract and effort determine payoffs
Experimental Game
![Page 8: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/8.jpg)
8
Experimental Game (2)
Trust Fine BonusWage:Desired effort:Incentive:
Effort cost: c(e) = 7e – 7Payoff if contract rejected: 0 for both
Payoff Principal
Payoff Agent
w [-700, 700]
ê [1, 20]-
35e – w
w – c(e)
w [-700, 700]
ê [1, 20]
f {0,24,52,80}
w [-700, 700]ê [1, 20]
b{0,24,52,80}
35e–w if e≥ê 35e–w+f if e<ê
35e–w–b if e≥ê 35e–w if e<ê
w –c(e) if e≥ê w –c(e)–f if e<ê
w –c(e)+b if e≥ê w –c(e) if e<ê
![Page 9: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/9.jpg)
9
Standard Theoretical Predictions
• Trust Contract: – e = 1 (minimal effort)
• Fine Contract, Bonus Contract: – e = ê if fine is sufficiently large: f c(ê)
(“incentive compatibility”)
– Otherwise, e = 1
– Equivalent for bonus (framing of incentives)
– Higher fine/bonus induces higher effort: f ,b {0, 24, 52, 80} enforceable effort levels: {1, 4, 8, 12}
– limited possibility for sanctions/rewards
![Page 10: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/10.jpg)
11
A Comprehensive Experimental Design (1)
A. Baseline Treatments: No experience of Trust before Fine/Bonus
Treatment label
Phase 1(Period 1-
10)
Phase 2(Period 11-
20)
Phase 3(Period 21-
30)
No. Independent matching
groups
FT FINE TRUST - 6
BT BONUS TRUST - 6
TTT TRUST TRUST TRUST 6
B. Trust experience before Fine/Bonus
TFT TRUST FINE TRUST 6
TBT TRUST BONUS TRUST 6
Random matching in each period to minimize strategic effects
![Page 11: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/11.jpg)
12
A Comprehensive Experimental Design (2)
C. Repeated game and Trust experience before Fine/Bonus
Treatment label
Phase 1(Period 1-
10)
Phase 2(Period 11-
20)
Phase 3(Period 21-
30)
No. of pairs
TTT Partner
TRUST TRUST TRUST 12
TFT Partner
TRUST FINE TRUST 18
TBT Partner
TRUST BONUS TRUST 17
![Page 12: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/12.jpg)
13
Procedures
1. Experiments at the University of St. Gallen
2. Computerised, z-Tree (Fischbacher 1999)
3. 456 participants
4. CHF 45 (€30) for 1.5 – 2 hours
![Page 13: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/13.jpg)
14
Results
![Page 14: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/14.jpg)
15
Period 1-10
Period 11-20
Period 21-30
Voluntary cooperation exists and is stable over time
![Page 15: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/15.jpg)
16
14
812
20A
ctua
l effo
rt
1 4 8 12Optimal effort (best reply)
Phase 1 of FT
14
812
20A
ctua
l effo
rt
1 4 8 12Optimal effort (best reply)
Phase 1 of BT
Higher incentives induce higher effort
• 68% of all contracts are incentive compatible
• Most principals (about 90%) choose maximal fine, bonus
![Page 16: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/16.jpg)
171
3
5
7
9
11
13
15
17
19
1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10
Period
Bonus_ST
Bonus_P
1
3
5
7
9
11
13
15
17
19
Fine_ST
Fine_P
1
3
5
7
9
11
13
15
17
19
Trust_ST
Trust_P
Phase 1 Phase 2 Phase 3
TRUST
Partner vs.
Stranger
FINE
Partner vs.
Stranger
BONUS
Partner vs.
Stranger
![Page 17: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/17.jpg)
18
Results From These Graphs
1. Trust contracts can induce high effort (“trust-
and-reciprocity” is an important mechanism)
2. Monetary incentives are effective
3. Repeated interaction has strong effect
4. Framing (Bonus vs Fine)?
5. Crowding out of voluntary cooperation?
![Page 18: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/18.jpg)
19
• But, take a look at the distribution of data again
How to proceed?
• Evaluate these effects within a unifying
statistical model
• Convincing structural model?
• Effort is bounded below and above
Tobit-Regression
![Page 19: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/19.jpg)
20
Period 1-10
Period 11-20
Period 21-30
Distribution of effort conditional on wage
Two groups of data: • e=1 independent of fixed wage
• e>1 positively correlated with fixed wage
![Page 20: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/20.jpg)
21
05
1015
20
Act
ual e
ffort
0 100 200 300 400Fixed wage
bandwidth = .8
Trust0
510
1520
Act
ual e
ffort
0 100 200 300 400Offered compensation (w-f)
bandwidth = .8
Fine
05
1015
20A
ctua
l effo
rt
0 100 200 300 400Fixed wage
bandwidth = .8
Trust
05
1015
20
Act
ual e
ffort
0 100 200 300 400Fixed wage
bandwidth = .8
Trust
05
1015
20
Act
ual e
ffort
0 100 200 300 400Offered compensation (w)
bandwidth = .8
Bonus
05
1015
20
Act
ual e
ffort
0 100 200 300 400Fixed wage
bandwidth = .8
Trust
TBT
TFT0
510
1520
Act
ual e
ffort
0 100 200 300 400Fixed wage
bandwidth = .8
Trust
05
1015
20
Act
ual e
ffort
0 100 200 300 400Fixed wage
bandwidth = .8
Trust
05
1015
20
Act
ual e
ffort
0 100 200 300 400Fixed wage
bandwidth = .8
Trust
05
1015
20
Act
ual e
ffort
0 100 200 300 400Fixed wage
bandwidth = .8
Trust
05
1015
20
Act
ual e
ffort
0 100 200 300 400Offered compensation (w-f)
bandwidth = .8
Fine
05
1015
20
Act
ual e
ffort
0 100 200 300 400Fixed wage
bandwidth = .8
Trust
TFT-Partner
TTT-Partner
05
1015
20
Act
ual e
ffort
0 100 200 300 400 500Fixed wage
bandwidth = .8
Trust
05
1015
20
Act
ual e
ffort
0 100 200 300 400Offered compensation (w)
bandwidth = .8
Bonus
05
1015
20
Act
ual e
ffort
0 100 200 300 400Fixed wage
bandwidth = .8
Trust
TBT-Partner
05
1015
20
Act
ual e
ffort
0 100 200 300 400Fixed wage
bandwidth = .8
Phase 2 of FT
05
1015
20
Act
ual e
ffort
0 100 200 300 400Fixed wage
bandwidth = .8
Phase 2 of BT
BTFT
Robustness of Data Pattern
![Page 21: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/21.jpg)
22
How to proceed?
Hurdle Model
1. Estimate p = prob(e>1)
2. Estimate ê = f(x|e>1)
For Step 2 use Tobit with upper bound 20
• But, take another look at the distribution of data
![Page 22: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/22.jpg)
23
14
812
20A
ctua
l effo
rt
1 4 8 12Optimal effort (best reply)
Phase 1 of FT
14
812
20A
ctua
l effo
rt
1 4 8 12Optimal effort (best reply)
Phase 1 of BT
Distribution of effort conditional on best reply effort
Three groups of data:• e=1 independent of best reply effort
• e=e*
• other choices
![Page 23: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/23.jpg)
24
14
812
20
Act
ual e
ffort
1 4 8 12Optimal effort (best reply)
Phase 2 of TFT
14
812
20
Act
ual e
ffort
1 4 8 12Optimal effort (best reply)
Phase 2 of TBT
14
812
20
Act
ual e
ffort
1 4 8 12Optimal effort (best reply)
Phase 2 of TFT-R
14
812
20
Act
ual e
ffort
1 4 8 12Optimal effort (best reply)
Phase 2 of TBT-R
TFT (left), TBT (right) TFT-Partner (left), TBT-Partner (right)
Robustness of Data Pattern
![Page 24: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/24.jpg)
25
How to proceed?
Double Hurdle Model
1. Estimate p = prob(e>1)
2. Estimate q = prob(e=e*|e>1)
3. Estimate ê = f(x|e>1 and e≠e*)
For Step 3 use Tobit with upper bound 20
![Page 25: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/25.jpg)
26
Can trust contracts do better than incentive contracts?
• Applying this structure we evaluate effectiveness of trust
contracts, monetary incentives, repeated game, framing,
crowding out
• Important question: Can trust contracts perform better than
incentive contracts (cet. par.)?
• We need to compare trust contracts with equally expensive
incentive contracts; i.e., holding total compensation
constant
• Use estimates of p, q and ê to determine expected effort for
payoff-equivalent contracts
![Page 26: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/26.jpg)
27
Expected effort in Phase 1 (Vergleich von IC Vertraegen mit Trust, e0 immer 12)
0
2
4
6
8
10
12
14
16
18
20
50 100 150 200 250 300 350 400 450 500 550 600 650 700
compensation
Exp
ecte
d e
ffo
rt
P*e(Trust)
P*e(Fine)
p*e(Bonus)
Yes! Trust contracts can do better
than incentive contracts
Data: FT, BT, only incentive compatible contracts
![Page 27: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/27.jpg)
28
Expected effort in Phase 2 (Vergleich von IC Vertraegen mit Trust, e0 immer 12)
0
5
10
15
20
25
50 100 150 200 250 300 350 400 450 500 550 600 650 700
compensation
Exp
ecte
d e
ffo
rt
P*e(Trust)
P*e(Fine)
p*e(Bonus)
Data: TFT, TBT, only incentive compatible contracts
Robustness: 3-Phases-Data Stranger
![Page 28: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/28.jpg)
29
Data: TFT-Partner, TBT-Partner, only incentive compatible contracts
Expected effort in Phase 2 (Vergleich von IC Vertraegen mit Trust, e0 immer 12)
0
2
4
6
8
10
12
14
16
18
20
50 100 150 200 250 300 350 400 450 500 550 600 650 700
compensation
Exp
ecte
d e
ffo
rt
P*e(Trust)
P*e(Fine)
p*e(Bonus)
Robustness: 3-Phases-Data Partner
![Page 29: Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred](https://reader035.vdocuments.us/reader035/viewer/2022081512/56649d805503460f94a64834/html5/thumbnails/29.jpg)
30
Summary
• Trust contracts and monetary incentives are both effective in inducing effort
• We find substantial crowding out of voluntary cooperation due to incentives; if the contract is incentive compatible most subjects exactly choose rational effort
• Trust contracts may be more beneficial for a principal than an incentive compatible contract with bonus or fine
• Other results: Repeated game important, framing relatively unimportant
• Interestingly, non-incentive compatible contracts perform relatively well (further analyses needed)