1. Performance Incentives and the Dynamics of Voluntary Cooperation Simon Gächter (University of Nottingham) Esther Kessler (University College London) Manfred Königstein (University of Erfurt)

2. 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

3. 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)

4. 4  There is reciprocity-based voluntary cooperation Fehr, Kirchsteiger & Riedl (QJE 1993): Motivation (3)

5. 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

6. 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)

7. 7 Principal-agent game: –Principal offers work contract –Agent can accept or reject –Agent chooses effort –Contract and effort determine payoffs Experimental Game

8. 8 Experimental Game (2) TrustFineBonus Wage: Desired effort: Incentive: Effort cost: c(e) = 7e – 7 Payoff 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

9. 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

10. 10 Alternative Predictions Voluntary cooperation: –Effort is larger than economic rationality predicts: e > e* –Higher effort increases joint payoff (“efficiency”) Trust-and-Reciprocity mechanism: –Wage is higher than economic rationality predicts –Higher wages lead to higher effort Monetary incentives (Fine/Bonus) induce crowding out of voluntary cooperation Framing of incentives matters (Fine versus Bonus) Voluntary cooperation is higher in repeated games

11. 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 FTFINETRUST-6 BTBONUSTRUST-6 TTTTRUST 6 B. Trust experience before Fine/Bonus TFTTRUSTFINETRUST6 TBTTRUSTBONUSTRUST6 Random matching in each period to minimize strategic effects

12. 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 PartnerTRUST 12 TFT PartnerTRUSTFINETRUST18 TBT PartnerTRUSTBONUSTRUST17

13. 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

14. 14 Results

15. 15 Period 1-10Period 11-20Period 21-30 Voluntary cooperation exists and is stable over time

16. 16 Higher incentives induce higher effort 68% of all contracts are incentive compatible Most principals (about 90%) choose maximal fine, bonus

17. 17 TRUST Partner vs. Stranger FINE Partner vs. Stranger BONUS Partner vs. Stranger

18. 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?

19. 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

20. 20 Period 1-10Period 11-20Period 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

21. 21 TBT TFT TFT-Partner TTT-Partner TBT-Partner BTFT Robustness of Data Pattern

22. 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

23. 23 Distribution of effort conditional on best reply effort Three groups of data:e=1 independent of best reply effort e=e* other choices

24. 24 TFT (left), TBT (right)TFT-Partner (left), TBT-Partner (right) Robustness of Data Pattern

25. 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

26. 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

27. 27 Yes! Trust contracts can do better than incentive contracts Data: FT, BT, only incentive compatible contracts

28. 28 Data: TFT, TBT, only incentive compatible contracts Robustness: 3-Phases-Data Stranger

29. 29 Data: TFT-Partner, TBT-Partner, only incentive compatible contracts Robustness: 3-Phases-Data Partner

30. 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)