2011 5th MIT Sloan Sports Analytics Conference

1. Moral Hazard in Long-Term Guaranteed Contracts: Theory and Evidence from the NBA Arup Sen, Boston University J. Bradford Rice, Analysis Group

2. The Central Question Do players play harder towards the end of their contract If the answer is yes, is there a reason why do teams award long-term contracts when incentives would seem to be maximized with short term contracts? Are players ‘fooling’ teams repeatedly with the improved performance in the later stages of the contract? Can this be an equilibrium? Is this applicable to other labor markets?

3. Anecdotal Motivation:Thecurious case of the Seattle Supersonics In 2004-05 Had many key players (and their coach) in the last year of their deals Thought to be reasonably talent deficient they made a surprising run to the second round of the playoffs after winning 50 games In 2005-06 With many of the same pieces signed to big deals they went 35-47. Arguably the biggest fall off was Jerome James who went to the Knicks and proceeded to provide the blueprint for Eddy Curry.

4. Theoretical Model Performance is a combination of effort and ability (in our model performance=ability+ effort) The only ‘benefit’ players get from exerting costly effort is to affect future contracts. Players are risk averse and teams are risk- neutral. Incentives are largest in the final period of the new contract, at which point players are anticipating a new contract. Main Result Players improve performance as the contract expiry comes closer Long-term contracts can be Pareto optimal in spite of the ‘moral hazard’ concerns that come with guaranteed contracts.

5. Theory Results Why can long-term contracts be optimal then? Players are risk-averse and willing to give per-period wage concessions in return for job security and avoiding random shocks from year to year. Players are concerned about the effect that not putting forth effort might have on their reputations and may be ’persuaded’ to put forth some effort in non-contract years. We see a steeper period to period improvement in younger players. For older players, whose value is already established the slope of effort levels is lower- which is consistent with what see empirically.

6. Empirical Analysis We want to see whether player performance improves as the end of the contract draws closer. Independent variable of interest- years remaining on current contract Dependent variable- NBA player efficiency index Our estimation equation- Performance= α+β*years remaining+µ*controls on observable player ability Our coefficient of interest is β, we expect the sign to be negative and we run a few variants of this equation.

7. Empirical Analysis contd… Data- Unbalanced panel 654 players in the NBA from 2000-06 (with player information going back to as early as 1991)for a total of 2260 player-year observation. Source: basketball-reference.com, USA today salary database Controls- various player characteristics including physical attributes, college attended, draft position etc The fact that we have multiple observations for 90% of players in our dataset means we are able to do fixed effects analysis.

8. Results The effect of years remaining in contract on player performance is significant and negative. Performance improves as we move closer to the end of the contract. Players perform 7-8 % better in the last year of their contract compared to the penultimate year. They do a whopping 23% worse when they have 3 years left on their contracts. On average the first year has them performing 7 % worse than an average year (we control for team specific experience).

9. Results contd.. If we take players for whom we see 2 consecutive years spread over 2 contracts then there is a 16% drop-off from the contract year to the subsequent year. There is an obvious bias here but still it acts as a useful robustness check. The coefficient on the interaction of experience and years remaining is positive suggesting that the adverse effort incentives for more experienced players is reduced. A player with 2 years experience will see a 15% increase in performance from the penultimate to final year which is twice the output differential a player with 6 years experience sees.

10. Other Key Points Why not heavily incentivize players? Multi-tasking (easier in other sports) Team success may lead to free-riding Collective bargaining and real world concerns. Are teams fooled in equilibrium? No, in equilibrium they anticipate this increasing effort profile when negotiating the terms of the contract. They contract based on the maximum incentive compatible level of effort that they can coax out of the players.

11. The Last part of the puzzle Do players actually give up salary on a per-period basis? Tough to test empirically. Anecdotal evidence that players opt out of lucrative last years of long-term contracts to get longer guaranteed deals- e.g. Richard Jefferson.

12. Alternative Interpretations We don’t necessarily take our model literally but we feel that it provides a useful insight into how this market operates Can think of ‘ability’ as evolving over time- qualitatively that is the same as our model Also recent years may serve as a better benchmark of performance going forward and hence the player’s value. Our results are consistent with that interpretation

13. Conclusion This is useful analysis for many labor markets that have guaranteed contracts- the prime example is academia with the tenure system. While the NBA as a market has many peculiarities it also gives insight into how utility maximizing individuals will behave especially when reputation matters.