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Testing for moral hazard in guaranteed contracts – Stiroh ( Economic Inquiry, 2007 )

Testing for moral hazard in guaranteed contracts – Stiroh ( Economic Inquiry, 2007 ). Guaranteed contracts are paid in spite of performance, and indeed despite injury. Question: do players who get them shirk?. Arguments against:.

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Testing for moral hazard in guaranteed contracts – Stiroh ( Economic Inquiry, 2007 )

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  1. Testing for moral hazard in guaranteed contracts – Stiroh (Economic Inquiry, 2007) • Guaranteed contracts are paid in spite of performance, and indeed despite injury. Question: do players who get them shirk?

  2. Arguments against: • Employers should be able to anticipate shirking, and adjust contracts accordingly. But: shirking takes place by low effort, and it is difficult to differentiate effort and skill. • Future contract value can be negatively affected by shirking during the current one.

  3. If players do shirk: • A longer-term contract provides more security, hence should yield more shirking. • Older players, with less to fear from lost future earnings, should shirk more. • Shirking should to a greater extent involve unmeasurable activities.

  4. Question 1: Test whether value of free-agent contracts depends on productivity in contract year • Regress contract value, length and annual salary (separately) on player’s historical performance, whether he is in contract year, age, position. Results as expected.

  5. Question 2: How does performance depend on contract status? • Moral-hazard hypothesis predicts rising performance in contract year, declining performance in first year after signing. • Problem: perhaps rising performance in year before free-agent contract signed is a selection problem; only those who are improving get these contracts, so of course they would have great performances in prior year. • Solution: if this hypothesis is true, they should continue to improve in first year of new contract. • Results: performance consistently increase in contract year, and frequently (depending on precise econometric specification) fall in first year of new contract.

  6. Question 3: Are teams affected by contract status of all players? • Test: Regress team winning percentage (in 2000) on percentage of players in contract year, percentage of players with guaranteed multi-year contract, along with average player age and team payroll. • Result: percentage of team with long-term contracts strongly and negatively associated with winning percentage. Percentage of team in contract year positively and somewhat strongly associated. • Recommendation: use contracts of more money and less length?

  7. The basic economic model of crime • Crime is a rational act; crimes are committed when the expected benefits exceed the expected costs. • Things that affect the probability of conviction may affect criminal behavior differently than things that affect the consequences of conviction.

  8. The designated hitter as crime and punishment (John Charles Bradbury and Douglas J. Drinen, Economic Inquiry 2007) • American League (AL) pitchers don’t hit themselves, and can therefore hit batters with fewer expected consequences. National League (NL) pitchers must hit. • Implication: AL pitchers should hit batters less. • Similar to Sam Peltzman’s findings that seat-belt laws and auto air bags promote riskier driving. • However, the penalty for a hit batter is that the batter is awarded first base. Pitchers are weak hitters, and are followed in the lineup by the best hitters, and so giving them a free pass is costly. This too would prompt the NL to have lower rates of hit pitchers.

  9. Testing the deterrence theory • Previous work notes that AL pitchers hit batters less than NL pitchers. But these are “macro” studies, not looking at individual “micro” events. • Test: Regress probability of any player getting hit on whether DH rule is in effect, batter OPS, pitcher-quality measures (opposing OPS, pitcher’s walk rate – to standardize for unintentional HBP), opponent being HBP in previous half-inning, whether pitcher appears in inning with HBP in previous half-inning, whether previous hitter hit home run, game situation. • Findings: large score differential, team currently losing, at-bat following home run, HBP in previous half-inning, and pitcher hitting after previous HBP. Latter increases pitcher’s probability of being hit by four times. • Lack of pitchers hitting explains 80% of difference between HBP rates in AL, NL.

  10. The late-1990s mystery • In the second half of the 1990s, NL HBP rates rose above AL temporarily for first time. • Explanation: expansion disproportionately affected NL (three new teams). Therefore lower pitcher quality in NL. • In addition, “double warning rule” had disproportionate effect on AL rates, since they were higher to begin with.

  11. Deterrence example #2: Fouls in college basketball (Robert E. McCormick and Robert D. Tollison, Journal of Political Economy 1984). • Atlantic Coast Conference (ACC) had third official some of the time, 1954-1983. • Effect on fouls called ambiguous: more fouls will be detected, but fewer may be committed to begin with. Fouls (called and not) will decline, but number actually called could go either way.

  12. McCormick and Tollison (continued) • Data: ACC tournament games; three officials, 1979-1983 and two before. • Also, two rule changes: prior to 1973, first six fouls in a half led to one free throw. • Testing effect of third official: regress fouls called on game score, team height difference, difference in team and coach experience, importance of game (measured by attendance), referee experience, number of officials, costs and benefits of fouling (fouled team’s field-goal and free throw shooting percentage), pace of game (combined score). • Primary result: number of officials is negatively related to fouls called – about 17 per game. All other variables except attendance significant as expected.

  13. What about tendency toward “false arrests” – i.e., bad foul calls? • Indirect test: number of upsets in tournament. Assumption: the better the officiating, the more likely the higher-seeded team will win. A third official might preserve the mean of game outcomes but lower the variance. • Must also standardize for rise in size of NCAA tournament. • Third official reduces chance of upset by ten percent, other things equal. A third official reduces the variance of game outcomes. • A third official also increases scoring, which authors interpret as less output-destroying conflict.

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