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U.S. companies are often criticized for being overly short-term oriented. This paper documents that those criticisms have a long history, going back at least thirty-five years. The paper then considers the implications of sustained short-termism for corporate profits, venture capital investments and returns, private equity investments and returns, and corporate valuations. The paper finds little long-term evidence that is consistent with the predictions of the short-term critics.

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1. Introduction

The business of sports draws considerable attention from the media and the general public. Fans and sports writers frequently speculate about the effects of money on athletic performance. There is general agreement that more financial resources usually lead to better athletic performance. In team sports, higher pay can be used to lure better players from other teams and therefore improve performance. However, performance can also be affected by pay inequality among players within a team. On the one hand, pay inequality could have a negative effect because it may hinder cooperation among team members. In many sports, team cooperation is critical for good performance. If pay inequality creates tensions or animosity among team members, performance is likely to suffer. On the other hand, inequality could have a positive effect on performance by providing incentives. The prospect of a very large salary could be a powerful drive behind an athlete’s performance. Pay inequality might also enhance performance if low paid players learn from high paid players. This would happen when pay inequality is associated with skill inequality. For example, if a highly paid superstar can teach other players, the overall performance of a team may improve. Given that arguments can be made both ways, it is not surprising that there is little agreement on the effects of pay inequality on team performance. The purpose of this paper is to determine whether, on balance, the effect of pay inequality on performance is positive or negative.

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12Modelling Long-term Commodities: the development of a Simulation Model
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4. Conclusion

The analysis in this paper shows that pay inequality within MLB teams has a negative effect on performance. The effect remains statistically significant even after controlling for total payroll. The result is the same as that of DeBrock et al. (2004) who use data from 1985 through 1998. My paper confirms their finding using the most recent data and using a different measure of pay inequality.

The fact that pay inequality leads to worse performance implies that managers should strive for pay equality in their teams. For example, instead of hiring two low-priced players and one superstar, performance may be better if three medium-priced players are hired. Given these results, it is surprising that there is not a more equal distribution of pay in baseball. One possible explanation is that managers may care about attendance as well as winning. They may be willing to sign up an expensive superstar who will attract fans even though it will increase pay inequality and may hinder performance.

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In addition to pay inequality and performance, I use data on the total payroll of each team. This is a measure of financial resources which could be an important determinant of performance. I measure payroll in current dollars and do not adjust for inflation. While 2003 dollars are not exactly comparable to 2004 dollars, 2003 inflation was low enough not to influence the results significantly.

Table 1 shows the descriptive statistics of each variable. In the first row we see that on average the highest paid 20% of players earn about 61% of the total payroll. This implies that on a 30 player team, the six best paid players earn more than the remaining 24 combined. According to this measure, the team with the most equitable pay is the New York Yankees during the 2003 season when the top 20% of players earned only 42% of total payroll. The team with the highest inequality was the Colorado Rockies during the 2004 season. On that team, five players earned more than 78% of the team’s total payroll.

The second row in Table 1 shows that the average winning percentage is 50% which has to be the case since for every game won there is a game lost. The Detroit Tigers have the lowest winning percentage in the data with only 26% of games won during the 2003 season. The maximum winning percentage in the data is for the St. Louis Cardinals, who won nearly 65% of their games during the 2004 season. Finally, the last row in Table 1 shows that the average payroll is about 70 million dollars. The range of payroll is quite striking. It goes from less than 20 million dollars for the Tampa Bay Rays to over 184 million for the New York Yankees.

Table 1: Descriptive Statistics

TERM PAPER ECONOMICS | Demand | Financial …

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The conclusions above are subject to a number of limitations. First, it is unclear to what extent the results can be generalized to other sports. Each sport requires a different degree of cooperation among team members. Therefore, the relationship between pay inequality and performance is likely to differ across sports. Second, the error terms for each team could be correlated over time. For example, if a team wins a lot of games one year given its payroll and pay inequality, that team is likely to win a lot of games the next year as well. Therefore, the estimation procedure may need to correct for this autocorrelation. Finally, there may be other variables that affect performance, e.g. coach salary or quality of training facilities. Including these in the regression would increase the precision of my estimates as well as eliminate potential omitted variable bias.

The channels through which pay inequality affects performance are not clear. I can think of two possibilities. One is that pay inequality leads to tensions within the team and impairs performance. The other possibility is that baseball requires players of similar quality. Pay inequality is probably associated with skill inequality, and it may be the skill inequality that drives down performance. An excellent pitcher cannot win the game when the outfielders cannot catch or throw. It may be possible to distinguish these two channels empirically. Using statistics on individual player skill level, one could construct a measure of skill inequality for a team and include it as an additional control. The coefficient on pay inequality in that case would capture the effect of pay inequality on performance while holding skill inequality constant. A negative impact of pay inequality would then support the idea that pay inequality leads to tensions which affect performance. This investigation, however, is left for future research.

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