The introduction of the reserve clause in Major League Baseball: evidence of its impact on select player salaries during the 1880s


This paper investigates the impact of baseball’s reserve clause as it evolved from a “gentleman’s agreement” to a formal contract stipulation. Using data describing the salaries of 34 Major League Baseball players during the 1880s, we test whether average salaries, remuneration to marginal product, and the premium paid to a player for changing teams were materially impacted when the reserve clause became binding in 1887. The empirical results suggest that, controlling for player attributes and the overall macroeconomy, average real salaries in the sample fell by 6–9% after the binding reserve clause. We also find that the premium for moving to a new team was reduced by 70% after the binding reserve clause was implemented, supporting Rottenberg’s invariance principle.

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Fig. 1


  1. 1.

    The contract clause was agreed to by the players who stipulated that at most 14 players on each team would be reserved and a player’s salary would not decrease without the player’s consent. The concern over the reserve clause and its implications prompted John Montgomery Ward to form the Brotherhood of Professional Baseball Players in 1885, which was a forerunner to the current Major League Baseball Players Association formed in 1966, and the Player’s League in 1890. Bradbury (2017) provides evidence that the Player’s League corresponded to an increase in player salaries through increased competition for high-quality players.

  2. 2.

    This was not the first lawsuit concerning free agency. In 1970, Curt Flood, center fielder for the St. Louis Cardinals, sued Major League Baseball after he was involuntarily traded in 1969 to the Philadelphia Phillies. Curt Flood argued that Major League Baseball violated antitrust statutes and sued for economic damages. Although he ultimately lost his case, it was heard by the U.S. Supreme Court and arguably galvanized players for future action against the reserve clause.

  3. 3.

    This formulation is similar to Marburger (1994).

  4. 4.

    There are few empirical studies that estimate monopsony exploitation although Pigou (1920) and Robinson (1933) spend considerable effort discussing the topic in a theoretical context. In addition to Scully’s study, Persky and Tsang (1974) analyzed the level of Pigouvian exploitation in the US economy, relating the ratio of marginal product to real wages as a function of unionization, unemployment, inflation, the capital stock, and government imposed controls in the labor market. They found that exploitation increased with unemployment, inflation, the capital stock, and governmental intervention. The only variable negatively correlated with exploitation was unionization.

  5. 5.

    This variable was included in the production function in Scully (1974).

  6. 6.

    Total home game attendance was collected from The Baseball Encyclopedia. In general, team prices are not available from this era; however, the National League agreed to fix gate prices at $0.50 in 1879 (Haupert 2015). Teams in the American Association and the Union Association fixed gate prices at $0.25 (U.S. Congress 1952, p. 25).

  7. 7.

    Alternative production functions have been investigated in the literature. MacDonald and Reynolds (1994) use runs scored and earned run average as the primary inputs to winning whereas Bradbury (2007) uses the difference between runs scored and runs allowed, arguing that earned run average is not a good measure of pitching quality as the measure depends on the quality of a team’s defense, which is beyond control of the pitcher. We estimated our model following Bradury and found qualitatively similar results. When we estimated our model following MacDonald and Reynolds, we obtained negative marginal products for some players so we chose not to use this specification.

  8. 8.

    Scully’s production function included two additional variables: a dummy variable that took a value of one if the team finished the season within five games of first place (CONT) and another that took a value of one if the team finished more than twenty-five games out of first place (OUT). The inclusion of these two variables in a team’s production function has been criticized by other authors, e.g., Boal and Ransom (1997). While we include CONT in our attendance and revenue functions, we do not include CONT or OUT in our production function.

  9. 9.

    Slugging percentage is defined as the total bases obtained by the team divided by the total number of at-bats. Team and player data were obtained from, last accessed August 2008.

  10. 10.

    Teams in the 1880s did generate very little additional revenue through concession sales. Moreover, at the time there were no media, merchandise or stadium revenue, nor was there league revenue sharing, thereby avoiding one of the criticisms of using team total revenue offered by Krautmann (1999). We do not anticipate the measurement error in our estimate of real total revenue to prove debilitating to the estimation results reported herein.

  11. 11.

    See "Appendix" for an extended discussion on exactly how to calculate a player’s marginal product.

  12. 12.

    Krautman did not investigate the MRP of pitchers arguing that pitchers in the modern era are often specialists, i.e., starters, closers, or setup men, and therefore, the appropriate measure of a pitcher’s productivity is less clear than for position players. Furthermore, the Krautman approach would sacrifice 30% of our sample, which seems excessive given its already limited size.

  13. 13.

    Pitchers in the 1880s were less specialized than in the modern era. Furthermore, including ERA and other pitching statistics directly into the team production function yields negative marginal products for numerous players. While it is not inconceivable and an input would have a negative marginal product we do not think baseball players would be allowed to play, either by managers or owners, if they had an obvious negative marginal product. Therefore, we choose not to use the ERA as the pitching input in our production function.

  14. 14.

    There are potentially negative effects of using a ratio as the regressand (see Kronmal 1993, for example), including possible specification bias. On the other hand, any measurement error in the estimated real marginal product is shifted to the left-hand side of the estimating equation, where it is expected to only influence the efficiency of the estimates.

  15. 15.

    We acknowledge Brad Humphreys for this valuable suggestion. During the sample period, there were two peaks (March 1882 and March 1887) and two troughs (May 1885 and April 1888) in the business cycle.

  16. 16.

    We choose to measure salaries relative to 1887 because that is the year that the binding contract-based reserve clause was introduced. While we use the GDP deflator of Johnston and Williamson (2002), we re-estimated all of our models using the historical CPI calculated by Hoover (1960) and the GDP deflator provided in Barro and Ursua (2008) and obtained qualitatively and quantitatively similar results.

  17. 17.

    As was pointed out by a helpful referee, it is likely that there were salary declines in the pre-1887 period when the reserve system was less formal but, nevertheless, did exist. We do not have pre-1880 salary data with which to test the impact of the less formal reserve system although a report by the U.S. Congress (1952) provides anecdotal evidence that the top three players on Boston’s club experienced a significant decline in their salaries when the three-player reserve list was implemented in 1881.

  18. 18.

    The RC dummy variable was also interacted with the NEWLEAGUE and NONPITCHER dummy variables, but these interactions were found to be insignificant. They were dropped from the final specifications reported here.

  19. 19.

    Whether a player changed teams voluntarily or involuntarily is not identifiable in our data and is a potential avenue for future research as the rent distribution might differ across the two modes by which a player changes teams.

  20. 20.

    The “microscope effect” occurs when a player demands a premium for playing in a city in which he will receive considerably more attention and scrutiny. Some players demand a compensating differential for the additional pressure such scrutiny entails. This is arguably one component to the inflated salaries for modern-era players in New York and Boston, for instance. Whether the microscope effect would have pertained to professional baseball in the 1880s is not clear. Newspaper accounts of the day do not focus much on the off-field behavior of players and there is virtually no mention of baseball players during the off-season.

  21. 21.

    Anecdotal evidence suggests that teams in New York, Boston, and Baltimore (the closest team to Washington between 1972 and 2005) all pay substantial premiums to players.

  22. 22.

    Population counts were obtained from the U.S. Census Bureau.

  23. 23.

    This result is alluded to, but not derived, by Chelius and Dworkin (1980) and Krautmann (1999).


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Helpful suggestions by seminar participants at West Virginia University, Clemson University, the University of Georgia, Wake Forest University, Greensboro College, and the University of Wisconsin-La Crosse are acknowledged.

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Correspondence to Craig A. Depken II.

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A player’s slugging average does not have a one-to-one relationship with the team’s slugging percentage; the marginal product from the team production function overstates the marginal product of an individual player’s offensive or pitching contribution. To see this, note that team slugging percentage can be written as

$$\begin{aligned} TSA_k= & {} \frac{\sum _i H_{ik} + \sum _i D_{ik} + 2\sum _i T_{ik} + 3\sum _iHR_{ik}}{\sum _i AB_{ik}}, \end{aligned}$$

where \(i = 1 \ldots N_k\) indexes the number of players on team k, H is the number of hits (of any kind), D is the number of doubles, T is the number of triples, HR is the number of homeruns hit by the players on the team, and AB is the number of at-bats by the players on the team.

An individual player’s slugging average is:

$$\begin{aligned} SA_i= \,& {} \frac{H_{i} + D_{i} + 2T_{i} + 3HR_{i}}{AB_{i}}, \end{aligned}$$

which can be rewritten as

$$\begin{aligned} AB_iSA_i= \,& {} H_{i} + D_{i} + 2T_{i} + 3HR_{i}. \end{aligned}$$

Summing both sides of Eq. (6) over the N players on team k one obtains:

$$\begin{aligned} \sum _iAB_{ik}SA_{ik}= & {} \sum _iH_{ik} + \sum _iD_{ik} + 2\sum _iT_{ik} + 3\sum _iHR_{ik}. \end{aligned}$$

The right-hand side of Eq. (7) equals \(TSA_k\times \sum _i{AB_{ik}}\) so that the team’s slugging average can be written as

$$\begin{aligned} \sum _iAB_{ik}SA_{ik} = TSA_k\sum _i{AB_{ik}}. \end{aligned}$$

This, in turn, suggests that the marginal impact of a player’s slugging average on team slugging percentage can be written as:

$$\begin{aligned} \frac{\partial TSA_k}{\partial SA_i} = \frac{AB_{i}}{\sum _iAB_{ik}}dSA_{i}, \end{aligned}$$

where the first term is the percentage of a team’s at-bats for player i and \(dSA_{i}\) is the change in a player’s individual slugging percentage.Footnote 23

For non-pitchers, slugging average captures their contribution to team win percentage. However, during the 1880s all pitchers hit, and therefore pitchers contributed to team win percentage through their offensive and pitching efforts.

It is possible to derive the marginal impact of a pitcher’s individual strikeout-to-walk ratio on the team’s strikeout-to-walk ratio as:

$$\begin{aligned} \frac{\partial TSW_k}{\partial SW_i} = \frac{K_{i}}{\sum _iK_{ik}}dSW_{i}. \end{aligned}$$

An individual pitcher’s contribution to the team strikeout-to-walk ratio is the product of that pitcher’s strikeout-to-walk ratio and the percentage of team strikeouts for which the pitcher accounted.

Combining the two derivatives, it is possible to calculate each player’s marginal win percentage as:

$$\begin{aligned} MWP_{it} = (SA_{it} \times PERAB_{it}\times MP_{TSA}) + (SW_{it} \times PERSO_{it} \times MP_{TSW}), \end{aligned}$$

where \(SA_{it}\) denotes player i’s slugging average in year t, \(PERAB_{it}\) denotes player i’s percentage of team at-bats in year t, \(MP_{TSA}\) denotes the marginal product of team slugging percentage, \(SW_{it}\) denotes player i’s strikeout-to-walk ratio (pitched) in year t, \(PERSO_{it}\) denotes player i’s share of team strikeouts pitched in year t, and \(MP_{TSW}\) is the marginal product of team strikeout-to-walk ratio.

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Ashcraft, J.K., Depken, C.A. The introduction of the reserve clause in Major League Baseball: evidence of its impact on select player salaries during the 1880s. Cliometrica 14, 105–128 (2020).

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  • Sports economics
  • Monopsony
  • Free agency
  • Negotiation

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