Regime Switching and Wages in Major League Baseball under the Reserve Clause

Haupert, Michael and Murray, James (2011): Regime Switching and Wages in Major League Baseball under the Reserve Clause.

Abstract

Over the course of the 20th century American wages increased by a factor of about 100, while the wages of professional baseball players increased by a factor of 450, but that increase was neither smooth nor consistent. We use a unique and expansive dataset of salaries and performance variables of Major League Baseball pitchers that spans over 400 players and 60 years during the reserve clause era to identify factors that determine salaries and examine how the importance of various factors have changed over time. We employ a Markov regime-switching regression model borrowed from the macroeconomics literature which allows regression coefficients to switch exogenously between two or more values as time progresses. This method lets us identify changes in wage determination that may have occurred because of a change in the league's competitiveness, a change in the relative bargaining power between players and teams, or other factors that may be unknown or unobservable. We find that even though Major League Baseball was a tightly controlled monopsony with the reserve clause, there was a significant shift in salary determination that lasted from the Great Depression until after World War II where players' salaries were more highly linked to their recent performance.

• Item Type: MPRA Paper
• Language: English
• Keywords: Major League Baseball; Salary determination; Markov-Regime switching
• Subjects: J - Labor and Demographic Economics > J3 - Wages, Compensation, and Labor Costs > J31 - Wage Level and Structure ; Wage Differentials; C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C23 - Panel Data Models ; Spatio-temporal Models; C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes

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