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Common Factors in Major League Baseball Game Attendance

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  • Young Hoon Lee

    (Department of Economics, Sogang University, Seoul)

Abstract

This paper applies a panel data model with observed common factors to Major League Baseball (MLB) panel data from 1904 to 2012 to analyze attendance. In particular, it aims to identify common factors. The empirical results suggest that MLB fan preferences were simple in the early years (1904?1957) with respect to common factors and then became multi-faceted in later years (1958?2012), because the number of significant common factors increased from four to seven. Time trends and per capita gross domestic product were significant over the whole sample period, but outcome uncertainties and offensive performance, such as slugging performance, became newly significant common factors influencing attendance in later years. This indicates that fans consider not only their home team¡¯s characteristics but also the characteristics of the away teams; then, in the modern era, it became critical for the league to implement elaborate business measures to promote competitive balance and slugging performance.

Suggested Citation

  • Young Hoon Lee, 2016. "Common Factors in Major League Baseball Game Attendance," Working Papers 1604, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
  • Handle: RePEc:sgo:wpaper:1604
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    File URL: https://tinyurl.com/ywanh5es
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    References listed on IDEAS

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    1. Ahn, Seung C. & Lee, Young H. & Schmidt, Peter, 2013. "Panel data models with multiple time-varying individual effects," Journal of Econometrics, Elsevier, vol. 174(1), pages 1-14.
    2. Rodney Fort & James Quirk, 1995. "Cross-subsidization, Incentives, and Outcomes in Professional Team Sports Leagues," Journal of Economic Literature, American Economic Association, vol. 33(3), pages 1265-1299, September.
    3. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
    4. Seung C. Ahn & Young H. Lee, 2014. "Major League Baseball Attendance," Journal of Sports Economics, , vol. 15(5), pages 451-477, October.
    5. Dennis Coates & Brad R. Humphreys & Li Zhou, 2014. "Reference-Dependent Preferences, Loss Aversion, And Live Game Attendance," Economic Inquiry, Western Economic Association International, vol. 52(3), pages 959-973, July.
    6. Matti Keloharju & Juhani T. Linnainmaa & Peter Nyberg, 2016. "Return Seasonalities," Journal of Finance, American Finance Association, vol. 71(4), pages 1557-1590, August.
    7. Dennis Coates & Brad R. Humphreys, 2012. "Game Attendance and Outcome Uncertainty in the National Hockey League," Journal of Sports Economics, , vol. 13(4), pages 364-377, August.
    8. Baimbridge, Mark & Cameron, Samuel & Dawson, Peter, 1996. "Satellite Television and the Demand for Football: A Whole New Ball Game?," Scottish Journal of Political Economy, Scottish Economic Society, vol. 43(3), pages 317-333, August.
    9. Seung C.Ahn & Young H. Lee, 2014. "Major League Baseball Attendance: Long-term Analysis Using Factor Models," Working Papers 1402, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
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    Cited by:

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    2. Gregory A. Falls & Paul A. Natke & Linlan Xiao, 2022. "College football attendance in the long run: The Football Championship Subdivision," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(6), pages 2172-2183, September.
    3. Adam C. Merkle & Catherine Hessick & Britton R. Leggett & Larry Goehrig & Kenneth O’Connor, 2020. "Exploring the components of brand equity amid declining ticket sales in Major League Baseball," Journal of Marketing Analytics, Palgrave Macmillan, vol. 8(3), pages 149-164, September.
    4. Dominik Schreyer & Sascha L. Schmidt & Benno Torgler, 2019. "Football Spectator No-Show Behavior," Journal of Sports Economics, , vol. 20(4), pages 580-602, May.

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    Keywords

    Attendance; outcome uncertainty; common factors; factor loading; panel data; competitive balance;
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