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THE PENNSYLVANIA STATE UNIVERSITY SCHREYER HONORS COLLEGE DEPARTMENT OF ECONOMICS THE STADIUM SUBSIDY GAME ALEXANDER ELLIS SPRING 2020 A thesis submitted in partial fulfillment of the requirements for baccalaureate degrees in Mathematics and Economics with honors in Economics. Reviewed and approved* by the following: Peter Newberry Assistant Professor of Economics Thesis Supervisor Russell Chuderewicz Teaching Professor of Economics Honors Adviser * Electronic approvals are on file. i ABSTRACT This thesis analyzes the strategic situation that allows sports teams in the US to secure large subsidies from cities. Using a simple league model and a two-period subsidy auction model, the paper establishes conditions under which a league will strategically leave viable cities open to extract greater subsidies in the future. That finding is then compared with historical subsidy data for NFL, MLB, NBA, and NHL teams1. To that end, historical data on the largest open markets in each of the Big Four leagues was compiled independently for this paper. However, a regression of subsidies on open market size fails to provide evidence of the relationship predicted by the league and subsidy auction model. Additionally, linear regression shows that metropolitan population explains at most half of the variation in team revenues, contrary to the league model’s assumption that revenues are determined entirely by metro population. 1 NFL, MLB, NBA, and NHL refer to the National Football League, Major League Baseball, National Basketball Association, and National Hockey League, respectively. ii TABLE OF CONTENTS LIST OF TABLES ....................................................................................................... iii LIST OF FIGURES ..................................................................................................... iv ACKNOWLEDGEMENTS ......................................................................................... v Chapter 1 Introduction ................................................................................................. 1 Chapter 2 Literature Review ........................................................................................ 3 Models of Leagues and Subsidies .................................................................................... 3 Contingent Valuation Studies .......................................................................................... 6 Chapter 3 League Model .............................................................................................. 9 Multiple Teams per City .................................................................................................. 9 Talent, Revenue, and Profit .............................................................................................. 10 Social Value ..................................................................................................................... 15 Chapter 4 Stadium Subsidy Game Model .................................................................... 16 General Two-Period Model .............................................................................................. 17 Two-Period Model: Numerical Example ......................................................................... 20 Comparative Statics: 훼, 휆 ................................................................................................. 23 Chapter 5 Comparison to Data ..................................................................................... 26 League Model vs Revenue & Profit Data ........................................................................ 26 Contingent Valuation: Case Studies ................................................................................. 31 Testing Subsidy Data ....................................................................................................... 33 Chapter 6 Conclusion ................................................................................................... 35 Appendix A Verification of Four Properties of 휎(푗, 푛). ............................................. 37 Appendix B Derivations under Revenue Sharing ....................................................... 39 Appendix C Deriving the Social Value Constant “c” ................................................. 41 Appendix D Regression Output: Revenue vs Metro Population ................................ 42 Appendix E Historical Subsidy & Vacant City Data .................................................. 44 Appendix F Regression Output: Subsidy vs. Time, Avg Vacant City........................ 50 iii BIBLIOGRAPHY ........................................................................................................ 52 iv LIST OF TABLES Table 1. Profits by Team, Time Period .................................................................................... 17 Table 2. Case 1: League’s Offers in Period 2 by Team 1 Location Decision .......................... 18 Table 3. Case 2: League’s Offers in Period 2 by Team 1 Location Decision .......................... 19 Table 4. Case 3: League’s Offers in Period 2 by Team 1’s Location Decision ....................... 20 Table 5. Meaning and Value of Constants ............................................................................... 20 Table 6. Single Team Values for Each City ............................................................................. 21 Table 7. Case 1: League’s Period 2 Offers by Team 1 Location Decision .............................. 22 Table 8. Case 2: League’s Period 2 Offers by Team 1 Location Decision .............................. 22 Table 9. Case 3: League’s Period 2 Offers by Team 1 Location Decision .............................. 23 Table 10. Period 1 City Choice vs 훼, 휆 .................................................................................... 24 Table 11. Regression of Revenue on Metro Population .......................................................... 30 Table 12. NHL Revenue Regressed on Metro Population and Southern Binary Variable ...... 30 Table 13. Results of Subsidies Regressed on Avg Vacant City, Time .................................... 34 v LIST OF FIGURES Figure 1. NFL, MLB Team Revenues & Profits, 2018-19 ...................................................... 27 Figure 2. NBA, NHL Team Revenues & Profits, 2018-19 ...................................................... 28 vi ACKNOWLEDGEMENTS Thank you to Peter Newberry and James Tybout for helping me through the process of writing this thesis. You have both given me a better understanding of economics and the research process, and I hope to continue improving as a researcher over the next several years. I would also like to thank all the students in ECON 489M who gave suggestions for improving this paper. I enjoyed our thesis class – especially before we had to move online – and I hope at least a few of my suggestions were helpful for you as well. Finally, thank you to my parents and my dog, Layla, for enduring my late-night thesis work while at home this semester. 1 Chapter 1 Introduction Since 2000, US taxpayers have spent at least $16.7 billion2 to subsidize sports stadiums for the Big Four sports leagues (the NFL, MLB, NBA, and NHL), despite those leagues taking in a combined $38 billion in revenue – and keeping $8 billion in profits – in 2019 alone (Forbes)3. Cities are often forced to offer teams enticing deals to avoid losing them to other cities; those deals often include property tax exemptions, below-market leases, stadium naming rights, and hundreds of millions of dollars in public money for stadium construction. In this paper, I will investigate the competition between cities that produces such large subsidies for sports teams, and I aim to explain teams’ location decisions. In particular, I will seek to establish conditions under which leagues strategically leave large cities open to extract subsidies in the future. Stadium subsidies are a compelling topic because they do not appear to make economic sense. The most common claim made to justify these subsidies – namely, that sports teams make a sufficient economic impact to repay their cities – is unsupported by the literature (Baade, 1996). Though stadiums may have some impact on a city’s economy, that impact is quite small compared to the size of the city’s economy and is also mitigated by a crowding-out effect; rather than exclusively attracting new economic activity to the city, sporting events often take business away from other local establishments. The intangible value of teams to fans both within the city and outside it is considerably larger, though that value cannot be easily captured by the city paying the subsidy (Noll & Zimbalist, 1997). 2 $16.7 billion is the sum of subsidy figures from various sources, including Marquette’s NSLI (2015). 3 I calculated revenue and profit by summing the numbers published separately by Forbes for each league. 2 Though the economic results of subsidies are worth discussing, an even more interesting question is why cities commit to paying subsidies. The first and most obvious answer is that cities want to keep their teams where they are. US sports teams are privately owned franchises whose owners will move their teams to more profitable cities if the opportunity arises. For example, Brooklyn Dodgers owner Walter O’Malley infamously moved his team to Los Angeles in 1957 after being denied his preferred stadium location in Brooklyn. Though O’Malley’s decision was economically sound, the people of Brooklyn were understandably