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An Analysis of Nba Franchise Revenues

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An Analysis of Nba Franchise Revenues DOES LOSING MATTER? AN ANALYSIS OF NBA FRANCHISE REVENUES A THESIS Presented to The Faculty of the Department of Economics and Business The Colorado College In Partial Fulfillment of the Requirements for the Degree Bachelor of Arts By Lance Nicholas Jacobs May 2009 111 DOES LOSING MATTER') AN ANALYSIS OF NBA FRANCHISE REVENUES Lance Nicholas Jacobs May, 2009 Economics Abstract The National Basketball Association (NBA) is one of the four largest professional sports organizations in the United States, There are currently 23 teams in the NBA that gathered over $100 million in revenue during the 2007-08 season alone. This study examines the components of total NBA franchise revenues and investigates the effect that multiple losing seasons has on total revenue performance. A fixed-ellects regression analysis is used to examine the effect of multiple losing seasons on total NBA franchise revenue. All the statistics and data observed in this study are from the 10 year period of 1999 to 2008. The findings in this study provide valuable infom1ation to NBA teams as to whether losing consecutive seasons affects total revenue performance. KEYWORDS: (National Basketball Association, Revenues, Consecutive Losing Seasons) ON MY HONOR, I HAVE NEITHER GIVEN NOR RECEIVED UNAUTHORIZED AID ON THIS THESIS Signature TABLE OF CONTENTS ABSTRACT ............................ '" ............ ............. ... ................. .... ... 11l ACKNOWLEDGEMENTS..... ........... ... ............. ...... ........ ... ... .......... ... IV I. INTRODUCTION ........................................................................ II. LITERATURE REVIEW.................................. ............................... 6 Superstar Impact. .. 7 New Stadiums......................................................................... 8 Ticket Prices........................................................................... 11 Player Productivity ........................................ ". ... ................... ... 14 Sponsorships........................................................................... 15 Conclusion ................................ " . .... 16 lII. THEORy........................................... ........................................ 18 Dependent Variable................................................................... 19 Independent Variables................................................................ 19 Dummy Variables..................................................................... 24 IV. DATA AND METHODOLOGy......................................................... 29 Variables Summary. '" .................... ..................... ...................... 30 Dependent Variable..... ................................................ ............... 33 Independent Variables.. ......................................... ...................... 34 Method............................................ ....................................... 41 V. RESULTS....... .............................. ................................................ 43 Modell..................................... .............................................. 45 ModeI2............................ ....................................................... 47 Model 3...................................................................... ............. 49 VI. CONCLUSION.............................................. ................................ 52 Significant Variables ................................................................ ". 53 Limitations. .. 55 Further Research.............. ..................................................... ...... 56 SOURCES CONSULTED...................... .............................. .............. 58 LIST OF TABLES 4.1 Variables Summary .............................. '" ... ... ... ................................. 30 4.2 NBA Teams and Conferences................................ ....................... 32 5.1 Fixed Effects Regression Results................................................... 44 LIST OF MODELS 4.1 Simple Regression Equation"."" " ... "",,.,,"""""" """".""""".,,",,",,. 28 LIST OF FORMULAS 4.1 Win Percentage.......... ....................... ................................................... 36 4.2 Fixed Effects Regression Model.. ........................ ........................... 42 IV ACKNOWLEDGEMENT I would like to recognize Professor Andrew Nelson for assisting me in creating this project and for his advisement throughout the process of senior thesis. His positive criticisms and insightful suggestions proved valuable in each and every meeting. Finally, I would like to thank my mother Molly and my father Scott for always giving constant support and guiding me through the strenuous process of writing this thesis. I cannot thank them enough for there unwavering support in all of my endeavors and for providing me with the opportunity to attend this wonderful institution. I dedicate this thesis to them. CHAPTER [ INTRODUCTION The National Basketball Association (NBA) is one of the four largest professional team sports organizations in terms of popularity in the United States. The other three are Major League Baseball (MLB), The National Hockey League (NHL), and The National Football League (NFL). There are currently 23 teams in the NBA that gathered over 100 miIlion dollars in revenue during the 2007-2008 season. [n recent years most professional sports, including the NBA, have undergone dramatic changes in order to generate greater revenues and growth in specific regional economies. I These changes include the sponsorship and naming rights of stadiums, and the strategy of building new stadiums to generate a "honeymoon effect"· therefore greatly increasing revenues for a short period of time2 However, there has been an absence of research about how two or more consecutive losing seasons effects the amount of revenue that NBA franchises can generate. This research paper will focus on examining the effect that two or more consccutive losing seasons has on NBA franchise revenues. One would assume that winning has a positive effect on revenues and losing has a negative effect, but this paper j The Economic Determinants of Professional Spons Franchise Values. Donald L Alexander and \',\"ilham Kern. Journal of Sports Economics 2004; 5; 51. \Vhen is the Honeymoon Over? National Basketball Association Attendance 1971-2000. John C. Lcadley and Zenon X. Zygmont. Journal of Sports Economics 2005; 6; 203. *The honeymoon effect represenL"> the relationship bct"\veen spectator attendance at a professionai sporting event and the age of the sports facility at which the event is held. 2 will detennine if there is a secondary effect on franchise revenues if a team loses consecutive seasons. The hypothesis is that the total revenue that an NBA franchise accumulates will not be significantly affected by losing consecutive seasons. As previously mentioned, 23 teams in the NBA arc making over 100 million dollars in franchise revenue a year. Where are these teams making this enonnous amount of money and in which sectors are revenues the most significant? Some people may wonder how sports entertainment is generating this money and it is indeed an interesting phenomenon. For example, in the 2007·2008 season the New York Knieks generated the most revenue of any team in the NBA, accumulating 196 million dollars in total revenue. One might assume that the Knicks had a very high win percentage, thus generating higher revenue from attendance due to people wanting to see a winning team. This is definitely not the case. The New York Knicks' finished the 2007·2008 season with a record of23 wins and 59 losses which translates to a winning percentage of 28%3 This brings up the question: where and how are the Knicks generating so much revenue if they are losing so many games? The answer, I believe, lies in their market size. The Knicks play their home games at Madison Square Garden which is located in the largest market in tenns of population4 in the United States. From a business standpoint this is a very interesting situation because, in sports, losing usually translates to bad attendance resulting in less revenue from ticket sales and attendance. However, this research paper will detennine the exact cffect that multiple losing seasons has on franchise revenues. 4 Population is defined by the metropolitan ~tatistical area of each city. 3 Now let's compare New York to a much smaller market such as San Antonio, where the San Antonio Spurs play their home games. The San Antonio Spurs ranked 10th in the league in total franchise revenue, generating 138 million dollars in the 2007-2008 season. This market is much smaller in population than the enonnous market New York City has, yet somehow the Spurs are earning tremendous amounts of revenue. In comparison, San Antonio has a population of 1,990,675 and New York City has a population of 18,815,988 5 Although San Antonio is collecting $70 million less in revenues, it is interesting to wonder how they are in loth place among 30 NBA teams in tenns of total revenues. In fact they are bringing in more revenue than larger market teams such as the Philadelphia 76ers and the Denver Nuggets. Since the 1998-99 season the Spurs have won 4 championships and have had a range of win percentages from .646 to .768. They are one of the most suecessful teams on the court during this era in tenns of winning. This eould be an explanation of why they bring in so much revenue as compared to teams who play in larger markets. People
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