Implications of State Income Tax Policy on NBA Franchise Success: Tax Policy, Professional Sports, and Collective Bargaining
Bibliographic record
Abstract
Introduction The National Basketball Association (NBA) is a sports entertainment enterprise with yearly revenues surpassing $4 billion (5). The majority of these revenues are derived from ticket sales, merchandising and television revenues. The distribution of these revenues between franchises and players has been negotiated and is governed by the Collective Bargaining Agreement (CBA). The current version of the CBA was implemented before the 1984-85 season and was most recently re-negotiated prior to the 2005 season. The current CBA contract expires following the 2010-2011 NBA season, but league owners have the option to extend the agreement through the 2011-2012 NBA season (5). A large component of the CBA is the provision of a salary cap. The salary cap dictates a fixed percentage of league revenues which are to be paid to players in terms of salaries and benefits. NBA teams are presented with a yearly salary cap number to be used as player compensation. This amount can only be exceeded utilizing certain exceptions as further defined by the CBA. One justification for the salary cap is the concept that it is designed to benefit middle and small market teams. It is argued that larger market teams have significantly more ability to profit from ticket, merchandising and television revenues. This advantage could be used to enlist top talent by paying salaries far exceeding those of smaller markets. In using superior financial resources to lure and retain better talent (players, coaches and management), it is feared that larger market teams could dominate the league over a prolonged period. The salary cap system, it is argued, should allow every NBA franchise an equal opportunity in acquiring and obtaining comparable resources. While not a perfect system, the CBA should work to distribute resources (player skill, coaching talent and management expertise) more evenly throughout the league. While the CBA only governs player salaries, the even distribution of quality players throughout the league should also dissuade quality coaches and management from concentrating and distribute them throughout the league. League ownership believes that an equal chance of team success should promote larger game attendance and provide for a healthier competitive balance in the league. However, these goals have repeatedly been disputed in research (7, 3, 9) which have found increased disparity of play after the imposition of revenue sharing amongst teams and other results inconsistent with stated goals. This paper will extend this research by examining potential causes of the breakdown between the intended goals of the CBA and its results. In assessing NBA franchise success, the incentive structure facing potential resources (players, coaches, management) should be examined. The different tax environment of NBA franchises is a potential variable which could disrupt league parity. It is argued in this paper that resources are influenced by the financial incentives created by varying state income tax rates applied to the differing NBA franchises based on location. The implications of these findings could have impacts on future CBA negotiations. Methodolgy The study examines the potential for state tax income tax policy to influence NBA team success. The model employs data for eleven years (2000 through 2010) of previous NBA seasons. Also included are the rates (in percentage terms) for the individual states top marginal tax brackets for these eleven years. The basketball data was assembled using information from a sports database website (6). The income tax bracket data was derived using information from the tax foundation website (10). For ease of computation and data gathering, only the top marginal tax bracket was used. As NBA salaries escalate, the importance of lower tax brackets becomes nominal. The data from the Canadian-based team was removed. The examination is on the impact of income taxes on player decisions, which in the United States will be uniform at the federal level and vary only at the state level. …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".