An Analysis of the Nba Luxury Tax

IS IT BETTER TO GIVE OR RECEIVE? AN ANALYSIS OF THE NBA LUXURY TAX.

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

Ricky Boebel

April, 2015

IS IT BETTER TO GIVE OR RECEIVE? AN ANALYSIS OF THE NBA LUXURY TAX.

Ricky Boebel

April, 2015

Mathematical Economics

Abstract

The results showed that teams that project themselves to have a winning record should breach the tax threshold. However, these franchises should not pay beyond one standard deviation of the average tax figure in a given year. Teams that project themselves to have a losing record should stay under the threshold. This is surprising as many franchises, particularly those in small markets, often go to drastic lengths to stay below the tax to the detriment of on and off-court performance. Over the period studied, an average of 6 teams paid the tax. The model found that regardless of market size around 15 teams per year would increase franchise net worth by having payrolls above the tax.

KEYWORDS: (NBA, Tax, Salary Cap, Net Worth) JEL CODES: (A100, C120, J000)

ON MY HONOR, I HAVE NEITHER GIVEN NOR RECEIVED UNAUTHORIZED AID ON THIS THESIS

Signature

TABLE OF CONTENTS

Abstract ...... 2 Acknowledgements ...... 5 Introduction ...... 6 Luxury Tax Overview ...... 7 Literature Review ...... 9 Dataset ...... 14 Model ...... 17 Results ...... 20 Conclusion ...... 26 References ...... 28 Appendix ...... 29

Acknowledgements

Firstly, I’d like to thank my thesis advisor Neal Rappaport for guiding me through the process with positivity and thoughtfulness. I would also like to thank my Father, without his ever growing PhD-sized shadow driving me, this paper may have never have been finished. Also deserving of acknowledgement is my Mother and the many chickens she maintains to this day, especially Todd. To my Dell Latitude E6420 laptop, I thank you for your four years of service. While you may have failed me in the middle of this thesis, I’ll always remember the good times when you could still turn on. Lastly, I’d like to thank NBA Commissioner David Stern, your tenure in the league was defined by your style and grace and without you this paper’s topic may not exist.

Introduction

The luxury tax is a mechanism of controlling team spending in the NBA. For every dollar a team exceeds the league set threshold, it pays a dollar back to the NBA and other non-tax paying franchises. Since its introduction in the 1999 Collective

Bargaining Agreement (CBA) teams have paid over a billion dollars in luxury taxes.

This paper asks the question: does paying the tax increase or decrease team net worth? And is this effect dependent on team performance?

The results showed teams that project themselves to have a winning record should breach the tax threshold. However, these franchises should never pay much beyond one standard deviation of the average tax payment. Teams that project themselves to have a losing record should stay under the threshold. These results are somewhat surprising as it suggest that teams should be more willing to pay the tax than they are currently. Franchises, particularly those in small markets, often go to drastic lengths to stay below the tax, often to the detriment of on-court performance. Over the period studied, an average of 6 teams per year paid the tax. My data states that regardless of market size around 15 teams in a given year would be positively affected by passing the tax threshold.

Luxury Tax Overview

There are a number of ways professional sport leagues choose to control player salaries. The National Football league sets a hard salary cap that cannot be exceeded by any team. The English Premier League has no salary cap allowing teams to spend according to their means. The NBA attempts to find a compromise between these two cap structures with the luxury tax, also known as a soft salary cap. As it is currently structured, the league office sets the tax level before the season based on the NBA’s projected Basketball Related Income (BRI). Under the

CBA that was negotiated in 2011, players’ salaries must account for approximately half of all BRI. In 2014, the league set the tax threshold by projecting 53.51% BRI then subtracted projected benefits (primarily used for player pension plans) and divided by the number of teams in the NBA (30), which totaled to a $71.75 million tax threshold. The teams with payrolls over the threshold must pay a tax back to the league depending on the quantity they went over the tax.

For example, last season the Brooklyn Nets had a payroll of $106.5 million, $34.75 million over the tax threshold. Because of the escalating incremental system they paid a $90.57 million in taxes. Below is a table of the five teams that exceeded the luxury tax in 2014. Notice the wide range between the maximum and minimum tax payment.

Figure 1: 2013-2014 Luxury Tax Teams

TEAM Tax Paid/Received (millions)

Brooklyn Nets $ 90.60

New York Knicks $ 36.30

Miami Heat $ 14.40

Los Angeles Lakers $ 8.90

Los Angeles Clippers $ 1.30

Tax redistributed per $ 3.03 team

The funds from the luxury tax go one of two places. It can be designated for “league purposes” or up to 50% can be issued to the non-taxpaying teams. For example, last year $151.5 million was paid in luxury taxes. The league decided to issue the maximum 50% to the non-taxpaying teams, meaning they divided half of the total tax into 25 equal payments to the franchises with payrolls below the luxury tax threshold.

In all but one year, the 2011-2012 lockout season, the commissioner's office has issued the maximum of 50% to the non-tax paying teams.

Several changes have been made to the luxury tax system since its inception in

1999. In its first 6 seasons, the tax was triggered just twice (2003 and 2004). Many believe this was because the exact luxury tax threshold was not set until after the 8 season. This changed in 2005, when the newly negotiated CBA mandated that the tax threshold be set before the season, based on a projection of BRI by the league office. This is a major development as it gave teams an exact tax threshold before making personnel decisions, thus eliminating the possibility of teams accidentally paying the tax.

Until the 2011 CBA the tax had been very simplistic, for every dollar a team went over, a dollar was paid to the league. In 2011, the league introduced an incremental tax rate as shown in the table above. Here, franchises are charged a gradually increasing tax rate as they go over set payroll ranges. Furthermore, a repeater penalty was put in the agreement that mandated teams pay a higher still repeater tax rate if they overstep the threshold in three of the past four seasons. However, it is impossible to identify the effects of this repeater rate currently as there have only been three seasons since the latest CBA was enacted.

Literature Review

Empirical economic research on the NBA’s luxury tax system is fairly limited due to its recent inclusion into the Collective Bargaining Agreement (CBA). Baseball was the first professional sport to implement a luxury tax in the mid-1990’s. Ajilore and

Hindrickson (2005) found that the luxury tax has led to greater competitive balance in Major League Baseball. In reference to this paper, the result implies that tax paying teams would not see a jump in performance. Ajilore and Hindrickson contend

9 that the redistribution of funds to smaller market teams would result in increased competitive balance as smaller teams would increase spending due to the additional income.

However, the distribution of wealth in Major League Baseball (MLB) differs greatly from that of the NBA. The MLB tax rates are a fraction of the NBA’s, yet teams are still less willing to exceed the tax threshold in baseball. Since 1999, 22 NBA franchises have paid the tax versus five in the MLB. While the baseball system is different, it is the most comparable salary cap structure to the NBA’s luxury tax system.

Dietl et al(2009) analyzed luxury taxes from a holistic viewpoint, creating a mathematical model of how luxury taxes affect competitive balance, social welfare and team profits. This model was purely theoretical and did not focused in on one sports league in particular. The authors concluded that profits should increase for both small and large market teams provided the tax is set at a low enough level for large market teams to exceed it and pay back into the system. This suggests that there could be a difference in results from seasons where many pay the tax versus only a few teams paying the tax.

Additionally, Dietl et al’s model did not account for the possibility of a mixed league with a combination of teams maximizing profits and others maximizing wins. Some

NBA teams appear to not be maximizing wins when they choose to develop young

10 talent rather than give veterans playing time. In essence, these teams are valuing player development over current wins in hope of achieving future success. These so called “tanking teams” are rarely ever featured among the taxpayers of the league as their payroll is often lowered by less expensive young talent. We aim to find out whether these lower tier teams maximize profits by paying less in payroll and receiving the tax.

Li (2011) found that the marginal product of labor of NBA stars approximates their salaries. The luxury tax was not factored into the study, but it does demonstrate that

NBA teams purchase labor in a rational manner. If we think about the tax as an additional cost of labor for franchises, then Li’s finding indicate that the implementation of the tax would decrease a team’s marginal product of labor below total player cost.

Another way to look at NBA valuation research is whether the increase/decrease in a franchise’s value is team driven or league driven. Hausman and Leonard (1997) found that superstar players, such as Michael Jordan in the 90s, are worth millions to not only their own teams but also the league as a whole. The study found that

Jordan was worth approximately $53.2 million to all other NBA teams due to factors such as TV and merchandise revenue. This demonstrates how dependent owners of struggling teams are on the marquee teams to generate interest in the league along with bringing in greater home attendance and local TV ratings. This superstar effect,

11 shows how team worth can be dependent on the state of the league around them and the importance of controlling for this effect when modeling.

An important aspect of the salary cap is knowing the different ways in which general managers and owners choose to structure their rosters. In a 2014 piece for fivethirtyeight.com, statistician and journalist Nate Silver notes that players on their original rookie scale contracts are the best bargains in the NBA. Every player drafted into the league signs a rookie-scale contract. There is very little negotiation in the amount a draftee can sign for, it is largely pre-determined in the CBA. For example, last year the rookie scale started with the first overall pick making a salary of $4.6 million progressively decreasing to $2 million for the 10th pick and $900,000 for the

30th. These salaries marginally increase over the players first four years in the league but, as Silver states in his article, teams stand to make large net profits on average from these below market-value contracts. Furthermore, as a player’s career continues their profitability decreases and salary increases. Older players are more likely to get hurt, force a trade under tumultuous circumstance and simply just not be able to exceed their contracts value for the team. In most cases, it is impossible for players to double or triple their performance, even if their salary does.

Figure 2: NBA Draft Pick Value vs. Cost Comparison in their first 5 seasons

(Source: http://fivethirtyeight.com/features/how-much-is-winning-the-nba-draft- lottery-really-worth/)

This relates back to the luxury tax as teams made up of players still on rookie scale contracts will very rarely breach the tax threshold. Conversely, teams that choose to trade away draft picks and players still on their rookie deals often exceed the threshold. Based on Silver’s analysis, these tax teams would be less profitable than their tax receiving counterparts and therefore paying the luxury tax would be correlated with lower profits and franchise values.

Dataset

The luxury tax was first put into action during the 2002 season. However, in both

2002 and 2005 no tax was paid or received by teams as league-wide salaries and benefits were not sufficient to trigger the tax threshold in accordance with the 1999

CBA.1 In 2005, another CBA altered the tax system. The primary implication was providing teams with the tax threshold prior to the season, instead of calculating the actual figure at the end of the season. This league wide policy shift made a reduction in the dataset by 4 seasons a logical step to isolate the effect of the tax on franchise value. This gave 9 seasons of data from the 13 possible, leaving 270 observations spanning from 2006 to 2014.

The years used in the dataset are interesting from a league perspective. Stagnant franchise values had a large impact on the owners’ decision to lock out the players in

2011. This lockout gave the owners a 6% increase in their share of Basketball

Related Income (BRI), from a 43 percent to 49 percent. In the ensuing seasons, the difference between the new and old CBA has increased team worth almost exponentially. Another aspect of the 2011 lockout was a shortened season. Only 56 of 82 games were played in this regular season, leaving a discontinuity in the dataset.

1 Details obtained from: http://www.cbafaq.com/salarycap.htm 14

Figure 3: Tax Paid Distribution

Looking at the spread of tax data, there appears to be a cluster of teams that both receive and pay a relatively insignificant amount of money into the tax system.

Teams that received every year of the dataset collected a total of 20.9 million, that’s a $2.3 million average per season. Compare this to the $160 million the average

NBA team earned in revenue last season and it may be difficult to imagine the income from the luxury tax making a measurable impact on franchise value on a year to year basis. On the other end of the spectrum, the top 4 teams in total accumulative tax payments were: Brooklyn (87.1 million), LA Lakers(101.1 million), Dallas ($102.4.1 million) and New York (174.8 million). These teams accounted for 75% of the $624 million total tax paid in the 9 season period.

Overall, the average franchise paid close to $1 million annually in luxury tax, when both payers and receivers of the tax are included. However, the average standard deviation per year is $8.25 million. The mean number teams above one standard deviation in tax paid was just under four, meaning they pay more than the sum of the mean plus one standard deviation into the system. Conversely, no team has ever received tax one standard deviation below the mean. To give these numbers some perspective, one would expect there to be five teams one standard deviation above and below the mean under the premise of the tax being normally distributed. This non-normality in the luxury tax figures suggests there may be a need for further investigation on how the tax affects the teams paying the majority of the tax versus those paying and receiving insignificant sums around the mean.

The dependent variable, net worth of a team, was taken from Forbes annual

“Business of Basketball” article that lists a valuation of every team in the league.2

The team valuations are released in an early February issue of Forbes Magazine and are based on the previous year’s financial performance. For instance, the franchise valuations from the February 9th, 2015 issue are based on performance from the 2013-2014 NBA season and thus the tax figure is coupled with the other data from this season.

2 Source: http://www.forbes.com/nba-valuations/ 16

Data on tax payments came from NBA journalist Larry Coon for both the tax received and paid out by each team.3 Coon also runs a website called CBAfaq.com, which was invaluable in building an understanding of the CBA and its various iterations over the past 15 years. As for data on payroll and revenue, Rodney Forts sports economics data base was pivotal in completing the dataset.

Model

A least-squares regression model is used to measure the effect of the tax on the net worth of each franchise. 퐻0, the null hypothesis, is that no correlation exists between tax and team worth. 퐻1, the alternate hypothesis, is that tax is significantly correlated with team worth.

푊표푟푡ℎ푖푗 = 푊표푟푡ℎ푃푖푗 + 푇표푡푎푙푅푒푣푒푛푢푒푖푗 + 푃푎푦푟표푙푙푖푗 + 퐿푢푥푢푟푦푇푎푥푖푗 + 푆푒푚𝑖푠푖푗 + 푆표푙푑푖푗

+ 퐶퐵퐴푖푗 + 퐿표푐푘표푢푡푖푗 + 푇표푝푆푝푒푛푑푒푟푠푖푗

The model accounts for large scale structural changes to the league as well as team specific variables. Firstly there is WorthP, which is the team’s worth from the previous season, this controls for past value from the entire history of the franchise.

Total Revenue is the sum of all 30 teams’ revenue for the season, this accounts for how the overall health of the league contributes to each teams value. Payroll is the

3 http://cbafaq.com/blog/?p=117 17 team’s total player salary expenses excluding the luxury tax, which shows the effect of player expenses outside the context of the tax system. LuxuryTax represents the total amount paid or received by a team i in year j.

Figure 4: Summary of Variables

Variable Description

푊표푟푡ℎ푖푗 The worth of the team i based on the Forbes Magazine valuation

from after year j.

푊표푟푡ℎ푃푖푗 The worth of the team i from year j−1.

푇표푡푎푙푅푒푣푒푛푢푒푖푗 The sum of every NBA team’s revenue in year j.

푃푎푦푟표푙푙푖푗 Team i’s total payroll from year j.

퐿푢푥푢푟푦푇푎푥푖푗 Team i’s luxury tax figure for year j. Note that a positive dollar

amount indicates payment in and a negative indicates a team

receiving money.

푆푒푚𝑖푠푖푗 A Dummy variable that is a 1 if team i reaches the semifinals of the

NBA playoffs in year j.

푆표푙푑푖푗 Dummy variable that is a 1 if the sale of a team takes place in year

퐶퐵퐴푖푗 Dummy variable that is a 1 if year j is 2013 or 2014.

퐿표푐푘표푢푡푖푗 Dummy variable that is a 1 if year j is 2011.

푇표푝푆푝푒푛푑푒푟푠푖푗 Dummy variable that is a 1 if team i’s luxury tax is one standard

deviation above the mean tax figure in year j.

All remaining inputs in the model are dummy variables. CBA is a 1 for the seasons after the 2011-12 lockout seasons as there was a CBA that included a revenue sharing policy favorable to the owners. After this point we observe a notable increase in the growth of teams’ values. Another notable difference in the 2011-12 season is that none of the tax money was redistributed directly to the non-taxpaying teams. At the end of the season league offices decided to claim all of the $32 million paid in taxes that year. The dummy variable Lockout accounts for the discontinuity.

Over the dataset’s 9 seasons, 8 NBA teams were bought and sold. In general, the selling of a team gives a real value to the team’s Forbes’ estimated valuation, often higher as the Forbes valuation is from a neutral arbitrator. The winning bid for an

NBA team often comes from someone willing to pay above market value due to how rarely franchises are up for sale. For example, last June the Los Angeles Clippers sold for $2 billion, well over triple their Forbes valuation of $550 million five months before the sale.

Semis measures short term on-court success of team i. This is a 1 if team i reaches the semifinals of the NBA playoffs in year j. One could argue a short term positive impact on value may occur from contending for a title. I theorize an increase in team worth could be due to a rise in playoff revenues as well as future anticipated success. Furthermore, contending teams garner greater secondary revenue sources such as merchandise and sponsorship sales because of their short term success.

The final dummy variable tests the hypothesis that the upper strata of taxpayers are affected by the tax differently than those contributing lesser amounts. The

Topspender variable is a 1 for teams above one standard deviation from the mean luxury tax payment in year j. During the 9 seasons examined, there are a total of 30 teams that satisfy this criteria in a given year. These franchises have tax payments ranging from $6 million to $90 million. Because the rest of the sample is much more clustered around the mean, I hypothesize the tax will have a greater effect on valuation for these 30 teams.

Results

Figure 5 shows the results of the linear regression from the model. Of the nine dependent variables, seven were found to be significantly affecting the net worth of

NBA teams. These variables are net worth from the previous year, total league revenue, payroll, luxury tax, the 2011 lockout, the years following the 2011 CBA and the top spender dummy variable. Robust standard errors are also used as evidence of heteroscedasticity were found in the dataset.

Figure 5: Regression Results for All Teams

(a)All teams Variable Coefficient P-Value

Worth Previous 1.61 <0.001** Total Revenue 0.08 0.007** Payroll -1.8 0.03* Luxury Tax 3.92 0.007** Semis -4.94 0.755 Sold 44.53 0.465 CBA 73.57 0.048* Lockout 78.29 <0.001** Top Spenders -103.71 0.007**

*= 95% confidence level, **=99% confidence level

I observe that worth from the previous year drives the regression with a highly significant p-value (<0.001). This makes intuitive sense as the variable represents the team’s entire history up to a year before the valuation. This includes past performance, fan loyalty, market size, local television contracts and sponsorship deals, all major determinants in franchise worth. Total league revenue was also highly significant (.007) with a positive coefficient. Higher revenues often are an indicator of a greater level of all around talent in the league. As mentioned by

Hausman and Leonard, the presence of stars and successful franchises can lead to economic gains for all teams. This is supported by the above regression that showed a positive correlation between total revenue and team worth.

Payroll shows a significantly negative relationship to team value (0.03). This follows the natural line of reasoning that teams with greater player expenses on labor should have a decreased net value, holding other variables constant. The CBA dummy variable shows the effect of the 2011 CBA in the two seasons following the work stoppage. Predictably, this raised team worth (0.048) because the owners attained a higher share of BRI in labor negotiations.

The Lockout dummy variable is separated from CBA as it is the only season with a work stoppage in the 9 years sampled. Its coefficient’s sign was also positive and statistically significant level (<.001). The loss of 26 games in this season would be detrimental in the short run. However, the CBA was so lucrative for owners in the long term it out weighed losing close to a third of regular season fixtures for one season. This also points to how franchise value is strongly tied to structural changes for not only the small market franchises, but the league as a whole.

Teams paying the most tax (over one standard deviation) show a decrease in net worth. These upper echelon spenders often load their rosters up with high priced veterans, either via free agency or trade, in hope of elevating their team to contend for a championship. In other words, franchises are mortgaging the future to succeed in that season. Nate Silver’s study on player contracts states that veterans produce a much smaller return on labor than the less expensive rookie scale contracts. When a

22 franchise builds a team with a high percentage of players not on rookie deals, it becomes difficult to stay out of the very highest level of tax paying franchises.

One example of this is the Orlando Magic, a small market team who only paid the tax once before 2010. After a Finals appearance in 2009, the Magic paid over $31 million in taxes over the next two seasons. There large tax bills were a consequence of bringing in high priced veterans to keep the magic in playoff contention. However, their free agent gambles were largely fruitless and franchise centerpiece Dwight

Howard left for Los Angeles in the summer of 2012. Since then, Orlando has been a consistent tax receiver and currently sits as the league’s 18th most valuable franchise. This sequence of events shows the trap that NBA franchises can fall into.

Front Offices feel pressure to win immediately and jeopardize the franchise’s future by joining the top spenders of the league.

On the other end of the spectrum is the San Antonio Spurs. On the court they are the most successful team of the last 15 years, making the playoffs every single season and winning five titles. This success is also reflected off the court, the Spurs are the 11th highest valued team despite their location in the 4th smallest market in the league. The Spurs have only paid the tax four out of the past nine seasons and only once did they pay over $3 million. They have never paid one standard deviation above the mean tax payment. These tax figures agree with the regression results

23 that point to teams increasing franchise worth by keeping their payroll relatively close to the tax threshold.

The most surprising regression results were linked to the tax variables. Luxury Tax was positively correlated with team worth, this translates to teams who pay more in tax experiencing an increase in net worth. For every million in tax paid, the team gains roughly $4 million in net worth. Conversely, for every million of tax received, teams lose $4 million in net worth. This illustrates that paying the tax is not necessarily detrimental to team worth. Of course, situations still exist where breaching the luxury tax threshold would be ill advised.

Figure 6: Regression Results based on Wins

(b)Below .500 (c)Equal or above .500 Variable Coefficient P-Value Coefficient P-Value

Worth Previous 1.95 <0.001**1.36 <0.001** Total Revenue 0 0.928 0.11 0.011* Payroll -2.13 0.016* -1.76 0.135 Luxury Tax 3.25 0.291 3.75 0.042* Semis ommited - -0.72 0.962 Sold -5.93 0.887 135.32 0.319 CBA 75.19 0.126 103.54 0.039* Lockout 63.11 0.019* 90.9 <0.001** Top Spenders -207.01 0.026* -68.42 0.044*

*= 95% confidence level, **=99% confidence level

In order to analyze these situations, the dataset is stratified into two categories: teams that finished the season above or at a 50% winning percentage and those that finish below a 50% winning percentage. Looking at Figure 6, column (b) shows the regression results of just teams with winning percentages under 50%. First we see that the Luxury tax is no longer significantly positive in this regression. This suggests that the generally smaller tax values are not large enough to have a measurable impact on franchise value.

Another contributing factor may be that tax paying teams with losing records sign veterans that suffer injuries or simply play poorly. Out of the 121 observations with losing records, just 11 paid the tax, of those eleven, six were classified as big spenders. Even with this small number of top spenders, we still see a negative statistically significant relationship (0.026) that exists in the first regression. This implies that these franchises misjudged their rosters’ abilities by a large margin prior to breaching the threshold.

Some of the large scale changes in the league had a lesser positive effect on the valuations of less successful teams. Both the CBA and total revenue variables transform from having a positive statistically significant coefficient to no statistical significance. This secondary result is an interesting area of further study as it may suggest winning teams see a greater return from league wide structural changes than losing teams.

Looking at regression results of teams at or above .500, we observe many more similarities to the original regression. The only difference in the coefficients is payroll has shifted from negatively affecting franchise worth to having no effect. This could indicate that successful teams generate more financial return from players than losing teams. Overall, Regression (c) shows that conclusions found in regression (a) are more applicable to winning teams than losing teams. These successful franchises are able to pay a moderate amount of tax without experiencing a drop in value.

Conclusion

This paper modeled factors affecting team valuation with a focus on determining the effect of the luxury tax. I uncovered that the magnitude of tax paid or received changed the effect it had on team worth. I could divide teams in the NBA into three groups based on tax paid or received:

1. Teams that receive the tax, typically $2 to $4 million.

2. Teams that pay a moderate amount or tax, approximately under $8 million.

3. Teams that pay large amounts of tax. (Classified as those that pay above one

standard deviation from the mean tax figure from a given season)

The regression analysis determined that teams in group (1) that finished the season with a losing record do not see a decrease or increase in net worth due to the tax

26 received. Winning teams that receive the tax see a decrease in net worth from the income. This is because of the opportunity cost of not upgrading personnel that an already successful team incurs by not paying the tax.

Teams in group (2) that ended their season with losing record, just 1.9% of all teams sampled, saw no effect on net worth from their luxury tax payment. While teams in group (2) with winning records experienced an increase in franchise value due to the tax.

Group (3) represents the point of diminishing returns for tax payers. When teams pay above one standard deviation of the average luxury tax payment for that year, franchise worth is negatively affected. On average this dividing line is around $8 million. These teams account for around 75% of all tax payments.

These Results point to real inefficiencies in the way general managers construct

NBA rosters. Of the 149 teams sampled that were at or above .500, just 50 paid the tax. The results of this paper suggest many of the 99 teams that chose not to pay the tax missed out on potential financial gains.

Over the time period an average of 6 teams paid the tax each year. The regression results suggest that number should be approximately 15 for teams to maximize franchise value for the next season. However, a 250% increase in the number of

27 teams paying the tax could drastically change the effect of the tax on team value.

When only a handful of teams pay the tax, the tax payers gain a competitive advantage over the many tax receivers. A future study on this subject could get to the root of where the increase in franchise value from the tax originates. Is it a result of putting a better quality product on the court regardless of the opponent? Or is it due to the franchise bettering its roster relative to the rest of the league?

Another area of further study would be on long term growth. Our model simply looks at year to year franchise growth. When the luxury tax is 20-30 years old, data will be available on how best to manage a team’s payroll to maximize growth 5-10 years in the future. Furthermore, the 2011 CBA introduced both an incremental tax rate as well as a repeater penalty. Currently only 3 seasons of data are available under this rule, but as the years go we could see behavioral changes begin to take hold among both tax payers and receivers.

References

Ajilore, O., & Hendrickson, J. (2011). The impact of the luxury tax on competitive balance in Major

League Baseball.

Dietl, H. M., Lang, M., & Werner, S. (2010). The effect of luxury taxes on competitive balance, club profits, and social welfare in sports leagues.International Journal of Sport Finance, 5(1), 41-

51.

Hausman, J. A., & Leonard, G. K. (1997). Superstars in the National Basketball Association:

Economic value and policy. Journal of Labor Economics, 15(4), 586-624.

Li, H. (2011). True Value in the NBA: An Analysis of On-Court Performance and Its Effects on

Revenues. University of California, Berkeley.

Kaplan, R. A. (2004). The NBA luxury tax model: A misguided regulatory regime. Columbia Law

Review, 1615-1650.

Marburger, D. R. (1997). Gate revenue sharing and luxury taxes in professional sports. Contemporary Economic Policy, 15(2), 114-123.

Quirk, J. (1997). The salary cap and the luxury tax: Affirmative action programs for weak-drawing franchises. Stee-rike Four, 97-109.

Wiseman, F., & Chatterjee, S. (2003). Team payroll and team performance in major league baseball: 1985–2002. Economics Bulletin, 1(2), 1-10.

Appendix

Appendix 1: Teams in Top Spender Category (yellow indicates champion)

Year 2006 2007 2008 2009 2010 2011 2012 2013 2014 total NYK NYK NYK NYK LAL ORL LAL LAL BRK/NJN DAL DAL DAL DAL LAL BOS MIA NYK CLE CLE CLE DAL MIA BRK/NJN DEN BOS BOS NYK MIA ORL BOS # 2 1 6 4 5 3 3 4 2 30 teams

Appendix 2: Tax Figures since 2002

$284.60

$672.65

TOTAL

$1,068.30

-$ 18.70 -$

-$ 37.90 -$

-$ 11.30 -$

-$ 85.10 -$

-$ 34.80 -$

-$ 89.50 -$

-$ 40.77 -$

$ 4.30 $

$ 1.40 $

$ 5.00 $

-$ 137.60 -$

-$ 102.50 -$

$ 18.50 $

-$ 5.00 -$

$ 18.50 $

$ 15.60 $

$ 18.50 $

$ 14.17 $

$ 18.50 $

$ 15.30 $

$ 18.50 $

$ 13.13 $

$ 18.50 $

$ 17.80 $

3.03

2014

$75.75

$151.50

-$ 36.30-$

-$ 14.40-$

-$ 90.60-$

$ $

-$ 8.90 -$

-$ 1.30 -$

1.47

2013

$35.30

$70.60

-$ 10.00-$

-$ 13.30-$

-$ 29.30-$

-$ 12.90-$

$ $

-$ 3.90 -$

-$ 1.20 -$

$0.00

2012

$32.00

$ - - $

-$ 12.60-$

-$ 2.50 -$

-$ 6.10 -$

-$ 2.70 -$

-$ 7.40 -$

-$ 0.70 -$

2011CBA

2011

$17.50

$55.20

$72.70

-$ 20.10-$

-$ 19.90-$

-$ 18.90-$

$ 2.40 $

-$ 5.00 -$

-$ 2.30 -$

-$ 0.80 -$

-$ 5.70 -$

2010

$41.10

$70.30

$111.40

-$ 11.00-$

-$ 21.40-$

-$ 17.60-$

-$ 15.90-$

-$ 14.90-$

$ 3.70 $

-$ 3.10 -$

-$ 8.80 -$

-$ 5.00 -$

-$ 5.20 -$

-$ 3.00 -$

-$ 5.50 -$

2009

$20.60

$66.70

$87.30

-$ 23.70-$

-$ 23.60-$

-$ 13.70-$

$ 2.90 $

-$ 5.90 -$

-$ 4.90 -$

-$ 7.20 -$

-$ 8.30 -$

2008

$24.20

$68.20

$92.40

-$ 19.70-$

-$ 13.60-$

-$ 19.60-$

-$ 14.00-$

$ 3.10 $

-$ 3.90 -$

-$ 8.30 -$

-$ 5.10 -$

-$ 8.20 -$

$8.00

2007

$47.50

$55.50

NET TAX PAYMENTS 2002-2012 PAYMENTS TAX NET

-$ 45.10-$

$ 1.90 $

-$ 0.20 -$

-$ 1.00 -$

-$ 2.00 -$

-$ 7.20 -$

2006

$14.00

$57.60

$71.60

-$ 37.20-$

-$ 17.30-$

$ 2.40 $

-$ 0.90 -$

-$ 7.80 -$

-$ 3.70 -$

-$ 4.70 -$

2005CBA

$0.00

2005

$ - - $

2004

$52.00

$102.10

$154.10

-$ 13.10-$

-$ 28.80-$

-$ 39.90-$

-$ 17.60-$

-$ 25.00-$

$ 5.40 $

$ 3.50 $

$ 5.40 $

$ 1.40 $

$ 5.40 $

-$ 4.10 -$

-$ 5.10 -$

-$ 8.40 -$

-$ 2.70 -$

-$ 9.40 -$

2003

$75.20

$94.00

$169.20

-$ 17.40-$

-$ 52.00-$

-$ 12.80-$

-$ 24.40-$

-$ 10.00-$

-$ 18.50-$

$ 6.00 $

$ 5.50 $

$ 0.90 $

$ 6.00 $

$ 3.60 $

$ 6.00 $

-$ 1.20 -$

-$ 6.00 -$

-$ 4.70 -$

-$ 5.10 -$

-$ 7.60 -$

-$ 5.80 -$

-$ 3.70 -$

$0.00

2002

$ - - $

1999CBA

League:

Distrib:

Paid:

WAS

UTA

TOR

SAN

SAC

POR

PHX

PHI

ORL

OKC/SE

NYK

NOH

MIN

MIL

MIA

MEM

LAL

LAC

IND

HOU

GSW

DET

DEN

DAL

CLE

CHI

CHA

BRK/NJ

BOS ATL

TEAM

Appendix 3: Revenue by team 2002-2012

11- 10- 09- 08- 07- 06- 05- 04- 03- 02- 12 11 10 09 08 07 06 05 04 03 Revenue $ $ $ $ $ $ $ $ $ $ Atlanta Hawks 99 109 105 103 102 95 92 87 83 78 $ $ $ $ $ $ $ $ $ $ Boston Celtics 143 146 151 144 149 117 111 110 104 97 $ $ $ $ $ $ $ $ $ $ Brooklyn Nets 84 89 89 92 98 102 93 87 93 94 $ $ $ $ $ $ $ $ Charlotte Bobcats 93 101 98 96 95 93 89 73 $ $ $ $ $ $ $ $ $ $ Chicago Bulls 162 185 169 168 165 161 149 136 123 119 $ $ $ $ $ $ $ $ $ $ Cleveland Cavaliers 128 149 161 159 159 152 115 102 93 72 $ $ $ $ $ $ $ $ $ $ Dallas Mavericks 137 166 146 154 153 140 140 124 117 117 $ $ $ $ $ $ $ $ $ $ Denver Nuggets 110 113 113 115 112 104 100 94 89 75 $ $ $ $ $ $ $ $ $ $ Detroit Pistons 125 141 147 171 160 154 138 134 121 102 $ $ $ $ $ $ $ $ $ $ Golden State Warriors 127 139 119 113 112 103 89 81 76 70 $ $ $ $ $ $ $ $ $ $ Houston Rockets 135 150 153 160 156 149 142 141 125 82 $ $ $ $ $ $ $ $ $ $ Indiana Pacers 98 101 95 97 101 107 110 108 104 94 $ $ $ $ $ $ $ $ $ $ Los Angeles Clippers 108 108 102 102 99 98 95 83 77 72 $ $ $ $ $ $ $ $ $ $ Los Angeles Lakers 197 208 214 209 191 170 167 156 170 149 $ $ $ $ $ $ $ $ $ $ Memphis Grizzlies 96 99 92 88 95 98 101 98 75 63 $ $ $ $ $ $ $ $ $ $ Miami Heat 150 158 124 126 131 131 132 119 93 91 $ $ $ $ $ $ $ $ $ $ Milwaukee Bucks 87 92 92 91 94 88 87 78 77 70 Minnesota $ $ $ $ $ $ $ $ $ $ Timberwolves 96 97 95 96 100 103 103 101 97 85 $ $ $ $ $ $ $ $ $ $ New Orleans Hornets 100 109 100 95 95 91 83 78 80 80 $ $ $ $ $ $ $ $ $ $ New York Knicks 243 244 226 202 208 196 185 181 170 160 $ $ $ $ $ $ $ $ $ $ Oklahoma City Thunder 127 126 118 111 82 81 81 81 73 70 $ $ $ $ $ $ $ $ $ $ Orlando Magic 126 140 108 107 100 92 89 82 78 80 $ $ $ $ $ $ $ $ $ $ Philadelphia 76ers 107 116 110 115 116 112 110 110 107 109 $ $ $ $ $ $ $ $ $ $ Phoenix Suns 121 136 147 148 148 145 132 132 111 109

$ $ $ $ $ $ $ $ $ $ Portland Trail Blazers 117 132 127 121 114 82 77 78 88 97 $ $ $ $ $ $ $ $ $ $ Sacramento Kings 96 104 103 109 117 128 126 119 118 102 $ $ $ $ $ $ $ $ $ $ San Antonio Spurs 135 139 135 133 138 131 122 121 108 105 $ $ $ $ $ $ $ $ $ $ Toronto Raptors 121 134 138 133 138 124 105 94 100 96 $ $ $ $ $ $ $ $ $ $ Utah Jazz 111 120 121 118 119 114 96 91 88 85 $ $ $ $ $ $ $ $ $ $ Washington Wizards 102 109 107 110 118 112 108 106 94 98