Tax Migration: Rate Effects on Skill Level in the NBA

Brady Seitz

Advised by Professor Steven Smith

Senior Thesis in Economics Haverford College

April 2016

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Table of Contents

3 ……………………………………………………………… Abstract 4 …………………………………………………………….... Introduction 7 ……………………………………………………………… Literature Review

10 …………………………………………………………….... NBA Constraints 12 ……………….……………………………………………. Tax Rules 13……………………………………………………………… Data

14 ……………………………………………………………... Summary Statistics 15 …………………………………………………………….. Table 1: Tax Rates by Team 16………………...…………………………………………… Methodology 18 ……………………………………………………………. Results

19 ……………………………Table 2: Effects of Tax Rates on Win Shares by Contract Value 21 ………………...………………………………Table 3: Unrestricted vs. Restricted Free Agents 23 ……………………………………………………………. Conclusion

25 …………………………………………………………….. Works Cited

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Abstract:

This paper examines differentials and their effect on tax migration in the . Using contract level data for individuals between 2010 and

2014, I identify the effects that state and local marginal income tax rates for 30 cities have on free agent decision-making in the NBA. The plethora of performance measures allows us to control for free agent skill level, and finds that franchises under lower state and local marginal income tax rates see no significant advantage at attracting higher skilled free agents.

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Introduction:

Tax migration is an oft-discussed topic in labor economics. As mobile factors of production, labor supply could be impacted by tax rates when individuals have the opportunity to migrate in congruence with their preferences.

Tax rates have been influential on the movement of labor supply throughout history. Currently, US states are seeing an impact with tax migration. In the case of Tennessee, neighboring states leak their workers into the Tennessee work force (Brett 2015). These neighboring states all have higher tax rates than

Tennessee (which happens to have no income tax). These states lose valuable tax dollars and workers. High benefit states are left with a larger tax burden, as richer individuals no longer pay into the system. (Reynolds 2015). The results are not stable, and someone will have to change to absorb the newfound tax gap. With an increasing connected world economy, the factors of influencing migration are becoming more important. This has motivated the study to see the effects of differing local tax rates and migration in .

Tax rates may have an effect on professional sports. Differing tax rates can upset the competitive balance of a professional sports league. The sets a limit on the amount of money a franchise can pay their players. The

NBA has operated under a salary cap over the last thirty years, making it a great place to look for an impact of tax rates on skill. The purpose of the salary cap is to limit the spending when creating a franchise. If all teams are held to the same 5 limit of paying players, the teams operate on an even playing field. The local and state tax rates of an NBA franchise have an effect on the after-tax take home pay of players. The aim is to see if tax rates also affect player decision-making.

Players may choose to sign for teams in lower tax rate cities in an attempt to maximize their post-tax earnings. This would allow low-tax teams to attract more talent for the same pre-tax expenditure. This effect is clearer to understand with maximum level contracts. Players are limited in the amount of money they earn per year if they are offered maximum level contracts. Offers from teams in low tax level cities will always be higher when measured post-tax, and will never have a chance to be matched by teams who compete in high tax areas, except for restricted free-agent cases.

Each year as NBA free agency opens during the off-, media outlets discuss the best potential suitors for each free agent. Players forego millions of dollars in post-tax salary based on these decisions, and media outlets are quick to reason that these tax rates influence their decisions. Trevor Ariza accepted a four-year, 32 million-dollar contract to return to Houston, despite being offered the exact same contract by the Washington Wizards. The Washington Post reported that the money was a factor, as the lack of income tax would allow his money to go much farther. There are a number of reasons why NBA players may choose to sign for franchises that are out of the control of the NBA. But the

NBA can control one thing, and that is the amount of money that can be offered to each player. Through maximum and minimum salary restrictions, salary floors that a franchise must spend on player , to curb lavish spending, 6

the NBA is able to budget expenditures in order to even the competitive balance.

In addition to the media attention regarding Trevor Ariza, Carmelo Anthony’s

decision was equally scrutinized. SI.com writer Michael McCann along with tax

expert Robert Raiola accounted for federal, state, and local income tax rates

when comparing potential free agent offers. An offer nearly $35 million dollars

higher in pre-tax numbers from the NY Knicks shrunk to a net benefit of $12

million once tax rates were calculated compared to his next best offer. Despite

the NBA’s effort in controlling expenditures, they so far have ignored the tax

discrepancies. This is a departure from some of the NBA’s earlier decisions.

With fluctuations affecting the take home pay of the Toronto

Raptors, the NBA decided to intervene and provide a stipend to be distributed

within the players of the organization. This clearly differs with the NBA’s opinion

on tax rate differentials throughout the US, which they do not view as a

competitive advantage1.

This paper aims to measure the effects of local tax rates on the free agent decisions made in the NBA. Using performance data from the NBA, I examine whether lower income tax rates allow NBA franchises to sign higher skill level free agents. By examining the tax rate affecting each free agent decision over our sample, I am able to determine the effect of the marginal tax rate on player skill. The coefficient on the tax rate variable is the main finding of interest.

The results indicate that tax rate differentials will have differing effects on skill level of free agent signings for NBA franchises. Players at both extremes for

1 According to league sources 7

contract levels do not seem to account for tax rates, while players around the

average contract value will be affected.

The paper begins with a discussion of previous research done on tax

migration. I then look more precisely into the NBA salary cap and tax structure. I

then discuss the data and empirical strategy. The paper concludes with a

discussion of results, finishing with a conclusion.

Literature Review

Tiebout first looked at the theoretical effects of tax rates on the labor supply. Using a theoretical framework, Tiebout found that local governments that offer different tax packages would face tax migration for mobile factors of production. The labor supply that is able to move locations will select an area that best fits their tax preferences (Tiebout 1956).

Professional sports have become an interesting way to study labor economics. The availability and detail in performance measures gives insight into the decision-making process individuals make when it comes to signing contracts. Contract data for professional sports is easily accessible but that is not what makes professional sports unique. Although measuring performance in the labor market is possible, sports have accessible and transparent performance data. The data is extensive and gives access to a myriad of performance metrics that are not as available in the labor market as a whole.

There have been many studies looking at the influence of tax rates on the migration of skilled labor. Net are a critical factor when selecting a . A 8 study of tax rates for both average income and high-income earners confirmed this. Egger used data on tax profiles from 2002 to calculate the tax progression for well-paid workers. Egger then calculated the progressivity of personal income tax rates by looking at the difference between the tax rates for both average and five times the average earners. Then, Egger estimated the effect of these income tax variables to see the effect of migration of skilled workers and expatriates into OECD countries. The results they found show that

“the progressivity of the tax system at high income brackets is quantitatively the most important component for expatriates or migration” (Egger et al 2008).

Grogger et al examined this issue through the scope of emigration. He measured the earnings differential between low and high skilled workers and found that more educated migrants move to places with a higher earning differential. More importantly, “This correlation is stronger when wage differences are adjusted for , implying that well-educated migrants weigh post-tax earnings when choosing a destination” (Grogger et al. 2008).

Liebig, Puhani, and Sousa-Poza investigated the variation in local tax rates within Switzerland and its results on internal migration between provinces.

Due to the varying community tax rates in Switzerland, the authors were able to isolate migratory responses to tax rate variations for different groups. Using

Swiss Census data, the authors found that young Swiss college graduates are most sensitive to tax rate differences. Consistent with previous findings, tax rate increases will cause outmigration, especially among skilled (Liebig et al

2007). 9

Studies with free agents in other major sports have been conducted measuring tax rates. Alm, Kaempfer, and Sennoga examined the impact on the of free agents in Major League to income taxes effects on player salaries. The study finds that teams in tax friendly states (Florida, Texas,

Washington) enjoy salary savings of 2% to 3% relative to other MLB teams (Alm et al 2012). This study examined the benefits to MLB teams, rather than individual decision-making. The finding of interest was whether the tax burden bore to the individual or the team. The MLB has a far less strict salary cap, with the variation in spending across MLB teams significantly more stratified than in comparison to the NBA. Thus, teams are far less constrained financially in the

MLB, potentially giving us far different results. The teams in the MLB are thus far more able to capitalize on tax rate differentials. (Sreeker 2015).

Nolan Kopkin released the most recent paper dealing with the effect of local taxes on NBA salary decisions in 2008. He found that an increase in the marginal state and local tax rate decreases the average level of free agent an

NBA team could sign. Kopkin collected contract level data and marginal tax rates over a period of time, and examined the changes in tax rates of an individual’s team over time. The data expands on his original set, encompassing

2010 to 2014. The methodology and data collection lead to different results.

Kopkin’s cutoff date for data collection is important for a variety of reasons. First off, a new collective bargaining agreement was signed after this date that has had a plethora of effects on player salaries; a new salary cap was calculated, new maximum and rookie contracts were agreed to, and new exceptions were 10

added2. The increase in advanced metrics in order to measure player performance will also help us to measure the ability level of free agents more effectively. Leading analyst writer Kirk Goldsberry stated, “metrics like points per possession and PER have significantly improved the analytical discourse surrounding basketball”. Specifically, Kopkin’s paper estimated player skill level through traditional box score statistics such as points, rebounds, and assists. This paper will improve on this methodology by using a new statistic, win shares, which is a catchall player performance statistic.

NBA Salary Constraints and Tax Rules

NBA Salary Cap

A Salary Cap is a standardized limit on the amount of money an NBA

team can spend on player contracts. Salary Caps are structured in order to

maintain competitive balance in a league. A team with deep pockets cannot

spend their way to success, and must strategically sign players in order to not

exceed the cap. The NBA initiated a salary cap in 1984, and will continue to

operate under one for the coming years. The salary cap is based on a

percentage of revenue the NBA accumulates.

The NBA operates under a soft cap. The difference between a soft and hard cap is that a hard cap cannot be exceed for any reason, while in the NBA there are certain exceptions that will allow a team to go over. All of these exceptions help promote the basic premise of allowing teams to retain their own

2 Information from CBA 101 distributed by the NBA 11 players. The exceptions allow a team to offer more money to stay with their team, rather then sign for another team for less money. This exception is known around the league as the family of exceptions, made famous by legendary Boston Celtic Larry Bird. Teams may also exceed the salary cap by choice and choose to pay a “luxury tax”. This luxury tax becomes more and more expensive both based on how many dollars you exceed the cap by, and how many consecutive years the cap was exceeded. The luxury tax has become stricter in recent years, and as such, only 5 teams paid the tax last year. A basic binary regression has shown us that teams in higher tax rate areas are more willing to pay the luxury tax. These constraints lead NBA teams to make strategic decisions in free agency.

The collective bargaining agreement, which also sets the salary cap, has several other important implications for this paper. The NBA salary cap has both a salary ceiling and floor for teams and players alike. The NBA salary cap served as a constraint for NBA franchises nearly 80% of our sample3. The salary floor for teams was set as 80% of the cap prior to the 2011 season, and grew to

85% then 90% during the sample. Only 2 teams violated this salary floor during a sample. (Magic 2014, Nuggets 2014). Player individual minimum and maximums are scaled upward based on the amount of years they have played in the NBA. For 0-6 year veterans, Maximum salary is defined as 25% of the cap.

For 7-9 year veterans, it is defined as 30%. And for players with 10+ years of experience, it is defined as 35% of the salary cap.

3 Forty-one times did our teams exceed the cap and thus paid luxury tax penalties during our sample. 12

Tax Rules

The NBA tax rules are complex. Each NBA team plays 82 games in a

season, with 41 of these games being played in the NBA franchises home arena.

These 41 games are taxed at the home arena rate, regardless of where the NBA

player resides. The 41 remaining “away” games are taxed at the rate in which

the stadium is located. Practice days are also taxed at the rate of the home stadium, meaning tax rates will have an even larger effect than simply the 41 games. State income tax is also deductible from federal income tax in the United

States, but not the case in .

Despite other tax burdens on NBA players, I have chosen to only include

income tax rate and not property or sales tax rates. In order to maximize tax

collection, states often employ a combination of sales, property, and income tax

rates. These may differ significantly, and low income tax rates often are

accompanied by higher rates of the other two4. I chose to simply use income tax

rate, as this is the only tax that is mandatory to pay. Individuals in our sample

are free to live and purchase goods wherever they choose, however they must

always pay the state and local income tax rates. Although there are ways to

avoid sales and property tax penalties, income taxes are unavoidable for every

player in the sample.

4 Texas boasts property taxes of nearly 2%, 4th highest in the United States 13

Data:

The data set contains contract level data along with performance

measures for each player who signed a contract as a free agent from 2010 to

2014. The contract level data has free agent type, duration, total dollar amount,

per year dollar amount, previous team, and new team. The performance

measures include both regular and advanced stats, as well as age and position.

Team wins is also included in the dataset.

The contract level data is collected from Spotrac.com. The data contains

each player that signed a free agent contract dated from 2010 to 2014. This data

is collected annually, concluding for each NBA season. 500 contracts were

signed in the sample. Player performance measures are collected from

basketball-reference.com. Measures include points, rebounds, assist, steals,

blocks, turnovers, win shares, PER etc5. Performance measures are measured on a per game basis for the previous season. Marginal local, State and Federal

Tax rate data are collected from taxfoundation.org. The source for tax rates is combined in the data set to calculate the marginal tax rate affecting each individual’s contract. All individuals in the sample have their marginal income taxed at the highest bracket.

Luxury tax penalties were also included. The variable, TotalTaxPaid, is a cumulative sum (in millions of dollars) of the tax penalties a team paid over our

5 Traditional statistics were used in preliminary model which returned similar results 14 sample. This variable represents teams who were willing to exceed the salary cap, and therefore may have been able to attract more talent than they would have if they stayed constrained by the salary cap.

Above are the summary statistics for the main variables in the analysis.

Table 1 shows the tax rates at which each NBA franchise is taxed. This table illustrates the differences between the lowest paying NBA teams and the highest. As evidence by the table, there is a severe enough difference between some of the lowest and highest playing NBA teams by marginal tax rate. As these contracts are worth millions of dollars, a double-digit percentage difference in income tax rates will result in hundreds of thousands of dollars in savings for players who choose to play in no income tax locations. The salary savings become even more apparent, as I am examining multimillion-dollar contracts. An issue with the marginal tax rate arises with the . For every other team in the sample, they face the same federal tax rate. Located in Canada, the

Raptors are subject to Canadian Federal tax laws. The confounding factor lies in 15

the exchange rate fluctuations within our sample. As this is the only franchise in

which I face this issue, I have chosen to drop free agents who signed for or left

from the Toronto Raptors6.

Table 1: Tax Rates by Team

Methodology:

Win Shares:

Win Shares are a new advanced NBA statistic, which was created with the

purpose of assigning a single numerical value to the level of impact an NBA

6 Results remain unchanged when including Toronto in our analysis 16

player had during a season. I am using this new statistic as a proxy for NBA skill

level of our free agents. This statistic measures a player’s contribution to both

his teams offense and defense over the course of a season. The statistic

involves calculating a player’s points produced (assists, Effective Field Goal

percentage, offensive rebounds) relative to their pacing (points per possession

and possessions per game). This gives a measure of how much a player

contributed to a team’s offensive production, normalizing all teams to attempt the same number of shots over the period of a game. A similar calculation is done to

calculate defensive win shares, which are then added to offensive win shares to

create the Win Shares statistic. This serves as an effective proxy for skill at is

encompasses every contribution a player has on the court. Robustness checks

were conducted with a replacement for winshares7, and similar results were found.

Empirical Model

In order to test the hypothesis, ideally I would compare each individual’s

decision to sign for a team versus other team’s offers. Since other teams offers

are unavailable, I construct the methodology to circumvent this. I also include

variables to control for a teams ability to recruit free agents, and the amount of

money they can use to sign free agents. Team Wins account for the

performance of a team prior to the free agent signing window. By including this

variable, I control for a team who has potentially increased their labor supply

because individuals may be more willing to play for better performing teams.

7 Player Efficiency Rating was used in place of winshares 17

The player’s previous team is also included because individuals are offered more

money in the labor market if they resign with a team they have spent 2+ seasons

with, under the guidelines of the Larry Bird exceptions. Using the performance

measures gathered from basketball-reference.com, I regress winshares on

taxrate, lnavgsalary, age, TotalTaxPaid, TeamWins and year.

Winshares = B0 + B1TaxRate + B2lnavgsalary + B3age + B4TotalTaxPaid +

B5year + B6TeamWins

The TaxRate variable is constructed based on the combination of all the marginal income tax rates affected on a player (state, local) at year I, in the city they signed for.

The value of B1 will take on a significant, negative value if the hypothesis

is correct. The same nominal contract but less in real terms due to the tax rate

being higher, therefore the team should receive less talent.

There are several additions to the methodology. I segment the contract

data into 3 groups. I have minimum level, maximum level, and other contracts. I

then run the regression for those groups alone. By segmenting the contract

levels, I are controlling for different possible outcomes. Maximum level contract

offers are interesting to compare as they cannot receive any higher pre-tax

salary, so individuals may weight the income tax more highly in these cases.

In addition to grouping the contract levels, I also run a check on free agent

types. For the two types of free agents, Unrestricted versus Restricted, I run the

regression again. With restricted free agents, teams have a chance to match a 18 contract offer from other teams in the market. This gives us the chance to directly compare two offers, although I do not have the specific offer to compare it with. If teams are more willing to match the offer in higher taxed states, they are recognizing the undervaluation of the free agents they have signed.

Results

Our coefficient of interest throughout all our regression work is the coefficient on the TaxRate variable. This variable is created through combining state and local tax rates that each player must pay when they sign for a team in the NBA.

The main result of interest here is the coefficient on taxrate. The hypothesis suggested that I would see a negative significant result on this coefficient. The same nominal contract but less in real terms due to the tax rate being higher, therefore the team should receive less talent. None of the coefficients on TaxRate are significant. According to the results, higher skill-level individuals do not sign in relatively lower tax rate areas when facing equal contract values. 19

Table 2 shows the results of our empirical model regression. In column 1,

I run the main regression over every player in our sample. The coefficient on taxrate is positive, which I did not expect. For column 2, I observe only contracts that are worth more than 7.5 million dollars annually. Again, the coefficient on tax rate is positive. This may be a result of higher skilled individuals wanting to play in bigger markets, which may have higher tax rates. More skilled players are able to supplement their income via endorsements, which may draw them to higher tax areas despite the lower take home salary. Column 3 has contract 20

values between $2 million and $7.5 million8. For these individuals, the coefficient moves in the hypothesized direction. This column provides the most insight into our research question. These individuals earn enough that we can assume they received multiple offers. They are also less in demand than our column 1 contracts, meaning they have a greater incentive to maximize post-tax earnings, as these individuals are far less likely to be superstars. Column 4 shows individuals who made the NBA minimum salary. The coefficient on tax rate does not provide much insight, as these individuals do not have the bargaining power to move to teams they desire. Individuals minimum contract levels increase per year they spend in the league, while also the Salary Cap has expanded ever year in our sample. As players improve statistically, they are rewarded with higher per year contract values. This is shown by our statistically significant coefficient on the log of average salary per year. The very high coefficient illustrates that teams are willing to pay more money for more skilled players. TotalTaxPaid variable represents the luxury tax amount each team has paid over the 5 years of the sample. Recall that luxury tax fines are carried out for teams who have exceeded the salary cap. For this reason, it makes intuitive sense that teams who are willing to exceed the salary cap will receive higher skilled individuals in the free agent market. Despite this intuition, the TotalTaxPaid coefficient does not attain any significance.

8 A shift in cut-off values of contracts from $7.5 million to $10 million returns similar results. 21

Another specification I ran involved differentiating between restricted and unrestricted free agents. Table 3 shows the results of this specification. As I mentioned previously, unrestricted free agents are able to move freely and accept whatever contract value they choose, barring it fits into the financial structure set by the league. Restricted free agents, on the other hand, must accept offers to return to their previous team if it matches any outside offer.

Consistent with the findings above, the coefficient taxrate is again positive but insignificant. As we can see from the results above, wins are significantly positive for unrestricted free agents. A team winning more games in the season 22 prior to free agency will attract far more talented players than teams who performed worse the season prior. Teams who win more are far more in demand by free agents9, which can result in better skilled free agents for the same salary.

Based on all of the results I have compiled, it does not appear as though teams are able to sign higher skilled players in low tax areas. Using winshares as our proxy for NBA free agent skill, I found that the tax rate facing an NBA team would only slightly decrease the level of skill in the free agents they are attracting. NBA teams are too financially constrained through the salary cap.

Despite the constant talk about maximizing post-tax earnings in the media, income tax rates appear to be inconsequential for most of our free agents in the free agent market. There are a variety of reasons for the potential causes. Post-

Tax earnings may not be the deciding factor in the NBA free agent decision process. Individuals may value location and team success far greater than salary. If that were the case, individuals may take less money in order to move to a location that is more desirable. Although I attempted to control for team variables, players’ preferences of team and location are heterogeneous. Players have both coaches and teammates that they may prefer to play with, which again can outweigh any potential income differential resulting from differing marginal income tax rates. Individuals also view winning as a potential -off for compensation instead of a salary bonus. Free Agents often take less money in order to help their teams stay under the salary cap and attract other talent, thus

9 Recall unrestricted free agents can sign with any team, while restricted free agents must resign for original team if the offer is matched. 23

making them more likely to win games and compete for an NBA championship.

As teams get better and more competitive, they become more attractive to free

agents, regardless of how much they are able to pay them. For more

recognizable stars, moving to a bigger market may be more beneficial than

maximizing their contract potential.

Conclusion:

By observing contract level data from 2010 to 2015, I am able to show that

marginal income tax rates do not affect free agent decision making in the NBA.

The extensive use of performance measures in the NBA allow me to control for

free agent skill and player ability, isolating the effects of differing income tax rates

for NBA franchises.

Despite the constant media attention to income tax disparities throughout

NBA free agency, it appears that most of our NBA free agents are not

significantly influenced by marginal income tax rate differentials. Although I do

have a negative result, it appears to impact a small proportion of free agents.

Through our five-year sample, only individuals who signed for contracts in our

middle wage structure showed positive influence from income tax rates.

From a team perspective, franchises considering relocating may be drawn to areas with lower income tax rates. Although we see no evidence from past franchise relocations, it could possibly be a small factor in creating the most competitive franchise. 24

The NBA does not currently view differing income taxes as a competitive advantage, and this research sheds some light on their reasoning. The NBA would be opening up a huge discussion if they chose to address this. One potential idea floating around the league is to create the salary cap based on post-tax figures, but this research shows that the income tax differences do not seem to be affecting competitive balance. An adjustment for tax rates would also open up a whole variety of potential changes, many of which are just as unnecessary. Do teams such as the New York Knicks and the Los Angeles

Lakers really need any more advantages when it comes to attracting talent?

An interesting further research would be the examination of differing salary caps. We have cited the financially constraining nature of the NBA as a reason for why NBA teams may be unable to capitalize on tax rate differentials. There are a variety of salary cap structures throughout major American sports, and a comparative study may give us more insight.

Future research on this subject may look other high-income earners who are highly mobile and taxed in a similar way. Musicians face the same decisions as they tour, so looking for popular cities and frequency may be an interesting future endeavor. On the surface, it does not appear that these labor decisions will mimic those of average workers in America. Workers in boarder areas of states with highly differential income tax rates may be able to capitalize on this.

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