The use of tax money for construction and renovation of ...



Abstract

The use of tax money for construction and renovation of stadiums are sold as "economic development engines" for communities. Evidence shows little relationship between the presence of professional sports teams and real economic growth—and what relationship it does show is negative. “According to the National Taxpayers Union Foundation, a decade's worth of professional sports stadium construction has left federal, state, and local taxpayers $7.5 billion poorer, and the tab could double if 15 additional projects on the drawing board are built” ().

The United States have experienced an incredible surge in the number of new professional sports stadiums that have been built in recent years. New areanas are completed each year as cities have attempted to lure and retain sports franchises as a means to economic development and revitalization.

This paper examines the association between professional sports stadiums venues and real per capita person income in (number of cities) Standard Metropolitan Statistical Areas in the United States between the period of 1990 to 2000. Our empirical data accounts shows that sports stadiums do not have a positive effect on the real per capita person income for the time period of 1990 to 2000.

Public Policy

The public financing of large public facilities has always been a challenge. Several questions have to debated before a municipality determines to finance the project. Is it an appropriate use of public funds? What are the economic benefits that a sports facility may bring to a community? Will it be worth the cost? Are the intangible benefits that a sports facility may bring in to a community worth the expense? Are professional sports venues the economic engine that they claim to be? Do they really raise the per capita individual income level?

As public policy administrators we struggle with issue of using public funds to build a sports facility. Advocates for new sports facilities often stress the benefits that a new sports facility may bring. Opponents frequently point ourt that many economic impact studies on the topic have found that the benefits may not be substantial.

The use of public funds to finance public sports venues is not a new thing. According to Historian W. G. Hardy, “1,500 years ago Rome fell under the crushing burden of its welfare state, which included government-subsidized entertainment in the form of gladiator duels and other "games." “He estimates that Rome spent the equivalent of $100 million annually to support public entertainment. What is new about modern games is the size and number of deals featuring a marriage of tax dollars and politicians promising “jobs” ()."

Are professional sports venues the economic engine that they claim to be? Do they really raise the per capita individual income level?

Economic Engine

There is a hefty price tage for having a professional sports team in a community. The stadium costs are paid by taxpayers. Owners and players seldom live in the towns were they play. The playing season is short lived and it brings people into the area for a few hours. Cities interested in revitalizing their downtowns may consider reinvesting in infrastructures and services. They may consider economic development through good planning and business development. Professional sports franchises are not a cure for economic development.

According to The Heartland Institute, there are many reasons why professional sports stadiums fail to produce net economic benefits for host communites: opportunity costs, shifting current spending, and subsidies.

□ Opportunity costs

Opportunity cost principle refers to decisions that must be made when deciding to produce a certain good. Because resources are scarce, trade-offs must be made to choose the best resource at the expense of other products. The Heartland Institute states that “the true cost of using a resource is the value of the next hightest-valued alternative use of that resource, or its “opportunity cost.” The alternative to investing in a stadium or sports franchise include a new park, and industrial park or community college, or money to hire more police, firefighters, or theachers. In many cases, those alternative uses would produce more value than a new professional sports stadium.”

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□ Shifting current spending

“Most of the money spent at a sports stadium or arena would have been spent anyway at some other entertainment venue, such as a local theater, bowling alley, night club, or health club. Because they play so frequently, base ball and bsketball teamsrarely attract a significant portion of their audience from outside the metroplitian area. Football games attract fans from greater distances, but football teams host just eight regular season home games a year. ”

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□ Subsidies leave the community

“Much of a stadium’s subsidy goes directly into the pockets of team owners by raising the re-sale value of their teams. This money is unlikely to be reinvested in the community. Players seldom live for extended periods of time in the communities in which they work, and when they leave, their savings and spending go with them.”

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Intangible Benefits

Baseball and football professional sports are our national past time sports and considered part of our American heritage. How can you put a price tag on emotional appeal. Many cities measure their success on the number of major sports venues they offer. Having a professional sports team in a city provides fans something to talk about and enjoy both at home and work. It’s a source of wholesome and “good for you” family fun and entertainment. There is a certain amount of pride that’s associated with having a hometown team. The sense of pride and identity that may come from hosting a professional sports team is a costly benefit. These intangible benefits must be weighed against similar benefits that would have been created if the money were spent on something else. New schools, better police protection, or the reinvesting in downtown business districts and communities would have a similar positive effect on the city’s image and its residents’ self-esteem.

Theoretical Background

Professional sports teams are a business. Part of the array of duties for modern civic managers is the management and encouragement of businesses in their jurisdiction. Publicly subsidized stadia have been often criticized as not generating an economic return.[i] In an article published in the journal Regulation , dennis Coates and Brad R. Humphreys state “According to public finance theory, the decisionmakers who attempt to attract a new franchise or build a new stadium or arena mus tvalue the total consumption benefits, including all nonpecuniary benefits., more than the total costs, including the opportunity costs. The total consumption benefits cannot be directly measured because of the nonpecuniary component of those benefits; in order for these policies to make sense, the total value of the consumption benefits associated with these policies must be larger than was previously imagined.”[1]

Data Discussion

We decided to look at factors that reflected aspects of the quality of life and the economic well being of the citizens of a town. The United States Census collects information on communites of a range of sizes. We chose the Metropolitan Statistical Area as our level of examination, as it would include the regional effects of a sports team. Professional sports claim to have effect outside the boundaries of their home metropolitan region, as witnessed by the names of teams such as the Arizona Cardinals, the Florida Marlins and Texas Rangers.

"You can observe a lot by watching." --Yogi Berra

Looking at the 280 Metropolitan Statistical Areas (MSA) in the United States, and the distribution of teams, we found that teams were predominantly housed in MSA’s with greater than a million people in their populations. We wanted to include factors that reflected economic well being as well as harder to measure quality of life issues. Many measures of quality of life done by communities today factor in several elements [ii] to come up with some sort of an index. This has not been done on a nationwide basis that we were able to find.

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Figure 1

Figure one shows the distribution of teams across United States MSA’s, showing how the teams are grouped in the more populous areas. The one outlyer is Green Bay, Wisconsin.

For the metropolitan areas we looked at, the maximum number of teams in one metropolitan area was four.

Economic indicators include the percent of the population below the national poverty level (Percent Pov), the per capita income for residents of the MSA (Percap Income), the percent of households paying greater than 30% of their income on rent (PercGr30ofInc) and the annual rate of unemployment for that MSA for 2000 (AnnRateUnEmp2000).

The factors we we used to indicate or reflect the quality of life in an MSA were the percent of females over 25 with a degree beyond high school (PercFem25olABMPD), the percent of residents who work at home (PercWkHome), the length of the commute to work for those who work outside of the home (Up to 30 minute commute – PercCommUpTo30min, and percent commuting greater than 90 minutes – PercCommOvr90min). For a total of 51 MSA’s we were able to obtain homicide statistics. This sample includes all but three of the 26 MSA’s with professional sports teams. Figure 2 shows the descriptive statistics for our factors.

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Figure 2

Factor Analysis

Correlation Matrix(a)

a This matrix is not positive definite.

Communalities

| |Initial |Extraction |

|Popn2K |1.000 |.845 |

|CntSprt |1.000 |.848 |

|CntStad |1.000 |.848 |

|PercFem25olABMPD |1.000 |.749 |

|PercapIncome |1.000 |.826 |

|PercentPov |1.000 |.782 |

|PercWkHome |1.000 |.598 |

|PercCommUpTo30min |1.000 |.566 |

|PercCommOvr90min |1.000 |.502 |

|PercGr30ofInc |1.000 |.761 |

|Mrdr99 |1.000 |.761 |

|AnnRateUnEmp2000 |1.000 |.670 |

Extraction Method: Principal Component Analysis.

Total Variance Explained

|Component |Initial Eigenvalues |Extraction Sums of Squared Loadings|Rotation Sums of Squared Loadings |

| |Total |

| |1 |2 |3 |

|CntSprt |.895 |.203 |-.081 |

|CntStad |.895 |.203 |-.081 |

|Popn2K |.878 |.271 |-.009 |

|Mrdr99 |.827 |.275 |-.039 |

|PercapIncome |.642 |-.625 |-.152 |

|PercCommUpTo30min |-.633 |-.406 |-.017 |

|AnnRateUnEmp2000 |-.261 |.726 |.274 |

|PercentPov |-.307 |.692 |.457 |

|PercCommOvr90min |.212 |.643 |.211 |

|PercFem25olABMPD |.399 |-.634 |.434 |

|PercWkHome |.248 |-.533 |.502 |

|PercGr30ofInc |.170 |-.196 |.833 |

Extraction Method: Principal Component Analysis.

a 3 components extracted.

Rotated Component Matrix(a)

| |Component |

| |1 |2 |3 |

|Popn2K |.915 |-.033 |.081 |

|CntSprt |.910 |-.130 |.052 |

|CntStad |.910 |-.130 |.052 |

|Mrdr99 |.871 |-.031 |.041 |

|PercCommUpTo30min |-.735 |-.160 |.015 |

|PercentPov |-.063 |.882 |.018 |

|AnnRateUnEmp2000 |.004 |.806 |-.145 |

|PercapIncome |.379 |-.771 |.296 |

|PercCommOvr90min |.417 |.571 |-.051 |

|PercGr30ofInc |.029 |.204 |.848 |

|PercFem25olABMPD |.110 |-.418 |.750 |

|PercWkHome |.002 |-.259 |.728 |

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

a Rotation converged in 4 iterations.

Component Transformation Matrix

|Component |1 |2 |3 |

|1 |.929 |-.286 |.237 |

|2 |.365 |.820 |-.441 |

|3 |-.068 |.496 |.866 |

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

Component Score Coefficient Matrix

| |Component |

| |1 |2 |3 |

|Popn2K |.223 |.015 |.002 |

|CntSprt |.221 |-.029 |-.028 |

|CntStad |.221 |-.029 |-.028 |

|PercFem25olABMPD |-.013 |-.060 |.368 |

|PercapIncome |.067 |-.267 |.042 |

|PercentPov |.000 |.365 |.143 |

|PercWkHome |-.036 |.000 |.383 |

|PercCommUpTo30min |-.186 |-.077 |.017 |

|PercCommOvr90min |.116 |.236 |.036 |

|PercGr30ofInc |-.026 |.209 |.519 |

|Mrdr99 |.214 |.009 |-.019 |

|AnnRateUnEmp2000 |.022 |.311 |.034 |

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Component Scores.

Component Score Covariance Matrix

|Component |1 |2 |3 |

|1 |1.000 |.000 |.000 |

|2 |.000 |1.000 |.000 |

|3 |.000 |.000 |1.000 |

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Component Scores.

Conclusion

It can be argued that cultural and economic elites have controlled and continue to control important decision making process in the decision to construct new stadium sports facilities.

Edward I. Sidlow and Beth M. Henschen, “Building Balparks: The Public-Policy Dimensions of Keeping the Game in Town”, in The Economics and Politics of Sports Facilities, Edited by Wilbur C. Rich (Quorum Books, Westport, CT) 2000

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[1] Page 20, Dennis Coates and Brad R Humphreys, Regulation, Volulme 23, No. 2, 2000

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[i] Numerous citations to follow in Roger G. Noll and Andrew Zimbalist, Editors Sports, Jobs and Taxes The Economic Impact of Sports Teams and Stadiums (Brookings Institution Press, Washington D.C.) 1997.

[ii] Five Shoes Waiting

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