Selling the game: estimating the economic impact of professional sports through taxable sales.

Even including only out-of-region visitors in impact studies may still result in inflated estimates if a large portion of the non-local fans at a game are "casual visitors," that is, out-oftown guests who go to a sporting event but are visiting the host city for reasons other than the sporting event itself. For example, a college professor at an academic conference may buy a ticket to a local game, and therefore the ticket would be counted as a direct economic impact of the sports contest. The professor, however, would have come to the city and spent money on hotels and restaurants in the absence of the sporting match, and again, the money spent at the game substitutes for money that would have been spent elsewhere in the local economy.

Similarly, ex ante estimates may be biased upwards if event guests engage in "time-switching," which occurs when a traveler rearranges a planned visit to a city to coincide with a mega-event. One example of time-switching is someone who has always wanted to visit Hawaii who plans a trip during the NFL's Pro-Bowl. While the Pro-Bowl did influence the tourist's decision about when to come, it did not affect the decision whether to come. Therefore, total tourism spending in Hawaii is unchanged; the Pro-Bowl simply affects the timing of such spending.

Accounting for the substitution effect is likely to result in large reductions in the estimated economic impact of regular season games. In the case of mega-events, however, the substitution effect may be much smaller. Since these premier events are thought to attract large audiences from outside the local economy, many of whom come specifically for the event, the amount of spending that is new to the economy is thought to be quite a large proportion of the total amount of spending, whereas 5-20% of fans at a typical MLB game are visitors from outside the local metropolitan area, the percentage of visitors at an event like an All-Star Game or the Super Bowl is thought to be much higher (Siegfried and Zimbalist 2000).

A second source of bias is "crowding out," which results from the congestion caused by a game that dissuades local citizens from venturing near the playing venue during the game and thereby reduces economic activity. Attractions such as Chicago's Field Museum or Cleveland's Rock and Roll Hall of Fame are located next door to NFL stadiums, and their attendance suffers during the Chicago Bears or Cleveland Browns home games. Similarly, mega-events may dissuade regular recreational and business visitors from coming to a city during that time. While a city's hotels may be full of sports fans during the Super Bowl, if the city's hotels are generally full of vacationers or conventioneers anyway, the Super Bowl simply displaces other economic activity that would have occurred. High prices charged by hotels and other businesses in the hospitality industry also tend to dissuade casual visitors during mega-events. In other words, the economic impact of a mega-event may be large in a gross sense, but the net impact may be small. Scores of examples of this phenomenon exist. As a case in point, during the 2002 World Cup in South Korea, the number of European visitors to the country was higher than normal, but this increase was offset by a similar-sized decrease in the number of regular tourists and business travelers from Japan who avoided South Korea as a result of World Cup hassles. The total number of foreign visitors to South Korea during the World Cup in 2002 was estimated at 460,000, a figure identical to the number of foreign visitors during the same period in the previous year (Golovnina 2002).

A third source of bias comes from leakages. While money may be spent in local economies during sporting events, this spending may not wind up in the pockets of local residents. The taxes used to subsidize these events, however, are paid for by local taxpayers. The income multiplier for sporting events is likely to be much lower than for general expenditures as a result of the specialized nature of the service provided. In the NBA, for example, only 29% of players live in the metropolitan area in which their team plays (Siegfried and Zimbalist 2002).

Leakages during mega-events may also be quite high. The economic multipliers used in ex ante analyses are calculated using complex input-output tables for specific industries grounded in inter-industry relationships within regions based on an economic area's normal production patterns. During mega-events, however, the economy within a region may be anything but normal, and, therefore, these same inter-industry relationships may not hold. Since there is no reason to believe the usual economic multipliers apply during mega-events, any economic analyses based on these multipliers may, therefore, be highly inaccurate.

In fact, there is substantial reason to believe that during mega-events, these multipliers are highly overstated, which overestimates the true impact of these events on the local economy. Hotels, for example, routinely raise their prices during mega-events to three or four times their normal rates. The wages paid to a hotel's workers, however, remain unchanged, and, indeed, workers may be simply expected to work harder during times of high demand without any additional monetary compensation. As a hotel's revenue increases without a corresponding increase in costs, the return to capital (as a percentage of revenues) rises, while the return to labor falls. Capital income is far less likely than labor income to stay within the area in which it is earned, and, therefore, one might expect a fall in the multiplier effect during mega-events as a result of these increased leakages (Matheson 2004).

While ex ante estimates often do a credible job of determining the economic activity that occurs as a result of a sports team or mega-event, and although they may also address the issue of the substitution effect by excluding spending by local residents, they generally do a poor job of accounting for crowding-out, and they almost never acknowledge the problems associated with the application of incorrect multipliers. For these reasons, numerous studies have looked back at the actual performance of economies that have had professional franchises, built new playing facilities, and hosted mega-events and have compared the observed economic performance of host cities to that predicted in ex ante studies. These ex post analyses of stadiums and franchises, including those of Rosentraub (1994), Baade (1996), Coates and Humphreys (1999, 2003), and Siegfried and Zimbalist (2000), to name just a few, generally find little or no economic benefits from professional sports teams or new playing facilities.

In the area of mega-events, Baade and Matheson (2001) examine the MLB's All-Star Game and find that employment growth in host cities between 1973 and 1997 was 0.38% lower than expected, compared to other cities. A similar examination of the 1996 Summer Olympics in Atlanta, Georgia, found employment growth of between 3500 and 42,000 jobs, a fraction of the 77,000 new jobs claimed in ex ante studies (Baade and Matheson 2002). An examination of metropolitan area-wide personal income during 30 NCAA Men's Final Four basketball tournaments found that, on average, personal incomes were lower in host cities during tournament years (Baade and Matheson 2004a). A similar study of the 1994 World Cup in the United States found that personal income in host cities was $4 billion lower than predicted, a direct contradiction to ex ante estimates of a $4 billion windfall (Baade and Matheson 2004b). Coates and Humphreys (2002) examined the effect of post-season play in all four major U.S. sports on per capita personal incomes and found in all cases that hosting playoff games had a statistically insignificant impact on per capita incomes.

The remainder of this paper adds to the already-substantial body of work regarding ex post analyses of franchises, stadiums, and sporting events by using taxable sales data to estimate the effect of professional sports on local economies. In addition, this paper examines labor disputes, which serve as natural experiments for determining the economic impact of professional sports on host communities. If franchises do indeed provide large positive impacts on local economies, then their sudden absence as a result of work stoppages should result in observable negative effects on the city. Several previous studies examine the impact of sports on local metropolitan areas using strikes and lockouts as test cases. Zipp (1996) examines the effect of the 1994 MLB strike on 17 metropolitan statistical areas (MSAs), and he later extends his work to cover the effect of this strike on spring training venues in Florida (Zipp 1997). Baade and Matheson (2005) examine the 1981 and 1994/95 MLB baseball strikes, using personal income data, to arrive at an average net annual economic impact of a MLB team on a host city of between $16.2 million and $132.3 million, or between 5% and 50% of the figure generally suggested by baseball's boosters. Coates and Humphreys (2001) present the most comprehensive analysis of the economic consequences of sports strikes and lockouts. Their analysis of real per capita personal income finds no statistically significant effects from the strikes in MLB in 1972, 1981, and 1994/95 and strikes in the NFL in 1982 and 1987.