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Technical Review by Ibe Alozie

Assessing the Economic Impact of Sports Facilities on Property Values: A Spatial Hedonic Approach By: Xia Feng and Brad R. Humphreys[1]

I. Research Question

Brad Humphreys, Dennis Coates and many other urban economists have conducted research in the field of sports arenas and urban development. However, most research has focused on identifying and analyzing tangible, economic benefits of sports arenas on cities. Differentiating itself from prior research on the intangible benefits of sports arenas on cities, Xia Feng and Brad Humphreys’ paper proposes a spatial hedonic model that estimates the intangible benefits of two sports facilities in Columbus, Ohio on residential property values.

This discussion of the benefits of sports stadiums stems from the willingness of cities and towns to subsidize construction of expensive sports stadiums. As the rise in the size of these subsidies has coincided with the boom in the construction of new stadiums, urban economists conducted research on the costs and benefits of construction of new stadiums and arenas. Proponents of these subsidies posit income increases, job creation and multiplier effects (due to new spending) as tangible, positive impacts of building new sports stadiums. However, contrary to the aforementioned claims, made mostly by consulting firms (usually hired by the respective sports franchises), the findings from years of economic research have shown no positive impact of building new stadiums on cities. In fact, econometric evidence has shown that professional sports facilities can have little effect to net negative effects on the local economy.

Regardless of these well-respected and well-supported research projects, cities continue to subsidize the construction of sports stadiums. The continuation of this policy decision, which research finds in general to be neither cost-effective for cities nor beneficial to cities, forces consideration of intangible benefits. Few papers have empirically estimated the intangible benefits, such as the increased civic pride, increased city attractiveness or increased cultural benefits, of building sports stadiums. A couple papers have examined the impact of sports facilities on property values with varying results, and this study adds to the literature by providing new evidence based on data from different locations and different sports. Most importantly, this study does not ignore spatial effects. Spatial autocorrelation is the correlation among values of a single variable due to their close locational positions on a two-dimensional (2-D) surface. Spatial autocorrelation could have caused biased estimates and model misspecification in the few earlier models on the subject of stadium presence’s impact on housing prices

II. Theoretical Background

Because of the difficulty of measuring “intangible benefits or costs”, Feng and Humphreys assume that the presence of a stadium would be viewed as an intangible characteristic and the presence of a sports stadium would be capitalized in housing prices. Housing prices tend to be spatially correlated due to common neighborhood characteristics.

Feng and Humphreys use an adaptation of the spatial lag hedonic model:

(I − ρW y) −1 = I + ρW + ρ 2W2 + . . .

This model links each observation of the dependent variable to all observations of the explanatory variables through a spatial multiplier.

Using transactions data, containing observations on 9,504 single-family housing units, for the year 2000, Feng and Humphreys analyze the values of residential housing around Nationwide Arena and Crew Stadium in Columbus. The data set includes housing and neighborhood characteristics such as lot size, school quality, environmental quality and number of fireplaces.

To account for aspects of the model that were not incorporated into the adapted spatial lag hedonic model, certain modifications were made to the model. To account for the presence of Ohio Stadium, dummy variables were created. To control for the effects of businesses on housing values, Feng and Humphreys controlled for the number of commercial establishments in each zip code, which allowed the business-related variables to capture some of the effects of business location on residential property values.

III. Empirical Model

Known as a spatial weighting matrix, this symmetric matrix is used to define the locations for which the values of the random variables are correlated, and the rows in the weights matrix are standardized. The features of both housing markets and individual housing data make the definition of the spatial weights matrix W especially important. The aforementioned matrices specify “neighborhood sets”, and these neighborhood sets capture spatial interaction. Feng and Humphreys use GeoDa to specify the neighborhoods and to define the spatial weights matrix, and begin by using four different spatial weights to create the matrices. Next, Feng and Humphreys use the log-log form of the hedonic housing price with the appropriate spatial lags to best estimate the parameters.

IV. Results and Discussion

The results of the research of Feng and Humphreys suggest that the presence of sports facilities in Columbus have a significant positive distance-decaying effect on surrounding house values. For Nationwide Arena, at the average, all else equal, for each 1% decrease in the distance to the arena is associated with a 0.175% increase in the price of the average house. In dollar terms, a 1% decrease in distance from each house to the arena, on average, increases the price of an average house by $222. The primary variable used to evaluate the effects of sports facilities on surrounding housing values is the distance between each house and the sports facility, and analysis of this parameter shows that the presence of sports facilities has positive effects (though they diminish with distance) on housing values. Importantly, Feng and Humphreys also show that prior OLS models, which did not account for spatial autocorrelation, overestimated the distance parameters, and did not correct for heteroskedasticity when present.

V. Extensions

This paper elevated the credibility of the larger economic argument by finding the general importance of factoring spatial autocorrelation into property value modeling.   With regard to policy decisions, professional sports facilities generate intangible benefits in the local economy, and cities do have a rational economic argument to lodge in support of provision of subsidies to sports stadiums. While the costs of public support rarely exceed the cost of public funding for the stadiums directly, the subsequent rise in property values can set the foundation for more substantial growth in adjacent areas, and give the city’s business community the confidence necessary to invest. Feng and Humphreys offered a more precise method of analyzing costs and benefits, and show that there are positive effects (contrary to most research) of building sports facilities at least in this one example. This paper offers answers, and poses new questions. What other benefits can be discovered? How close can economists make it to quantifying the efficient subsidy level for stadiums and arenas?


[1] Humphreys, Brad & Feng, Xia. “Assessing the Economic Impact of Sports Facilities on Property Values: A Spatial Hedonic Approach.” LASE/NAASE Working Paper Series 8.12 (2008): 1-20. Web. 25 March 2015.


  1. As a big sports fan, I find this to be a very interesting topic that I have never given much thought to. Some examples of the economic cost of stadium building that are immediately relevant include the movement of the Atlanta Braves stadium in my home state. Renovations and metro city congestion have contributed to reasons for moving the home stadium to a more suburban area. I think it’s noteworthy that many large stadiums for professional teams of a big city actually are located well outside the downtown area, usually in a more open and less populous location. The size and traffic of people associated with a large sports venue provide reasons for situating these buildings in a smaller community outside of the city.

    Whether or not these venues are a benefit or a detriment to the city it is in depends highly on the type of stadium and the location. I know that many times, Olympic hosts have to scramble to establish sports facilities in a short amount of time and thus expend exorbitant amounts of money funding these less than ideally planned out structures. Once the games are finished, these buildings must then be converted into something useful. For example, the 2008 Summer Olympics in Beijing cost the Chinese economy a large sum of capital that really can never be fully recuperated. Although the giant bird nest stadium is iconic, it is not spatially efficient and eats up a vast space in an extremely densely populated city.

    Although the paper cited in this technical presentation finds that the two stadiums in Columbus are associated with higher house values, it doesn’t say enough to justify the cost of these buildings. In some ways, the residents who bear the cost of constructing and maintaining these sports facilities are investing into the value of their own properties, but I feel that this effect has the possibility of wearing off over time. When the buildings are fairly new, perhaps there is the intangible effect of excitement and novelty that enhances the surrounding real estate. But over time as the construction ages, and requires renovation, and quite possibly may even eventually close down, these buildings may have the opposite effect and actually lower the value of real estate nearby. I like this topic and this presentation, but it would be nice to see the results of some similar studies. It’s so difficult to assess the real value of these facilities with one isolated example; more empirical research involving more locations would be the start to understanding the true effects of sports facilities on surrounding property values.

  2. Ibe,

    This was a very interesting writeup, and I was surprised by both the results of the background studies and the conflicting result that this study found. It’s unfortunate that so many cities have continued to fund sports stadiums even though early studies had found no positive economic impact. On a general level, I would definitely think that stadiums would provide some sort of benefits in terms of jobs and local spending, but I suppose the consulting firms hired to support these projects would overstate the actual quantifiable impact. It’s interesting that this study then found the opposite, that there were positive effects for at least some economic aspect.

    I wonder how these effects translate to stadiums in other cities for other sports. The NHL and MLS are not the most popular leagues and it’d be interesting to see the effects for NFL stadiums in particular. A huge number of people travel to NFL stadiums and tailgate before the games, and there should be a lot of economic activity associated with these games. Also, I wonder how this effect changes with distance — you mention that the effect diminishes, but what at what distance from the stadium does this effect stop being significant? If somebody lives ten miles from a proposed stadium, would they see an increase in home price and should they support the stadium construction?

  3. It was really interesting to see how sports could relate to real estate market. I would expect that large stadiums for professional sports would definitely have positive economic effect on its neighborhoods due to increasing traffic. I must say the results of both previous studies and the one by Humphreys and Coates were surprising. However, I think it would have been useful to include or list suspected pros and cons of building stadiums. Also, I did not quite understand the reasons why previous studies focused only on intangible effects. I am curious to find out the reasons and methods that the researchers used to measure the degree of Intangible effects, such as increased city pride, increased city attractiveness, and increased cultural benefits.

    The study in this technical presentation concludes that the presence of sports facilities have a significant effect on surrounding house values. Although it is clear that closer proximity to the stadium increases the housing price, it is difficult to conclude that the net economic effect of building stadiums is actually positive. Surely, the presence of the stadium increases the housing price, which may have positive economics repercussions. However, the cost of building stadiums is generally very high, which implies that it may require a very long period of time for positive economic effects to overcome the cost of building stadiums.

  4. Interesting topic for the paper. It’s definitely something I’ve thought about and seen back in Washington on both the east and west sides of the state. In the Seattle area, the Sounders and Seahawks are a huge deal and every match draws between 45-65 thousand people. Due to this, traffic is always horrendous and getting to the game becomes a challenge, so people with closer properties suddenly become everybody’s best friend. The convenience factor is a big impact for obvious reasons.

    As other people have commented, it would be interesting to see how this translates to other sports since smaller ones have less draw, and how this compares to college sports since places like Michigan’s Big House draws almost 110,000 people per football game. In addition to the comparison between sports, looking at housing price vs. commercial/bar prices would also be interesting. The downtown Seattle area by the stadiums has become a thriving bar scene with the rise in popularity of the sports teams, so I’m sure looking at their profits vs how much they have to pay for the location could also help show positive economic impact of stadiums.

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