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Article Excerpt
We extend the literature on the impact of externalities using an approach based on a hybrid of hedonic and repeat-sales methods. The externality in question is groundwater contamination in Scottsdale, Arizona. The use of condominium sales allows us to assume that major physical characteristics remain unchanged, but location parameters may be altered by urban growth and development as well as contamination. We find an economically significant discount for properties located in the contaminated area. Interestingly, it does not appear until several years after the contamination becomes publicly known, and it seems to have disappeared before the end of the study period.
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The last three decades have seen the emergence of a voluminous literature examining the interaction between environmental factors and real estate markets, much of it concerning the extent to which negative environmental spillovers are capitalized into real estate values. These interests have given rise to two broad categories of real estate literature reviewed in Jackson (2001). The first of these is dominated by the appraisal profession and has focused on valuation concepts and methods (see, e.g., Chalmers and Jackson 1996, Jackson 1997, Weber 1997, Kinnard and Worzala 1999). The second category reports the results of empirical studies for the effects of environmental spillovers on real estate prices, especially in residential markets. The forms of environmental spillovers considered relate to land, water and air (Segerson 2001) and have included proximity to landfill sites (McClelland, Shulze and Hurd 1990, Kohlhase 1991, Thayer, Albers and Rahmatian 1992) as well as the presence of overhead power lines (Colwell 1990), air pollution (Graves et al. 1988), water quality (Leggett and Boekstael 2000), noise pollution (Pennington, Topham and Ward 1990) and groundwater contamination (Kiel 1995, Kiel and McClain 1996).
There are three general scenarios to describe the response of real estate prices to an environmental spillover. In the most straightforward, the presence (or severity) of an environmental problem is associated simply with the constant presence (or severity) of a price discount on properties affected by that problem. For example, properties affected by environmental contamination could be priced at a discount (perhaps equal to a constant percentage of value) relative to unaffected properties, or the discount could be a linear function of the severity of the contamination affecting that property. As the discount is related only to the presence (or severity) of contamination, it remains constant until the contamination is mitigated (wholly or to some degree).
The presence or severity of contamination, though, can be considered a (negative) hedonic attribute of the property just like any other, and therefore the implicit market price associated with contamination may change over time just as it does for other hedonic attributes. In the second scenario, then, the presence (or severity) of the environmental occurrence is associated with a price discount on affected properties, but the magnitude of the discount evolves in the same way that implicit marginal prices on other hedonic attributes evolve. For example, if the implicit discount associated with environmental contamination is elastic with respect to wealth, then the magnitude of the discount can be expected to grow over time as wealth increases (controlling for any mitigation). Alternatively, if information about environmental contamination dissipates through time then the discount may itself dissipate even if the presence and severity of contamination do not.
Neither of these scenarios, however, takes into account the dynamic response of housing consumers to an occurrence such as environmental contamination. Consumers who attach a relatively high premium to environmental factors can be expected to bid (or ask) relatively high prices for properties with favorable environmental attributes, and to bid (or ask) relatively low prices for those with environmental problems. Therefore, these environmentally sensitive consumers will tend to outbid less sensitive consumers for properties with favorable environmental attributes, and will tend to be outbid by less sensitive consumers for properties with environmental problems. In response to the sudden occurrence (or recognition) of an environmental problem, the outcome of such a market adjustment or "sorting" process is likely to be this: the households that are most sensitive to the occurrence will offer their properties at the greatest discount in order to leave immediately; they will be replaced by households with the least sensitivity to the occurrence; this process will be repeated at successively smaller magnitudes for successively less sensitive sellers and more sensitive buyers; and thus the initial discount will decline steadily in magnitude, even in the absence of any mitigation of the environmental contamination. Of particular interest in this article is the application of house price modeling to assess whether transaction prices reveal the effects of such a sorting process, and if so how long the adjustment process seems to take.
In a recent review article, Boyle and Kiel (2001) examine more than 30 papers that use hedonic approaches to test the effects of environmental externalities on house prices. They note that a common problem is that the tests are often conducted over short periods and as a consequence are generally unable to effectively capture changes in price over time. The main problem that Boyle and Kiel identified is the absence of data from before and after an environmental event, which means that not even the immediate effect of the event on prices can be adequately identified. (A solution to this problem is found in Colwell, Dehring and Lash (2000).) Boyle and Kiel also, however, note a common inability to detect any change in the contamination effects after the initial contamination event--that is, the studies they examined tended to focus on the first and most straightforward scenario without considering any evolution of the price effect over time.
Although interest in the persistence of contamination effects and their longer-term impact on property values is not new (Riechert 1999), these effects have been difficult to determine in hedonic studies, so previous studies provide conflicting evidence of the temporal effects of contamination and remediation (see Kiel 1995 versus Kohlhase 1991 and Kiel and McClain 1996). Some researchers (Mieszkowski and Saper 1978, Hite et al. 2001) have tried to use control areas to infer what would have happened had the externality not occurred. The success of this approach is, of course, dependent on the researcher's ability to limit the differences in inter alia market conditions and neighborhood quality between the control and study areas or to accommodate the differences by including sufficient spatial variables. Dale et al. (1999) attempted a variant of the control area approach by examining various neighborhoods and found that after a cleanup house prices recover more slowly for dwellings in closest proximity to the negative externality.
In contexts other than contamination, real estate analysts have used repeat-sales regression analysis to examine temporal change in property values. Hedonic analysis is superior to repeat-sale analysis when there are few repeat sales, but repeat-sales analysis may be superior to hedonic analysis for this purpose when there are sufficient repeat sales, when data on some of the key property attributes are unavailable and when the analyst can be confident that those attributes will not have changed over time. Changing values for property attributes or model parameters can be modeled within a hedonic price model, but early applications of the repeat-sales model used simple versions that lacked this capability. A notable exception was Palmquist (1982), which incorporated changing values of an indicator of environmental quality (noise pollution), but subsequent studies failed to build on this observation. Shiller (1993), however, showed how changes in measured attributes or in parameter values could be incorporated more generally into the repeat-sales model, thereby removing a key advantage of the hedonic price model.
In this article, we employ the hybrid repeat-sale/hedonic approach suggested by Palmquist (1982) and Shiller (1993) to investigate the effect of environmental contamination in a particularly rewarding situation. In this application the timing of the first perception of contamination is well known while changes in unmeasured attributes are likely to be minimal, which means that observed changes in prices can be reliably decomposed into those attributable to contamination and those attributable to changing marginal prices in the market. Moreover, our data collection period is quite long, especially after the contamination was recognized, which enables us to investigate whether the price effect of the initial contamination persists, grows or dissipates over time.
The remainder of the article is divided into four major sections. The next section introduces the hybridization of hedonic and repeat-sale models. The third section discusses the data and the specific models to be estimated, while the fourth section discusses the empirical results. Our findings are summarized in the concluding section.
Hedonic and Repeat-Sale Models
Hedonic house price studies have been employed for nearly four decades to assess the impact of negative externalities such as air pollution (Ridker and Henning 1968). The hedonic method has subsequently yielded a vast applied literature, the basic premise of which is that by estimating the implicit price of each of the physical and locational attributes associated with a property it is possible to isolate the impact of environmental events on the price surface. In this context, estimates of the price surface from the period before and after the event are essential. For example, if the producers of negative externalities select sites in less desirable neighborhoods to reduce costs, then without before-and-after data lower prices might be interpreted as evidence of negative externalities while they may reflect only preexisting market conditions. As we note above, however, often the paucity of data imposes a constraint on before-and-after analysis.
Analysts tend to use repeat-sale analysis to estimate price indices when they do not have sufficient attribute data to use hedonic analysis for this purpose, but there are several dimensions to the downside of using repeat-sale analysis. First, data on assets that sold only once during the study period are ignored. Second, several empirical studies (Mark and Goldberg 1984 and Case, Pollakowski and Wachter 1991) have concluded that repeat sales understate house price inflation by failing to account for aging and depreciation between...
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