Abstract:
Hedonic property value studies of water quality conventionally focus on water quality levels measured nearest a home. This study examines whether water quality at the nearest access point (i.e., a beach) matters more to local residents. Megan Kung, Dennis Guignet and Patrick Walsh conduct a hedonic analysis of water quality in the Long Island Sound, where an aging infrastructure and heavy precipitation lead to frequent sewage overflows. The analysis focuses on bacteria contamination and beach closures at various access points and monitoring sites. Results suggest that decreases in water quality measured at the nearest beach yield a larger negative effect and impact homes at a farther spatial extent than previously suggested in the literature.
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Model 1 has two variants (SAC and FE) which follow the conventional approach in the literature and link homes to the water quality measures at the closest monitoring site. The SAC is a general spatial model, which includes a spatiotemporal lag of neighboring house prices as a means to account for spatially correlated omitted variables and FE is a municipality-by-year fixed-effects model. The SAC 1 results suggest homes within 500 meters (m.) of the Sound are affected the most, experiencing an average decrease in price of 0.16% for a 10% increase in enterococci. For the homes in this distance bin, which have an average price of $1,001,651, this translates to an average decrease in home value of $1,583. A similar elasticity is estimated for the 500–1,000 m bin. Any negative elasticity estimates beyond 1,000 m are statistically insignificant. The estimated price effects are small relative to the overall price of a home, but are in line with previous estimates. The corresponding FE 1 model suggests a negative, but small and statistically insignificant, elasticity in the nearest-distance bin. The –0.0127 elasticity in the 500–1,000 m bin is similar to that of the SAC 1 model, but the two models differ in that the FE 1 model suggests possible negative elasticities as far as 2,000 m.
Cladophora, a wiry green seaweed, is found in great abundance in Little Narragansett Bay, fertilized by a high load of nitrogen entering the bay. Dense mats of the seaweed are oxygen factories during the day, but use up all of the oxygen during the night, leaving none for the animals. Only animals tolerant of very low oxygen, ones who can essentially hold their breath through the night, are found in areas where this seaweed is thick. In mid-summer, the seaweed is so abundant and productive, excess oxygen bubbles out of the water and can cause large mats of the seaweed to float to the surface. Credit: Jamie Vaudrey, UConn
https://phys.org/news/2017-02-unveils-tool-cleaner-island.htmlIn SAC and FE Models 2 and 3, the authors deviate from the conventional approach of matching to the nearest monitoring site, and instead explicitly account for water quality at the nearest beach. In doing so, they see that any previously negative coefficients corresponding to water quality at the portion of the waterbody nearest the home are now statistically insignificant.
In Model 2 when they consider water quality at the closest beach (conditional on water quality measured nearest the home), there is a strong negative effect that is larger in magnitude and spatial extent. SAC 2 shows that among homes nearest a beach (0–500 m bin), a 10% increase in enterococci decreases house prices by 0.31%. These homes have an average price of $1,259,349, and so this translates to an average implicit price of $3,904. This result is virtually identical in the FE variant of Model 2. Results suggest that the negative elasticity associated with water quality at the nearest beach could extend to 3,500 m. For homes in the farthest significant distance bin in SAC 2 (3,000–3,500 m, which have an average price of $844,851), the mean implicit price for a 10% increase in enterococci levels at the nearest beach is a decrease of $1,369. The FE 2 model suggests that this effect is even larger; the estimated –0.0531 elasticity for the 3,000–3,500 m bin suggests an average implicit price of $4,486. The statistically significant effects of beach enterococci levels are not consistently found in all distance bins out to 3,500 m.
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In a meta-analysis of hedonic property value studies examining water quality, Guignet et al. (2020) report a mean elasticity with respect to fecal coliform counts of –0.018 and –0.020 for waterfront and non-waterfront homes within 500 m, respectively. These are quite similar to our estimated elasticities with respect to enterococci counts.
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In the SAC 3 and FE 3 models, they account for the number of beach closure days in summer. The results suggest that home buyers and sellers do, on average, respond more to beach closures than to enterococci levels. The estimated price effects of beach closures are of the expected negative sign, with robust and statistically significant negative effects in all distance bins out to 2,000 m from the beach. With the exception of the 2,000–2,500 m bin, we find significant negative effects extending out to 3,500 and even 4,500min models SAC 3 and FE 3, respectively. In general, the estimated beach closures effect in the SAC and FE models are very similar. These more robust, farther extending, and statistically significant estimates seem reasonable given that beach closures and notifications are a more direct and salient signal to local residents regarding water quality. When comparing estimates across the variants of Models 2 and 3 in table 3, we see that accounting explicitly for beach closures decreases the magnitude and/or significance of the estimated beach enterococci elasticities, especially in the nearest-distance bins.
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For one additional beach day closed each summer season, the estimates translate to an average decrease in home value of $2,123 for homes in the 0–500 m bin, and $598 for homes in the 3,000–3,500 m bin. These estimates suggest that if the nearest beach is closed an additional week every year, there would be an average price decrease of $14,859 for homes in the 0–500 m bin, and $4,188 for homes in the 3,000–3,500 m bin. This is a plausible magnitud given that the average number of beach days closed per season is seven, and there have been instances where beaches were closed for most of, or even the entire, season.
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With these caveats in mind, local stakeholders can still make better-informed decisions by comparing the potential house price effects estimated in this study with the costs of policies and projects to improve water quality in the Long Island Sound.... Consider a hypothetical program in New Rochelle, a city in Westchester County, that reduces the number of beach closures each summer season from the average of seven days a year to zero. Our results from SAC 3, for example, suggest that this would yield a total increase in value of the 5,672 single-family homes and townhomes within 3.5 km of a beach in New Rochelle by about $50.2 million. Note that we omitted homes in the statistically insignificant 2,000–2,500m. bin for this calculation. As a rough comparison, a project to repair the sewer infrastructure and prevent stormwater infiltration and subsequent sewage overflows in New Rochelle cost about $20 million (Garcia 2015b), which is substantially less than the estimated capitalization effects in this purely illustrative example. These capitalization effects reflect only a portion of the benefits to local stakeholders because households farther away who use these beaches will also benefit.
https://www.journals.uchicago.edu/doi/suppl/10.1086/717265
by Megan Kung 1, Dennis Guignet 2, and Patrick Walsh 3
1. Economist, Los Angeles Regional Water Quality Control Board, 320 W. 4th Street #200, Los Angeles, CA 90013 USA (email: megan.kung@waterboards.ca.gov).
2. Assistant Professor, Department of Economics, Appalachian State University, 416 Howard Street, Room 3101B, Peacock Hall, ASU Box 32051, Boone, NC 28608 USA (email: guignetdb@appstate.edu).
3. Economist, National Center for Environmental Economics, US Environmental Protection Agency, 1200 Pennsylvania Avenue, NW, Washington, DC 20460 USA (email: walsh.patrick.j@epa.gov).
Published online December 3, 2021.
Marine Resource Economics via The University of Chicago Press on behalf of the MRE Foundation Volume 37, Number 1, January 2022.
