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Property values and water quality: A nationwide meta-analysis and the implications for benefit transfer, 2019-05
Citation:
Guignet, D., Matthew Heberling, M. Papenfus, O. Griot, AND B. Holland. Property values and water quality: A nationwide meta-analysis and the implications for benefit transfer, 2019-05. In Proceedings, NCEE working paper series: Virtual on-going workshop, Washington,DC, June 03, 2019. U.S. Environmental Protection Agency, Washington, DC, 2019-05, 2019.
Impact/Purpose:
The US Department of Agriculture (USDA) has a growing interest in measuring the value of ecosystem services provided by its programs and policies. The USDA has organized a workshop to explore new economic approaches because it faces data and methodological constraints. Our research proposes an approach to assess the benefits of improved water quality using existing, published hedonic property value studies. The hedonic method requires homeowners to be aware of and value changes in water quality such that it will be capitalized in their house prices. We examine the house price effects of water quality changes across different waterbodies and regions of the US to improve USDA’s assessment of its programs and policies. This paper already has been approved as a non-EPA proceedings document under ORD-030470 for the USDA workshop, "Applications and Potential of Ecosystem Services Valuation within USDA." This paper will also be published as part of EPA's National Center for Environmental Economics (NCEE) working paper series on research in environmental economics.
Description:
We conduct a meta-analysis using a comprehensive review of studies that examine the effects of water quality improvements on waterfront and non-waterfront housing values. Rather than conducting the meta-analysis using dollar values, this study estimates mean elasticity responses. We identify 36 studies that result in 656 unique observations. Mean property price elasticities with respect to numerous water quality measures are calculated (e.g., chlorophyll-a, fecal coliform, nitrogen, and phosphorous) for purposes of value transfer. In the context of water clarity, function transfers can be performed. We estimate numerous meta-regressions, and compare transfer performance across models using an out-of-sample transfer error exercise. The results suggest value transfers often perform just as well as more complicated function transfers. In our context, however, a simple function transfer that accounts for baseline water clarity performs best. We discuss the implications of these results for benefit transfer, and outline key limitations in the literature.