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Property values and water quality: A nationwide meta-analysis and the implications for benefit transfer - Washington, DC
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 - Washington, DC. In Proceedings, Applications and Potential of Ecosystem Services Valuation within USDA, DC, Washington, April 23 - 24, 2019. Northeastern Agricultural and Resource Economics Association (NAREA), NEWARK, DE, 1-79, (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.
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. These studies use only objective water quality measures, and examine homes across the United States. Rather than conducting a meta-analyses using dollar values, this study estimates mean elasticity responses, which is advantageous for benefit transfer because the projected property price changes can be tailored to baseline housing values and water quality levels. We assess the feasibility of using this literature for supporting broader water quality policy decisions. 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 in- and out-of-sample transfer error exercises. 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 quality performs best. We discuss the implications of these results for benefit transfer, and outline two key limitations in the literature. The first limitation relates to the lack of studies examining some regions and types of waterbodies, and the second is the disconnect between the water quality metrics used by economists and those examined by water quality modelers and policy makers.
