Examining Implicit Price Variation for Lake Water Quality

Abstract

Hedonic price models are commonly used to estimate implicit prices for lake water quality across small geographic regions that might be assumed to be a part of a common real estate market. Yet recent studies expand the geographic scale of the hedonic model potentially obscuring important differences in implicit prices across markets. We estimate implicit prices for lake water quality across multiple states in the northeast and upper Midwest in the United States of America at three different geographic scales: substate, state, and multistate. We find implicit price estimates are heterogeneous at both the substate and state-levels, which is not accounted for in state-level or multistate hedonic models. Our results show that estimates across a broad geographic scale can be driven by a single subregion within the defined area. Overall, the study demonstrates that using a single hedonic model over a large geographic area may obscure important heterogeneity in implicit prices used to estimate potential benefits for water-quality improvements.

Spatial Heterogeneity in Hedonic Price Effects for Lake Water Quality

“…CVs for Secchi range from as low as 0.21 for a Substate area in New Hampshire (Gibbs et al 2002) and as high as 0.90 at the national level (Moore et al 2020). While 0.21 is the minimum CV, the next three smallest CVs are 0.31, 0.32, and 0.34 from Michael, Boyle, and Bouchard (2000), Gibbs et al (2002), and Swedberg et al (2022), respectively. We choose 0.25 as the minimum CV as it falls in between 0.21 and 0.31.…”

“…Studies conducted at the local level demonstrate differences in implicit values for water quality, which are confirmed by the Guignet et al (2022) meta-analysis that reports significant differences in elasticity estimates across broad regions of the country (see also Heberling, Guignet, and Papenfus (2022)). Further, Zhang, Phaneuf, and Schaeffer (2022) and Swedberg et al (2022) studies observe heterogeneity in value estimates at the Regional and State levels. Within a national housing market framework, Mamun et al (2023) observe spatial heterogeneity by state and ecoregion, while Moore et al (2020) do not find evidence for heterogeneity at the state level.…”

“…For example, Zhang, Phaneuf, and Schaeffer (2022) consider seven regional lake housing markets made up of two to eight states in each. Swedberg et al (2022) at the State and Substate levels. Mamun et al (2023) and Moore et al (2020) both consider a larger spatial scale using a "nationwide housing market" comprised of lakes from 43 and 32 states, respectively.…”

“…Copyright 2023 matching time frame.25 Such reporting will allow richer meta-analysis to clarify if results observed are real spatial differences or simply due to differences in investigator choices across studies.26 Another consideration is that the distributions we report of elasticity estimates indicate that estimates can be zero or negative when the expectation that elasticity estimates will be positive and significant. There are counter intuitive hedonic estimates published in the peer-reviewed literature from time to time (e.g.,Swedberg et al 2022), but not often. Thus, our study suggests more anomalous outcomes than what a casual observation of the literature reveals.…”

Data Practices for Studying the Impacts of Environmental Amenities and Hazards with Nationwide Property Data

“…Contributors to this article have used ZTRAX data to estimate: the cost of land acquisitions for conservation purposes (Nolte 2020); property value effects of national parks and historic sites (Zabel, Nolte and Paterson 2024); the benefits of lake water quality (Mamun et al 2023;Swedberg et al 2024); the effects of water markets on agricultural land values (Chaudhry, Fairbanks and Nolte 2024); the cost of hazardous chemical releases and the benefits of subsequent cleanups Guignet et al 2024); the risk of flood damage to residential homes (Gourevitch et al 2023); the effects of flood insurance policies (Hennighausen et al 2024;Pollack et al 2024); and property value impacts of critical habitat under the U.S.…”