Improving Water Quality in an Iconic Estuary: An Internal Meta-analysis of Property Value Impacts Around the Chesapeake Bay

Abstract

This study conducts a meta-analysis and benefit transfer of the value of water clarity in the Chesapeake Bay estuary to estimate the property value impacts of pollution reduction policies. Estimates of the value of water clarity are derived from separate hedonic property value analyses of 14 counties bordering the Bay. The meta-analysis allows us to: 1) estimate the average effect of water clarity in the Chesapeake Bay, 2) investigate heterogeneity of effects across counties based on socioeconomic and ecological factors, 3) evaluate different measures of water clarity used in the original hedonic equations, and 4) transfer the values to Bayfront counties in nearby jurisdictions to estimate the property value impacts of the Total Maximum Daily Load (TMDL), a policy to reduce nutrient and sediment pollution entering the Bay that is expected to improve water clarity and ecological health. We also investigate the in-sample and out-of-sample predictive power of different transfer strategies and find that a simpler unit value transfer can outperform more complex function transfers. We estimate that aggregate near-waterfront property values could increase by roughly $400 million to $700 million in response to water clarity improvements from the TMDL.

The Chesapeake Bay program modeling system: Overview and recommendations for future development

“…The Bay supports economically important fisheries, with blue crabs, striped bass, and oysters generating the largest revenue (Dewar et al, 2009) and shellfish aquaculture activities growing rapidly (Hudson et al, 2016). The Bay waters also enhance coastal property values and support a vital tourist economy, including nature-based recreation industries (Klemick et al, 2018). However, increases in agricultural activity, urbanization, suburban sprawl, stream alterations, and air pollution since colonial times, and intensification since the mid-20th century, have led to excessive nutrient and sediment inputs entering the Bay (Brush, 2009), adversely affecting the health of the Bay ecosystem and the economic services it provides (CBF, 2014).…”

Macro-Impacts of Air Quality on Property Values in China—A Meta-Regression Analysis of the Literature

“…In this case, the random-effect model is a popular approach for meta-regression analyses and widely used in previous studies [48,99]. Compared with the random-effect model, the fixed-effect model only allows for within-study variations, which is likely to neglect the characteristics of different studies [102], for example, the differences between housing markets. Further, Braden, Feng [103] argued that the fixed-effect models generate inefficient results in meta-regression analyses.…”

Benefit Transfer Challenges: Perspectives from U.S. Practitioners

“…One approach would be to use a form of cross-validation (Hastie, Tibshirani, & Friedman, 2001) to characterize the out-of-sample prediction accuracy for benefit transfer functions. Stapler and Johnston (2009) used a cross-validation approach to examine out-of-sample predictions for a meta-regression model of the marginal value of fish from a collection of recreation demand studies; Klemick et al (2016) examined out-of-sample transfer errors based on hedonic property value estimates of the benefits of increasing water clarity in the Chesapeake Bay; and Newbold et al (2017) used cross-validation to help guide variable selection for a meta-regression model of WTP estimates from stated preference studies.…”