Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Non-point source pollution and the its impact on water quality has garnered interest from policymakers, residents, and scientists in the past decade. We develop a novel method that links water quality indicators derived from a hydrological process model with housing sales data between 1990 and 2013 to estimate the marginal value of water quality changes in the Upper Big Walnut Creek (UBWC) watershed in Ohio. Econometric results indicate that a one-foot increase of Secchi-disk depth in the Hoover Reservoir leads to 7.72% increase in the housing price of an average residential property located within 0.3 miles from the reservoir, with an aggregate impact of around $6 million in the watershed. We find that the impact of water quality is heterogeneous over space, decreases with distance from the reservoir, and is insignificant beyond 0.3 miles. This study provides an alternative approach to fill the gap when observational water quality data are limited and provides reliable estimations of water quality impact, which is essential to evaluate the benefits and costs associated with land use change and urban development.