Dennis Guignet

This study provides step‐by‐step guidance for practitioners and local stakeholders on how to use existing study results to conduct benefit transfer (BT), and ultimately make informed predictions of how improvements in lake water clarity may benefit surrounding communities. The procedures are demonstrated using a publicly available meta‐dataset developed by the United States Environmental Protection Agency, and a subsequent meta‐analysis that synthesizes the literature on how improvements in water clarity impact home values. The BT procedures are demonstrated using a case study of 14 large lakes in Kosciusko County, Indiana. Lake‐specific average increases in home values, as well as the value of the housing stock in aggregate, are calculated for illustrative improvements in lake water clarity. This analysis provides a critical bridge to better connect high‐quality, academic research with real‐world policy analysis, and ultimately serves to better equip local governments and stakeholders to make more informed policy and land use decisions.

We discuss data quality and modeling issues inherent in the use of nationwide property data to value environmental amenities. By example of ZTRAX, a U.S.-wide real estate database, we identify challenges and propose guidance for: (1) the identification of arm’s-length sales, (2) the geo-location of parcels and buildings, (3) temporal linkages between transaction, assessor, and parcel data, (4) the identification of property types, such as single-family homes and vacant lands, and (5) dealing with missing or mismeasured data for standard housing attributes. We review current practice and show that how researchers address these issues can meaningfully influence research findings.

Leaded fuel used by piston-engine aircraft is the largest source of airborne lead emissions in the United States. Previous studies have found higher blood lead levels in children living near airports where leaded aviation fuel is used. However, little is known about the health effects on adults. This study is the first to examine the association between exposure to aircraft operations that use leaded aviation fuel and adult cardiovascular mortality. We estimated the association between annual piston-engine air traffic and cardiovascular mortality among adults age 65 and older near 40 North Carolina airports during 2000 to 2017. We used several strategies to minimize the potential for bias due to omitted variables and confounding from other health hazards at airports, including coarsened exact matching, location-specific intercepts, and adjustment for jet-engine and other air traffic that does not use leaded fuel. Our findings are mixed but suggestive of adverse effects. We found higher rates of cardiovascular mortality within a few kilometers downwind of single- and multi-runway airports, though these results are not always statistically significant. We also found significantly higher cardiovascular mortality rates within a few kilometers and downwind of single-runway airports in years with more piston-engine air traffic. We did not consistently find a statistically significant association between cardiovascular mortality rates and piston-engine air traffic near multi-runway airports, where there was greater uncertainty in our measure of the distance between populations and aviation exposures. These results suggest that (i) reducing lead emissions from aviation could yield health benefits for adults, and (ii) more refined data are needed to obtain more precise estimates of these benefits. Subject Areas: Toxic Substances, Health, Epidemiology, Air Pollution, Ambient Air Quality. JEL codes: Q53, I18.

Hedonic property value studies of water quality conventionally focus on water quality levels measured nearest a home. This study examines whether water quality at the nearest access point (...

We construct a comprehensive, publicly available meta-dataset based on 36 hedonic studies that examine the effects of water quality on housing values in the United States. The meta-dataset includes 656 unique estimates and entails a cluster structure that accounts for price effects at different distances. Focusing on water clarity, we estimate reduced-form meta-regressions that account for within-market dependence, statistical precision, housing market and waterbody heterogeneity, publication bias, and methodological practices. Although we find evidence of systematic heterogeneity, the out-of-sample transfer errors are large. We discuss the implications for benefit transfer and future work to improve transfer performance.