Research
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The Effect of Contamination on Self Reporting Environmental Quality: US Coal Mining and Drinking Water Utilities
Abstract
Inducing self-reporting compliance with a regulatory standard requires careful incentive compatibility design when self-reporting may be incriminating or costly. I study how US drinking water utilities’ self-reporting compliance responds to exogenous decreases in regulated water quality caused by coal mining contamination. I measure a utility’s exposure to water contamination from coal mining with an instrumental variable that uses the plausibly exogenous temporal and spatial changes in coal mining induced by the Acid Rain Program. I find that an additional coal mine upstream of a utility causes a large and significant decrease in self reporting water quality tests. This is driven by an increase in the cost of self reporting due to contamination, without a commensurate increase in the penalties for not monitoring.Working Papers
A More Complete Valuation of US Lake Water Quality
Abstract
Standard hedonic models of water quality capture only the value of lakes near a home, understating willingness to pay for water bodies that residents visit but do not live beside. This paper estimates the marginal willingness to pay for lake water quality across more than 300 Core Based Statistical Areas in the contiguous United States using an embedded recreation demand model within a hedonic house price framework. In a first stage, I estimate a discrete-choice recreation demand model at the census block group level, in which residents choose among lake recreation sites within their local market or an outside option, as a function of travel cost and site cyanobacterial harmful algal bloom (cyanoHAB) levels measured from daily satellite imagery. This yields a block-group-level expected compensating surplus from lake recreation. In a second stage, this recreation surplus is embedded as a regressor in a hedonic house price model, alongside local dissolved oxygen readings, to recover the total (direct amenity plus recreational) value of lake water quality. The analysis draws on three novel data sources at national scale: cell phone mobility data (Advan) tracking approximately 46 million devices to measure recreational visits to over 2,000 lakes, satellite-derived cyanobacterial cell counts (NOAA’s Cyanobacterial Assessment Network) as a high-frequency, highly visible measure of water quality, and ATTOM property transaction records for single-family homes sold between 2019 and 2022. This is the first application of national cell phone mobility data within an embedded recreation hedonic model, and the largest-scale hedonic estimate of lake water quality to combine recreation demand and property values. By capturing the value that non-shoreline residents place on lakes they travel to visit, the approach offers a more complete accounting of the benefits of pollution abatement policy than hedonic models restricted to properties near the water’s edge.Are Municipal Heat Ordinances Effective Climate Adaptation Tools?