Conference Agenda

Lead contamination in drinking water remains a significant public health threat in the U.S., driven by complex challenges and impacts within public drinking water systems. Previous research has shown socio-demographic disparities in lead exposure, but the underlying factors, particularly historical ones, are not well understood. In this study, we use widely recognized spatially explicit maps to quantify the relationship between historical place-based practices and contemporary lead concentration in drinking water nationwide. Specifically, we analyze the 1930s Home Owners’ Loan Corporation (HOLC) maps and spatially link them to block group-level lead concentration in drinking water across 202 U.S. cities over the past three decades while accounting for various socio-demographic factors. Our analysis reveals that communities formerly classified as high lending risks exhibit higher lead concentration levels in drinking water and are more likely to have lead concentrations exceeding the Environmental Protection Agency’s reporting and action limits. These findings highlight the enduring effects of historical place-based policies on present-day environmental outcomes and emphasize the need for targeted infrastructure investments and policy interventions to mitigate lead exposure in vulnerable communities.

This study examines how current conditions shape people’s preferences for public policies that improve environmental quality. We use a stated preference survey with experimentally varied status quo levels in a setting with a spatially explicit freshwater health score across a wide geographic area. We provide causal evidence that people have a higher willingness to pay when status quo water quality levels are worse. These findings highlight the importance of accurately describing the status quo condition in tated preference studies. This study also provides empirical insights into the monetized economic benefits of landscape-wide water quality improvements in Canada. We find that the public’s willingness to pay for water quality improvements varies by spatial scale and proximity to the policy site. Local improvements in home basins or sub-basins are estimated to have a higher willingness to pay than distant ones. Recreational users have substantially higher willingness to pay, underscoring the joint role of non-use and use values.

This paper empirically implements a structural framework to identify and estimate use and non-use values associated with water quality improvements. I combine revealed preference data from a random utility travel cost model of recreation demand with stated preference data from a contingent valuation referendum to jointly estimate welfare measures within a consistent utility-theoretic setting. The approach allows total willingness to pay for water quality improvements to be decomposed into use and non-use components, addressing an identification challenge in nonmarket valuation.

The empirical analysis uses web-based survey data from the general population of Michigan, which include detailed trip-level recreation behavior and referendum responses for statewide water quality changes. Recreation demand parameters are first identified from observed site choices and travel costs, while stated preference responses inform preferences over quality changes beyond observed use. Building on the structural model of Day et al. (2019), I extend the framework to allow for joint estimation of revealed and stated preference data, enabling separate identification of use and non-use values without imposing ad hoc assumptions.

The results indicate that structurally identified use and non-use values differ meaningfully from estimates obtained using simpler ad hoc approaches that rely on partial welfare measures or residual valuation. These differences have important implications for benefit–cost analysis of water quality policies, particularly when non-use values constitute a substantial share of total benefits. The paper contributes to the literature on nonmarket valuation by providing an empirically tractable and theoretically consistent method for welfare decomposition.

Payment for ecosystem services (PES) programs are widely used to mitigate negative externalities, yet questions remain about how to design these programs efficiently to achieve environmental objectives at the lowest possible cost. This paper evaluates the cost-effectiveness of alternative PES contract types and enrollment mechanisms in an agricultural water conservation program through a novel integration of stated preference methods and simulation modeling. Specifically, we implement a stated preference survey to elicit farmers' willingness-to-accept (WTA) for alternative water conservation contracts and combine these estimates with predicted environmental benefits to simulate program implementation across contract types and enrollment mechanisms for the universe of eligible fields. Results indicate that considering program benefits or costs (WTAs) in isolation leads to suboptimal design choices, highlighting the importance of ex-ante cost-effectiveness evaluations that integrate both dimensions. More broadly, our methods demonstrate how stated preference methods can be leveraged to inform the design of cost-effective PES programs.