Evidence suggests that municipal water utility administrators in the western US price water significantly below its marginal cost and, in so doing, inefficiently exploit aquifer stocks and induce social surplus losses. This paper empirically identifies the objective function of those managers, measures the deadweight losses resulting from their price-discounting decisions, and recovers the efficient water pricing policy function from counterfactual experiments. In doing so, the estimation uses a “continuous-but-constrained- control” version of a nested fixed-point algorithm in order to measure the important intertemporal consequences of groundwater pricing decisions.

This paper develops a dynamic model of neighborhood choice along with a computationally light multi-step estimator. The proposed empirical framework captures observed and unobserved preference heterogeneity across households and locations in a flexible way. We estimate the model using a newly assembled data set that matches demographic information from mortgage applications to the universe of housing transactions in the San Francisco Bay Area from 1994 to 2004. The results provide the first estimates of the marginal willingness to pay for several non-marketed amenities?neighborhood air pollution, violent crime, and racial composition?in a dynamic framework. Comparing these estimates with those from a static version of the model highlights several important biases that arise when dynamic considerations are ignored.

We test for residential sorting and changes in neighborhood characteristics in response to the cleanup of hazardous waste sites using restricted access fine-geographical-resolution block data. We examine changes between 1990 and 2000 in blocks within 5km of sites that are proposed to the National Priority List that fall in a narrow interval of Hazardous Ranking Scores, comparing blocks near sites that were cleaned with those near sites that were not. Cleanup leads to increases in population density and housing unit density; increases in mean household income and shares of college-educated; but also to increases in the shares of minorities.

By constraining an individual’s choice during a search, housing discrimination distorts sorting decisions away from true preferences and results in a ceteris paribus reduction in welfare. This study combines a large-scale field experiment with a residential sorting model to derive utility-theoretic measures of renter welfare loss associated with the constraints imposed by discrimination in the rental housing market. Results from experiments conducted in five cities show that key neighborhood amenities are associated with higher levels of discrimination. Counterfactual simulations based on the sorting model suggest that discrimination imposes damages equivalent to 4.4% and 3.5% of the annual incomes for African American and Hispanic/Latinx renters, respectively. Damages are increasing in income for African American renters, such that effects become stronger for economically mobile households. Renters of color must make substantial investments in additional search to mitigate the costs of these constraints. We find that a naive model ignoring discrimination constraints yields biased estimates of willingness to pay for key neighborhood amenities.

Households “sort” across neighborhoods according to their wealth and their preferences for public goods, social characteristics, and commuting opportunities. The aggregation of these individual choices in markets and in other institutions influences the supply of amenities and local public goods. Pollution, congestion, and the quality of public education are examples. Over the past decade, advances in economic models of this sorting process have led to a new framework that promises to alter the ways we conceptualize the policy evaluation process in the future. These “equilibrium sorting” models use the properties of market equilibria, together with information on household behavior, to infer structural parameters that characterize preference heterogeneity. The results can be used to develop theoretically consistent predictions for the welfare implications of future policy changes. Analysis is not confined to marginal effects or a partial equilibrium setting. Nor is it limited to prices and quantities. Sorting models can integrate descriptions of how nonmarket goods are generated, estimate how they affect decision making, and, in turn, predict how they will be affected by future policies targeting prices or quantities. Conversely, sorting models can predict how equilibrium prices and quantities will be affected by policies that target product quality, information, or amenities generated by the sorting process. These capabilities are just beginning to be understood and used in applied research. This survey article aims to synthesize the state of knowledge on equilibrium sorting, the new possibilities for policy analysis, and the conceptual and empirical challenges that define the frontiers of the literature.

Growing evidence indicates that neighborhoods affect human capital accumulation, raising concern that the exclusionary effects of housing discrimination could contribute to persistent inequality in the United States. Using data from HUD’s most recent Housing Discrimination Study and microlevel data on neighborhood attributes in 28 US cities, we find that minorities are steered toward neighborhoods with less economic opportunity and greater exposures to crime and pollution. Holding preferences and income constant, discriminatory steering alone can explain a disproportionate number of minority households found in high-poverty neighborhoods in the United States and the higher exposure of African American mothers to toxic pollutants.

Using data from Pennsylvania and an array of empirical techniques to control for confounding factors, we recover hedonic estimates of property value impacts from nearby shale gas development that vary with water source, well productivity, and visibility. Results indicate large negative impacts on nearby groundwater-dependent homes, while piped-water-dependent homes exhibit smaller positive impacts, suggesting benefits from lease payments. Results have implications for the debate over regulation of shale gas development.

Local pollution exposures have a disproportionate impact on minority households, but the root causes remain unclear. This study conducts a correspondence experiment on a major online housing platform to test whether housing discrimination constrains minority access to housing options in markets with significant sources of airborne chemical toxics. We find that renters with African American or Hispanic/Latinx names are 41% less likely than renters with white names to receive responses for properties in low-exposure locations. We find no evidence of discriminatory constraints in high-exposure locations, indicating that discrimination increases relative access to housing choices at elevated exposure risk.

We propose a new strategy for a pervasive problem in the hedonics literature: recovering hedonic prices in the presence of time-varying correlated unobservables. Our approach relies on an assumption about home buyer rationality, under which prior sales prices can be used to control for time-varying unobservable attributes of the house or neighborhood. Using housing transactions data from California's Bay Area between 1990 and 2006, we apply our estimator to recover marginal willingness to pay for reductions in three of the EPA's “criteria” air pollutants. Our findings suggest that ignoring bias from time-varying correlated unobservables considerably understates the benefits of a pollution reduction policy.