Use of Property Values and Location Decisions for Environmental Valuation
The economics literature has developed various methods to recover the values for environmental commodities. Two such methods related to revealed preference are property value hedonic models and equilibrium sorting models. These strategies employ the actual decisions that households make in the real estate market to indirectly measure household demand for environmental quality. The hedonic method decomposes the equilibrium price of a house based on the house’s structural and neighborhood/environmental characteristics to recover marginal willingness to pay (MWTP). The more recent equilibrium sorting literature estimates environmental values by combining equilibrium housing outcomes with a formal model of the residential choice process. The two predominant frameworks of empirical sorting models that have been adopted in the literature are the vertical pure characteristics model (PCM) and the random utility model (RUM). Along with assumptions on the structure of preferences, a formal model of the choice process on the demand side, and a characterization of the supply side to close the model, these sorting models can predict outcomes that allow for re-equilibration of prices and endogenous attributes following a counterfactual policy change. Innovations to the hedonic model have enabled researchers to more aptly value environmental goods in the face of complications such as non-marginal changes (i.e., identification and endogeneity concerns with respect to recovering the entire demand curve), non-stable hedonic equilibria, and household dynamic behavior. Recent advancements in the sorting literature have also allowed these models to accommodate consumer dynamic behavior, labor markets considerations, and imperfect information. These established methods to estimate demand for environmental quality are a crucial input into environmental policymaking. A better understanding of these models, their assumptions, and the potential implications on benefit estimates due to their assumptions would allow regulators to have more confidence in applying these models’ estimates in welfare calculations.