The real economic cost of homeownership depends on an intricate system of taxes and subsides that vary over time and across the United States. We incorporate the key features of this system into a framework for measuring the annual user-cost of housing and we use it to document how housing costs and subsidies varied over time, across space, and with household demographics in 2016-2017. Then we examine how the Tax Cuts and Jobs Act of 2017 subsequently reduced subsidies and increased the relative cost of housing. We report how these changes varied by geography, homeownership, race, and voting behavior.

We provide the first evidence on the rate at which spatial variation in all-cause mortality risk is capitalized into US housing prices. Using a hedonic framework, we recover the annual implicit cost of a 0.1 percentage-point reduction in mortality risk among older Americans and find that this cost is less than $3453 for a 67 year old and decreasing with age to less than $629 for an 87 year old. These estimates, while similar to estimates from the market for health care, are far below comparable estimates from markets for labor and automobiles, suggesting that the housing market provides an alternative, substantially cheaper channel for reducing mortality risk. We find this conclusion to be robust to a wide range of econometric model specifications, including accounting for associated expenditures on property taxes and the physical and financial costs of moving.

We build on the intuitive (static) modeling framework of Rosen (1974) and specify a simple, forward-looking model of location choice. We use this model, along with a series of graphs, to describe the potential biases associated with the static model and relate these biases to the time series of the amenity of interest. We then derive an adjustment factor that allows the potentially biased static estimates to be converted into forwardlooking estimates. Finally, we illustrate these concepts with two empirical applications: the marginal willingness to pay to avoid violent crime and the marginal willingness to pay to avoid air pollution.

We investigate the economic determinants of contract structure and entry with transfer contracts, which specify that manufacturers directly sell their products in retail stores while retailers collect sales revenue and return a transfer to the manufacturers. Using a unique data set describing entry decisions of clothing manufacturers into a retail department store, we estimate a two-sided, asymmetric-information entry model. We compare profit estimates under transfer contracts to counterfactual profit estimates under common alternative contract formats. Results show that, when adverse selection is present, transfer contracts dominate other contract formats from the retailer's perspective; otherwise, the common alternative contract formats dominate.

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 use data from a housing-assistance experiment to estimate a model of neighborhood choice. The experimental variation effectively randomizes the rents which households face and helps identify a key structural parameter. Access to two randomly selected treatment groups and a control group allows for out-of-sample validation of the model. We simulate the effects of changing the subsidy-use constraints implemented in the actual experiment. We find that restricting subsidies to even lower poverty neighborhoods would substantially reduce take-up and actually increase average exposure to poverty. Furthermore, adding restrictions based on neighborhood racial composition would not change average exposure to either race or poverty. (JEL I32, I38, R23, R38)

This paper estimates a dynamic microeconometric model of housing supply. The model features forward-looking landowners who optimally choose both the timing and the nature of construction while taking into account expectations about future prices and costs. The model is estimated using a unique dataset describing individual landowners in the San Francisco Bay Area. Results indicate that geographic and time-series variation in costs are key to understanding where and when construction occurs. Pro-cyclical costs provide an incentive for some landowners to build before price peaks. Results also indicate that landowners actively “time” the market, which reduces the elasticity of supply. (JEL C51, D12, E32, R21, R23, R31)

We construct and estimate a two-sided, asymmetric-information entry model where there exists a contractual, revenue-sharing agreement between the two sides. Using a unique dataset describing the two-sided entry decisions of clothing manufacturers into a retail department store, we recover the economic determinants driving the observed contractual and entry patterns. Estimation results show that the entry of a manufacturer can generate important spillovers for the sales of other manufacturers. In counterfactual experiments, we find that the nature of the contract minimizes the adverse effects of asymmetric information and that manufacturer profits would increase if they could reveal their private information.

The hedonic model, which has been used extensively in the Environmental, Urban, and Real Estate literatures, allows for the estimation of the implicit prices of housing and neighborhood attributes, as well as households' demand for these non-marketed amenities. A recognized drawback of the existing hedonic literature is that the models assume a myopic decision-maker. In this paper, we estimate a dynamic hedonic model and find that the average household is willing to pay $472 per year for a ten percent reduction in violent crime. In addition, we find that the traditional, myopic model suffers from a 21 percent negative bias.

White teenagers are substantially more likely to search for employment than black teenagers. This differential occurs despite the fact that, conditional on race, individuals from disadvantaged backgrounds are more likely to search. While the racial wage gap is small, the unemployment rate for black teenagers is substantially higher than that of white teenagers. We develop a two-sided search model where firms are partially able to search on demographics. Model estimates reveal that firms are more able to target their search on race than on age. Employment and wage outcome differences explain half of the racial gap in labor force participation rates.

THE MICROFOUNDATIONS OF HOUSING MARKET DYNAMICS

We use a unique dataset linking information about buyers and sellers to the complete census of housing transactions in the San Francisco metropolitan area for a period of 15 years to examine the microfoundations of housing market dynamics. We develop a tractable model of neighborhood choice in a dynamic setting along with a computationally straightforward estimation approach. This approach allows the observed and unobserved features of each neighborhood to evolve in a completely flexible way and uses information on neighborhood choice and the timing of moves to recover semi-parametrically: (i) preferences for housing and neighborhood attributes, (ii) preferences regarding the performance of the house as a financial asset (e.g., expected appreciation, volatility), and (iii) moving costs. This model and estimation approach is potentially applicable to the study a wide set of dynamic phenomena in housing markets and cities. In this paper, we use the model to develop testable implications of housing market efficiency and in particular rational expectations on the part of home buyers. We begin by showing that when the model is restricted so that all households have identical preferences, rational expectations implies the absence of predictable returns, i.e., the absence of the positive persistence in housing prices shown in the literature following Case and Shiller (1989). Thus, as the houses considered in an analysis are closer substitutes for one another, the predictability of returns should fall to zero. We examine this hypothesis empirically by studying the dynamics of housing prices at various levels of aggregation across both geographic and ∗PRELIMINARY AND INCOMPLETE