RESEARCH

Abstract:  We characterize and quantify optimal urban transportation policies in the presence of congestion and environmental externalities. A municipal government sets public transit policies --- fares and frequencies --- and road prices to maximize welfare. The government faces a budget constraint that introduces monopoly-like distortions and the potential need to cross-subsidize modes. We apply this framework to Chicago, for which we construct a new dataset that comprehensively captures transportation choices. We find that road pricing alone leads to large welfare gains by reducing externalities, but at the expense of travelers, whose surplus falls even if road pricing revenues are fully rebated. The optimal public transit price is near zero, with increased bus and train frequencies. Combining transit policies with road pricing slackens the budget constraint, allowing for even higher transit frequencies and lower prices, thereby increasing consumer surplus after rebates.

Abstract: How much of the observed house price differentials and household sorting is due to restrictions in choice sets, arising from implicit and explicit forms of discrimination, versus household preferences? To answer this question, we build a two-sided housing matching model that combines admission rules with traditional discrete choice models, allowing for heterogeneous choice sets across demographic groups. Additionally, we construct a novel dataset that links households and real-estate developments to the historic street grid of the 1940 Minneapolis metro area. Using an instrumental variable approach, we find that explicit discriminatory restrictions in neighborhoods reduce the likelihood of non-White and White Eastern and Southern European immigrant households by 10 and 2.8 percentage points, respectively. We also show that traditional discrete-choice models of neighborhood demand with misspecified choice sets can yield biased estimates of preferences for neighborhood characteristics, especially when there is selection in the characteristics of neighborhoods restricted to a subset of residents. Our two-sided housing matching model jointly estimates heterogeneous choice sets and preference parameters, revealing that different demographic groups faced substantially different choice sets. On average, minority households are 8 percentage points less likely to have a neighborhood in their choice set than non-minority households, even after controlling for explicit forms of discrimination and rents. Simulating a counterfactual scenario without these restrictions and preferences for co-patrons, we find that household preferences account for three-quarters of the observed segregation in 1940.

Abstract: This paper studies one of the largest spatially targeted redevelopment efforts implemented in the United States: public housing demolitions sponsored by the HOPE VI program. Focusing on Chicago, we study welfare and racial disparities in the impacts of demolitions using a structural model that features a rich set of equilibrium responses. Our results indicate that demolitions had notably heterogeneous effects where welfare decreased for minority households, especially those who were displaced from public housing, and increased for higher-income White households. Counterfactual simulations explore how housing policy mitigates negative effects of demolitions and suggest that increased public housing site redevelopment is the most effective policy for reducing racial inequality.

Abstract: This paper shows the endogeneity of amenities plays a crucial role in determining the welfare distribution of a city's residents. We quantify this mechanism by building a dynamic model of residential choice with heterogeneous households, where consumption amenities are the equilibrium outcome of a market for non-tradables. We estimate our model using Dutch microdata and leveraging variation in Amsterdam's spatial distribution of tourists as a demand shifter, finding significant heterogeneity in residents' preferences over amenities and in the supply responses of amenities to changes in demand composition. This two-way heterogeneity dictates the degree of horizontal differentiation across neighborhoods, residential sorting, and inequality. Finally, we show the distributional effects of mass tourism depend on this heterogeneity: following rent increases due to growing tourist demand for housing, younger residents---whose amenity preferences are closest to tourists---are compensated by amenities tilting in their favor, while the losses of older residents are amplified.

Abstract: In many economic applications, nested demand structures are used to capture flexible substitution patterns while preserving tractability. However, assuming a known nesting structure can be problematic, as misspecification may lead to biased estimates. We propose a simple two-step estimation strategy that jointly recovers an unobserved nesting structure and structural parameters using market-level data on choices and product characteristics. In the first step, we extend the grouped fixed-effects estimator of Bonhomme and Manresa (2015) to accommodate the asymptotic properties of the nested logit model and address price endogeneity. In the second step, we estimate preference parameters conditional on the inferred nesting structure. We consider empirical settings with longitudinal observations of products across several markets and potential price endogeneity. We demonstrate the strong performance of our method in Monte Carlo simulations, where we recover the population nesting structure with at least 99% accuracy. We also apply our approach to the U.S. beer market using NielsenIQ data, identifying four distinct beer groups and estimating a demand system that reveals rich substitution patterns. For this application, we benchmark our model against several alternative demand models---including a naively grouped nested logit and a mixed logit---and show that it more accurately captures substitution patterns in an out-of-sample validation exercise.