RESEARCH

WORKING PAPERS

Location Sorting and Endogenous Amenities: Evidence from Amsterdam

New draft! Joint with Tomás Domínguez-Iino. Conditionally accepted at Econometrica. Replication package under review.

Supplementary Material.

Awarded Best Student Paper Prize 2019 by the Urban Economics Association and Best Job Market Paper Prize 2019 by the European Economic Association.

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.

Optimal Urban Transportation Policy: Evidence from Chicago

Draft. Joint with Felipe Barbieri, Juan Camilo Castillo, Nathaniel Hickok, and Tobias Salz. R&R at Econometrica.

Supplementary Appendix

Awarded NBER Transportation Economics in the 21st Century Grant

Featured: BFI Insights, Chicago Booth Review , The Pie

Abstract: We characterize and quantify optimal urban transportation policies in the presence of congestion and environmental externalities. We formulate a framework in which a municipal government chooses among transportation equilibria through its choice of public transit policies---prices and frequencies---as well as road pricing. 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 reduced bus and increased train frequencies. Combining transit policies with road pricing allows for higher transit frequencies and lower prices due to a slack budget constraint, increasing consumer surplus after rebates.

Neighborhood Revitalization and Inequality: Evidence from Chicago’s Public Housing Demolitions

New draft! Joint with Eric Chyn and Bryan Stuart. 

Featured: BFI Insights, Chicago Booth Review, CBR Line of Inquiry

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.

PUBLICATIONS

Supplementary Appendix.

Featured: Marginal Revolution. Covid Economics: Vetted and Real-Time Papers, Issue 13. VoxTalks, Episode 28.

SELECTED WORK IN PROGRESS

Data-Driven Nests in Discrete Choice Models

Joint with Elena ManresaSlides.

Presented at (by coauthor or myself): NYU, Cornell, Minnesota, UCL, Caltech

Abstract: Nested logit models represent consumers as agents that choose sequentially over product groups before choosing a final product, hence allowing for flexible substitution patterns across products. However, assuming knowledge of the nest structure has proven problematic in some applications. We propose a method that estimates both the nest structure as well as the structural parameters using product share data. We consider two different settings with price endogeneity: (1) longitudinal observations of products across a large number of markets, where conditional on a product fixed effect prices are exogenous and (2) single-market observations with a cost-shifter. In each setting, we develop estimators to recover the structure of the nest and the parameters and analyze its statistical properties. We propose two-step estimation strategies where in the first step we classify products and in the second step, we recover structural parameters. More specifically, in (1) we use the Bonhome and Manresa (2015) estimator to recover groups, and in the second step, we estimate the model conditional on the estimated nest structure. In (2) we make use of a control function approach to classify products using k-means clustering. We showcase the good performance of our method through a Monte Carlo experiment, and we apply it to the U.S. automobile market data first used in Berry, Levinsohn, and Pakes (1995).

Sorting by Choice? Separating Preferences from Discrimination in Housing Markets

Joint with Aradhya Sood

Awarded Russell Sage Foundation and Gates Foundation Pipeline Grant for Emerging Scholars.

Presented at (by coauthor or myself): Toronto Urban Brownbag, Toronto IO Brownbag, UEA Fall Meeting 2022, SEA 2022, AREUEA National Meeting 2023, Russell Sage and Gates Foundations Emerging Scholars Conference 2023, UEA Fall Meeting 2024, OIGI Fall Research Conference 2024, Junior Spatial Conference 2024

Featured: Chicago Booth Review

Abstract: How much of the observed across neighborhood segregation is due to discrimination versus household preferences for neighbors’ characteristics? We study this question using the discriminatory policy of racial covenants, which prevented racial and ethnic minorities from residing in covenanted houses during the first half of the 20th century in the U.S. To quantify the relative role of explicit and implicit discrimination as well as household preferences, we construct a novel data that links households and developments to the historic street grid and build a two-sided housing matching model that restricts the choice set of neighborhoods for the minority households but not the non-minority households. Using an instrumental variable approach, we first show that having a fully covenanted development reduces the probability of non-White and White Eastern and Southern European immigrant households by 27.8% and 15%, respectively. We show that traditional neighborhood demand discrete choice models produce biased estimates of preferences for neighborhood characteristics and elastisticies when they do not account for restrictions on the choice sets for the households that face discrimination and that this bias increases with the share of developments restricted to minority households.