Job Market Paper. Joint with Tomás Domínguez-Iino.

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

This paper argues that the endogeneity of amenities plays a crucial role in the welfare distribution of a city's residents by reinforcing location sorting. We quantify this channel by leveraging spatial variation in tourism flows and the entry of home-sharing platforms, such as Airbnb, as shifters of location characteristics to estimate a dynamic model of residential choice. In our model, consumption amenities in each location are the equilibrium outcome of a market for services, which are supplied by firms and demanded by heterogeneous households. We estimate the model using detailed Dutch microdata, which allows us to track the universe of Amsterdam's residents over time and the evolution of a rich set of neighborhood amenities. Our results indicate significant heterogeneity across households in their valuation of different amenities, as well as in the response of amenities to demographic composition. We show that allowing for this endogenous response increases inequality between demographic groups whose preferences are closely aligned, but decreases it if substantially misaligned, suggesting heterogeneity in the two-way mapping between households and amenities plays a crucial distributive role. Finally, we highlight the distributional implications of our estimates by evaluating currently debated policies, such as zoning, as well as price and quantity regulations in housing markets.


Almagro, Milena and Andrés-Cerezo, David (2020)

The Construction of National Identities, Theoretical Economics, 15 (2), 763-810

Supplementary Appendix.

Almagro, Milena and Orane-Hutchinson, Angelo (2020)

Supplementary Appendix.

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



Joint with Eric Chyn and Bryan Stuart.

This paper provides new evidence on the welfare impacts of urban renewal programs on neighborhoods. We study one of the largest spatially targeted redevelopment efforts in the United States to date: public housing demolitions sponsored by the HOPE VI program. Focusing on Chicago, we estimate a structural model of neighborhood choice that features a rich set of equilibrium responses to demolitions. Overall, demolitions increased welfare by 1%. However, these effects were unevenly distributed across demographic groups. We find that demolitions reduced welfare for Black households, especially those with low-income levels. These negative impacts arise because demolitions were followed by increases in rents and decreases in the neighborhood-level Black population share. In contrast, higher-income white households received the largest increase in welfare, because they value the reduction in the Black population share and especially value the removal of public housing. We also find that changes in demographic composition can explain 37% of the overall welfare effect coming from demolitions. Endogenous housing supply responses increase welfare for all groups and lower inequality by increasing the availability of housing in neighborhoods that become more attractive.

Presented at (by coauthor or myself): European UEA 2021, U Wisconsin-Madison, Notre Dame, OIGI Fall 2021, American UEA 2021, Atlanta Fed, Rochester, SMU, Chicago Booth, Central Bank of Colombia, Bureau of Economic Analysis, Barcelona Summer Forum Trade Workshop, IEB Urban Workshop, 2022 NBER SI Real Estate + Urban,


Joint with Felipe Barbieri, Juan Camilo Castillo, Nathaniel Hickok, and Tobias Salz.

Despite high public transit subsidies, American commuters still overwhelmingly use socially inefficient cars. In this project, we quantify optimal urban transportation policies in the presence of congestion, network, and environmental externalities. Given dire municipal budgets for public transit, we account for budget considerations. We show theoretically that a budget-constrained social planner introduces both quantity and quality distortions similar to those of a monopolist. We then move to an empirical analysis of the transportation system in Chicago based on an equilibrium model. To estimate supply and demand, we combine data from public and private sources that include the universe of public transit trips, ride-hailing, taxi trips as well as car trips based on cell phone location records. As a theoretical benchmark, we characterize optimal prices and service levels across all modes. Our main counterfactual determines optimal prices and service levels for existing public transit modes while allowing for profit-maximizing responses of private market participants.

Awarded NBER Transportation Economics in the 21st Century Grant

Presented at (by coauthor or myself): Harvard, Chicago Booth, MIT, Rice, Texas A&M, Yale, CEMFI, EIEF Applied Micro Junior Conference, Tinos IO Conference


Joint with Aradhya Sood.

Racially-restrictive covenants, which prevented the sale and rental of housing to several racial and ethnic minorities, were a common phenomenon in the first half of the 20th century in many northern cities in the U.S. In this paper, we study how these racially-restrictive covenants affected the socio-economic and geographic structure of urban areas and how their effects have persisted over time. In the first part of the paper, we leverage plausible exogenous variation in the changes of water bodies and soil quality to predict the presence of covenants. We find that racial covenants are negatively correlated with natural amenities, suggesting that they were used as substitutes of location characteristics that were potentially highly valued by city residents. In the second part of the paper, we will employ a location choice model to disentangle the various channels through which racial covenants shaped the geography of northern cities and measure the welfare of counterfactual housing policies.

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


Joint with Elena Manresa. Slides.

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).

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