Location Sorting and Endogenous Amenities: Evidence from Amsterdam

NEW DRAFT! Joint with Tomás Domínguez-Iino. Revision requested at Econometrica.

This paper argues that the endogeneity of amenities plays a crucial role in determining the welfare distribution across a city's residents. We quantify this mechanism by constructing a dynamic model of residential choice with heterogeneous households, where urban consumption amenities are the equilibrium outcome of a market for non-tradables. We estimate our model using Dutch administrative microdata and leverage spatial variation in tourism flows and the entry of home-sharing platforms, namely Airbnb, as shifters of location characteristics in Amsterdam. Our results reveal significant heterogeneity across local residents in their valuation of different amenities, as well as in the response of amenities to demographic composition. We then show that the distributional effects of the tourist boom hinge on this heterogeneity: after initial rent increases due to a reduction in the housing supply available to locals, younger groups---the most similar to tourists---are compensated by having amenities tilt in line with their preferences, while older families end up being additionally hurt by this shift in amenities. We show that taxes on undesirable amenities are more welfare-enhancing relative to tourism taxes.

Online Appendix. 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.

The Welfare and Distributional Consequences of Neighborhood Change: Evidence from Chicago's Public Housing Demolitions

Draft. Joint with Eric Chyn and Bryan Stuart

This paper studies 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 welfare impacts using a structural model that features a rich set of equilibrium responses motivated by descriptive analysis. Our results indicate that demolitions reduced welfare for Black and Hispanic households, especially those with low-income levels. In contrast, higher-income white households benefited. Counterfactual simulations explore how housing policy can mitigate negative impacts of demolitions and suggest increased public housing site redevelopment is the most effective policy for reducing racial inequality.

Featured: BFI Insights

Disparities in COVID-19 Risk Exposure: Evidence from Geolocation Data

Joint with Joshua Coven, Arpit Gupta, and Angelo Orane-Hutchinson. Revision requested at Regional Science and Urban Economics 

We examine the determinants of COVID-19 risk exposure in the context of the initial wave in New York City. In the first wave of the pandemic, out-of-home activity related to commuting was strongly associated with COVID-19 cases at the ZIP code level and hospitalization at an individual level. After layoffs of workers decreased commuting, case growth continued through household crowding. A larger share of individuals in crowded housing, or commuting to essential and frontline work, are Black, Hispanic, and lower-income---contributing to disparities in disease risk. Structural socio-economic inequalities help determine the cross-section of COVID-19 risk exposure in urban areas.


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.


Optimal Urban Transportation Policy: Evidence from Chicago

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

We quantify optimal urban transportation policies in the presence of congestion, network, and environmental externalities. We show theoretically that, beyond externality distortions, a budget constrained social planner introduces additional inefficiencies 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 public sources and cellphone location records to construct a novel data set of the universe of public transit, ride-share, taxi, and car trips. Finally, we quantify optimal policies for a battery of scenarios. We find that congestion prices on private cars returns the largest efficiency gains relative to the status quo, but they cause a large, regressive decrease in consumer surplus. 

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, NBER Market Design, LACEA-LAMES, Philadelphia Fed, UCLA Spatial Conference, Berkeley, GEA, ASSA Meetings 2023, Toronto, Georgetown, Johns Hopkins, Maryland, Wharton Real Estate.

De Jure versus De Facto Discrimination: Evidence from Racial Covenants

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.

Presented at (by coauthor or myself): Toronto Urban Brownbag, Toronto IO Brownbag, UEA Fall Meeting 2022, SEA 2022

Data-Driven Nests in Discrete Choice Models

Joint with Elena ManresaSlides.

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, Caltech

Social Networks and Geographic Mobility

Joint with Olivia Bordeu and Gregorio Caetano.  

Although geographic mobility is a key driver of economic opportunity, lower-income households tend to move less frequently. This paper explores the role of local social networks as an additional friction to geographic mobility and its importance across income groups. We start by documenting how social connections affect household production and mobility across labor markets. We focus our empirical analysis on childcare because it is a critical component of household production. We find that lower-income families rely more on relatives for their childcare needs rather than using market providers. Further, we also find that households who use more their social networks for childcare are less likely to move. We propose a dynamic model of households' childcare production and location choice, and estimate the model by matching key moments in the data. We quantify how much local social ties can explain mobility frictions and how it varies across income groups.

The Welfare Effects of Public Housing: Evidence from the Netherlands

Joint with Hans Koster and Giorgio Pietrabissa.

The Political Economy of the Racial Housing Gap: Evidence from Chicago's Alderman Prerogative

Joint with Tyler Jacobson, Fern Ramoutar and  Silvia Vannutelli.