Research

Working papers

“Bunching in Real-Estate Markets: Regulated Building Heights in New York City” - Paper, - Conditionally accepted - Journal of Urban Economics. Updated 04/2024
- with Jan Brueckner and Dave Leather.
Abstract This paper presents a real-estate application of the bunching methodology widely used in other areas of applied microeonomics. The focus is on regulated building heights in New York City, where developers can exceed a parcel’s regulated height by incurring additional costs. Using the bunching methodology, we estimate the magnitude of these extra costs, with the results showing a modest increase in the marginal cost of floor space beyond the regulated building height. We use these estimates to predict the additional floor space that would be created by complete removal of building-height regulation in NYC. While this last exercise is circumscribed by our focus on a limited number of zoning categories, the results suggest that New York could secure notably more housing through lighter height regulation.

“Union and Firm Labor Market Power” - Paper, Appendix, Supplemental Material - Revise and resubmit - Econometrica. Updated 03/2024
- with Miren Azkarate-Askasua.
Previously circulated as “The Aggregate Effects of Labor Market Concentration”
Abstract Can union and firm market power counteract each other? What are the output and welfare effects of employer and union labor market power? Using data from French manufacturing firms, we leverage mass layoff shocks to competitors to identify a negative effect of employment concentration on wages. In line with the reduced form evidence and the French institutional setting, we develop and estimate a multi-sector bargaining model that incorporates employer market power. We find that, in the absence of unions, output decreases by 0.48 percent because they partially counteract distortions coming from oligopsony power. The reallocation of employment across space is key to realize the output gains from unions.

“Correcting Small Sample Bias in Linear Models with Many Covariates” - Paper, Appendix, Replication Files, Example - Updated 11/2022
- with Miren Azkarate-Askasua.
Abstract Estimations of quadratic forms in the parameters of linear models exhibit small-sample bias. The direct computation for a bias correction is not feasible when the number of covariates is large. We propose a bootstrap method for correcting this bias that accommodates different assumptions on the structure of the error term including general heteroscedasticity and serial correlation. Our approach is suited to correct variance decompositions and the bias of multiple quadratic forms of the same linear model without increasing the computational cost. We show with Monte Carlo simulations that our bootstrap procedure is effective in correcting the bias and find that is faster than other methods in the literature. Using administrative data for France, we apply our method by carrying out a variance decomposition of a linear model of log wages with person and firm fixed effects. We find that the person and firm effects are less important in explaining the variance of log wages after correcting for the bias and depending on the specification their correlation becomes positive after the correction.

“The Birthplace Premium” - Paper
Honorable Mention at the Best Student Paper Award, 10th European Meeting of the Urban Economics Association.
Abstract Why do people stay in economically distressed areas? In this paper, I explore a simple, yet overlooked hypothesis: people like to live close to what they call home. Using administrative data for France, I find: (i) the share of migrants who return to their birthplace is almost twice as large as the share of migrants who go to any other particular location; (ii) there is a negative relationship between labor flows and distance from the workers’ birthplace; and (iii) workers accept a wage discount between 9 to 11 percent to live in their home location. To understand the implications of these findings, I build a dynamic quantitative migration model into which I introduce home bias, understood as a utility cost of living away from one’s birthplace. I use the model to separately identify home bias and migration costs from the data. I find that differences in birth location lead to average welfare differences of up to 30 percent in consumption-equivalent terms, and explain 43 percent of the total dispersion in welfare. Finally, I show that a migration model without home bias overstates the migration response of agents. This underestimates the pass-through of local productivity to real wages and overestimates the efficiency costs associated with place-based policies.

Work in progress

“Employment sensitivity in Network Economies”
- with François de Soyres and Shekhar Tomar.

Pre-PhD Working Papers

“The effects of intraday foreign exchange markets operations in Latin America: results for Chile, Colombia, Mexico and Peru”, 2014, with Miguel Fuentes, Pablo Pincheira, Juan Manuel Julio, Hernán Rincón, Santiago García-Verdú, Marco Vega, Erick Lahura and Ramon Moreno. BIS Working Papers 462.

“On central bank interventions in the Mexican peso/dollar foreign exchange market”, 2013, with Santiago García-Verdú. BIS Working Papers 429.