Research
Working Papers
I show that unobserved sorting patterns of firms and workers across space can account for the tight link between rising aggregate wage inequality and rising spatial inequality in West Germany. Two-sided sorting patterns of workers and firms interact with a change in technology to produce a spatially concentrated increase in inequality, driving up regional disparities. These sorting patterns are determined jointly in equilibrium and depend on theoretical objects that are difficult to measure in the data. This paper develops a novel bi-clustering method to recover these objects empirically and uses these results to structurally estimate a dynamic spatial search model with two-sided sorting. I find that regional sorting of firms is more pronounced than regional sorting of workers and the former is an important determinant of workers' job ladders and lifetime values. Compensating differentials between regions are large, driven in part by better labor market outcomes in rich places. The model allows me to consider the redistributive effects of spatial policy, which I find to be strong.
Job Amenity Shocks and Labor Reallocation (joint with Sadhika Bagga, Aysegul Sahin, and Gianluca Violante)
We introduce aggregate shocks to the value of job amenities in a frictional equilibrium model of the labor market with on-the-job search, where the job creation cost is sunk and quits create vacancies. We examine how key labor market indicators respond to this shock: when the valuation of the amenity is heterogeneous in the population, labor reallocation ensues. A calibrated version of the model can quantitatively account for many peculiar traits of the post-pandemic labor market recovery through three aggregate shocks: a temporary fall in productivity to account for the short, but sharp, downturn; a rise in the opportunity cost of work; and, crucially, a persistent increase in the value that workers put on job amenities. Cross-sectoral patterns of vacancies, quit rates, and job-filling rates where sectors are ranked by the share of teleworkable jobs offer support to the view that the key amenity in question is the ability to work remotely.
Publications and Accepted Papers
Labor Market Selection and the Dynamics of a Recovery
Accepted, Journal of Political Economy Macroeconomics, 2025 [new draft - January 2025]
This paper explores the role of selection in shaping the dynamics of unemployment during recoveries. A matching model with many-to-many matching and permanent worker heterogeneity delivers such selection and generates recovery unemployment dynamics that mirror the data closely. In line with empirical evidence, the model predicts that, during a recession, firms become more selective and job finding rates decline more for less productive, unemployed workers. This reinforces negative composition effects and creates a feedback loop, which slows down the recovery. I find empirical support for the cyclicality of job seeker quality implied by the model in data from the NLSY.
We study a general equilibrium model of the labor market in which agents slowly learn about their suitability for jobs. Our model reproduces desirable features of the data, many of which standard models fail to replicate. We explore how, in such an environment, asymmetric information can lead to substantial misallocation. We calibrate our model to US data and quantify the welfare loss arising from misallocation due to informational frictions. The tractability of the model allows us to explore the responsiveness of wages and employment to an aggregate shock. We find that wage rigidity arises endogenously because of protracted learning, and in line with the data, the model is able to generate a larger and more persistent employment response.
A new IV approach for estimating the efficacy of macroprudential measures (joint with Niklas Gadatsch and Isabel Schnabel) - Economics Letters, 2018
We propose a new identification strategy to assess the efficacy of macroprudential measures. We use a novel instrumental variable based on the idea that a politically sensitive macroprudential measure is more likely to be implemented if a politically independent institution, such as a central bank, is in charge. Our results show that borrower-based macroprudential measures have had a strong and statistically significant dampening effect on credit growth in the European Union.
Work in Progress
Who will gain and who will lose from AI-induced task automation? This paper develops, estimates, and applies a quantitative task-based model to answer this question. In this theory, workers possess heterogeneous portfolios of task-specific skills, which govern both their exposure to productivity gains due to task complementarity and their ability to adapt to displacement by switching occupation. Leveraging the structure of the model and Bayesian techniques, we estimate the distribution of (unobserved) multi-dimensional skills. To implement our estimation, we use data from the NLSY and LLM-generated occupational time diaries. The estimated model matches salient empirical features of worker mobility. We use our framework to quantify the distribution of dynamic earnings effects due to frontier AI technologies. As a proof-of-concept, we study the labor market impact of self-driving vehicles; the findings highlight the importance of accounting for within-occupation heterogeneity. In ongoing work, we are extending theory, estimation, and our quantitative analysis of AI-induced automation.
An Assignment Model Approach to the Labor Share (joint with Georgios Nikolakoudis and Narek Alexanian)