joint with Nezih Guner and Claudio Luccioletti

Abstract

We use a spatial heterogeneous agent model of family formation to study the role of geography in shaping trends in marriage and inequality in the US. The United States has undergone dramatic shifts in household and family structures since the 1980s. Married female labor force participation increased significantly, marriage has declined, and positive assortative mating has risen. Along with a rising skill premium and a declining gender gap, income inequality among households has also widened. We document that these changes had an important geographic dimension: the decline in marriage was much more significant in smaller cities, and marital sorting declined in smaller cities but increased in larger ones. We interpret these facts within a model where households decide where to live, whether or not to get married, and with whom. The framework allows us to quantify the importance of each channel in shaping trends in marriage and inequality.

Abstract

This paper examines the effects of geographic heterogeneity in labor market returns on marriage market outcomes, and the impact of family ties on the geographic distribution of labor. I document that workers in cities that pay relatively lower wages to their occupation (i.e., workers who have higher potential pecuniary returns from migration) are less likely to marry and more likely to divorce. Through the lenses of a dynamic structural model, I assess the micro and macro implications of the interplay between marriage and migration. I find that, overall, the marriage market increases the concentration of workers in more productive locations.

joint with Giovanni Gallipoli

Abstract

Do workers derive different returns from similar jobs? Are earnings informative about changes in overall returns from work? We estimate the value of worker-occupation matches in an equilibrium model that distinguishes between wages and latent returns. We define a measure of employment rents that has three properties: (i) it reflects both wages and unobserved match values; (ii) it delivers a monetary metric for compensating differentials; (iii) it illustrates how the marginal workers within a match affect the rents of others. We show that earnings data reliably approximate the evolution of average rents between 1980 and 2018 despite differences in unobserved match values. The results highlight a dichotomy: while the existence of rents is due to latent values, their evolution is driven by productivity and technology.

joint with Giovanni Gallipoli

Abstract

We merge data on the nutritional content of a subset of packaged (bar-code level) food products to longitudinal home-scanner data on the shopping behavior of US households. We use a Random Forest regression to impute the nutritional content of the remaining food products. The resulting dataset is used to study the association between marital status and the dietary habits of the household members.

joint with Chenyu Hou

Abstract

Uncertainty about the fundamental aspects of the evolution of infections in the population (e.g. the infection rate and the fraction of infected population) is a prominent feature of newly discovered viruses. This paper studies the role of early testing as a tool available to policymakers for learning about the structural parameters underlying the evolution of a pandemic. The paper analyses the informational content of testing at the different stages of a pandemic and how learning through testing interacts with other instruments in the definition of the optimal policy.