Are economically diverse cities more resilient? Building on the insights of a simple model of labor flows, we document using matched employer-employee micro-level data from France that more diverse cities–occupationally or industrially–experience shallower decreases in gross outflows and smaller declines in employment following negative labor demand shocks. We then show how such data also allows us to measure the implied insurance value of a city using a sufficient-statistics approach in a canonical random utility dynamic discrete choice model across sectors, occupations, and cities. In this framework, the diversity of outside options impacts a worker’s welfare. Finally, we formally investigate the relationship between measured economic diversity and the theory-implied insurance value across French cities.

We develop a simple methodology to estimate the heterogeneous welfare effects of any small shock to residents within a city. The methodology relies only on modest assumptions regarding residents’ choice of where to consume and work and delivers an expression that shows that the welfare elasticity to any small shock can be written as a function of (1) the spatial patterns of consumption and income; and (2) the price and wage effects of the shock. We then apply this methodology to ask the question: Is tourism good for locals? Using detailed spatial data on expenditure and income patterns of residents in Barcelona, we show that plausibly exogenous shifts in tourist expenditure due to compositional differences in their country of origin across time and over space in the city crowds out local expenditure by increasing prices but partially compensates through increases in wages. The incidence of the tourism shock, however, is highly heterogeneous across the city, with inner city residents bearing the the largest welfare losses and peripheral residents enjoying the greatest welfare gains

The standard search and matching model does not does not reproduce the cyclical fluctuations in vacancies and unemployment nor the null contemporaneous correlation between the vacancy-unemployment ratio and the labor productivity from 1990 to 2020 in the US. This paper studies the role of shocks to beliefs combined with adaptive learning about wages in a search and matching model applied to the business cycle. The resulting learning model fits US data better than its non sentiment version and than its rational expectation counterpart. Specifically, learning explains the low correlation, while belief shocks emerge as a key driver of labor market fluctuations. The model is also consistent with wage forecasts made by professional forecasters.

This paper investigates the importance of complementarities between education and technology adoption in accounting for cross-country income differences. We document that, across countries, education is robustly correlated with measures of technology adoption and usage and with the prevalence of more traditional forms of organization of production where technology adoption is more limited and productivity is lower. Motivated by this, we build a general equilibrium model with endogenous investments in human capital. Production can take place in sole proprietorships where education does not determine technology adoption, or in a more modern sector where managers hire a workforce and the productivity of a given technology depends on their education level. Economies differ in terms of barriers to education and barriers to entering the modern sector. We calibrate a version with no barriers to relevant features of the U.S. economy. Increasing the aforementioned barriers to match relevant targets for the average country in the bottom quartile of the income distribution leads to an income of roughly one third os the U.S. level. A model where individuals acquire education, but where technology adoption is absent, can only generate a fall to about one-half of the U.S. level. We conclude that the interaction between education and technology adoption is quantitatively meaningful in accounting for the cross-country income dispersion.