Unemployment rates differ widely across local labor markets. I offer new empirical evidence that high local unemployment emerges because of elevated local job-losing rates. Local employers, rather than local workers or location-specific factors, account for most of the spatial gaps in job stability. I propose a theory in which spatial differences in job loss emerge in equilibrium because of systematic differences between employers across local labor markets. The spatial sorting decisions of employers in turn shape heterogeneity across locations. Labor market frictions induce productive employers to overvalue locating close to each other. The optimal policy incentivizes them to relocate toward areas with high job-losing rates, providing a rationale for commonly used place-based policies. I estimate the model using French administrative data. The estimated model accounts for over three-quarters of the cross-sectional dispersion in unemployment rates and for the respective contributions of job-losing and job-finding rates. Inefficient location choices by employers amplify spatial unemployment differentials fivefold. Both real-world and optimal place-based policies can yield sizable local and aggregate welfare gains.

This article estimates that the macroeconomic damages from climate change are an order of magnitude larger than previously thought. Exploiting natural global temperature variability, we find that 1ºC warming reduces world GDP by over 20% in the long run. Global temperature correlates strongly with extreme climatic events, unlike country-level temperature used in previous work, explaining our larger estimate. We use this evidence to estimate damage functions in a neoclassical growth model. Business-as-usual warming implies a present welfare loss of more than 30%, and a social cost of carbon in excess of $1,200 per ton. These impacts suggest that unilateral decarbonization policy is cost-effective for large countries such as the United States.