This thesis studies the economics of local labor markets. There are three chapters in the thesis, and each chapter studies how economic outcomes are affected by local labor market conditions. The first chapter studies the incidence of local labor demand shocks. This chapter starts from the observation that low-skill workers are comparatively immobile. When labor demand slumps in a city, college-educated workers tend to relocate whereas non college workers are disproportionately likely to remain to face declining wages and employment. A standard explanation of these facts is that mobility is more costly for low-skill workers. This chapter proposes and tests an alternative explanation, which is that the incidence of adverse shocks is borne in large part by (falling) real estate rental prices and (rising) social transfers. These factors reduce the real cost of living differentially for low-income workers and thus compensate them, in part or in full, for declining labor demand. I develop a spatial equilibrium model which, appropriately parameterized, identifies both the magnitude of unobserved mobility costs by skill and the shape of the local housing supply curve. Nonlinear reduced form estimates using U.S. Census data document that positive labor demand shocks increase population more than negative shocks reduce population, that this asymmetry is larger for lows kill workers, and that such an asymmetry is absent for wages, housing values, and rental prices. Estimates of the full model using a nonlinear, simultaneous equations GMM estimator suggest that (1) the asymmetric population response is primarily accounted for by an asymmetric housing supply curve, (2) the differential migration response by skill is primarily accounted for by transfer payments, and (3) estimated mobility costs are at most modest and are comparable for high-skill and low-skill workers, suggesting that the primary explanation for the comparative immobility of low-skilled workers is not higher mobility costs per se, but rather a lower incidence of adverse labor demand shocks. The second chapter, written jointly with Daron Acemoglu and Amy Finkelstein, studies how local area health spending responds to permanent changes in local area income. This chapter is motivated by the fact that health expenditures as a share of GDP have more than tripled over the last half century, and a common conjecture is that this is primarily a consequence of rising real per capita income, which more than doubled over the same period. We investigate this hypothesis empirically by instrumenting for local area income with time-series variation in global oil prices between 1970 and 1990 interacted with cross-sectional variation in the oil reserves across different areas of the Southern United States. This strategy enables us to capture both the partial equilibrium and the local general equilibrium effects of an increase in income on health expenditures. Our central estimate is an income elasticity of 0.7, with an elasticity of 1.1 as the upper end of the 95 percent confidence interval. Point estimates from alternative specifications fall on both sides of our central estimate, but are almost always less than 1. We also present evidence suggesting that there are unlikely to be substantial national or global general equilibrium effects of rising income on health spending, for example through induced innovation. Our overall reading of the evidence is that rising income is unlikely to be a major driver of the rising health share of GDP. The third chapter, written jointly with Kory Kroft, studies theoretically and empirically how optimal Unemployment Insurance (UI) benefits vary with local labor market conditions. Theoretically, we derive the relationship between the moral hazard cost of UI and the unemployment rate in a standard search model. The model motivates our empirical strategy which tests whether the effect of UI benefits on unemployment durations varies with the local unemployment rate. In our preferred specification, a one standard deviation increase in the local unemployment rate reduces the magnitude of the duration elasticity by 32%. Using this estimate to calibrate the optimal level of UI benefits, we find that a one standard deviation increase in the unemployment rate leads to a 6.4 percentage point increase in the optimal replacement rate. JEL classification: J61, 110, J65.