Homeownership and the Distributional Effects of Local Shocks

I develop a dynamic quantitative spatial framework that combines key features of quantitative spatial and lifecycle housing models to study the distributional effects of spatially heterogeneous shocks. The model features many locations, moving costs, uninsurable income risk, lifecycle dynamics, housing tenure choice and housing frictions. The model is set in continuous time, which enables efficient computation. I apply the framework to analyze the welfare effects of heterogeneous productivity shocks across U.S. cities. I find that local productivity shocks have important distributional consequences: on average, a 1% shock to local productivity raises residents’ welfare by 0.37%. The pass-through from a local productivity shock to welfare varies substantially by age and housing tenure. I show that homeownership plays a central role in spatial redistribution: in an otherwise identical model without homeownership, the average welfare effect of a 1% local productivity shock is just 0.03%. This is because house price changes counteract the welfare effects of wage changes for renters, but augment them for owners. These results suggest that accounting for homeownership is essential for understanding the distributional effects of spatially heterogeneous shocks.