Direct and Spillover Effects from Staggered Adoption of Health Policies: Evidence from Covid-19 Stay-at-Home Orders

Local policies can have substantial spillovers both across geographies and markets. We estimate U.S. county level direct and spillover effects of Stay-at-Home-Orders (SHOs) aimed at containing the spread of COVID-19 on mobility and social interaction measures. We propose a modified difference-in-difference regression design, based on contiguous-county triplets. This approach compares treated counties, which adopted the SHO, and neighbors, to the neighbor’s neighbors, which we term hinterland, counties. We find that mobility in neighboring counties declined by a third to a half as much as in the treated locations. These spillover effects are concentrated in neighbors that share media markets with treated counties. Using directional mobility data, we decompose the spillover decline in mobility into reductions in external visits coming from the treated county and an even stronger voluntary decline in the neighbor county’s own traffic. Together, our results provide strong evidence that SHOs operate through information sharing and illustrate the quantitative importance of voluntary social distancing. The finding that the estimated spillovers are in the same direction as the direct effects casts doubt on the prevailing narrative that a more nationally coordinated policy response would have accomplished a greater reduction in mobility and contacts.