Before revision: We propose a simple cross-sectional research design to identify causal effects that is robust to unobservable heterogeneity . When many observational units are adjacent , it may be sufficient to regress the "spatial first differences" (SFD) of the outcome on the treatment and omit all covariates.
After revision: We propose a simple cross-sectional research design to identify causal effects in the presence of unobservable heterogeneity without instruments. When units are dense in physical space , it may be sufficient to regress the "spatial first differences" (SFD) of the outcome on the treatment and omit all covariates.