We examine spatial spillovers in institutional development. Dependent variables are institutional measures reflecting politics, law, and governmental administration. The explanatory variable of interest is the level of institutions in bordering countries—a spatial lag of the dependent variable. Our spatial model directly leads to the identification strategy for the endogenous spatial lag. We implement new results in spatial econometrics to counter missing-data problems usually rife in spatial empirics. Spatial institutional spillovers are statistically significant and economically important. A counter-factual exercise – the non-existence of the USSR – reveals large direct and indirect spillovers. Numerous robustness exercises bolster conclusions, including yearly cross-section regressions, fixed effects estimates, and adding many extra explanatory variables. Moreover, we provide a new theoretical result showing the robustness of estimates in the presence of omitted variables. We extend the core model, allowing different effects for better and worse neighbors, using inverse distance weights, estimating the spatial-Durbin model, and using Polity's institutional measure.