We document a statistical association between the severity of the persecution, displacement and mass murder of Jews by the Nazis during World War II and long-run economic and political outcomes within Russia. Cities that experienced the Holocaust most intensely have grown less, and both cities and administrative districts (oblasts) where the Holocaust had the largest impact have worse economic and political outcomes since the collapse of the Soviet Union. We provide evidence that the lasting impact of the Holocaust may be attributable to a permanent change it induced in the social structure across different regions of Russia.

We study the (perfect Bayesian) equilibrium of a sequential learning model over a general social network. Each individual receives a signal about the underlying state of the world, observes the past actions of a stochastically generated neighbourhood of individuals, and chooses one of two possible actions. The stochastic process generating the neighbourhoods defines the network topology. We characterize pure strategy equilibria for arbitrary stochastic and deterministic social networks and characterize the conditions under which there will be asymptotic learning—convergence (in probability) to the right action as the social network becomes large. We show that when private beliefs are unbounded (meaning that the implied likelihood ratios are unbounded), there will be asymptotic learning as long as there is some minimal amount of “expansion in observations”. We also characterize conditions under which there will be asymptotic learning when private beliefs are bounded.