Learning, proximity and voting: theory and empirical evidence from nuclear referenda

This paper presents novel evidence on the pattern of voting in referenda and develops a spatial learning model that helps explain such behavior. In particular, we shed light on the determinants of voters' choices over nuclear power using data on two Italian referenda. Exploiting the panel structure of the data, we document that voting against nuclear power increases, whenever the distance from the closest nuclear plant decreases. However, we detect a different voting behavior between municipalities close to existing reactors and those close to proposed ones. A possible explanation is that many citizens hold more precise information on nuclear safety because they have experienced the presence of a reactor in their vicinity for many years. Therefore, we propose a model of voting with endogenous information acquisition interacting both proximity and learning effects, whose results are compatible with the empirical findings. Citizens receive public and private signals and revise their beliefs on the risk of living close to a plant. Such revision process is nested into a spatial voting model establishing conditions for a similar or different voting behavior of the electorate based on the proximity from the reactor.