Specialized Learning and Political Polarization

This paper presents a model that demonstrates how developments in information technologies can generate increased political polarization in the absence of any changes in voter preferences. In contrast to the previous literature on the topic, the model abstracts away from possible ideological bias in the news media, and studies how specialization in information by the voters can generate political polarization. When there is heterogeneity among voters in terms of how much they care about different aspects of ideological policies, specialization in information allows for differentiation in learning strategies adopted by the electorate. Specialization allows voters to better respond to variables that influence their ideological positions, but that decreases their overall responsiveness to party platforms. In particular, equilibrium policies polarize more in fractionalized societies where there is greater disagreement about which issues matter the most. When the learning technology allows for specialization in finer subissues, it effectively transforms the society into a more fractionalized one without changing the underlying preferences of the voters, and therefore increases polarization. JEL Classification Numbers: D72, D80, Z13