|This centre is a member of The LSE Research Laboratory [RLAB]: CASE | CEE | CEP | FMG | SERC | STICERD||Cookies?|
Paper No' EOPP 034: | Full paper
Save Reference as: BibTeX File | EndNote Import File
Keywords: income dynamics; redistributive politics, polarization, Bayesian learning, Latin America.
JEL Classification: D31, D72, D83, P16.
Is hard copy/paper copy available? YES - Paper Copy Still In Print.
This Paper is published under the following series: Economic Organisation and Public Policy Discussion Papers
Share this page: Google Bookmarks | Facebook | Twitter
Abstract:The political left turn in Latin America, which lagged its transition to liberalized market economies by a decade or more, challenges conventional economic explanations of voting behavior. While the implications of upward mobility for the political preferences of forward-looking voters have been studied, neither the upward mobility model nor conventional myopic median voter models are well equipped to explain Latin America’s political transformation. This paper generalizes the forward-looking voter model to consider a broad range of dynamic processes. When voters have full information on the nature of income dynamics in a transition economy, we show that strong support for redistributive policies will materialize rapidly if income dynamics offer few prospects of upward mobility for key sections of the electorate. In contrast, when voters have imperfect information, our model predicts a slow and politically polarizing shift toward redistributive voter preferences under these same non-concave income dynamics. Simulation using fitted income dynamics for two Latin American economies suggests that the imperfect information model better accounts for the observed shift back to the left in Latin America, and that this generalized, forward-looking voter approach may offer additional insights about political dynamics in other transition economies.
Copyright © STICERD & LSE 2005 - 2014 | LSE, Houghton Street, London WC2A 2AE | Tel: +44(0)20 7955 6699 | Email: email@example.com | Site updated 23 April 2014