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A Two-Part Bayesian Model with Elicited Priors to Analyze Longitudinal Government Expenditures in Latin America

Abstract

Longitudinal government expenditure data are often used in political science to assess politicians' agenda, presidents' distributive strategies, and coalition bargaining. Typically, this type of data are semicontinuous; contains some temporal dependence; and present a positive correlation between the probability of expenditure disbursed and the expected level of expenditure by each unit. In this thesis I use a Bayesian two-part model to separately estimate the likelihood of municipalities receiving national investments over time and mean expenditure trajectories among those chosen to receive national investments. I use elicited priors from fieldwork interviews with national and local politicians to estimate more precise posterior distributions. This approach extends to government expenditure data desegregated by states or municipalities. Applications to data from Brazil and Mexico uncovers two temporal patterns in government expenditures: funds are targeted to municipalities governed by co-partisan mayors, regardless of the president's vote share. Regions lacking either supportive voters or local allies receive little or no distributive funds whatsoever.

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