Essays on the political economy of inequality and redistribution

About this book

This dissertation deals with how the distribution of economic resources affects policy outcomes, particularly with regard with redistribution, from three different angles. The first chapter deals with campaign contributions, by proposing a new model of electoral politics based on two main assumptions: individual political participation is endogenous and can take two distinct forms, voting and contributing resources to campaigns. The model shows that the interaction between contributions and voting leads to an endogenous wealth bias in the political process. I then use this framework to reassess the relationship between inequality and redistribution. The model also delivers a number of testable predictions on how inequality will affect political participation, which are supported by data from US presidential elections. The second chapter considers the possibility of "non-institutional" channels through which demands over redistribution can be expressed, which could generically be called "revolutions", and analyzes its relationship with population. The essay documents a negative relationship between population and inequality in the cross-country data, and proposes an explanation based on the interaction of "institutional" and "revolutionary" channels of popular request for redistribution. This model generates additional predictions that refine that first stylized fact, and they are subject to extensive empirical scrutiny in a cross-country context. The data robustly confirm these predicted patterns. Finally, the third chapter focuses on corruption--more specifically, on the effect of political stability on incumbent officials' incentives to engage in corrupt behavior. The essay shows that high levels of instability can have different effects on different types of corruption, and that this interaction leads to a non-monotonic relationship approximating a U-shape between stability and corruption. It then provides support for this prediction using cross-country data.