Citizen Participation and Political Trust in Latin America and the Caribbean: A Machine Learning Approach

Abstract

This paper advances the understanding of the linkages between trust in government and citizen participation in Latin America and the Caribbean, using machine learning techniques and Latinobarómetro 2020 data. Proponents of the concept of stealth democracy argue that an inverse relationship exists between political trust and citizen participation, while deliberative democracy theorists claim the opposite. The paper estimates that trust in national governments or other governmental institutions plays neither a dominant nor consistent role in driving political participation. Instead, interest in politics, personal circumstances such as experience of crime and discrimination, and socioeconomic aspects appear to drive citizen participation much more strongly in the Latin America and the Caribbean region. This is true across models imposing simple linear trends (logit and lasso) and others allowing for nonlinear and complex relations (decision trees). The results vary across the type of participation—signing a petition, participation in demonstrations, or involvement in a community issue—which the paper attributes to increasing net costs associated with participation.