Mobilizing for Elections: Patronage and Political Machines in Southeast Asia [Hardcover]

Provides a new framework for understanding how and why politicians distribute patronage to win elections using Southeast Asian case studies.This book compares patronage politics in Southeast Asia, examining the sources and implications of cross-national and sub-national differences. It will be useful for scholars and students interested in comparative and Southeast Asian politics, electoral politics, clientelism and patronage, and the historical development of political institutions.This book compares patronage politics in Southeast Asia, examining the sources and implications of cross-national and sub-national differences. It will be useful for scholars and students interested in comparative and Southeast Asian politics, electoral politics, clientelism and patronage, and the historical development of political institutions.Politicians in Southeast Asia, as in many other regions, win elections by distributing cash, goods, jobs, projects, and other benefits to supporters, but the ways in which they do this vary tremendously, both across and within countries. Mobilizing for Elections presents a new framework for analyzing variation in patronage democracies, focusing on distinct forms of patronage and different networks through which it is distributed. The book draws on an extensive, multi-country, multi-year research effort involving interactions with hundreds of politicians and vote brokers, as well as surveys of voters and political campaigners across the region. Chapters explore how local machines in the Philippines, ad hoc election teams in Indonesia, and political parties in Malaysia pursue distinctive clusters of strategies of patronage distribution  what the authors term electoral mobilization regimes. In doing so, the book shows how and why patronage politics varies, and how it works on the ground.1. Patronage and Political Machines in Southeast Asia; 2. Historical and Institutional Foundations: National Parties, Ad Hoc Teams, and Local Machines; 4. TargetinglÓ5