S cholars typically understand vote buying as offering particularistic benefits in exchange for vote choices. This depiction of vote buying presents a puzzle: with the secret ballot, what prevents individuals from accepting rewards and then voting as they wish? An alternative explanation, which I term "turnout buying," suggests why parties might offer rewards even if they cannot monitor vote choices. By rewarding unmobilized supporters for showing up at the polls, parties can activate their passive constituencies. Because turnout buying targets supporters, it only requires monitoring whether individuals vote. Much of what scholars interpret as vote buying may actually be turnout buying. Reward targeting helps to distinguish between these strategies. Whereas Stokes's vote-buying model predicts that parties target moderate opposers, a model of turnout buying predicts that they target strong supporters. Although the two strategies coexist, empirical tests suggest that Argentine survey data in Stokes 2005 are more consistent with turnout buying.
Although many studies of clientelism focus exclusively on vote buying, political machines often employ diverse portfolios of strategies. We provide a theoretical framework and formal model to explain how and why machines mix four clientelist strategies during elections: vote buying, turnout buying, abstention buying, and double persuasion. Machines tailor their portfolios to the political preferences and voting costs of the electorate. They also adapt their mix to at least five contextual factors: compulsory voting, ballot secrecy, political salience, machine support, and political polarization. Our analysis yields numerous insights, such as why the introduction of compulsory voting may increase vote buying, and why enhanced ballot secrecy may increase turnout buying and abstention buying. Evidence from various countries is consistent with our predictions and suggests the need for empirical studies to pay closer attention to the ways in which machines combine clientelist strategies.
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