Is it possible to predict malfeasance in public procurement? With the proliferation of e-procurement systems in the public sector, anti-corruption agencies and watchdog organizations have access to valuable sources of information with which to identify transactions that are likely to become troublesome and why. In this article, we discuss the promises and challenges of using machine learning models to predict inefficiency and corruption in public procurement. We illustrate this approach with a dataset with more than two million public procurement contracts in Colombia. We trained machine learning models to predict which of them will result in corruption investigations, a breach of contract, or implementation inefficiencies. We then discuss how our models can help practitioners better understand the drivers of corruption and inefficiency in public procurement. Our approach will be useful to governments interested in exploiting large administrative datasets to improve the provision of public goods, and it highlights some of the tradeoffs and challenges that they might face throughout this process.

What are the effects of natural disasters on electoral results? Some authors claim that catastrophes have a negative effect on the survival of leaders in a democracy because voters have a propensity to punish politicians for not preventing or poorly handling a crisis. In contrast, this paper finds that these events might be beneficial for leaders. Disasters are linked to leader survival through clientelism: they generate an inflow of resources in the form of aid, which increase money for buying votes. Analyzing the rainy season of 2010-2011 in Colombia, considered its worst disaster in history, I use a difference-indifferences strategy to show that in the local election incumbent parties benefited from the disaster. The result is robust to different specifications and alternative explanations. Moreover, places receiving more aid and those with judicial evidence of vote-buying irregularities, are more likely to reelect the incumbent, supporting the mechanism proposed by this paper. * I would like to thank Oeindrila Dube, Rebecca Morton, Adam Przeworski and Alastair Smith for helpful comments. Maria Paula Contreras, Diego Eslava, and Gabriel Angarita provided superb research assistance. The usual caveat applies.

Using rich micro-data from Brazil, we show that multiple machine learning models display high levels of performance in predicting municipality-level corruption in public spending. Measures of private sector activity, financial development, and human capital are the strongest predictors of corruption, while public sector and political features play a secondary role. Our findings have implications for the design and cost-effectiveness of various anti-corruption policies.

What are the effects of war on political behavior? Colombia is an interesting case in which conflict and elections coexist, and illegal armed groups intentionally affect electoral outcomes. Nonetheless, groups have used different strategies to alter these results. This paper argues that differential effects of violence on electoral outcomes are the result of deliberate strategies followed by illegal groups, which in turn result from military conditions that differ between them. Using panel data from Senate elections from 1994 to 2006 and an instrumental variables approach to address potential endogeneity concerns, this paper shows that guerrilla violence decreases turnout, while paramilitary violence has no effect on participation, but reduces electoral competition and benefits non-traditional third parties. FARC violence is significantly higher during election years, while paramilitary violence is lower. This is consistent with the hypothesis that the guerrillas’ strategy is to sabotage elections, while paramilitaries establish alliances with certain candidates.

Political clientelism is a dyadic relation in which a politician (the patron) gives material goods and services to a citizen (the client), in exchange for political support. If, at different stages of this relationship, both the patron and the client have incentives to defect and not honor informal agreements, what makes clientelism self-enforcing? The following paper presents a game-theoretical model of political clientelism in which a candidate disciplines a majority of voters through the promise of a future flow of benefits. A mixed strategy involving a randomized allocation of resources among constituencies makes clientelism feasible when the politician’s action is contingent on the result of the election. Higher campaign budgets and lower voter aversion towards clientelistic parties, as well as higher patience and higher heterogeneity across groups of voters, make clientelism more likely. Swing voters tend to be gifted more frequently than core supporters with this frequency increasing as group heterogeneity increases, presenting a positive association.

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We study experimentally the properties of the majority runoff system and compare them to the ones of plurality rule, in the setup of a divided majority. Our focus is on Duverger's famous predictions that the plurality rule leads to a higher coordination of votes on a limited number of candidates than the majority runoff rule. Our experiments show that, in contradiction with Duverger's predictions, coordination forces are strong in majority runoff elections. We indeed observe similar levels of coordination under both rules, even when sincere voting is an equilibrium only under majority runoff. Our results suggest that the apparent desire to coordinate, and not vote sincerely, under the majority runoff rule is to some extent not rational. Finally, we find insignificant differences between runoff and plurality systems in terms of both electoral outcomes and welfare. This is so exactly because coordination forces are strong under both rules. But, this does not mean that the two rules are equally socially desirable. Majority runoff rule entails an additional cost: second rounds that take place frequently.