results of such tests. In some cases, with appropriate knowledge of the corruption mechanism, the true values of the …

The ability to predict corruption is crucial to policy. 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. We … predictors of corruption, while public sector and political features play a secondary role. Our findings have implications for …

algorithms and, importantly, the basic structures of decision theory that it embeds. To make a problem amenable to algorithmic … application. We use decision theory, including behavioural economics, to highlight the choices embedded within this problem space … lockstep advancement in awareness and application of decision theory. Such awareness may help to mitigate some of the …