In all modern bureaucracies, politicians retain some discretion in public employment decisions, which may lead to frictions in the selection process if political connections substitute for individual competence. Relying on detailed matched employer-employee data on the universe of public employees in Brazil over 1997–2014, and on a regression discontinuity design in close electoral races, we establish three main findings. First, political connections are a key and quantitatively large determinant of employment in public organizations, for both bureaucrats and frontline providers. Second, patronage is an important mechanism behind this result. Third, political considerations lead to the selection of less competent individuals. (JEL D72, D73, J45, O17)

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This paper investigates the consequences of liquidation and reorganization on the allocation and subsequent utilization of assets in bankruptcy. Using the random assignment of judges to bankruptcy cases as a natural experiment that forces some firms into liquidation, we find that the long‐run utilization of assets of liquidated firms is lower relative to assets of reorganized firms. These effects are concentrated in thin markets with few potential users and in areas with low access to finance. These findings suggest that when search frictions are large, liquidation can lead to inefficient allocation of assets in bankruptcy.

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.

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