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There is current a large concern with corruption around the world as it may be one of the causes for lagging development. There is also a concern that corrupt government will succeed to stay in power using the money obtained in corruption activities to finance political campaigns. Consequently, corruption might jeopardize economic development for a long period of time and questions democracy. To test the consequences and causes of corruption we need to measure the phenomenon. Traditional measures rely on perception surveys despite the shortcomings of these measures. Field and natural experiments or even survey experiments are other alternatives to measure the phenomenon. In this paper we review the measures available in the literature and propose an index based on objective information from random audit reports. We show that this index is a tool to analyze municipalities in Brazil and that our index is consistent with expected (stylized) behavior, it is relatively easy to compute, and it is normalized between 0 and 1. ; Existe no mundo hoje em dia uma grande preocupação com corrupção. Há uma percepção geral de que a corrupção pode ser uma das causas para o desenvolvimento tardio. Também há uma preocupação de que governos corruptos seriam bem sucedidos em manter-se no poder utilizando-se do dinheiro obtido com atividades corruptas para financiar suas campanhas eleitorais. Consequentemente, a corrupção pode comprometer o desenvolvimento econômico por um longo período de tempo e também colocar em xeque a democracia. Para testar as consequências e causas da corrupção é necessário, antes de tudo, medir o fenômeno. As medidas tradicionais partem de pesquisas de percepção com todos os problemas relacionados a essa medida. Experimentos naturais e de campo, ou até experimentos com pesquisa de campo são outras alternativas para medir o fenômeno. Neste artigo revisamos as medidas disponíveis na literatura e propomos um índice baseado em informações objetivas de relatórios de auditoria aleatória. Mostramos que o índice ...

While corruption is documented to have high social costs, the mechanisms that enable and deter corruption are not entirely understood. This paper takes advantage of the introduction of a random-audits program in Brazil, for which the only practical effect is information disclosure, to assess the effects of monitoring on corruption deterrence: because auditors were entitled to investigate transfers that occurred prior to the time of audit, we are able to compare incumbents' decisions when they did not know they could be audited with their subsequent decisions, when they knew they had a much higher probability of being exposed. We depart from a simple theoretical model to derive empirically testable predictions, which are contingent upon local constraints and embezzlement opportunities, of the effects of the program on the prevalence of corruption. The results are that corruption dramatically dropped after the program was introduced; nevertheless, the decrease in corruption has not led to higher compliance or better health outcomes. Politicians seem to have adapted, and irregularities have only moved to where it is less straightforward to identify corruption.