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Transparency, Accountability, and Corruption Displacement

$315,415FY2014SBENSF

University Of California-San Diego, La Jolla CA

Investigators

Abstract

Despite ample funding from the international community, anti-corruption interventions have largely failed to contain corruption. Scholars and policymakers agree that increasing transparency and improving accountability should reduce corruption. Armed with information about corrupt actions, citizens will punish corrupt officials. Institutions of accountability are a key part of this mechanism, as they provide the channel through which citizens and political superiors can act on the information. Yet, the evidence to support these arguments is mixed. Corruption is common across different transparency and accountability environments, from countries rich in information and avenues for taking action against corruption to countries lacking in both. This project will address several possible reasons for this divergence between theory and results. Drawing on work in behavioral economics, it will discern whether politicians respond strategically to anti-corruption interventions by shifting their corruption to forms less vulnerable to detection and punishment. Furthermore, it will combine top-down anti-corruption efforts, such as large-scale audits of accounts, with a bottom-up effort targeting citizens, which typically are executed separately. Finally, the interventions in this project will educate citizens about the roles and responsibilities of government and the action options available to them, in addition to informing them about corruption among their government officials. The interventions of this project will occur in Malawi's local (district) government. To address some of the deficiencies of past anti-corruption interventions, the interventions will combine a regularly scheduled top-down audit of the district government with a bottom-up intervention designed to involve citizens in the anti-corruption process and educate them about their government and avenues of action available to them. The citizen transparency intervention will include broadcasting the main findings about their officials on the local radio, providing written reports about the treated officials to a randomly selected group of citizens, and calling selected district officials before a group of chiefs, civil society representatives, media representatives, and a randomly selected group of citizens to discuss the findings. The meeting will also educate citizens about the avenues of reporting corruption and demanding a reduction in corruption available to them. Shifts in corruption patterns within each district will be measured by conducting a survey of the district officials after the transparency interventions and comparing the results to the 2013 baseline survey. This work holds great promise for both policymaking and science. Donors and international organizations believe that corruption undermines prosperous and peaceful governments in Africa. By providing a specific theory of behavior and creating precise measures of individual corruption, this project will advance the debate regarding institutions, politician incentives, and behavior. By using randomized experiments, this project employs some of the most rigorous designs and tests available to social scientists. Finally, by sampling actual politicians in the surveys measuring outcomes, this project explores political phenomena with those who actually practice politics. Insights from this project can prove invaluable to inform not just the study of corruption, but also its practical dimensions. The design uses actual audits executed by official government personnel, making this study's findings and implications very relevant to those interested in combating corruption. The project findings will be presented to policymakers and researchers in the form of discussions, policy papers, and research articles to academic, government, and policy audiences. This project will also train dozens of citizens -private and government officials- in research methods.

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