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Corruption, democracy and economic performance in Sub-Saharan Africa.

Africa
Comparative Politics
Democracy
Development
Political Economy
Developing World Politics
Corruption
Empirical
Evans T. Awuni
Willy Brandt School of Public Policy, Universität Erfurt
Evans T. Awuni
Willy Brandt School of Public Policy, Universität Erfurt

Abstract

The entire African continent has been labelled as the most corrupt in the world. Not only is it considered corrupt but also less democratic and the poorest in terms of economic performance. Various researchers and political commentators attempt to link the political and economic woes of Africa to the prevalence of corruption. There is also a school of thought that connects the potential of the electoral mechanism in holding politicians accountable as a way in which democracy may reduce corruption and positively induce economic performance. Yet, this position is highly contested and the theoretical and empirical debate surrounding these remain unsettled. For example, one could argue that where market failure is pervasive and institutions are inefficient (as the case may be in Africa), corruption may facilitate economic performance by smoothing assorted development processes but democracy may be hampered as corrupt politicians may persistently buy their way to power. This paper contributes to both the theoretical and empirical debate on the corruption, democracy and economic performance interrelationship in sub-Sahara Africa by adopting a creative approach to studying both perception and real/experienced corruption. The study firstly uses the Transparency International’s corruption perception index, the World Bank’s control of corruption estimates as well as Medina and Schneider’s estimate of shadow economies, and different measures of economic performance such as GDP per capita and GDP growth. Using panel data involving 48 sub-Saharan African countries and applying different estimation techniques including Instrumental Variables (IV) approach, pooled ordinary least squares and random-effects models, the results are mixed. To test the robustness of the results, a second dataset, which captures real corruption experiences in the form of paid bribe, is then used.