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Corruption and Growth Under Weak Identification

  • Philip Shaw

    (University of Connecticut)

  • Marina-Selini Katsaiti

    (University of Connecticut)

  • Marius Jurgilas

    (University of Connecticut)

The goal of this paper is to revisit the influential work of Mauro [1995] focusing on the strength of his results under weak identification. He finds a negative impact of corruption on investment and economic growth that appears to be robust to endogeneity when using two-stage least squares (2SLS). Since the inception of Mauro [1995], much literature has focused on 2SLS methods revealing the dangers of estimation and thus "traditional" types of inference under weak identification. We reproduce the original results of Mauro [1995] with a high level of confidence and show that the instrument used in the original work is in fact "weak" as defined by Staiger and Stock [1997]. Thus we update the analysis using a test statistic robust to weak instruments. Our results suggest that under Mauro's original model there is a high probability that the parameters of interest are locally almost unidentified in multivariate specifications. To address this problem, we also investigate other instruments commonly used in the corruption literature and obtain similar results. After identifying an instrument with sufficient strength we fail to reject a zero effect of corruption on investment and economic growth.

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Paper provided by University of Connecticut, Department of Economics in its series Working papers with number 2006-17.

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Length: 26 pages
Date of creation: Sep 2006
Date of revision: Mar 2007
Handle: RePEc:uct:uconnp:2006-17
Note: The authors would like to thank Paulo Mauro, Gautam Tripathi, Nicholas Shunda, Christian Zimmermann, and Francis Ahking for comments and suggestions. We would also like to thank the contributing participants of the Sixth Annual Missouri Economics Conference for their valuable feedback.
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