Corruption And Growth Under Weak Identification
AbstractThe goal of this paper is to revisit the influential work of Mauro  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 , 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  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 . 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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Bibliographic InfoArticle provided by Western Economic Association International in its journal Economic Inquiry.
Volume (Year): 49 (2011)
Issue (Month): 1 (01)
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Other versions of this item:
- C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
- D73 - Microeconomics - - Analysis of Collective Decision-Making - - - Bureaucracy; Administrative Processes in Public Organizations; Corruption
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