Corruption and Growth Under Weak Identification

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 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.

An Economic Model of Fair Use

The doctrine of fair use allows unauthorized copying of original works of art, music, and literature for limited purposes like criticism, research, and education, based on the rationale that copyright holders would consent to such uses if bargaining were possible. This paper develops the first formal analysis of fair use in an effort to derive the efficient legal standard for applying the doctrine. The model interprets copies and originals as differentiated products and defines fair use as a threshold separating permissible copying from infringement. Application of the analysis to several key cases (including the recent Napster case) shows that this interpretation is consistent with actual legal reasoning. The analysis also underscores the role of technology in shaping the efficient scope of fair use.