Abstract
The effect of corruption on economic growth has attracted interest in empirical development economics. The conventional view of corruption as impediment for growth has been challenged by the ‘grease-on-the-wheels’ hypothesis. We take a new perspective on the issue and suggest corruption as macro risk, referred to as a ‘gamble’ hypothesis. Using cross-country data and two alternative indicators of corruption, we find corruption to be a significant driver of heteroscedasticity in total productivity. This supports the new gamble hypothesis. We also note some misleading interpretations in the previously published frontier applications. To avoid these shortcomings, we apply a flexible semi-nonparametric estimator.
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