Impact of Corruption on Per-Capita Income Growth: A Meta-Analysis

Abstract

Corruption is an indication of weak institutional quality and could have potentially adverse effects on economic growth. To synthesize the empirical findings, we extracted 406 effect estimates from 32 studies, following a peer-reviewed and pre-published systematic review protocol. The evidence base indicates that the partial correlation coefficients for the effect of corruption on per-capita GDP growth are predominantly negative and tend to be significant beyond study selection bias. However, these results from simple precision-effect and funnel-asymmetry tests (PETs and FATs) also indicate that the association is weak (about 0.05-0.10) and may conceal substantial between-study variations. Meta-regression analysis (MRA) accounts for about 29-40 percent of the variations and indicates that the negative association between corruption and per-capita GDP growth is not robust to inclusion of moderating variables reflecting study characteristics. We also report that direct effect of corruption is weaker than indirect effects, adverse effect of corruption in low-income countries is less adverse than mixed-country samples, and journal articles tend to report stronger negative effects.