This study investigates the effects of corruption on tax revenues for Central African countries using data for the period 2002-2020. While exploring the possible corrosive effects of corruption on tax revenues, variables such as inflation, income, and industry-added value are also considered. We employed the conditional quantile regression method, and the robustness checks our findings. Our findings can serve as a guide for policymakers in making decisions in the field of political economy that potential reforms in the revenue system and administration are expected to yield positive results.
Corruption, Central African countries, Conditional quantile regression