Corruption and economic development in energy-rich economies

Comparative Economic Studies, June, 2009 by Yelena Kalyuzhnova, Ali M. Kutan, Taner Yigit

CONCLUSION AND POLICY IMPLICATIONS

We have tested several hypotheses regarding the determinants of corruption in energy-rich economies. Concerning our first hypothesis, we found that easing regulations on business activity reduces corruption. With respect to our second hypothesis, we find results that establishing a more democratic regime improves corruption rankings. Testing our third hypothesis, we observe that energy-rich countries with a higher level of education tend to have less corruption. For the last two hypotheses, we found that there is no bi-causality between corruption and the GDP per capita growth rate, but that there is one between corruption and the level of GDP per capita. Corruption reduces both the growth rate of GDP per capita and its level while the level of GDP per capita only affects corruption, suggesting that it is only the higher level of economic development, measured by the level of per capita GDP, that reduces corruption.

These results suggest that corruption is not only a threat for economic growth but also for economic development and improvements over time in the standard of living in energy-rich countries. On the other hand, since corruption reacts only to GDP per capita but not necessarily the growth rate of GDP, policy makers need to design long-term development strategies to fight against corruption. Our results from the GDP per capita regression suggest that improvements in democracy, fiscal policy, and energy production can improve the long-term sustainable development of energy-rich countries and hence aid in their fight against corruption.

In addition, we have discovered some important linkages between our resource-abundance proxies and socio-economic variables such as education and the political regime. We have also observed that resource abundance may not necessarily hurt economic development in energy-rich countries. Without careful modelling of such linkages, it would be difficult to correctly explain the patterns of corruption and growth in energy-rich economies. In this sense, our paper has provided some methodological insights on modelling corruption and growth in countries with rich energy-specific assets, and this modelling strategy may also be applicable to countries that posses other types of natural resources.

APPENDIX

DATA DESCRIPTION

In this Appendix, we describe the variables which we used in the presented regressions.

COR: Corruption Rank. Source: Transparency International, http:// www.transparency.org/policy_research/surveys_indices/cpi, accessed 22 May 2007.

Energy-specific variables

BARREL: Oil production scaled by GDP per capita. Source: BP Statistical Review (2006).

GAS: Natural Gas production scaled by GDP per capita. Source: BP Statistical Review (2006).

ORES: Oil reserves scaled by GDP per capita. Source: BP Statistical Review (2006).

GRES: Natural Gas reserves scaled by GDP per capita. Source: BP Statistical Review (2006).

STATE: Dummy variable that is equal to one for the countries which have state national oil company and equal to zero otherwise.