Causal relationship between energy consumption and GDP growth revisited: A dynamic panel data approach

This paper uses the panel data of energy consumption and GDP for 82 countries from 1972 to 2002. Based on the income levels defined by the World Bank, the data are divided into four categories: low income group, lower middle income group, upper middle income group, and high income group. We employ the GMM-SYS approach for the estimation of the panel VAR model in each of the four groups. Afterwards, the causal relationship between energy consumption and economic growth is tested and ascertained. We discover: (a) in the low income group, there exists no causal relationship between energy consumption and economic growth; (b) in the middle income groups (lower and upper middle income groups), economic growth leads energy consumption positively; (c) in the high income group countries, economic growth leads energy consumption negatively. After further in-depth analysis of energy related data, the results indicate that, in the high income group, there is a great environmental improvement as a result of more efficient energy use and reduction in the release of CO₂. However, in the upper middle income group countries, after the energy crisis, the energy efficiency declines and the release of CO₂ rises. Since there is no evidence indicating that energy consumption leads economic growth in any of the four income groups, a stronger energy conservation policy should be pursued in all countries.     

Genetic distance,economic growth and top income shares: Evidence from OECD countries

The relationship between economic growth and income inequality remains a puzzle in the literature. The main problem has been finding a way to account for the endogeneity of growth. Using century-long data of 14 OECD countries, this study disentangles the growth–inequality relationship. In doing so, our main contribution is employing genetic and geographical distances as instruments for economic growth. The instruments are constructed on the premise that the growth of one country spills over to the others if they are connected through trade and other forms of exchange; however, the genetic and geographical distances between countries represent barriers to such spillovers. Using alternative specifications and measures, we find that growth reduces the inequality measured by top income shares. As capital share increases in the growth process and capital substitutes labour, inequality-reducing strength of growth declines. Another important finding is that the effect of growth on top income shares is more significant among the highest income groups.