A Dynamic Causality Study between Electricity Consumption and Economic Growth for Global Panel: Introduction

A Dynamic Causality Study between Electricity Consumption and Economic Growth for Global Panel: IntroductionDue to rising energy demand around the word especially in the developed and developing countries, soaring oil prices concerns about energy supply security, the debate of rising GHGs and climate change, a common energy policy will become indispensable for future or near future all over the world. Now-a-days, energy efficiency measures will play a vital role as energy savings as a result most of the countries all over the world fear that such policy measure will harm their economic development especially higher income countries. Thus the most import question arises whether the new energy policy and policy for reducing the GHG’s emissions will strike the world economy, especially in the developed and developing societies. One of the best known methods is to investigate the short-run and long-run causal relationship between energy consumption and economic growth for different panels using the time series data.
That is why in this paper the principal purpose has been made to investigate the dynamic causal relationships between electricity consumption and economic growth for five different panels namely high income, upper middle income, lower middle income, and low income panels based on World Bank income classification and also for global panel of 76 countries using the time series data from 1960 to 2008. For this study, the variable electricity consumption (kWh per capita) and per capita real GDP (constant 2000 US $) are considered as the proxies for energy consumption and economic growth respectively for all of these panels.
On the basis of the modern econometrics techniques, the dynamic causal relationships between electricity consumption and economic growth are examined. The testing procedure involves the following steps: At the first step whether each variable contains a unit root is examined using different panel unit root tests. If the variables contain a unit root the second step is to test whether there is a long run-cointegration relationship between the variables. If a long-run relationship between the variables is found, the final step is to estimate panel vector error correction model in order to infer the Granger causal relationship between the variables. Finally using the GMM technique the long-run and short-run elasticities of economic growth with respect to electricity consumption are estimated.
The direction and policy implications for the causal relationship between electricity consumption and economic growth can be classified as follows. If unidirectional causal relationship from electricity consumption to economic growth is found, any restriction on the use of energy leads to a reduction of economic growth. Thus about this negative effect on economic growth that caused by a policy of restriction of energy use in order to slow down the rate of climate change grows by reducing GHG’s, many countries of the world will be worried especially high income countries. On the other hand if unidirectional causal relationship from economic growth to electricity consumption is found, any restriction on the use of electricity has very little or no adverse impacts on economic growth. A bi-directional causal relationship implies that both the variables are jointly determined and will affect at the same time. If no causal relationship between these two variables is found, the hypothesis of neutrality holds indicates that any restriction on energy use will not work as a barrier for economic development of the panel.
The organizational structure of the paper is as: Section 2 discusses the literature review; Section 3 discusses data sources and descriptive statistics; Section 4 provides econometric modeling framework with empirical analysis and finally section 5 concludes with a summary of the main findings and policy implications. there