We know macroeconomic variables tend to exhibit a trend over time. As a result it is more appropriate to consider the regression equation with constant and trend terms at level form. Since first differencing is likely to remove any deterministic trend in the variables, regression should include only constant term. Therefore both constant and trend terms are included in the model for the test statistics while utilizing level form and only constant term is included for first differenced of the variables in their logarithmic form. The test results for five panels are given below in Table.

The tests results support that both the variables are integrated of order 1 for high income, upper middle income, and lower middle income panels and also for global panel but only the variable economic growth is integrated of order 1 for low income panel.

Panel Cointegration

From the panel unit root tests results it is found that both the series economic growth and electricity consumptions are integrated of order 1 for all panels except low income panel. For low income panel only the variable economic growth is integrated of order 1. Therefore the cointegration analysis is conducted to examine whether there is a long-run relationship between the variables using the Kao ADF type test and Johansen Fisher panel cointegration test proposed by Maddala and Wu.

The Johansen Fisher panel conintegration test is panel version of the individual Johansen conintegration test. The Johansen Fisher panel cointegration test is based on the aggregates of the p-values of the individual Johansen maximum eigenvalues and trace statistic. If and low income panels both the variables are not cointegrated.

From the tests results in Tables and it is found that there is a long-run relationship between electricity consumption and economic growth for high income, upper middle income and global panels but for lower middle income p is the p-value from an individual cointegration test for cross-section i.

The X value is based on ^-values for Johansen’s cointegration trace test and maximum eigenvalue test. In the Johansen type panel cointegration tests results heavily depends on the number of lags of the VAR system. The results are obtained here use one lag and are given below in Table. so

The cointegration relationship indicates that the existence of causal relationship between the variables but it does not indicate the direction of causal relationship between variables. From the equations and given the use of a VEC and VAR structure, variables are treated as endogenous variables. The F test is applied here to examine the direction of any causal relationship between the variables. The electricity consumption does not Granger cause economic growth in the short run, if and only if all the coefficients f321k ’s V k are not significantly different from zero in equations and. Similarly the economic growth does not Granger cause electricity consumption in the short run if and only if all the coefficients f312k ’s V k are not significantly different from zero in equations and. There are referred to as the short-run Granger causality test. The coefficients on the ECM represent how fast deviations from the long-run equilibrium are eliminated. Another channel of causality can be studied by testing the detecting the causal relationship between variables using the Engle and Granger test procedure. The panel short-run and long-run Granger causality results are reported below in Table-. The findings in Table indicate that there is bidirectional causality between economic growth and electricity consumption both in the short-run and long-run for high income, upper middle income and global panels. Unidirectional short-run causality is found from economic growth to electricity consumption in lower middle income panel and no short-run causal relationship is found between economic growth and electricity consumption for low income panel.

This equation is augmented with lead and lagged differences of the dependent and explanatory variables to control for serial correlation and endogenous feedback effects. Here the GMM is applied to estimate both equation which control the problem of endogeneity and serial correlation of regressors. The estimated results are given in Table. From the estimated results in Table it is found that in the long-run electricity consumption has significant positive impact on economic growth for all panels. The range of positive long-run elasticity of economic growth with respect to electricity consumption is from 0.8125 for global panel to 0.2145 for low income panel. It is also found that short-run elasticities are significant for all panels and ECM is significant only for upper middle income panel. The range of short-run elasticity is 0.2122 for high income panel to 0.00278 for low income panel. It is also found that the long-run elasticity is higher than short-run elasticity for all five panels which indicates that over times higher electricity consumption gives rise to more economic growth for all panels.