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This two-step approach is justified asymptotically by the fact that the estimator β ˆ in the first step is super-consistent-it converges at the rate of n instead of the usual rate n (see Stock, 1987). If the unit root test is rejected, one concludes that there is cointegration among the variables, and plugs the ECT into the VECM as the second step. To test for cointegration, a unit root test is applied to the estimated ECT term. The ECT term is constructed as the residual from this regression, ECT t = ɛ ˆ t (hence the alternative name, residual-based approach). Furthermore, such impacts could persist for years, because a reduction in energy consumption will probably cause a deceleration in economic growth and thus lead to a further reduction in energy consumption, given that the results indicate the existence of endogeneity.
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Restrictions on energy consumption should be strongly discouraged, particularly in the case of America, which demonstrates a high elasticity. Those results will help to identify if G 2 globally has greater impacts than G 1 in the nexus. In Section 4.4.2, both short- and long-run analysis for the Europe and Central Asia case is performed. Once more, it is possible to observe that G 2 has greater impacts on energy consumption than G 1. In the remaining variables, only the long-run elasticities between globalization and energy consumption reveals statistical significance at the 1% level for models 8 and 10, a 5% level for model 7, and a 10% level for model 9. Furthermore, the long-run elasticities between economic growth and energy consumption have a statistical significance at the 5% level for models 6 and 7 and a statistical significance at the 10% level for model 9.
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However, it should be noted that the short-run impacts between economic growth and energy consumption had a statistical significance of 5% for model 8. Notes: ***, **, and * denotes statistical significance at 1%, 5%, and 10% level, respectively.īoth the short-run impacts and the long-run elasticities of energy consumption and economic growth revealed the existence of a bidirectional causality. By looking into the G 1 and G 2 coefficients it is possible to observe that overall G2 has higher impacts that G 1 on energy consumption. Regarding globalization, impacts on energy consumption are observed at the statistical significance level of 5%. The coefficients of China’s energy consumption and economic growth on the American nexus revealed no statistical significance. Also, an outlier in 2012 needed to be controlled. The results revealed that the early 1980s recession and the 1987 stock market crash permanently impacted on the American aggregate energy–growth nexus.
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a Denotes statistical significance at 10% level.
RAMSEY RESET TEST EVIEWS SERIAL
Notes: Diagnostic tests results are based on F-statistic ARS means adjusted R-squared SER means standard error of regression JB means Jarque–Bera normality test LM means Breusch–Godfrey serial correlation LM test ARCH means ARCH test and Reset means Ramsey RESET test. Notes: ***, **, and * denote statistical significance at 1%, 5%, and 10% level, respectively.