مصرف انرژی و تولید ناخالص داخلی واقعی در G-7 : تست رابطه علیت چند افقی در حضور موجودی سرمایه

This paper applies two recent time series methods to re-examine the causal relationship among energy consumption, real GDP and capital stock in G-7 countries. These methods, the Dufour et al. [2006, Journal of Econometrics, 132:337–362] multiple horizon causality testing and the Hill [2007, Journal of Applied Econometrics, 22:747–765] sequential causality testing allow to test for (non)causality in a multivariate framework and can further reveal the time profile of causal effects, the presence of causation delays and the direct or indirect nature of the causal effects. Given the trending nature of the time series employed, we further take into account the presence of structural breaks in the form of trend changes. Our empirical results show that multi-horizon causality testing does uncover crucial information with respect to the dynamic interaction among energy consumption, real GDP and capital stock, while structural breaks do exist and appear to be critical for causality inference. In regard to causality direction, we find that real GDP dominates in anticipating energy consumption in G-7 countries.

The potential causal relationship between energy consumption and economic growth, along with the policy implications that accrue from such a relation, has been under theoretical and empirical scrutiny at least since the earlier oil shocks of the 1970s. Kraft and Kraft (1978) are the first who examined the relation between income and energy consumption in the U.S. The literature has grown substantially thereafter, while the convention of the Kyoto Protocol on 2005 renewed attention of applied researchers, leading to a large amount of empirical work during the 2000s. In particular, research interest is focused on whether energy conservation policies, i.e. constraints regarding the use of energy, can be implemented in developed or developing countries without producing adverse effects on economic growth. Payne (2010) and Ozturk (2010) provide extensive surveys of the empirical literature regarding causality between energy consumption and economic growth. Most of these studies use the Granger (1969)1 concept of causality to examine the relationship between energy consumption and economic growth, addressing the question of how useful the variables are in forecasting each other or whether energy consumption takes precedence over growth and vice versa. The vector autoregression (VAR) framework developed by Sims, 1972 and Sims, 1980 and the corresponding VAR-based causality tests have been the dominant method of causality testing between the two variables in many empirical studies.

This study empirically re-examines the causal relationship between energy consumption and real GDP in G-7 countries using annual data over the period 1960–2010. Our contribution is threefold. First, we employ a trivariate framework to test for causality between energy consumption and real GDP by including capital stock as an additional variable in the VAR model. Second, we employ two recent time series causality testing methods; the Dufour et al. (2006) multiple horizon and the Hill (2007) sequential testing procedures. Both use an extension of the original definition of Granger (1969) causality proposed by Dufour and Renault (1998) that is based on linear predictability at higher forecast horizons, and can provide useful additional information on the time profile of causal effects and more specifically on the presence of causal delays, horizons at which causal effects take place, short-run or long-run causality (forecast horizons) and the direct or indirect nature of causal effects. Third, given the changing long run growth rates of the time series we employ, we control for structural breaks in the form of trend changes by employing the recent techniques of Perron and Yabu (2009) and Kejriwal and Perron (2010), while also employing the GLS-based tests of Carrion-i-Silvestre et al. (2009) to test for unit roots when the presence of – at least one – break in the linear trend has been established. Our results show that multi-horizon causality testing does uncover substantial information with respect to the dynamic interaction among energy consumption, real GDP and capital stock, the duration of causal effects and their indirect (for some countries) nature manifested via the capital stock. In addition, we observe structural breaks in the form of level and/or slope changes in the trend in almost all of the time series and we show that when these changes are taken into account, causality test results and causality direction can be affected.