CAUSALITY ANALYSIS BETWEEN ENERGY CONSUMPTION, ECONOMIC GROWTH AND ENVIRONMENTAL SUSTAINABILITY IN INDONESIA - Achmad Inggis, Raka
The purpose of this study is to investigate the causal relationship between energy consumption (EC), carbon emission (CAR), foreign direct investment (FDI) and economic growth (GDP) in Indonesia. By using straight-forward annual data (1981- 2017), the author conducts granger causality analysis, Johansen cointegration test, and FEVD analysis through VECM Model. The objectives of the research are: (1) to discover the existence of long-run causality between the variables, (2) to discover the existence of short-run causality between the variables, and (3) to define the variables that affect the most for economic growth, energy consumption, carbon emission and foreign direct investment in the future. The results of long-run analysis support the hypothesis of there is one (or more) longrun causality between GDP, EC, CAR and FDI in Indonesia as it is found two cointegrating equations within the model. Moreover, the results of short-run analysis also support the hypothesis of there is one (or more) short-run causality between GDP, EC, CAR and FDI in Indonesia. There are at least three short-run causal relation between the variables. However, the FEVD analysis does not support the hypothesis of only energy consumption that affects the most for GDP, EC, CAR and FDI in the future. The forecast results for the short-run and long-run in the future for each variables (except CAR) show that their own variables do affect the most for themselves, not only the energy consumption. It is interesting that, for the CAR, the forecast result is dynamically changing. These findings are important, especially for the government, where the results of short term causality explain that CAR and FDI are causing each other. The government should be aware that there is no evidence that the EC will drive the GDP. Therefore, the project of expanding the supply of energy to drive the energy consumption and to drive economic growth should be re-evaluated. To have a robust regression, the models have been tested to meet the assumption of non-serially correlated and non-heteroskedastic, therefore the model is assumed acceptable.