Modeling The Causality Relationships Between Gdp/Gni and Electricity Consumption According to Income Levels of Countries By Generalized Estimating Equations

Gross domestic product (GDP) and energy consumption in the economic evaluations of countries are seen as two basic concepts of development. The need for energy resources in recent years has brought countries closer to technology, but in some cases, it causes problems such as wars. It is also important to determine the economic feasibility of energy consumption as well as the feasibility of many aspects such as the origin, usage, and necessity of energy. When we look at the crises that have taken place in the last 20 years, it is once again seen that energy is the dynamism and indispensable necessity of the countries. If we look at the effect of the consumed energy on the country s economy, the first economic variable will be GDP. Interpretation and evaluation of GDP, which reveals steady growth, will give effective results on economic indicators of the country. A lot of research has been done in the literature between the amount of energy consumption (according to the sectors, type of energy used, supply, and etc.) and the GDP which is the most important indicator of the country s economy. The final relationship between these two variables has been examined in details for different countries and energy concepts. In previous studies, it is sometimes observed that energy consumption is a cause of GDP or vice versa, and sometimes a two-way causality between them is determined. On the other hand, a causality relationship can not be always determined between the variables. In this case a suitable regression model can be established without looking for causality. In this study, the causality relationship between the GDP values, categorized by five income levels, and the energy consumptions of the countries between 1980 and 2014 is determined by using the Granger causality test. When we look at the results of the causality test, we find that only one causality relationship exists between high income level countries by GDP and the energy consumption of them. According to the causality test result, dependent and independent variable are determined before generalized estimating equations (GEE) method is used for modelling the data. In GEE method, the smallest values of QIC and QICC information criteria are found in the direction of causality relationships. The same causality assessment is done between gross national incomes (GNI) of countries categorized by income levels and energy consumptions, and it is concluded that the GEE models established according to the causality relationship direction are much better fit to the data. These findings obtained from this study suggests that causality test is a guide for us when we have insufficient knowledge in determining dependent and independent variables before fitting regression models to the data.