Estimation with macroeconomic variables in long-term elasticity of gasoline consumption

In this study attempted to calculate the stationarity value of the baseline data in proposing approximate parameters, for a regression equation which is an estimation of time-series data from gasoline. The function of stationary data in the time series model is crucial, to propose a long-term estimate, so that a study can show the time variable used, can explain the process of cointegration analysis among the variables being carried out research. This research uses model building from Baltagi and Griffin (1983), with cointegration analysis technique for variable data of gasoline and other consumption during 1960-2017 period in U.S. From the research that has been carried out shows that the value of gasoline consumption and income per community in the U.S during the year 1960-2017 mutual cointegration in the long term. There is a significant relationship among the 4 variables in the research on long-term time scale. Thus, this study can explain how the relationship between economic variables and the level of gasoline consumption in U.S. Country during the period of research data. The results of this study support previous research conducted by Baltagi and Griffin (1983), but there are differences in the use of data, if in this study using time series data, in Baltagi and Griffin study using time series data from several countries.