Analysis of Data Inflation Energy and Gasoline Price by Vector Autoregressive Model
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Keywords:AICC, VAR(p) model, Granger causality, Impulse Response Function, Forecasting
AbstractThe study of multivariate time series data analysis has become many topics of research in the fields of economics and business. In the present study, we will analyze data energy inflation and gasoline prices of Indonesia over the years from 2014 to 2020. The purpose of this study is to obtain the best model of the dynamic relationship between inflation and gasoline prices. The dynamic modeling that will be used in this research is modeling using the Vector Autoregressive (VAR) model. From the analysis results, the best model is the VAR model with order 3 (p=3), VAR(3). Based on the best model, VAR(3), further studies will be discussed with regard to Granger causality analysis, Impulse Response Function, and Forecasting.
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How to Cite
Nairobi, N., Ambya, A., Russel, E., Paujiah, S., Pratama, D. N., Wamiliana, W., & Usman, M. (2022). Analysis of Data Inflation Energy and Gasoline Price by Vector Autoregressive Model. International Journal of Energy Economics and Policy, 12(2), 120–126. https://doi.org/10.32479/ijeep.12497