Analysis of Data Inflation Energy and Gasoline Price by Vector Autoregressive Model

The 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 be...

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Bibliographic Details
Published inInternational journal of energy economics and policy Vol. 12; no. 2; pp. 120 - 126
Main Authors Saib, Nairobi, Ambya, Ambya, Russel, Edwin, Paujiah, Sipa, Pratama, D. N., Wamiliana, Wamiliana, Usman, Mustofa
Format Journal Article
LanguageEnglish
Published Mersin EconJournals 01.04.2022
Subjects
AICC
Causality
Crude oil prices
Data analysis
Energy economics
Energy industry
Forecasting
Gasoline prices
Granger causality
Impulse Response Function
Innovations
Time series
VAR(p) model
Variables
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Summary:The 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.
ISSN:2146-4553
2146-4553
DOI:10.32479/ijeep.12497