Analysis of Some Energy and Economics Variables by Using VECMX Model in Indonesia
Time series modeling analysis is one of the methods to forecast based on past data and conditions. The analytical tool that is commonly used to forecast multivariate time series data is the Vector Autoregressive (VAR) model. However, when the variables have cointegration and stationary at the first...
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| Format: | Article |
| Language: | English |
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EconJournals
2022-03-01
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| Series: | International Journal of Energy Economics and Policy |
| Subjects: | |
| Online Access: | https://econjournals.com/index.php/ijeep/article/view/11897 |
| _version_ | 1828015286016540672 |
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| author | Mustofa Usman Luvita Loves Edwin Russel Muslim Ansori Warsono Warsono Widiarti Widiarti Wamiliana Wamiliana |
| author_facet | Mustofa Usman Luvita Loves Edwin Russel Muslim Ansori Warsono Warsono Widiarti Widiarti Wamiliana Wamiliana |
| author_sort | Mustofa Usman |
| collection | DOAJ |
| description |
Time series modeling analysis is one of the methods to forecast based on past data and conditions. The analytical tool that is commonly used to forecast multivariate time series data is the Vector Autoregressive (VAR) model. However, when the variables have cointegration and stationary at the first difference value, then the VAR model is modified into the Vector Error Correction Model (VECM). In VECM, all variables can be used as endogenous variables. If exogenous variables are involved in the VECM model, then the model is called as Vector Error Correction Model with Exogenous variables (VECMX). In the present study, a time series modeling analysis was used to analyze the price of gasoline, the money supply in a broad sense (M2), oil and gas exports, and consumption imports over the years from 2012 to 2020. By using information on the criteria of Akaike Information Criterion Corrected, Hannan–Quinn Criterion, Akaike Information Criterion, and Schwarz Bayesian Criterion, the best VAR(p) model is obtained with order 3, or lag 3. Based on the VAR(3) model, the cointegration test is conducted, and the result shows that there is a long-term relationship among variables, namely, there is a cointegration relationship between variables with rank = 1. Based on the cointegration rank = 1 and the smallest value of the information criteria and comparison of some candidate best models, namely, VECMX(2,1), VECMX(2,2), VECMX(3,1), VECMX(3,2), and VECMX(4,1), we found that the best model is VECMX(3,1) with lag 3 for endogenous variables and lag 1 for exogenous variables. Based on this best model, further analysis of Granger causality, Impulse Response Function (IRF), and forecasting is discussed.
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| first_indexed | 2024-04-10T10:15:38Z |
| format | Article |
| id | doaj.art-5b431b5cd895400a9f48c84c7e9a3991 |
| institution | Directory Open Access Journal |
| issn | 2146-4553 |
| language | English |
| last_indexed | 2024-04-10T10:15:38Z |
| publishDate | 2022-03-01 |
| publisher | EconJournals |
| record_format | Article |
| series | International Journal of Energy Economics and Policy |
| spelling | doaj.art-5b431b5cd895400a9f48c84c7e9a39912023-02-15T16:21:54ZengEconJournalsInternational Journal of Energy Economics and Policy2146-45532022-03-0112210.32479/ijeep.11897Analysis of Some Energy and Economics Variables by Using VECMX Model in IndonesiaMustofa Usman0Luvita Loves1Edwin Russel2Muslim Ansori3Warsono Warsono4Widiarti Widiarti5Wamiliana Wamiliana6Universitas Lampung, INDONESIAUniversitas LampungUniversitas LampungUniversitas LampungUniversitas LampungUniversitas LampungUniversitas Lampung Time series modeling analysis is one of the methods to forecast based on past data and conditions. The analytical tool that is commonly used to forecast multivariate time series data is the Vector Autoregressive (VAR) model. However, when the variables have cointegration and stationary at the first difference value, then the VAR model is modified into the Vector Error Correction Model (VECM). In VECM, all variables can be used as endogenous variables. If exogenous variables are involved in the VECM model, then the model is called as Vector Error Correction Model with Exogenous variables (VECMX). In the present study, a time series modeling analysis was used to analyze the price of gasoline, the money supply in a broad sense (M2), oil and gas exports, and consumption imports over the years from 2012 to 2020. By using information on the criteria of Akaike Information Criterion Corrected, Hannan–Quinn Criterion, Akaike Information Criterion, and Schwarz Bayesian Criterion, the best VAR(p) model is obtained with order 3, or lag 3. Based on the VAR(3) model, the cointegration test is conducted, and the result shows that there is a long-term relationship among variables, namely, there is a cointegration relationship between variables with rank = 1. Based on the cointegration rank = 1 and the smallest value of the information criteria and comparison of some candidate best models, namely, VECMX(2,1), VECMX(2,2), VECMX(3,1), VECMX(3,2), and VECMX(4,1), we found that the best model is VECMX(3,1) with lag 3 for endogenous variables and lag 1 for exogenous variables. Based on this best model, further analysis of Granger causality, Impulse Response Function (IRF), and forecasting is discussed. https://econjournals.com/index.php/ijeep/article/view/11897VAR modelVECMXtime seriesGranger causalityImpulse response function |
| spellingShingle | Mustofa Usman Luvita Loves Edwin Russel Muslim Ansori Warsono Warsono Widiarti Widiarti Wamiliana Wamiliana Analysis of Some Energy and Economics Variables by Using VECMX Model in Indonesia International Journal of Energy Economics and Policy VAR model VECMX time series Granger causality Impulse response function |
| title | Analysis of Some Energy and Economics Variables by Using VECMX Model in Indonesia |
| title_full | Analysis of Some Energy and Economics Variables by Using VECMX Model in Indonesia |
| title_fullStr | Analysis of Some Energy and Economics Variables by Using VECMX Model in Indonesia |
| title_full_unstemmed | Analysis of Some Energy and Economics Variables by Using VECMX Model in Indonesia |
| title_short | Analysis of Some Energy and Economics Variables by Using VECMX Model in Indonesia |
| title_sort | analysis of some energy and economics variables by using vecmx model in indonesia |
| topic | VAR model VECMX time series Granger causality Impulse response function |
| url | https://econjournals.com/index.php/ijeep/article/view/11897 |
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