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Analysis of Some Energy and Economics Variables by Using VECMX Model in Indonesia

Author

Listed:
  • Mustofa Usman

    (Universitas Lampung, INDONESIA)

  • Luvita Loves

    (Universitas Lampung)

  • Edwin Russel

    (Universitas Lampung)

  • Muslim Ansori

    (Universitas Lampung)

  • Warsono Warsono

    (Universitas Lampung)

  • Widiarti Widiarti

    (Universitas Lampung)

  • Wamiliana Wamiliana

    (Universitas Lampung)

Abstract

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.

Suggested Citation

  • Mustofa Usman & Luvita Loves & Edwin Russel & Muslim Ansori & Warsono Warsono & Widiarti Widiarti & Wamiliana Wamiliana, 2022. "Analysis of Some Energy and Economics Variables by Using VECMX Model in Indonesia," International Journal of Energy Economics and Policy, Econjournals, vol. 12(2), pages 91-102, March.
    • Handle: RePEc:eco:journ2:2022-02-9
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    References listed on IDEAS

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    Cited by:

    1. Akhmad Akhmad & Ambo Asse & Nursalam Nursalam & Ibrahim Ibrahim & Bunyamin Bunyamin & Ansaar Ansaar & Sahajuddin Sahajuddin, 2023. "The Impact of the Increase of Oil Fuel Price and Government Subsidy on Indonesia’s Economic Performance," International Journal of Energy Economics and Policy, Econjournals, vol. 13(6), pages 547-557, November.

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    More about this item

    Keywords

    VAR model; VECMX; time series; Granger causality; Impulse response function;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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