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Dynamic Modeling Using Vector Error-correction Model: Studying the Relationship among Data Share Price of Energy PGAS Malaysia, AKRA, Indonesia, and PTT PCL-Thailand

Author

Listed:
  • Warsono Warsono

    (Department of Mathematics, Faculty of Science and Mathematics, Universitas Lampung, Indonesia,)

  • Edwin Russel

    (Department of Management, Faculty of Economic and Business, Universitas Lampung, Indonesia.)

  • Almira Rizka Putri

    (Department of Mathematics, Faculty of Science and Mathematics, Universitas Lampung, Indonesia,)

  • Wamiliana Wamiliana

    (Department of Mathematics, Faculty of Science and Mathematics, Universitas Lampung, Indonesia,)

  • Widiarti Widiarti

    (Department of Mathematics, Faculty of Science and Mathematics, Universitas Lampung, Indonesia,)

  • Mustofa Usman

    (Department of Mathematics, Faculty of Science and Mathematics, Universitas Lampung, Indonesia,)

Abstract

Vector Error-Correction Model (VECM) is a method of statistical analysis frequently used in many studies in time series data of economy, business and finance, and data energy. It is applied across researches due to its simplicity and limited restrictions. VECM can explain not only the dynamic behavior of the relationship among variables of endogenous and exogenous, but also among the endogenous variables. Moreover, it also explains the impact of a variable or a set of variables on others by means of Impulse Response Function and Granger Causality analysis. It can also be used for forecasting multivariate time series data. In this research, the relationship of three share price of energy (from three Asean countries: PGAS Malaysia, AKRA Indonesia, and PTT Thailand) will be studied. The data in this study were collected from October 2005 to August 2019. Based on the comparison of some VECM models, it was found that the best model is VECM (2) with cointegration rank=3. The dynamic behavior of the data is studied through Impulse Response Function (IRF), Granger Causality analysis and forecasting for the next five periods(weeks).

Suggested Citation

  • Warsono Warsono & Edwin Russel & Almira Rizka Putri & Wamiliana Wamiliana & Widiarti Widiarti & Mustofa Usman, 2020. "Dynamic Modeling Using Vector Error-correction Model: Studying the Relationship among Data Share Price of Energy PGAS Malaysia, AKRA, Indonesia, and PTT PCL-Thailand," International Journal of Energy Economics and Policy, Econjournals, vol. 10(2), pages 360-373.
    • Handle: RePEc:eco:journ2:2020-02-42
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    Cited by:

    1. Mustofa Usman & M. Komarudin & Munti Sarida & Wamiliana Wamiliana & Edwin Russel & Mahatma Kufepaksi & Iskandar Ali Alam & Faiz A.M. Elfaki, 2022. "Analysis of Some Variable Energy Companies by Using VAR(p)-GARCH(r,s) Model : Study From Energy Companies of Qatar over the Years 2015 2022," International Journal of Energy Economics and Policy, Econjournals, vol. 12(5), pages 178-191, September.
    2. Mustofa Usman & M. Komarudin & Nurhanurawati Nurhanurawati & Edwin Russel & Ahmad Sidiq & Warsono Warsono & F. A.M Elfaki, 2023. "Dynamic Modeling and Analysis of Some Energy Companies of Indonesia Over the Year 2018 to 2022 By Using VAR(p)-CCC GARCH(r,s) Model: -," International Journal of Energy Economics and Policy, Econjournals, vol. 13(4), pages 542-554, July.
    3. 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.

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    More about this item

    Keywords

    Cointegration; VAR model; VECM model; Granger Causality; Impulse Response Function; Forecasting.;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • 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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