IDEAS home Printed from https://ideas.repec.org/a/eco/journ2/2019-02-45.html
   My bibliography  Save this article

Vector Autoregressive with Exogenous Variable Model and its Application in Modeling and Forecasting Energy Data: Case Study of PTBA and HRUM Energy

Author

Listed:
  • Warsono Warsono

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

  • Edwin Russels

    (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

Owing to its simplicity and less restrictions, the vector autoregressive with exogenous variable (VARX) model is one of the statistical analyses frequently used in many studies involving time series data, such as finance, economics, and business. The VARX model can explain the dynamic behavior of the relationship between endogenous and exogenous variables or of that between endogenous variables only. It can also explain the impact of a variable or a set of variables on others through the impulse response function (IRF). Furthermore, VARX can be used to predict and forecast time series data. In this study, PTBA and HRUM energy as endogenous variables and exchange rate as an exogenous variable were studied. The data used herein were collected from January 2014 to October 2017. The dynamic behavior of the data was also studied through IRF and Granger causality analyses. The forecasting data for the next one month was also investigated. On the basis of the data provided by these different models, it was found that VARX (3,0) is the best model to assess the relationship between the variables considered in this work.

Suggested Citation

  • Warsono Warsono & Edwin Russels & Wamiliana Wamiliana & Widiarti Widiarti & Mustofa Usman, 2019. "Vector Autoregressive with Exogenous Variable Model and its Application in Modeling and Forecasting Energy Data: Case Study of PTBA and HRUM Energy," International Journal of Energy Economics and Policy, Econjournals, vol. 9(2), pages 390-398.
    • Handle: RePEc:eco:journ2:2019-02-45
    as

    Download full text from publisher

    File URL: https://www.econjournals.com/index.php/ijeep/article/download/7223/4268
    Download Restriction: no
    File URL: https://www.econjournals.com/index.php/ijeep/article/view/7223/4268
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gourieroux,Christian & Monfort,Alain, 1997. "Time Series and Dynamic Models," Cambridge Books, Cambridge University Press, number 9780521423083, January.
    2. Ekhlas Al-hajj & Usama Al-mulali & Sakiru Adebola Solarin, 2017. "The Influence of Oil Price Shocks on Stock Market Returns: Fresh Evidence from Malaysia," International Journal of Energy Economics and Policy, Econjournals, vol. 7(5), pages 235-244.
    3. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    4. Gebhard Kirchgässner & Jürgen Wolters & Uwe Hassler, 2013. "Introduction to Modern Time Series Analysis," Springer Texts in Business and Economics, Springer, edition 2, number 978-3-642-33436-8, August.
    5. Lutz Kilian, 2013. "Structural vector autoregressions," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 22, pages 515-554, Edward Elgar Publishing.
    6. Juselius, Katarina, 2006. "The Cointegrated VAR Model: Methodology and Applications," OUP Catalogue, Oxford University Press, number 9780199285679.
    7. Ankit Sharma & Sasmita Giri & Harsh Vardhan & Sujeet Surange & Rohan Shetty & Vishwaroop Shetty, 2018. "Relationship between Crude Oil Prices and Stock Market: Evidence from India," International Journal of Energy Economics and Policy, Econjournals, vol. 8(4), pages 331-337.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. Walid Mansour & Hechem Ajmi & Karima Saci, 2022. "Regulatory policies in the global Islamic banking sector in the outbreak of COVID-19 pandemic," Journal of Banking Regulation, Palgrave Macmillan, vol. 23(3), pages 265-287, September.
    4. 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.
    5. Nairobi Nairobi & Ambya Ambya & Edwin Russel & Sipa Paujiah & D. N. Pratama & Wamiliana Wamiliana & Mustofa Usman, 2022. "Analysis of Data Inflation Energy and Gasoline Price by Vector Autoregressive Model," International Journal of Energy Economics and Policy, Econjournals, vol. 12(2), pages 120-126, March.
    6. 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.
    7. Andrew K. Kamenju & Dr. T. Olweny, 2021. "The Nexus Between Internal Investment and Economic Growth in Kenya," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 11(2), pages 1-2.
    8. Rialdi Azhar & Fajrin Satria Dwi Kesumah & Ambya Ambya & Febryan Kusuma Wisnu & Edwin Russel, 2020. "Application of Short-term Forecasting Models for Energy Entity Stock Price (Study on Indika Energi Tbk, JII)," International Journal of Energy Economics and Policy, Econjournals, vol. 10(1), pages 294-301.
    9. Sri Hasnawati & Mustofa Usman & Ahmad Faisol & Faiz A. M. Elfaki, 2023. "Analysis and Modeling Gross Domestic Product, Carbon Dioxide Emission, Population Growth, and Life Expectancy at Birth: Case Study in Qatar," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 467-483, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nairobi Nairobi & Ambya Ambya & Edwin Russel & Sipa Paujiah & D. N. Pratama & Wamiliana Wamiliana & Mustofa Usman, 2022. "Analysis of Data Inflation Energy and Gasoline Price by Vector Autoregressive Model," International Journal of Energy Economics and Policy, Econjournals, vol. 12(2), pages 120-126, March.
    2. 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.
    3. Dufour, Jean-Marie & Pelletier, Denis & Renault, Eric, 2006. "Short run and long run causality in time series: inference," Journal of Econometrics, Elsevier, vol. 132(2), pages 337-362, June.
    4. John Geweke & Joel Horowitz & M. Hashem Pesaran, 2006. "Econometrics: A Bird’s Eye View," CESifo Working Paper Series 1870, CESifo.
    5. Tüzemen Samet & Barış-Tüzemen Özge & Çelik Ali Kemal, 2021. "The relationship between information and communication technologies and female labour force participation in Turkey," Economics and Business Review, Sciendo, vol. 7(4), pages 121-145, December.
    6. Helmut Lütkepohl, 2013. "Vector autoregressive models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 6, pages 139-164, Edward Elgar Publishing.
    7. Arnaut, Javier L., 2022. "The importance of uranium prices and structural shocks: Some implications for Greenland," Energy Policy, Elsevier, vol. 161(C).
    8. Dreger, Christian & Wolters, Jürgen, 2016. "On the Empirical Relevance of the Lucas Critique: the Case of Euro Area Money Demand," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 43(1), pages 61-82.
    9. Signe Rosenberg, 2015. "The Impact of a Change in Real Estate Value on Private Consumption in Estonia," Research in Economics and Business: Central and Eastern Europe, Tallinn School of Economics and Business Administration, Tallinn University of Technology, vol. 7(2).
    10. Bardsen, Gunnar & Eitrheim, Oyvind & Jansen, Eilev S. & Nymoen, Ragnar, 2005. "The Econometrics of Macroeconomic Modelling," OUP Catalogue, Oxford University Press, number 9780199246502.
    11. Papież, Monika & Śmiech, Sławomir, 2015. "Dynamic steam coal market integration: Evidence from rolling cointegration analysis," Energy Economics, Elsevier, vol. 51(C), pages 510-520.
    12. M. Aubry & P. Renou-Maissant, 2013. "Investigating the semiconductor industry cycles," Applied Economics, Taylor & Francis Journals, vol. 45(21), pages 3058-3067, July.
    13. Lanne, Markku & Meitz, Mika & Saikkonen, Pentti, 2017. "Identification and estimation of non-Gaussian structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 196(2), pages 288-304.
    14. Jacobs, Jan P.A.M. & Wallis, Kenneth F., 2010. "Cointegration, long-run structural modelling and weak exogeneity: Two models of the UK economy," Journal of Econometrics, Elsevier, vol. 158(1), pages 108-116, September.
    15. Cross, Jamie & Nguyen, Bao H., 2017. "The relationship between global oil price shocks and China's output: A time-varying analysis," Energy Economics, Elsevier, vol. 62(C), pages 79-91.
    16. Lin, Boqiang & Xu, Bin, 2018. "How to promote the growth of new energy industry at different stages?," Energy Policy, Elsevier, vol. 118(C), pages 390-403.
    17. Hani El-Chaarani, 2019. "The Impact of Oil Prices on Stocks Markets: New Evidence During and After the Arab Spring in Gulf Cooperation Council Economies," International Journal of Energy Economics and Policy, Econjournals, vol. 9(4), pages 214-223.
    18. Stern, David I. & Enflo, Kerstin, 2013. "Causality between energy and output in the long-run," Energy Economics, Elsevier, vol. 39(C), pages 135-146.
    19. Dawid J. van Lill, 2017. "Changes in the Liquidity Effect Over Time: Evidence from Four Monetary Policy Regimes," Working Papers 704, Economic Research Southern Africa.
    20. Amine Ben Amar, 2022. "On the role of Islamic banks in the monetary policy transmission in Saudi Arabia," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(1), pages 55-94, March.

    More about this item

    Keywords

    VAR model; VARX 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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eco:journ2:2019-02-45. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ilhan Ozturk (email available below). General contact details of provider: http://www.econjournals.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.