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

Author

Listed:
  • Nairobi Nairobi

    (Department of Economic Development, Faculty of Economics and Business, Universitas Lampung, Indonesia)

  • Ambya Ambya

    (Department of Economic Development, Faculty of Economics and Business, Universitas Lampung, Indonesia)

  • Edwin Russel

    (Department of Economic Development, Faculty of Economics and Business, Universitas Lampung, Indonesia)

  • Sipa Paujiah

    (Department of Economic Development, Faculty of Economics and Business, Universitas Lampung, Indonesia)

  • D. N. Pratama

    (Department of Economic Development, Faculty of Economics and Business, Universitas Lampung, Indonesia)

  • Wamiliana Wamiliana

    (Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Lampung, Indonesia)

  • Mustofa Usman

    (Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Lampung, Indonesia)

Abstract

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.

Suggested Citation

  • 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.
    • Handle: RePEc:eco:journ2:2022-02-12
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    References listed on IDEAS

    as
    1. 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, April.
    2. Jorge Duarte Forero & Brando Hernandez & Wilman Orozco & Norberto Acu a & Mar a Jimena Wilches, 2019. "Analysis of the use of Renewable Energies in Colombia and the Potential Application of Thermoelectric Devices for Energy Recovery," International Journal of Energy Economics and Policy, Econjournals, vol. 9(5), pages 125-134.
    3. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    4. Yu, Tun-Hsiang (Edward) & Bessler, David A. & Fuller, Stephen W., 2006. "Cointegration and Causality Analysis of World Vegetable Oil and Crude Oil Prices," 2006 Annual meeting, July 23-26, Long Beach, CA 21439, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    5. Warsono Warsono & Edwin Russel & Wamiliana Wamiliana & Widiarti Widiarti & Mustofa Usman, 2019. "Modeling and Forecasting by the Vector Autoregressive Moving Average Model for Export of Coal and Oil Data (Case Study from Indonesia over the Years 2002-2017)," International Journal of Energy Economics and Policy, Econjournals, vol. 9(4), pages 240-247.
    6. Juselius, Katarina, 2006. "The Cointegrated VAR Model: Methodology and Applications," OUP Catalogue, Oxford University Press, number 9780199285679.
    7. 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.
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    More about this item

    Keywords

    AICC; VAR(p) model; Granger causality; Impulse Response Function; Forecasting;
    All these keywords.

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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