IDEAS home Printed from https://ideas.repec.org/a/cmj/seapas/y2013i1alexandruc,caragean,dobream.html
   My bibliography  Save this article

Vector Autoregressive Models Using “R”

Author

Listed:
  • Ciprian ALEXANDRU

    (Ecological University of Bucharest)

  • Nicoleta CARAGEA

    (National Institute of Statistics, Bucharest)

  • Ana Maria DOBRE

    (National Institute of Statistics, Bucharest)

Abstract

Multivariate data analysis in the context of autoregressive models has evolved as a standard instrument in econometrics. In present, there are developed packages available in R for estimating time series models; one of the most useful package is vars (Pfaff, 2008) containing functions for diagnostic testing, estimation of a restricted models, prediction, causality analysis, impulse response analysis and forecast error variance decomposition. Using the examples provided in the vars vignette, the authors tried to obtain results for the different methods and functions on the base of macroeconomic data set for Romania.

Suggested Citation

  • Ciprian ALEXANDRU & Nicoleta CARAGEA & Ana Maria DOBRE, 2013. "Vector Autoregressive Models Using “R”," SEA - Practical Application of Science, Romanian Foundation for Business Intelligence, Editorial Department, issue 1, pages 59-67, June.
    • Handle: RePEc:cmj:seapas:y:2013:i:1:alexandruc,caragean,dobream
    as

    Download full text from publisher

    File URL: http://seaopenresearch.eu/Journals/articles/SPAS_1_5.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    2. Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, vol. 16(1), pages 121-130, May.
    3. Caragea, Nicoleta & Alexandru, Ciprian Antoniade & Dobre, Ana Maria, 2012. "Bringing New Opportunities to Develop Statistical Software and Data Analysis Tools in Romania," MPRA Paper 48772, University Library of Munich, Germany.
    4. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    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. Cristian-Florin Dananau, 2015. "Non-governmental credit in Romania: a VECM-based approach," Romanian Statistical Review, Romanian Statistical Review, vol. 63(1), pages 87-106, March.
    2. Madalina-Gabriela ANGHEL & Aurelian DIACONU, 2016. "Equilibrium and auto regression models used for macroeconomic prognosis," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(7), pages 70-78, July.

    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. repec:cmj:journl:y:2013:i:27:alexandruc,caragean,dobream is not listed on IDEAS
    2. Mohamed, Hazik & Masih, Mansur, 2017. "Stock market comovement among the ASEAN-5 : a causality analysis," MPRA Paper 98781, University Library of Munich, Germany.
    3. Erie Febrian & Aldrin Herwany, 2009. "Volatility Forecasting Models and Market Co-Integration: A Study on South-East Asian Markets," Working Papers in Economics and Development Studies (WoPEDS) 200911, Department of Economics, Padjadjaran University, revised Sep 2009.
    4. David F. Hendry & Grayham E. Mizon, 2016. "Improving the teaching of econometrics," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1170096-117, December.
    5. Ma, Tao & Zhou, Zhou & Antoniou, Constantinos, 2018. "Dynamic factor model for network traffic state forecast," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 281-317.
    6. Abhijit Sharma & Theodore Panagiotidis, 2003. "An Analysis of Exports and Growth in India: Some Empirical Evidence (1971-2001)," Working Papers 2003004, The University of Sheffield, Department of Economics, revised Nov 2003.
    7. López Cabrera, Brenda & Schulz, Franziska, 2016. "Volatility linkages between energy and agricultural commodity prices," Energy Economics, Elsevier, vol. 54(C), pages 190-203.
    8. G. Lypny & M. Powalla, 1998. "The hedging effectiveness of DAX futures," The European Journal of Finance, Taylor & Francis Journals, vol. 4(4), pages 345-355.
    9. Francis X. Diebold, 1998. "The Past, Present, and Future of Macroeconomic Forecasting," Journal of Economic Perspectives, American Economic Association, vol. 12(2), pages 175-192, Spring.
    10. Siddhartha Pradeep, 2022. "Role of monetary policy on CO2 emissions in India," SN Business & Economics, Springer, vol. 2(1), pages 1-33, January.
    11. Committee, Nobel Prize, 2003. "Time-series Econometrics: Cointegration and Autoregressive Conditional Heteroskedasticity," Nobel Prize in Economics documents 2003-1, Nobel Prize Committee.
    12. Charles G. Renfro, 2009. "The Practice of Econometric Theory," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75571-5, July-Dece.
    13. Hendry, David F & Ericsson, Neil R, 1991. "An Econometric Analysis of U.K. Money Demand in 'Monetary Trends in the United States and the United Kingdom' by Milton Friedman and Anna Schwartz," American Economic Review, American Economic Association, vol. 81(1), pages 8-38, March.
    14. Dufrénot, Gilles & Jawadi, Fredj, 2013. "Computational tools in econometric modeling for macroeconomics and finance," Economic Modelling, Elsevier, vol. 34(C), pages 1-4.
    15. repec:jss:jstsof:27:i04 is not listed on IDEAS
    16. Caporin, Massimiliano & Ranaldo, Angelo & Santucci de Magistris, Paolo, 2013. "On the predictability of stock prices: A case for high and low prices," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5132-5146.
    17. Brannolte Cord & Kim Jeong-Ryeol & Hansen Gerd, 1999. "Nonlinear Error Correction Modeling in German Interest Rates / Ein nichtlineares Fehlerkorrekturmodell für die deutsche Zinsstruktur," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 219(3-4), pages 271-283, June.
    18. Kurita, Takamitsu, 2010. "Co-breaking, cointegration, and weak exogeneity: Modelling aggregate consumption in Japan," Economic Modelling, Elsevier, vol. 27(2), pages 574-584, March.
    19. Turner, Peter A. & Lim, Siew Hoon, 2015. "Hedging jet fuel price risk: The case of U.S. passenger airlines," Journal of Air Transport Management, Elsevier, vol. 44, pages 54-64.
    20. Amer Ait Sidhoum & Teresa Serra, 2016. "Volatility Spillovers in the Spanish Food Marketing Chain: The Case of Tomato," Agribusiness, John Wiley & Sons, Ltd., vol. 32(1), pages 45-63, January.
    21. Titelman Kardonsky, Daniel & Martner Fanta, Ricardo, 1992. "La demanda de dinero en Chile: una comparación de métodos alternativos de estimación de vectores de cointegración," Series Históricas 9584, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
    22. Sandrine Lardic & Valérie Mignon, 2004. "Robert F. Engle et Clive W.J. Granger prix Nobel d'économie 2003," Revue d'économie politique, Dalloz, vol. 114(1), pages 1-15.

    More about this item

    Keywords

    Autoregressive models; Testing; R; vars;
    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
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets

    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:cmj:seapas:y:2013:i:1:alexandruc,caragean,dobream. 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: Serghie Dan (email available below). General contact details of provider: https://seaopenresearch.eu/ .

    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.