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Generalized impulse response analysis in a fractionally integrated vector autoregressive model

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  • Do, Hung Xuan
  • Brooks, Robert Darren
  • Treepongkaruna, Sirimon

Abstract

We develop a generalized impulse response function for the fractionally integrated vector autoregressive (FIVAR) model using the Pesaran and Shin (1998) approach. Our method is different from the methodology shown in Chung (2001) since it does not require us to orthogonalize the error vector and, therefore, is independent of the ordering of the endogenous variables in the FIVAR. Being consistent with the long memory behaviour, we show that generalized and orthogonalized impulse responses of FIVAR evolve slowly at the same hyperbolic rates. However, we also note that they are different in a number of respects.

Suggested Citation

  • Do, Hung Xuan & Brooks, Robert Darren & Treepongkaruna, Sirimon, 2013. "Generalized impulse response analysis in a fractionally integrated vector autoregressive model," Economics Letters, Elsevier, vol. 118(3), pages 462-465.
    • Handle: RePEc:eee:ecolet:v:118:y:2013:i:3:p:462-465
    DOI: 10.1016/j.econlet.2012.12.023
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Do, Hung Xuan & Brooks, Robert & Treepongkaruna, Sirimon & Wu, Eliza, 2014. "How does trading volume affect financial return distributions?," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 190-206.
    2. Huang, Shupei & An, Haizhong & Wen, Shaobo & An, Feng, 2017. "Revisiting driving factors of oil price shocks across time scales," Energy, Elsevier, vol. 139(C), pages 617-629.
    3. Tschernig, Rolf & Weber, Enzo & Weigand, Roland, 2014. "Long- versus medium-run identification in fractionally integrated VAR models," Economics Letters, Elsevier, vol. 122(2), pages 299-302.
    4. Andrea Cipollini & Iolanda Lo Cascio & Silvia Muzzioli, 2015. "Financial connectedness among European volatility risk premia," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 15112, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    5. Cipollini, Andrea & Lo Cascio, Iolanda & Muzzioli, Silvia, 2018. "Risk aversion connectedness in five European countries," Economic Modelling, Elsevier, vol. 71(C), pages 68-79.
    6. Contreras-Reyes, Javier E., 2022. "Rényi entropy and divergence for VARFIMA processes based on characteristic and impulse response functions," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    7. Bissoondoyal-Bheenick, Emawtee & Do, Hung & Hu, Xiaolu & Zhong, Angel, 2022. "Sentiment and stock market connectedness: Evidence from the U.S. – China trade war," International Review of Financial Analysis, Elsevier, vol. 80(C).
    8. Andrea Cipollini & Iolanda Lo Cascio & Silvia Muzzioli, 2015. "Financial connectedness among European volatility risk premia," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0058, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    9. Do, Hung Xuan & Brooks, Robert & Treepongkaruna, Sirimon & Wu, Eliza, 2014. "The effects of sovereign rating drifts on financial return distributions: Evidence from the European Union," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 5-20.
    10. Andrea Cipollini & Iolanda Lo Cascio & Silvia Muzzioli, 2014. "Volatility risk premia and financial connectedness," Department of Economics 0047, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    11. Andrea Cipollini & Iolanda Lo Cascio & Silvia Muzzioli, 2014. "Volatility risk premia and financial connectedness," Center for Economic Research (RECent) 109, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    12. Pan, Qunxing & Mei, Xiaowen & Gao, Tianqing, 2022. "Modeling dynamic conditional correlations with leverage effects and volatility spillover effects: Evidence from the Chinese and US stock markets affected by the recent trade friction," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    13. Bissoondoyal-Bheenick, Emawtee & Do, Hung & Hu, Xiaolu & Zhong, Angel, 2021. "Learning from SARS: Return and volatility connectedness in COVID-19," Finance Research Letters, Elsevier, vol. 41(C).

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    More about this item

    Keywords

    Generalized impulse response; Fractionally integrated VAR model; Long memory;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • 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

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