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Generalized Impulse Response Analysis: General or Extreme?

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  • Hyeongwoo, Kim

Abstract

This note discusses a pitfall of using the generalized impulse response function (GIRF) in vector autoregressive (VAR) models (Pesaran and Shin, 1998). The GIRF is general because it is invariant to the ordering of the variables in the VAR. The GIRF, in fact, is extreme because it yields a set of response functions that are based on extreme identifying assumptions that contradict each other, unless the covariance matrix is diagonal. With an empirical example, the present note demonstrates that the GIRF may yield quite misleading economic inferences.

Suggested Citation

  • Hyeongwoo, Kim, 2009. "Generalized Impulse Response Analysis: General or Extreme?," MPRA Paper 17014, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:17014
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    1. Boyd, Derick & Caporale, Gugielmo Maria & Smith, Ron, 2001. "Real Exchange Rate Effects on the Balance of Trade: Cointegration and the Marshall-Lerner Condition," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 6(3), pages 187-200, July.
    2. Huang, Ying & Neftci, Salih N. & Guo, Feng, 2008. "Swap curve dynamics across markets: Case of US dollar versus HK dollar," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(1), pages 79-93, February.
    3. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    4. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    5. Cheung, Yin-Wong & Lai, Kon S. & Bergman, Michael, 2004. "Dissecting the PPP puzzle: the unconventional roles of nominal exchange rate and price adjustments," Journal of International Economics, Elsevier, vol. 64(1), pages 135-150, October.
    6. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
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    Cited by:

    1. Haakon Kavli & Kevin Kotzé, 2014. "Spillovers in Exchange Rates and the Effects of Global Shocks on Emerging Market Currencies," South African Journal of Economics, Economic Society of South Africa, vol. 82(2), pages 209-238, June.
    2. Cain, P.M., 2022. "Modelling short-and long-term marketing effects in the consumer purchase journey," International Journal of Research in Marketing, Elsevier, vol. 39(1), pages 96-116.
    3. Khodeir, Aliaa, 2015. "Migration Remittances Inflows and Macroeconomic Shocks: The Case of Egypt," MPRA Paper 103506, University Library of Munich, Germany, revised 2015.
    4. Gao, Liping & Kim, Hyeongwoo & Saba, Richard, 2013. "How Does the Oil Price Shock Affect Consumers?," MPRA Paper 49565, University Library of Munich, Germany.
    5. Kim, Hyeongwoo & Thompson, Henry, 2014. "Wages in a factor proportions model with energy input," Economic Modelling, Elsevier, vol. 36(C), pages 495-501.
    6. Randolph Beard, T. & Ford, George S. & Kim, Hyeongwoo, 2014. "Capital investment and employment in the information sector," Telecommunications Policy, Elsevier, vol. 38(4), pages 371-382.
    7. Kim, Hyeongwoo & Thompson, Henry, 2009. "Factor Proportions Wages in a Structural Vector Autoregression," MPRA Paper 17798, University Library of Munich, Germany.
    8. Ülkü, Numan & Karpova, Yekaterina, 2014. "Do international equity investors rebalance to manage currency exposure? A study of Greece foreign investor flows data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 29(C), pages 150-169.
    9. Bastos, Fabiano & Angelo Divino, Jose, 2009. "Exchange rate and output fluctuations in the small open economy of Mauritius," Policy Research Working Paper Series 5065, The World Bank.
    10. Ülkü, Numan & Demirci, Ebru, 2012. "Joint dynamics of foreign exchange and stock markets in emerging Europe," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(1), pages 55-86.
    11. Jin Zhang & David C. Broadstock, 2016. "The Causality between Energy Consumption and Economic Growth for China in a Time-varying Framework," The Energy Journal, , vol. 37(1_suppl), pages 29-54, January.
    12. Stefan Fiesel & Marliese Uhrig-Homburg, 2016. "Illiquidity Transmission in a Three-Country Framework: A Conditional Approach," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 17(3), pages 261-284, December.
    13. Numan Ülkü & Petar Petrov, 2015. "How Reliable Are the Findings of ‘Foreign’ Investor Studies That Use TIC Data? A Look from the Host Market," International Review of Finance, International Review of Finance Ltd., vol. 15(4), pages 521-553, December.
    14. Eskandar Elmarzougui & Bruno Larue, 2013. "On the Evolving Relationship Between Corn and Oil Prices," Agribusiness, John Wiley & Sons, Ltd., vol. 29(3), pages 344-360, June.
    15. T. Beard & John Jackson & David Kaserman & Hyeongwoo Kim, 2012. "A time-series analysis of the U.S. kidney transplantation and the waiting list: donor substitution effects," Empirical Economics, Springer, vol. 42(1), pages 261-277, February.
    16. Kim, Hyeongwoo, 2012. "VECM estimations of the PPP reversion rate revisited: The conventional role of relative price adjustment restored," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 223-238.

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    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
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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