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On The Asymptotic Distribution Of Impulse Response Functions With Long-Run Restrictions

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  • Vlaar, Peter J.G.

Abstract

This paper adopts a two-step technique to estimate structural vector error correction models and provides the asymptotic distribution of the impulse response functions of such a system. The method combines two popular tools in econometrics, namely, vector autoregressive cointegration analysis in the first step and structural vector autoregression analysis in the second. The proposed structural model structure is very general in the sense that all just-identifying or overidentifying schemes that can be expressed as linear restrictions on either the contemporaneous or long-run impact of the structural shocks are allowed for. The long-run restrictions complicate the derivation of the asymptotic distribution of the structural parameter estimates as these restrictions are a function of the reduced form parameters. Consequently, the asymptotic distribution involves an extra partial derivative.Useful comments by Peter Boswijk, Günter Coenen, Neil Ericsson, Sören Johansen, Klaus Neusser, Franz Palm, Paolo Paruolo, Peter van Els, Anders Warne, and ESEM 1998 participants are gratefully acknowledged. The paper also significantly benefited from suggestions by the co-editor Pentti Saikkonen and two anonymous referees.

Suggested Citation

  • Vlaar, Peter J.G., 2004. "On The Asymptotic Distribution Of Impulse Response Functions With Long-Run Restrictions," Econometric Theory, Cambridge University Press, vol. 20(5), pages 891-903, October.
    • Handle: RePEc:cup:etheor:v:20:y:2004:i:05:p:891-903_20
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    Cited by:

    1. Emanuele BACCHIOCCHI & Luca FANELLI, 2012. "Identification in structural vector autoregressive models with structural changes," Departmental Working Papers 2012-16, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    2. Juan José Echavarría Soto & Enrique López Enciso & Martha Misas Arango, 2008. "La tasa de cambio real de equilibrio en Colombia y su desalineamiento: estimación a través de un modelo SVEC," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 26(57), pages 282-319, December.
    3. Lütkepohl, Helmut, 2008. "Problems related to over-identifying restrictions for structural vector error correction models," Economics Letters, Elsevier, vol. 99(3), pages 512-515, June.
    4. Emanuele Bacchiocchi & Efrem Castelnuovo & Luca Fanelli, 2014. "Gimme a break! Identification and estimation of the macroeconomic effects of monetary policy shocks in the U.S," "Marco Fanno" Working Papers 0181, Dipartimento di Scienze Economiche "Marco Fanno".
    5. Bisio Laura & Faccini Andrea, 2010. "Does cointegration matter? An analysis in a RBC perspective," wp.comunite 0066, Department of Communication, University of Teramo.
    6. Velinov, Anton, 2016. "On the importance of testing structural identification schemes and the potential consequences of incorrectly identified models," VfS Annual Conference 2016 (Augsburg): Demographic Change 145581, Verein für Socialpolitik / German Economic Association.
    7. Skrobotov, Anton (Скроботов, Антон) & Turuntseva, Marina (Турунцева, Марина), 2015. "Theoretical Aspects of Modeling of the SVAR [Теоретические Аспекты Моделирования Svar]," Published Papers mak8, Russian Presidential Academy of National Economy and Public Administration.
    8. Kyungho Jang, 2008. "A Structural Vector Error Correction Model with Short-run and Long-run Restrictions," Korean Economic Review, Korean Economic Association, vol. 24, pages 199-232.
    9. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2014. "Dynamic Factor Models, Cointegration and Error Correction Mechanisms," Working Papers ECARES ECARES 2014-14, ULB -- Universite Libre de Bruxelles.
    10. Klemens Hauzenberger & Robert Stehrer, 2010. "An Empirical Characterization of Redistribution Shocks and Output Dynamics," wiiw Working Papers 68, The Vienna Institute for International Economic Studies, wiiw.

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