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Structure-Based SVAR Identification

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  • Emanuele BACCHIOCCHI
  • Riccardo Jack LUCCHETTI

Abstract

It may be desirable, for various reasons, to establish criteria for SVAR identification that do not depend on unknown parameters, but only on the set of restrictions that are imposed on the system a priori on theoretical grounds. In the context of linear systems, this was accomplished in Johansen (1995). This paper extends and amends the approach proposed by Lucchetti (2006); we introduce a set of criteria, which ensure identification independently of unknown parameters for a reasonably general class of models and discuss its possible generalization.

Suggested Citation

  • Emanuele BACCHIOCCHI & Riccardo Jack LUCCHETTI, 2015. "Structure-Based SVAR Identification," Departmental Working Papers 2015-11, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
  • Handle: RePEc:mil:wpdepa:2015-11
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    References listed on IDEAS

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    7. 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.
    8. Olivier Blanchard & Roberto Perotti, 2002. "An Empirical Characterization of the Dynamic Effects of Changes in Government Spending and Taxes on Output," The Quarterly Journal of Economics, Oxford University Press, vol. 117(4), pages 1329-1368.
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    More about this item

    Keywords

    SVAR; Identification; Rado Condition;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - 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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