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Structural analysis with independent innovations

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  • Herwartz, Helmut

Abstract

Structural innovations in multivariate dynamic systems are typically hidden and often identified by means of a-priori economic reasoning. Under multivariate Gaussian model innovations there is no loss measure available to distinguish alternative orderings of variables or, put differently, between particular identifying restrictions and rotations thereof. Based on a non Gaussian framework of independent innovations, a loss statistic is proposed in this paper that allows to discriminate between alternative identifying assumptions on the basis of nonparametric density estimates. The merits of the proposed identification strategy are illustrated by means of a Monte Carlo study. Real data applications cover bivariate systems comprising US stock prices and total factor productivity, and four couples of international breakeven inflation rates to investigate monetary autonomy of the Bank of Canada and the Bank of England.

Suggested Citation

  • Herwartz, Helmut, 2014. "Structural analysis with independent innovations," Center for European, Governance and Economic Development Research Discussion Papers 208, University of Goettingen, Department of Economics.
  • Handle: RePEc:zbw:cegedp:208
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    Cited by:

    1. Herwartz, Helmut & Walle, Yabibal M., 2014. "Openness and the finance-growth nexus," Journal of Banking & Finance, Elsevier, vol. 48(C), pages 235-247.

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    More about this item

    Keywords

    structural innovations; identifying assumptions; SVAR; Cholesky decomposition; news shocks; monetary independence;
    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
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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