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On the Identification of Codependent VAR and VEC Models

Author

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  • Trenkler, Carsten
  • Weber, Enzo

Abstract

In this paper we discuss identification of codependent VAR and VEC models. Codependence of order q is given if a linear combination of autocorrelated variables eliminates the serial correlation after q lags. Importantly, maximum likelihood estimation and corresponding likelihood ratio testing are only possible if the codependence restrictions can be uniquely imposed. However, our study reveals that codependent VAR and VEC models are not generally identified. Nevertheless, we show that one can guarantee identification in case of serial correlation common features, i.e. when q=0, and for a single vector generating codependence of order q=1.

Suggested Citation

  • Trenkler, Carsten & Weber, Enzo, 2010. "On the Identification of Codependent VAR and VEC Models," University of Regensburg Working Papers in Business, Economics and Management Information Systems 445, University of Regensburg, Department of Economics.
    • Handle: RePEc:bay:rdwiwi:16477
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    File URL: https://epub.uni-regensburg.de/16477/1/CodependenceIdentification.pdf
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    Cited by:

    1. Carsten Trenkler & Enzo Weber, 2013. "Testing for codependence of cointegrated variables," Applied Economics, Taylor & Francis Journals, vol. 45(15), pages 1953-1964, May.

    More about this item

    Keywords

    Codependence; identification; VAR; cointegration; serial correlation common features;
    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

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