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Cointegration analysis with state space models

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  • Martin Wagner

Abstract

This paper presents and exemplifies results developed for cointegration analysis with state space models by Bauer and Wagner in a series of papers. Unit root processes, cointegration and polynomial cointegration are defined. Based upon these definitions the major part of the paper discusses how state space models, which are equivalent to VARMA models, can be fruitfully employed for cointegration analysis. By means of detailing the cases most relevant for empirical applications, the I(1), MFI(1) and I(2) cases, a canonical representation is developed and thereafter some available statistical results are briefly mentioned.
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  • Martin Wagner, 2010. "Cointegration analysis with state space models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 94(3), pages 273-305, September.
    • Handle: RePEc:spr:alstar:v:94:y:2010:i:3:p:273-305
    DOI: 10.1007/s10182-010-0138-x
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    2. Bernardina Algieri, 2015. "Price and non-price competitiveness in export demand: empirical evidence from Italy," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 42(1), pages 157-183, February.

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    More about this item

    Keywords

    State space models; Unit roots; Cointegration; Polynomial cointegration; Pseudo maximum likelihood estimation; Subspace algorithms;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: 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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