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An alternative solution to the Autoregressivity Paradox in time series analysis

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  • Cubadda, Gianluca
  • Triacca, Umberto

Abstract

This note concerns with the marginal models associated with a given vector autoregressive model. In particular, it is shown that a reduction in the orders of the univariate ARMA marginal models can be determined by the presence of variables integrated with different orders. The concepts and methods of the paper are illustrated via an empirical investigation of the low-frequency properties of hours worked in the US.

Suggested Citation

  • Cubadda, Gianluca & Triacca, Umberto, 2011. "An alternative solution to the Autoregressivity Paradox in time series analysis," Economic Modelling, Elsevier, vol. 28(3), pages 1451-1454, May.
    • Handle: RePEc:eee:ecmode:v:28:y:2011:i:3:p:1451-1454
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    8. Cubadda, Gianluca & Hecq, Alain & Palm, Franz C., 2008. "Macro-panels and reality," Economics Letters, Elsevier, vol. 99(3), pages 537-540, June.
    9. Cubadda, Gianluca & Hecq, Alain & Palm, Franz C., 2009. "Studying co-movements in large multivariate data prior to multivariate modelling," Journal of Econometrics, Elsevier, vol. 148(1), pages 25-35, January.
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    Cited by:

    1. Nunzio Cappuccio & Diego Lubian, 2016. "Unit Root Tests: The Role of the Univariate Models Implied by Multivariate Time Series," Econometrics, MDPI, vol. 4(2), pages 1-11, April.

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    More about this item

    Keywords

    VAR models ARIMA models Final equations;

    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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