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Canonical Correlation Analysis in Panel Vector Error Correction Model. Performance Comparison

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  • Piotr Kębłowski

    (University of Łódź)

Abstract

Small sample properties of unrestricted and restricted canonical correlation estimators of cointegrating vectors for panel vector autoregressive process are considered when the cross-sectional dependencies occur in the process generating nonstationary panel data. It is shown that the unrestricted Box-Tiao estimator is slightly outperformed by the unrestricted Johansen estimator if the dynamic properties of the underlying process are correctly specified. The comparison of performance of the restricted canonical correlation estimator of cointegrating vectors for the panel VAR and for the classical VAR applied independently for each cross-section reveals that the latter performs better in small samples when the cross-sectional dependence is limited to the error terms correlations, even though it is inefficient in the limit, but it falls short in comparison to the former when there are cross-sectional dependencies in the short-run dynamics and/or in the long-run adjustments.

Suggested Citation

  • Piotr Kębłowski, 2016. "Canonical Correlation Analysis in Panel Vector Error Correction Model. Performance Comparison," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(4), pages 203-217, December.
    • Handle: RePEc:psc:journl:v:8:y:2016:i:4:p:203-217
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    More about this item

    Keywords

    canonical correlation analysis; cointegration; panel VEC model; LCCA; Box-Tiao approach;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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