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Orthogonal Impulse Response Analysis in Presence of Time-Varying Covariance

In: Research Papers in Statistical Inference for Time Series and Related Models

Author

Listed:
  • Valentin Patilea

    (Campus de Ker-Lann, CREST Ensai)

  • Hamdi Raïssi

    (Pontificia Universidad Católica de Valparaíso)

Abstract

In this paper, the orthogonal impulse response functions (OIRFs) are studied in the non-standard but quite common case where the covariance of the error vector is not constant in time. The usual approach for taking such covariance behavior into account consists in applying the standard tools to sub-periods of the whole sample. We underline that such a practice may lead to severe upward bias. We propose a new approach intended to give what we argue to be a more accurate summary of the time-varying OIRFs. This consists in averaging the Cholesky decomposition of nonparametric covariance estimators. In addition, an index is developed to evaluate the heteroscedasticity effect on the OIRFs analysis. The asymptotic behavior of the proposed estimators is investigated.

Suggested Citation

  • Valentin Patilea & Hamdi Raïssi, 2023. "Orthogonal Impulse Response Analysis in Presence of Time-Varying Covariance," Springer Books, in: Yan Liu & Junichi Hirukawa & Yoshihide Kakizawa (ed.), Research Papers in Statistical Inference for Time Series and Related Models, chapter 0, pages 419-443, Springer.
    • Handle: RePEc:spr:sprchp:978-981-99-0803-5_18
    DOI: 10.1007/978-981-99-0803-5_18
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