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Generating Univariate Fractional Integration within a Large VAR(1)

Author

Listed:
  • Guillaume Chevillon

    (Department of Information Systems, Decision Sciences and Statistics, ESSEC Business School)

  • Alain Hecq

    (Department of Quantitative Economics, School of Business and Economics, Maastricht University)

  • Sébastien Laurent

    () (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - Ecole Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique, Aix-Marseille Graduate School of Management)

Abstract

This paper shows that a large dimensional vector autoregressive model (VAR) of finite order can generate fractional integration in the marginalized univariate series. We derive high-level assumptions under which the final equation representation of a VAR(1) leads to univariate fractional white noises and verify the validity of these assumptions for two specific models.

Suggested Citation

  • Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating Univariate Fractional Integration within a Large VAR(1)," Working Papers halshs-01944588, HAL.
  • Handle: RePEc:hal:wpaper:halshs-01944588
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-01944588
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Gianluca Cubadda & Alain Hecq & Antonio Riccardo, 2018. "Forecasting Realized Volatility Measures with Multivariate and Univariate Models: The Case of The US Banking Sector," CEIS Research Paper 445, Tor Vergata University, CEIS, revised 30 Oct 2018.
    2. Alain Hecq & Luca Margaritella & Stephan Smeekes, 2019. "Granger Causality Testing in High-Dimensional VARs: a Post-Double-Selection Procedure," Papers 1902.10991, arXiv.org.

    More about this item

    Keywords

    final equation representation; long memory; vector autoregressive model; marginalization;

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - 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
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

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