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Long Run Covariance Matrices for Fractionally Integrated Processes

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Abstract

An asymptotic expansion is given for the autocovariance matrix of a vector of stationary long-memory processes with memory parameters d satisfying 0

Suggested Citation

  • Peter C.B. Phillips & Chang Sik Kim, 2007. "Long Run Covariance Matrices for Fractionally Integrated Processes," Cowles Foundation Discussion Papers 1611, Cowles Foundation for Research in Economics, Yale University.
  • Handle: RePEc:cwl:cwldpp:1611
    Note: CFP 1217.
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    File URL: https://cowles.yale.edu/sites/default/files/files/pub/d16/d1611.pdf
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    Cited by:

    1. Kruse, Robinson & Leschinski, Christian & Will, Michael, 2016. "Comparing Predictive Accuracy under Long Memory - With an Application to Volatility Forecasting," Hannover Economic Papers (HEP) dp-571, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    2. Phillips, Peter C.B., 2009. "Long memory and long run variation," Journal of Econometrics, Elsevier, vol. 151(2), pages 150-158, August.
    3. Qunyong Wang & Na Wu, 2012. "Long-run covariance and its applications in cointegration regression," Stata Journal, StataCorp LP, vol. 12(3), pages 525-542, September.
    4. Christopoulos, Dimitris & McAdam, Peter, 2017. "Do financial reforms help stabilize inequality?," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 45-61.
    5. Leschinski, Christian, 2017. "On the memory of products of long range dependent time series," Economics Letters, Elsevier, vol. 153(C), pages 72-76.
    6. Farzad Sabzikar & Qiying Wang & Peter C.B. Phillips, 2018. "Asymptotic Theory for Near Integrated Process Driven by Tempered Linear Process," Cowles Foundation Discussion Papers 2131, Cowles Foundation for Research in Economics, Yale University.

    More about this item

    Keywords

    Asymptotic expansion; Autocovariance function; Fourier integral; Long memory; Long run variance; Spectral density;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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