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Decomposition and asymptotic properties of quadratic forms in linear variables

Author

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  • R J Bhansali
  • L Giraitis
  • P Kokoszka

Abstract

An asymptotic theory is developed for a quadratic form Q_{n,X} in linear random variables X1,…,X_{n} which can exhibit long, short, or negative dependence and whose kernel depends on n. It offers conditions under which Q_{n,X} can be approximated in the L1 and L2 norms by a form Q_{n,Z} in i.i.d. random variables Z1,…,Z_{n}. In some cases, the rate of approximation is faster by the factor n^{-1/2} compared to existing results. The approximation, together with a new CLT for quadratic forms in i.i.d. variables Z_{k} with non-zero diagonal elements, allows us to derive the CLT for the quadratic form Q_{n,X} in the linear variables X_{k}. The assumptions are similar to the well-known classical conditions for the validity of the CLT in the i.i.d. case and require the existence of the fourth moment of the Z_{k}, and in some cases only the (2+e)-th moment where e>0 and small. The results have a number of statistical applications.

Suggested Citation

  • R J Bhansali & L Giraitis & P Kokoszka, "undated". "Decomposition and asymptotic properties of quadratic forms in linear variables," Discussion Papers 05/18, Department of Economics, University of York.
  • Handle: RePEc:yor:yorken:05/18
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    Cited by:

    1. Giraitis, Liudas & Phillips, Peter C.B., 2012. "Mean and autocovariance function estimation near the boundary of stationarity," Journal of Econometrics, Elsevier, vol. 169(2), pages 166-178.
    2. Abadir, Karim M. & Distaso, Walter & Giraitis, Liudas, 2009. "Two estimators of the long-run variance: Beyond short memory," Journal of Econometrics, Elsevier, vol. 150(1), pages 56-70, May.

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