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Biases of correlograms and of AR representations of stationary series

Author

Listed:
  • K Abadir
  • R Larsson

Abstract

We derive the relation between the biases of correlograms and of estimates of auto-regressive AR(k) representations of stationary series. We illustrate our approach with a simple AR(2) example, then apply it to the more substantive case of a fractionally-integrated processes where the results have not been derived before. In such a case, k needs to be asymptotically a concave and increasing function of the sample size T. It turns out that the AR representation of I(d) processes leads to biases that are much smaller than for traditional AR models, hence making it an attractive representation.

Suggested Citation

  • K Abadir & R Larsson, "undated". "Biases of correlograms and of AR representations of stationary series," Discussion Papers 05/21, Department of Economics, University of York.
    • Handle: RePEc:yor:yorken:05/21
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    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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