Properties of etimated characteristic roots
Estimated characteristic roots in stationary autoregressions are shown to give rather noisy information about their population equivalents. This is remarkable given the central role of the characteristic roots in the theory of autoregressive processes. In the asymptotic analysis the problems appear when multiple roots are present as this imply a non-differentiability so the d-method does not apply, convergence rates are slow, and the asymptotic distribution is non-normal. In finite samples this has a considerable influence on the finite sample distribution unless the roots are far apart. With increasing order of the autoregressions it becomes increasingly difficult to place the roots far apart giving a very noisy signal from the characteristic roots.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Clive W. J. Granger & Yongil Jeon, 2006. "Dynamics of Model Overfitting Measured in terms of Autoregressive Roots," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(3), pages 347-365, May.
- Søren Johansen, 2003.
"The asymptotic variance of the estimated roots in a cointegrated vector autoregressive model,"
Journal of Time Series Analysis,
Wiley Blackwell, vol. 24(6), pages 663-678, November.
- Soren JOHANSEN, 2001. "The Asymptotic Variance of the Estimated Roots in a Cointegrated Vector Autoregressive Model," Economics Working Papers ECO2001/01, European University Institute.
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- Pantula, Sastry G., 1989. "Testing for Unit Roots in Time Series Data," Econometric Theory, Cambridge University Press, vol. 5(02), pages 256-271, August. Full references (including those not matched with items on IDEAS)