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A LIMIT THEOREM FOR MILDLY EXPLOSIVE AUTOREGRESSION WITH STABLE ERRORS

Published online by Cambridge University Press:  30 January 2007

Alexander Aue
Affiliation:
Clemson University
Lajos Horváth
Affiliation:
University of Utah

Abstract

We discuss the limiting behavior of the serial correlation coefficient in mildly explosive autoregression, where the error sequence is in the domain of attraction of an α-stable law, α ∈ (0,2]. Therein, the autoregressive coefficient ρ = ρn > 1 is assumed to satisfy the condition ρn → 1 such that nn − 1) → ∞ as n → ∞. In contrast to the vast majority of existing literature in the area, no specific form of ρ is required. We show that the serial correlation coefficient converges in distribution to a ratio of two independent stable random variables.The authors thank P.C.B. Phillips and two anonymous referees for a very careful reading of the manuscript, pointing out several mistakes, and providing shorter and simpler proofs. This research was partially supported by NATO grant PST.EAP.CLG 980599 and NSF-OTKA grant INT-0223262. This work was done while the first author was at the University of Utah.

Type
Research Article
Copyright
© 2007 Cambridge University Press

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References

REFERENCES

Anderson, T.W. (1959) On asymptotic distributions of estimates of parameters of stochastic difference equations. Annals of Mathematical Statistics 30, 676687.Google Scholar
Bingham, N.H., C.M. Goldie, & J.L. Teugels (1987) Regular Variation. Cambridge University Press.
Brockwell, P.J. & R.A. Davis (1991) Time Series: Theory and Methods, 2nd ed. Springer-Verlag.
Chan, N.H. (1990) Inference for near-integrated time series with infinite variance. Journal of the American Statistical Association 85, 10691074.Google Scholar
Chan, N.H. & L.T. Tran (1989) On the first-order autoregressive process with infinite variance. Econometric Theory 5, 354362.Google Scholar
Chan, N.H. & C.Z. Wei (1987) Asymptotic inference for nearly nonstationary AR(1) processes. Annals of Statistics 15, 10501063.Google Scholar
Chan, N.H. & C.Z. Wei (1988) Limiting distributions of least squares estimates of unstable autoregressive processes. Annals of Statistics 16, 367401.Google Scholar
Csörgő, M. & L. Horváth (1993) Weighted Approximations in Probability and Statistics. Wiley.
De Acosta, A. & E. Giné (1979) Convergence of moments and related functionals in the general central limit theorem in Banach spaces. Zeitschrift für Wahrscheinlichkeitstheorie und Verwandte Gebiete 48, 213231.Google Scholar
Dickey, D.A. & W.A. Fuller (1979) Distributions of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association 74, 427431.Google Scholar
Dickey, D.A. & W.A. Fuller (1981) Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica 49, 10571072.Google Scholar
Fama, E.F. (1965) The behavior of stock-market prices. Journal of Business 38, 34105.Google Scholar
Gikhman, I.I. & A.V. Skorohod (1969) Introduction to the Theory of Random Processes. Saunders.
Giraitis, L. & P.C.B. Phillips (2006) Uniform limit theory for stationary autoregression. Journal of Time Series Analysis 27, 5160.Google Scholar
Ibragimov, I.A. & Y.V. Linnik (1971) Independent and Stationary Sequences of Random Variables. Wolters-Noordhoff.
Kaczor, W.J. & M.T. Nowak (2003) Problems in Mathematical Analysis, vol. 3, Integration. American Mathematical Society.
Mandelbrot, B. (1963) The variation of certain speculative prices. Journal of Business 36, 394419.Google Scholar
Mandelbrot, B. (1969) Long-run linearity, locally Gaussian process, H-spectra and infinite variances. International Economic Review 10, 82111.Google Scholar
Mijnheer, J. (2002) Asymptotic inference for AR(1) processes with (nonnormal) stable innovations, part 5: The explosive case. Journal of Mathematical Sciences 111, 38543856.Google Scholar
Mittnik, S. & S. Rachev (2000) Stable Paretian Models in Finance. Wiley.
Nelson, C.R. & C. Plosser (1982) Trends and random walks in macroeconomic time series: Some evidence and implications. Journal of Monetary Economics 10, 139162.Google Scholar
Petrov, V.V. (1975) Sums of Independent Random Variables. Springer-Verlag.
Phillips, P.C.B. (1988) Regression theory for near-integrated time series. Econometrica 56, 10211043.Google Scholar
Phillips, P.C.B. & T. Magdalinos (2007) Limit theory for moderate deviations from a unit root. Journal of Econometrics 136, 115130.Google Scholar
Samorodnitsky, G. & M. Taqqu (1994) Stable Non-Gaussian Random Processes. Chapman and Hall.
White, J.S. (1958) The limiting distribution of the serial correlation coefficient in the explosive case. Annals of Mathematical Statistics 29, 11881197.Google Scholar
Zolotarev, V.M. (1986) One-Dimensional Stable Distributions. Translations of Mathematical Monographs 65. American Mathematical Society.