Asymptotic Inference For Nonstationary Fractionally Integrated Autoregressive Moving-Average Models
AbstractThis paper considers nonstationary fractional autoregressive integrated moving-average (p,d,q) models with the fractionally differencing parameter d ( 1/2,1/2) and the autoregression function with roots on or outside the unit circle. Asymptotic inference is based on the conditional sum of squares (CSS) estimation. Under some suitable conditions, it is shown that CSS estimators exist and are consistent. The asymptotic distributions of CSS estimators are expressed as functions of stochastic integrals of usual Brownian motions. Unlike results available in the literature, the limiting distributions of various unit roots are independent of the parameter d over the entire range d ( 1/2,1/2). This allows the unit roots and d to be estimated and tested separately without loss of efficiency. Our results are quite different from the current asymptotic theories on nonstationary long memory time series. The finite sample properties are examined for two special cases through simulations.
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Bibliographic InfoArticle provided by Cambridge University Press in its journal Econometric Theory.
Volume (Year): 17 (2001)
Issue (Month): 04 (August)
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- Søren Johansen & Morten Ørregaard Nielsen, 2007.
"Likelihood Inference for a Nonstationary Fractional Autoregressive Model,"
07-27, University of Copenhagen. Department of Economics.
- Johansen, Søren & Nielsen, Morten Ørregaard, 2010. "Likelihood inference for a nonstationary fractional autoregressive model," Journal of Econometrics, Elsevier, vol. 158(1), pages 51-66, September.
- Søren Johansen & Morten Ørregaard Nielsen, 2010. "Likelihood inference for a nonstationary fractional autoregressive model," Working Papers 1172, Queen's University, Department of Economics.
- Søren Johansen & Morten Ørregaard Nielsen, 2007. "Likelihood inference for a nonstationary fractional autoregressive model," CREATES Research Papers 2007-33, School of Economics and Management, University of Aarhus.
- Morten Oerregaard Nielsen, .
"Efficient Inference in Multivariate Fractionally Integrated Time Series Models,"
Economics Working Papers
2002-6, School of Economics and Management, University of Aarhus.
- Morten Orregaard Nielsen, 2004. "Efficient inference in multivariate fractionally integrated time series models," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 63-97, 06.
- Jakob Roland Munch & Michael Svarer, . "Mortality and Socio-economic Differences in a Competing Risks Model," Economics Working Papers 2001-1, School of Economics and Management, University of Aarhus.
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