Asymptotic Approximations in the Near-Integrated Model with a Non-Zero Initial Condition

Pierre Perron () and Cosme VODOUNOU

Cahiers de recherche from Universite de Montreal, Departement de sciences economiques

Abstract: This paper considers various asymptotic approximations in the near-integrated firstorder autoregressive model with a non-zero initial condition. We first extend the work of Knight and Satchell (1993), who considered the random walk case with a zero initial condition, to derive the expansion of the relevant joint moment generating function in this more general framework. We also consider, as alternative approximations, the stochastic expansion of Phillips (1987c) and the continuous time approximation of Perron (1991). We assess how these alternative methods provide or not an adequate approximation to the finite-sample distribution of the least-squares estimator in a first-order autoregressive model. The results show that, when the initial condition is non-zero, Perron's (1991) continuous time approximation performs very well while the others only offer improvements when the initial condition is zero.

Keywords: Edgeworth exnsion; continuous-time asymotics; stochastic exnsion; distribution function; autoregressive model (search for similar items in EconPapers)
JEL-codes: C10 C13 (search for similar items in EconPapers)
Date: Written 1998
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Related works:
Journal Article: Asymptotic approximations in the near-integrated model with a non-zero initial condition (2001)
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Persistent link: http://EconPapers.repec.org/RePEc:mtl:montde:9815

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