EconPapers    
Economics at your fingertips  
 

Asymptotic approximations in the near-integrated model with a non-zero initial condition

Pierre Perron () and Cosme Vodounou

Econometrics Journal, 2001, vol. 4, issue 1, 42

Abstract: This paper considers various asymptotic approximations in the near-integrated first-order 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 con-dition, 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 (1991a). We assess, via a Monte Carlo simulation study, the extent to which these alternative methods provide adequate approximations 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, Perron¹s (1991a) continuous-time approximation performs very well while the others only offer improvements when the initial condition is zero.

Keywords: Edgeworth expansion; Continuous-time asymptotics; Stochastic expansion; Dis-tribution function; Autoregressive model. (search for similar items in EconPapers)
Date: 2001
References: Add references at CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Working Paper: Asymptotic Approximations in the Near-Integrated Model with a Non-Zero Initial Condition (1998) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ect:emjrnl:v:4:y:2001:i:1:p:42

Ordering information: This journal article can be ordered from
http://www.ectj.org

Access Statistics for this article

Econometrics Journal is currently edited by Richard J. Smith, Oliver Linton, Pierre Perron, Jaap Abbring and Marius Ooms

More articles in Econometrics Journal from Royal Economic Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing ().

 
Page updated 2019-09-12
Handle: RePEc:ect:emjrnl:v:4:y:2001:i:1:p:42