Cookies?
Library Header Image
LSE Research Online LSE Library Services

Conditional-sum-of-squares estimation of models for stationary time series with long memory

Robinson, Peter (2006) Conditional-sum-of-squares estimation of models for stationary time series with long memory. EM/2006/505. Suntory and Toyota International Centres for Economics and Related Disciplines, London School of Economics and Political Science, London, UK.

[img]
Preview
PDF
Download (210Kb) | Preview

Abstract

Employing recent results of Robinson (2005) we consider the asymptotic properties of conditional-sum-of-squares (CSS) estimates of parametric models for stationary time series with long memory. CSS estimation has been considered as a rival to Gaussian maximum likelihood and Whittle estimation of time series models. The latter kinds of estimate have been rigorously shown to be asymptotically normally distributed in case of long memory. However, CSS estimates, which should have the same asymptotic distributional properties under similar conditions, have not received comparable treatment: the truncation of the infinite autoregressive representation inherent in CSS estimation has been essentially ignored in proofs of asymptotic normality. Unlike in short memory models it is not straightforward to show the truncation has negligible effect.

Item Type: Monograph (Discussion Paper)
Official URL: http://sticerd.lse.ac.uk
Additional Information: © 2006 the author
Library of Congress subject classification: H Social Sciences > HB Economic Theory
Sets: Collections > Economists Online
Departments > Economics
Research centres and groups > Suntory and Toyota International Centres for Economics and Related Disciplines (STICERD)
Rights: http://www.lse.ac.uk/library/usingTheLibrary/academicSupport/OA/depositYourResearch.aspx
Identification Number: EM/2006/505
Date Deposited: 28 Apr 2008 14:59
URL: http://eprints.lse.ac.uk/4536/

Actions (login required)

Record administration - authorised staff only Record administration - authorised staff only