Inference on nonstationary time series with moving mean

Gao, Jiti and Robinson, Peter M. (2016) Inference on nonstationary time series with moving mean. Econometric Theory, 32 (02). pp. 431-457. ISSN 0266-4666

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Abstract

A semiparametric model is proposed in which a parametric filtering of a nonstationary time series, incorporating fractionally differencing with short memory correction, removes correlation but leaves a nonparametric deterministic trend. Estimates of the memory parameter and other dependence parameters are proposed, and shown to be consistent and asymptotically normally distributed with parametric rate. Tests with standard asymptotics for I(1) and other hypotheses are thereby justified. Estimation of the trend function is also considered. We include a Monte Carlo study of finite-sample performance.

Item Type:	Article
Official URL:	http://journals.cambridge.org/action/displayJourna...
Additional Information:	© 2014 Cambridge University Press
Library of Congress subject classification:	H Social Sciences > HB Economic Theory
Sets:	Departments > Economics
Project and Funder Information:	Project ID Funder Name Funder ID ES/J007242/1 Economic and Social Research Council http://dx.doi.org/10.13039/501100000269
Date Deposited:	12 May 2016 15:13
URL:	http://eprints.lse.ac.uk/66509/

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