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INFERENCE ON NONSTATIONARY TIME SERIES WITH MOVING MEAN

Published online by Cambridge University Press:  29 December 2014

Jiti Gao  and
Peter M. Robinson
Jiti Gao
Affiliation:
Monash University and London School of Economics
Peter M. Robinson*
Affiliation:
Monash University and London School of Economics
*
*Address correspondence to Peter Robinson, Department of Economics, London School of Economics, Houghton Street, London WC2A 2AE, UK; e-mail: p.m.robinson@lse.ac.uk.
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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.

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Type
ARTICLES
Information
Econometric Theory , Volume 32 , Issue 2 , April 2016 , pp. 431 - 457
Copyright
Copyright © Cambridge University Press 2014 

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