Inference on nonstationary time series with moving mean

Jiti Gao and Peter M. Robinson

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

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.

JEL-codes: J1 (search for similar items in EconPapers)
Date: 2014-12-29
New Economics Papers: this item is included in nep-ets and nep-ore
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Citations: View citations in EconPapers (1)

Published in Econometric Theory, 29, December, 2014, 32(02), pp. 431-457. ISSN: 0266-4666

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