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Inference on nonparametrically trending time series with fractional errors

Robinson, Peter (2009) Inference on nonparametrically trending time series with fractional errors. Econometric Theory, 25 (6). pp. 1716-1733. ISSN 1469-4360

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Identification Number: 10.1017/S0266466609990302


The central limit theorem for nonparametric kernel estimates of a smooth trend, with linearly generated errors, indicates asymptotic independence and homoskedasticity across fixed points, irrespective of whether disturbances have short memory, long memory, or antipersistence. However, the asymptotic variance depends on the kernel function in a way that varies across these three circumstances, and in the latter two it involves a double integral that cannot necessarily be evaluated in closed form. For a particular class of kernels, we obtain analytic formulas. We discuss extensions to more general settings, including ones involving possible cross-sectional or spatial dependence.

Item Type: Article
Official URL:
Additional Information: © 2009 Cambridge University Press
Divisions: Economics
Subjects: H Social Sciences > HB Economic Theory
Sets: Collections > Economists Online
Departments > Economics
Date Deposited: 11 Jan 2010 10:28
Last Modified: 20 Jun 2021 01:42

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