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Testing Time-Series Stationarity Against An Alternative Whose Mean Is Periodic

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Author Info
Hinich, Melvin A.
Wild, Phillip

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Abstract

We develop a test of the null hypothesis that an observed time series is a realization of a strictly stationary random process. Our test is based on the result that the kth value of the discrete Fourier transform of a sample frame has a zero mean under the null hypothesis. The test that we develop will have considerable power against an important form of nonstationarity hitherto not considered in the mainstream econometric time-series literature, that is, where the mean of a time series is periodic with random variation in its periodic structure. The size and power properties of the test are investigated and its applicability to real-world problems is demonstrated by application to three economic data sets.

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File URL: http://journals.cambridge.org/abstract_S1365100500020034
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Publisher Info
Article provided by Cambridge University Press in its journal Macroeconomic Dynamics.

Volume (Year): 5 (2001)
Issue (Month): 03 (June)
Pages: 380-412
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Handle: RePEc:cup:macdyn:v:5:y:2001:i:03:p:380-412_02

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  1. Barry E. Jones & Travis D. Nesmith, 2006. "Linear cointegration of nonlinear time series with an application to interest rate dynamics," Finance and Economics Discussion Series 2007-03, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
    Other versions:
  2. Barry E. Jones & Travis D. Nesmith, 1999. "Tests for non-linear dynamics in systems of non-stationary economic time series: the case of short-term US interest rates," Finance and Economics Discussion Series 1999-55, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
  3. Phillip Wild & Melvin J. Hinich & John Foster, 2008. "Are Daily and Weekly Load and Spot Price Dynamics in Australia’s National Electricity Market Governed by Episodic Nonlinearity?," Discussion Papers Series 368, School of Economics, University of Queensland, Australia. [Downloadable!]
  4. Phillip Wild & Melvin J. Hinich & John Foster, 2008. "The Use of Trimming to Improve the Performance of Tests for Nonlinear Serial Dependence with Application to the Australian National Electricity Market," Discussion Papers Series 367, School of Economics, University of Queensland, Australia. [Downloadable!]
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This page was last updated on 2009-11-28.


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