Abstract

This paper investigates the possibility, raised by Perron (1989, 1990a), that aggregate economic time series can be characterized as being stationary around broken trend lines. Unlike Perron, we treat the break date as unknown a priori. Asymptotic distributions are developed for recursive, rolling, and sequential tests for unit roots and/or changing coefficients in time series regressions. The recursive and rolling tests are based on a time series of recursively estimated coefficients, computed using increasing subsamples of the data. The sequential statistics are computed using the full data set and a sequence of regressors indexed by a "break" date. When applied to data on real postwar output from seven DECO countries, these techniques fail to reject the unit root hypothesis for five countries (including the U.S.), but suggest stationarity around a shifted trend for Japan.

Keywords

Unit rootSeries (stratigraphy)MathematicsEconometricsSequence (biology)A priori and a posterioriAggregate (composite)Structural breakStatisticsSet (abstract data type)Statistical hypothesis testingSequential analysisLong memoryAsymptotic analysisApplied mathematicsComputer science

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Year
1990
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article
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225
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Anindya Banerjee, Robin L. Lumsdaine, James H. Stock (1990). Recursive and Sequential Tests of the Unit Root and Trend Break Hypothesis: Theory and International Evidence. . https://doi.org/10.3386/w3510

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DOI
10.3386/w3510