Time Series Regression with a Unit Root

This paper studies the random walk, in a general time series setting that allows for weakly dependent and heterogeneously distributed innovations. It is shown that simple least squares regression consistently estimates a unit root under very general conditions in spite of the presence of autocorrela...

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Veröffentlicht in:Econometrica. - Wiley. - 55(1987), 2, Seite 277-301
1. Verfasser: Phillips, P. C. B. (VerfasserIn)
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 1987
Zugriff auf das übergeordnete Werk:Econometrica
Schlagworte:Unit root, time series, functional limit theory, Wiener process, weak dependence, continuous record, asympototic expansion Information science Mathematics Philosophy Economics
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520 |a This paper studies the random walk, in a general time series setting that allows for weakly dependent and heterogeneously distributed innovations. It is shown that simple least squares regression consistently estimates a unit root under very general conditions in spite of the presence of autocorrelated errors. The limiting distribution of the standardized estimator and the associated regression t statistic are found using functional central limit theory. New tests of the random walk hypothesis are developed which permit a wide class of dependent and heterogeneous innovation sequences. A new limiting distribution theory is constructed based on the concept of continuous data recording. This theory, together with an asymptotic expansion that is developed in the paper for the unit root case, explain many of the interesting experimental results recently reported in Evans and Savin (1981, 1984). 
540 |a Copyright 1987 The Econometric Society 
650 4 |a Unit root, time series, functional limit theory, Wiener process, weak dependence, continuous record, asympototic expansion 
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650 4 |a Mathematics  |x Applied mathematics  |x Statistics  |x Applied statistics  |x Inferential statistics  |x Statistical estimation  |x Estimation methods  |x Estimators 
650 4 |a Mathematics  |x Applied mathematics  |x Statistics  |x Statistical theories 
650 4 |a Mathematics  |x Applied mathematics  |x Statistics  |x Random walk 
650 4 |a Information science  |x Information analysis  |x Data analysis  |x Regression analysis  |x Linear regression  |x Least squares 
650 4 |a Mathematics  |x Applied mathematics  |x Statistics  |x Applied statistics  |x Descriptive statistics  |x Measures of variability  |x Statistical variance 
650 4 |a Mathematics  |x Applied mathematics  |x Statistics 
650 4 |a Mathematics  |x Applied mathematics  |x Statistics  |x Applied statistics  |x Statistical models  |x Time series models 
650 4 |a Philosophy  |x Applied philosophy  |x Philosophy of science  |x Scientific method  |x Hypothesis testing  |x Null hypothesis 
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773 0 8 |i Enthalten in  |t Econometrica  |d Wiley  |g 55(1987), 2, Seite 277-301  |w (DE-627)270425721  |w (DE-600)1477253-X  |x 14680262  |7 nnns 
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856 4 0 |u https://www.jstor.org/stable/1913237  |3 Volltext 
856 4 0 |u https://doi.org/10.2307/1913237  |3 Volltext 
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