Journal ArticleDOI
The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis
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In this paper, the authors consider the null hypothesis that a time series has a unit root with possibly nonzero drift against the alternative that the process is "trend-stationary" and show how standard tests of the unit root hypothesis against trend stationary alternatives cannot reject the unit-root hypothesis if the true data generating mechanism is that of stationary fluctuations around a trend function which contains a one-time break.Abstract:
We consider the null hypothesis that a time series has a unit root with possibly nonzero drift against the alternative that the process is «trend-stationary». The interest is that we allow under both the null and alternative hypotheses for the presence for a one-time change in the level or in the slope of the trend function. We show how standard tests of the unit root hypothesis against trend stationary alternatives cannot reject the unit root hypothesis if the true data generating mechanism is that of stationary fluctuations around a trend function which contains a one-time breakread more
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References
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Journal ArticleDOI
Co-integration and Error Correction: Representation, Estimation and Testing
TL;DR: The relationship between co-integration and error correction models, first suggested in Granger (1981), is here extended and used to develop estimation procedures, tests, and empirical examples.
Journal ArticleDOI
Distribution of the Estimators for Autoregressive Time Series with a Unit Root
David A. Dickey,Wayne A. Fuller +1 more
TL;DR: In this article, the limit distributions of the estimator of p and of the regression t test are derived under the assumption that p = ± 1, where p is a fixed constant and t is a sequence of independent normal random variables.
Journal ArticleDOI
Testing for a Unit Root in Time Series Regression
TL;DR: In this article, the authors proposed new tests for detecting the presence of a unit root in quite general time series models, which accommodate models with a fitted drift and a time trend so that they may be used to discriminate between unit root nonstationarity and stationarity about a deterministic trend.
Journal ArticleDOI
Likelihood ratio statistics for autoregressive time series with a unit root
David A. Dickey,Wayne A. Fuller +1 more
Book
Convergence of Probability Measures
TL;DR: Weak Convergence in Metric Spaces as discussed by the authors is one of the most common modes of convergence in metric spaces, and it can be seen as a form of weak convergence in metric space.
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Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis
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Distribution of the Estimators for Autoregressive Time Series with a Unit Root
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