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Journal ArticleDOI

The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis

Pierre Perron
- 01 Nov 1989 - 
- Vol. 57, Iss: 6, pp 1361-1401
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TLDR
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 break

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R&D, innovation, and technological progress: a test of the Schumpeterian framework without scale effects

TL;DR: In this paper, the authors use U.S. manufacturing industry data to estimate a system of three equations implied by a model of R&D-induced growth in steady state.
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Cointegration tests in the presence of structural breaks

TL;DR: In this paper, the authors investigated the properties of several cointegration tests when the marginal process of one of the variables in the cointegrating relationship is stationary with a structural break.
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The comovement between exchange rates and stock prices in the Asian emerging markets

TL;DR: In this paper, the authors investigated the comovement between exchange rates and stock prices in the Asian emerging markets and found that during crisis periods, contagion or spillover between asset prices, when compared with tranquil periods.
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A Dependence Metric for Possibly Nonlinear Processes

TL;DR: A transformed metric entropy measure of dependence is studied which satisfies many desirable properties, including being a proper measure of distance and capable of good performance in identifying dependence even in possibly nonlinear time series.
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A General Test for Time Dependence in Parameters

TL;DR: In this paper, the authors proposed a new test based on a Fourier series to approximate the unknown form of a nonlinear time series model, which has good size and power properties to detect structural breaks, seasonal parameters and random coefficients.
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

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.
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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