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Econometrica, 1981
Summary: [For part I see ibid. 49, 753-779 (1981; Zbl 0468.62021).] This paper investigates the exact sampling distribution of the least squares estimator of \(\beta\) in the model \(y_ t=\mu +\beta y_{t- 1}+u_ t\) where the \(u_ t\) are independently \(N(0,\sigma^ 2)\). The distribution is calculated for the case where \(y_ 0\) is a known constant and
Evans, G B A, Savin, N E
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Summary: [For part I see ibid. 49, 753-779 (1981; Zbl 0468.62021).] This paper investigates the exact sampling distribution of the least squares estimator of \(\beta\) in the model \(y_ t=\mu +\beta y_{t- 1}+u_ t\) where the \(u_ t\) are independently \(N(0,\sigma^ 2)\). The distribution is calculated for the case where \(y_ 0\) is a known constant and
Evans, G B A, Savin, N E
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Performance of unit-root tests for non linear unit-root and partial unit-root processes
Communications in Statistics - Theory and Methods, 2015ABSTRACTThis paper investigates the finite-sample performance of the augmented Dickey–Fuller (ADF), Phillips–Perron (PP), momentum threshold autoregressive (M-TAR), Kapetanios–Shin–Snell (KSS), and the inf-t unit-root tests. Simulation results show that the ADF and KSS tests have better size, whereas other tests generate severe size distortions when ...
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2003
Many economic and financial time series exhibit trending behavior or non-stationarity in the mean. Leading examples are asset prices, exchange rates and the levels of macroeconomic aggregates like real GDP. An important econometric task is determining the most appropriate form of the trend in the data.
Eric Zivot, Jiahui Wang
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Many economic and financial time series exhibit trending behavior or non-stationarity in the mean. Leading examples are asset prices, exchange rates and the levels of macroeconomic aggregates like real GDP. An important econometric task is determining the most appropriate form of the trend in the data.
Eric Zivot, Jiahui Wang
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Unit-roots und Unit-root-Tests
2001Unit-roots und Kointegration sind zwei Gebiete der Zeitreihenanalyse, die seit einigen Jahren Gegenstand intensiver Forschungsarbeiten sind und enge Verbindungen zur Okonometrie aufweisen. In der Tat spricht man deshalb heute auch von einer ″time series econometrics″.
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WIREs Computational Statistics, 2017
Unit roots are nonstationary autoregressive (AR) or autoregressive moving average (ARMA) time series processes which may include an intercept and/or a trend. These processes are used often in economics and finance, but can also be found in other scientific fields. Unit root tests address the null hypothesis of a unit root, and an alternative hypothesis
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Unit roots are nonstationary autoregressive (AR) or autoregressive moving average (ARMA) time series processes which may include an intercept and/or a trend. These processes are used often in economics and finance, but can also be found in other scientific fields. Unit root tests address the null hypothesis of a unit root, and an alternative hypothesis
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Approximate Conditional Unit Root Inference
Journal of Time Series Analysis, 2002Based on Cox and Reid (1987) adjustments of likelihood ratio (LR) tests for unit roots in higher‐order autoregressive models are proposed. While unit root inference does not fit directly into the framework of Cox and Reid, the ideas are applied in models with multi‐dimensional parameters of interest and only asymptotic orthogonality of parameters.
Hansen, Henrik, Rahbek, Anders Christian
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THE NONSTATIONARY FRACTIONAL UNIT ROOT
Econometric Theory, 1999This paper deals with a scalar I(d) process {yj}, where the integration order d is any real number. Under this setting, we first explore asymptotic properties of various statistics associated with {yj}, assuming that d is known and is greater than or equal to ½. Note that {yj} becomes stationary when d < ½, whose case is not our concern here.
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Marginal likelihood and unit roots
Journal of Econometrics, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Francke, M.K., de Vos, A.F.
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2018
A process might be non-stationary without being a unit root. The two concepts are related, but they are not identical and it is common to confuse the two. We can have non-stationarity without it being due to a unit root. We could have a seasonal model. Or, we could have a deterministic trend.
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A process might be non-stationary without being a unit root. The two concepts are related, but they are not identical and it is common to confuse the two. We can have non-stationarity without it being due to a unit root. We could have a seasonal model. Or, we could have a deterministic trend.
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, 1995 Classical and Bayesian unit root test procedures are reviewed, with an emphasis on testing principles and recent developments. A numerical illustration and annotated references and bibliography are provided.
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