Results 271 to 280 of about 196,071 (311)
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Applied Economics, 1997
Unit root tests have been known for a long time to suffer from a variety of problems. Considering that simulation methods are obvious candidates for solving some of these problems, the aim of this paper is to assess the performance of bootstrap tests of the unit root hypothesis of the Dickey–Fuller type.
DE ANGELIS D +2 more
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Unit root tests have been known for a long time to suffer from a variety of problems. Considering that simulation methods are obvious candidates for solving some of these problems, the aim of this paper is to assess the performance of bootstrap tests of the unit root hypothesis of the Dickey–Fuller type.
DE ANGELIS D +2 more
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SSRN Electronic Journal, 2021
In this paper, we propose a unit root test for functional time series. We derive a new analytical framework for nonstationary functional time series. Specifically, for the proposed test statistic, we derive its limit distribution under the null hypothesis of a random walk and its asymptotic behavior of alternative hypotheses of trend stationary, weakly
Yichao Chen, Chi Seng Pun
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In this paper, we propose a unit root test for functional time series. We derive a new analytical framework for nonstationary functional time series. Specifically, for the proposed test statistic, we derive its limit distribution under the null hypothesis of a random walk and its asymptotic behavior of alternative hypotheses of trend stationary, weakly
Yichao Chen, Chi Seng Pun
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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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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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Unit root and stationarity tests’ wedding
Economics Letters, 2001zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Carrion-i-Silvestre, J. L. +2 more
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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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‘Objective’ bayesian unit root tests
Journal of Applied Econometrics, 1992AbstractDue to weaknesses in traditional tests, a Bayesian approach is developed to investigate whether unit roots exist in macroeconomic time‐series. Bayesian posterior odds comparing unit root models to stationary and trend‐stationary alternatives are calculated using informative priors.
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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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Economics Letters, 1994
Abstract It is known that the Phillips-Perron's modified Z α test as an approximation to the Dickey-Fuller test does not perform well when the process is generated by the unit ARMA(1, 1) model: y t = y t -1 + e t + θe t -1 with θ close to – 1.
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Abstract It is known that the Phillips-Perron's modified Z α test as an approximation to the Dickey-Fuller test does not perform well when the process is generated by the unit ARMA(1, 1) model: y t = y t -1 + e t + θe t -1 with θ close to – 1.
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Econometric Reviews, 2009
In this article we propose wild bootstrap implementations of the local generalized least squares (GLS) de-trended M and ADF unit root tests of Stock (1999), Ng and Perron (2001), and Elliott et al. (1996), respectively. The bootstrap statistics are shown to replicate the first-order asymptotic distributions of the original statistics, while numerical ...
CAVALIERE, GIUSEPPE, Taylor A. M. R.
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In this article we propose wild bootstrap implementations of the local generalized least squares (GLS) de-trended M and ADF unit root tests of Stock (1999), Ng and Perron (2001), and Elliott et al. (1996), respectively. The bootstrap statistics are shown to replicate the first-order asymptotic distributions of the original statistics, while numerical ...
CAVALIERE, GIUSEPPE, Taylor A. M. R.
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