A TEST FOR STATIONARITY VERSUS TRENDS AND UNIT ROOTS FOR A WIDE CLASS OF DEPENDENT ERRORS
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Publication:3434189
DOI10.1017/S026646660606049XzbMath1170.62411OpenAlexW2145240853MaRDI QIDQ3434189
Anne Philippe, Liudas Giraitis, Remigijus Leipus
Publication date: 23 April 2007
Published in: Econometric Theory (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1017/s026646660606049x
Applications of statistics to economics (62P20) Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20)
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Leader nodes in communities for information spreading ⋮ Spectral approach to parameter-free unit root testing ⋮ The increment ratio statistic under deterministic trends ⋮ Rescaled variance tests for seasonal stationarity ⋮ Semiparametric stationarity and fractional unit roots tests based on data-driven multidimensional increment ratio statistics ⋮ A KPSS Test for Stationarity for Spatial Point Processes ⋮ Asymptotic independence of distant partial sums of linear processes ⋮ The increment ratio statistic ⋮ A two-sample test for comparison of long memory parameters ⋮ Evaluating currency risk in emerging markets ⋮ A simple test of changes in mean in the possible presence of long-range dependence ⋮ Detection of Stationary Errors in Multiple Regressions with Integrated Regressors and Cointegration ⋮ Testing for strict stationarity in a random coefficient autoregressive model
Cites Work
- Testing the null hypothesis of stationarity against the alternative of a unit root. How sure are we that economic time series have a unit root?
- On weak convergence of integral functionals of stochastic processes with applications to processes taking paths in \(L^ E_ p\)
- A new test for structural stability in the linear regression model
- Asymptotics for linear processes
- Weak convergence in \(L^p(0,1)\) of the uniform empirical process under dependence
- Detecting shocks: Outliers and breaks in time series
- Large-sample inference for nonparametric regression with dependent errors
- Broadband log-periodogram regression of time series with long-range dependence
- Rescaled variance and related tests for long memory in volatility and levels
- A model for long memory conditional heteroscedasticity.
- Log-periodogram regression of time series with long range dependence
- Gaussian semiparametric estimation of long range dependence
- Modeling volatility persistence of speculative returns: a new approach
- Exact local Whittle estimation of fractional integration
- The Hurst effect under trends
- Tests for Parameter Instability and Structural Change With Unknown Change Point
- Consistent estimation of the memory parameter for nonlinear time series
- Long-Term Memory in Stock Market Prices
- An Adaptive, Rate-Optimal Test of a Parametric Mean-Regression Model Against a Nonparametric Alternative
- A Fractional Dickey-Fuller Test for Unit Roots
- The Invariance Principle for Stationary Processes
- Estimation of Long Memory in the Presence of a Smooth Nonparametric Trend
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