STATIONARITY TESTS UNDER TIME-VARYING SECOND MOMENTS

DOI10.1017/S0266466605050553zbMath1083.62084MaRDI QIDQ3377445

A. M. Robert Taylor, Giuseppe Cavaliere

Publication date: 22 March 2006

Published in: Econometric Theory (Search for Journal in Brave)

zbMATH Keywords

tablesconsistencyunobserved components model

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Monte Carlo methods (65C05)

Related Items (16)

Testing for a change in persistence in the presence of non-stationary volatility ⋮ Forecasting cointegrated nonstationary time series with time-varying variance ⋮ Lagrange multiplier unit root test in the presence of a break in the innovation variance ⋮ Inference on the long-memory properties of time series with non-stationary volatility ⋮ Bootstrapping Autoregression under Non-stationary Volatility ⋮ ADAPTIVE LONG MEMORY TESTING UNDER HETEROSKEDASTICITY ⋮ Robust testing for explosive behavior with strongly dependent errors ⋮ Testing for parameter instability in predictive regression models ⋮ Cointegrating rank selection in models with time-varying variance ⋮ Testing for co-integration in vector autoregressions with non-stationary volatility ⋮ Quasi-maximum likelihood estimation and bootstrap inference in fractional time series models with heteroskedasticity of unknown form ⋮ MODEL COMPARISONS IN UNSTABLE ENVIRONMENTS ⋮ A robust test for autocorrelation in the presence of a structural break in variance ⋮ Tests of strict stationarity based on quantile indicators ⋮ Adaptive estimation of heteroskedastic functional-coefficient regressions with an application to fiscal policy evaluation on asset markets ⋮ Testing the Null of Co-integration in the Presence of Variance Breaks

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?
• Testing for a unit root in the presence of a variance shift
• Testing for structural change in conditional models
• Unit root tests with a break in innovation variance.
• Testing stationarity under a permanent variance shift
• Testing the Null Hypothesis of Stationarity Against an Autoregressive Unit Root Alternative
• Testing for the Presence of a Random Walk in Series with Structural Breaks
• Unit Root Tests under Time-Varying Variances
• Consistent Covariance Matrix Estimation for Dependent Heterogeneous Processes
• Long-Term Memory in Stock Market Prices
• A STRONG CONSISTENCY PROOF FOR HETEROSKEDASTICITY AND AUTOCORRELATION CONSISTENT COVARIANCE MATRIX ESTIMATORS
• Time Series Regression with a Unit Root
• Inference When a Nuisance Parameter Is Not Identified Under the Null Hypothesis

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