Structural change tests under heteroskedasticity: Joint estimation versus two‐steps methods

DOI10.1111/jtsa.12619OpenAlexW3197078531MaRDI QIDQ5095289

Pierre Perron, Yohei Yamamoto

Publication date: 8 August 2022

Published in: Journal of Time Series Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/jtsa.12619

zbMATH Keywords

likelihood ratio testU-statisticheteroskedasticityCUSUM testvariance profilenon-monotonic powerstructural change test

Mathematics Subject Classification ID

Hypothesis testing in multivariate analysis (62H15) Inference from stochastic processes (62Mxx)

Related Items (1)

Changepoint Detection in Heteroscedastic Random Coefficient Autoregressive Models

Cites Work

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• Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation
• Testing for a change in persistence in the presence of non-stationary volatility
• Assessing the relative power of structural break tests using a framework based on the approximate Bahadur slope
• Tests for a mean shift with good size and monotonic power
• Sources of nonmonotonic power when testing for a shift in mean of a dynamic time series
• Testing for structural change in conditional models
• Restoring monotone power in the CUSUM test
• Asymptotic theory for time series with changing mean and variance
• A breakpoint detection in the mean model with heterogeneous variance on fixed time intervals
• Tests for Parameter Instability and Structural Change With Unknown Change Point
• Least squares estimation and tests of breaks in mean and variance under misspecification
• Tests of the Hypothesis that a Linear Regression System Obeys Two Separate Regimes
• Efficient Tests for General Persistent Time Variation in Regression Coefficients
• THE LIMIT DISTRIBUTION OF THE CUSUM OF SQUARES TEST UNDER GENERAL MIXING CONDITIONS
• The Cusum Test with Ols Residuals
• Optimal Tests when a Nuisance Parameter is Present Only Under the Alternative
• Estimating and Testing Linear Models with Multiple Structural Changes
• The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis
• Testing jointly for structural changes in the error variance and coefficients of a linear regression model
• Testing for structural changes in linear regressions with time-varying variance
• Testing for structural change under non‐stationary variances
• Heteroscedasticity and Autocorrelation Robust Structural Change Detection
• Heterogeneous Change Point Inference
• Nonmonotonic power for tests of a mean shift in a time series§
• Estimating and Testing Structural Changes in Multivariate Regressions
• Econometric Theory and Practice
• The Estimation of the Parameters of a Linear Regression System Obeying Two Separate Regimes
• Application of Least Squares Regression to Relationships Containing Auto- Correlated Error Terms
• On the Usefulness or Lack Thereof of Optimality Criteria for Structural Change Tests

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