How to implement the bootstrap in static or stable dynamic regression models: test statistic versus confidence region approach

DOI10.1016/S0304-4076(01)00132-4zbMath1020.62015OpenAlexW2032107107MaRDI QIDQ1867716

Noud P. A. van Giersbergen, Jan F. Kiviet

Publication date: 2 April 2003

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0304-4076(01)00132-4

zbMATH Keywords

bootstraphypothesis testingautoregressive modelsasymptotic rejection probabilitiesresampling schemes

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Parametric tolerance and confidence regions (62F25) Linear regression; mixed models (62J05) Parametric hypothesis testing (62F03) Bootstrap, jackknife and other resampling methods (62F40)

Related Items (8)

Cross-section bootstrap for CCE regressions ⋮ Bootstrapping cointegration tests under structural co-breaks: A robust extended ECM test ⋮ Bootstrapping heteroskedastic regression models: wild bootstrap vs. pairs bootstrap ⋮ How Reliable are Bootstrap-based Heteroskedasticity Robust Tests? ⋮ More Efficient Tests Robust to Heteroskedasticity of Unknown Form ⋮ Alternative approaches to implementing Lagrange multiplier tests for serial correlation in dynamic regression models ⋮ LM tests of spatial dependence based on bootstrap critical values ⋮ The size and power of the bias-corrected bootstrap test for regression models with autocorrelated errors

Uses Software

• bootstrap
• bootlib

Cites Work

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