Residual bootstrap tests in linear models with many regressors

DOI10.1016/j.jeconom.2018.10.002zbMath1452.62508OpenAlexW2898315891WikidataQ129034193 ScholiaQ129034193MaRDI QIDQ1739866

Patrick Richard

Publication date: 29 April 2019

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

Full work available at URL: https://doi.org/10.1016/j.jeconom.2018.10.002

zbMATH Keywords

bootstrapasymptotic refinementslinear regressionsmany restrictions

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Asymptotic distribution theory in statistics (62E20) Linear regression; mixed models (62J05) Parametric hypothesis testing (62F03)

Related Items (2)

Testing many restrictions under heteroskedasticity ⋮ Interaction and quadratic effects in probit model with endogenous regressors

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity
• Nearly-singular design in GMM and generalized empirical likelihood estimators
• Inference in regression models with many regressors
• Hypothesis testing in linear regression when \(k/n\) is large
• Asymptotic behavior of M-estimators of p regression parameters when \(p^ 2/n\) is large. I. Consistency
• Asymptotic behavior of M estimators of p regression parameters when \(p^ 2/n\) is large. II: Normal approximation
• Asymptotic behavior of likelihood methods for exponential families when the number of parameters tends to infinity
• Asymptotics with increasing dimension for robust regression with applications to the bootstrap
• Robust heteroskedasticity-robust tests
• GMM inference when the number of moment conditions in large
• Dimension asymptotics for generalised bootstrap in linear regression
• Empirical process of residuals for high-dimensional linear models
• Bootstrap and wild bootstrap for high dimensional linear models
• Methods for Estimation and Inference in Modern Econometrics
• Asymptotic Normality and Consistency of the Least Squares Estimators for Families of Linear Regressions
• Conflict Among the Criteria Revisited; The W, LR and LM Tests
• Inference in Linear Regression Models with Many Covariates and Heteroscedasticity
• ALTERNATIVE ASYMPTOTICS AND THE PARTIALLY LINEAR MODEL WITH MANY REGRESSORS
• ASYMPTOTICS OF DIAGONAL ELEMENTS OF PROJECTION MATRICES UNDER MANY INSTRUMENTS/REGRESSORS
• Heteroskedasticity–robust tests with minimum size distortion
• The bootstrap and Edgeworth expansion
• On the asymptotic distribution of the Moran \(I\) test stastistic with applications

This page was built for publication: Residual bootstrap tests in linear models with many regressors