Inference in regression models with many regressors

DOI10.1016/j.jeconom.2012.05.011zbMath1443.62054OpenAlexW3124789966MaRDI QIDQ528054

Stanislav Anatolyev

Publication date: 12 May 2017

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

Full work available at URL: https://www.nes.ru/files/Preprints-resh/WP125.pdf

zbMATH Keywords

likelihood ratio testWald testlinear regressiontest powerLagrange multiplier test\(F\) testalternative asymptotic theorytest size

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Linear regression; mixed models (62J05) Parametric hypothesis testing (62F03) Asymptotic properties of parametric tests (62F05)

Related Items (15)

Inference in Linear Regression Models with Many Covariates and Heteroscedasticity ⋮ Maximum likelihood estimators in linear regression models with Ornstein-Uhlenbeck process ⋮ Factor models with many assets: strong factors, weak factors, and the two-pass procedure ⋮ ASYMPTOTICS OF DIAGONAL ELEMENTS OF PROJECTION MATRICES UNDER MANY INSTRUMENTS/REGRESSORS ⋮ Joint inference based on Stein-type averaging estimators in the linear regression model ⋮ Inference on the best policies with many covariates ⋮ Testing many restrictions under heteroskedasticity ⋮ Residual bootstrap tests in linear models with many regressors ⋮ Bootstrap inference for instrumental variable models with many weak instruments ⋮ Hypothesis testing in linear regression when \(k/n\) is large ⋮ Hahn-Hausman test as a specification test ⋮ Pseudo-maximum likelihood estimators in linear regression models with fractional time series ⋮ Testing additive versus interactive effects in fixed-\(T\) panels ⋮ Identification strength with a large number of moments ⋮ Spectrum estimation: a unified framework for covariance matrix estimation and PCA in large dimensions

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