Choices between OLS with robust inference and feasible GLS in time series regressions

DOI10.1016/j.econlet.2018.07.036zbMath1402.62194OpenAlexW2883555759WikidataQ129453562 ScholiaQ129453562MaRDI QIDQ1788026

Kun Ho Kim, Richard T. Baillie

Publication date: 8 October 2018

Published in: Economics Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.econlet.2018.07.036

zbMATH Keywords

asymptotic biasrobust inferenceGLSOLSfeasible GLS

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Nonparametric robustness (62G35) Linear regression; mixed models (62J05)

Related Items (1)

(Consistently) testing strict exogeneity against the alternative of predeterminedness in linear time-series models

Cites Work

• Unnamed Item
• Estimating the dimension of a model
• A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix
• Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances
• Generalized Least Squares with an Estimated Autocovariance Matrix
• Least squares estimation in the regression model with autoregressive-moving average errors
• Semiparametric Sieve-Type Generalized Least Squares Inference

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