A Combination Method for Averaging OLS and GLS Estimators
Qingfeng Liu () and
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Qingfeng Liu: Department of Economics, Otaru University of Commerce, Otaru 047-8501, Japan
Econometrics, 2019, vol. 7, issue 3, 1-12
To avoid the risk of misspecification between homoscedastic and heteroscedastic models, we propose a combination method based on ordinary least-squares (OLS) and generalized least-squares (GLS) model-averaging estimators. To select optimal weights for the combination, we suggest two information criteria and propose feasible versions that work even when the variance-covariance matrix is unknown. The optimality of the method is proven under some regularity conditions. The results of a Monte Carlo simulation demonstrate that the method is adaptive in the sense that it achieves almost the same estimation accuracy as if the homoscedasticity or heteroscedasticity of the error term were known.
Keywords: model averaging; OLS; GLS; combination method (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jecnmx:v:7:y:2019:i:3:p:38-:d:265453
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