Generalized Cp Model Averaging for Heteroskedastic Models

Qingfeng Liu ()

ビジネス創造センターディスカッション・ペーパー (Discussion papers of the Center for Business Creation) from Otaru University of Commerce

Abstract: This paper proposes a model averaging method, the generalized Mallows’ Cp (GC) method, which works well for heteroskedastic models. Under some regularity conditions, we provide a feasible form of the GC method and show that the GC method has asymptotic optimality not only as a model averaging method but also as a model selection method for heteroskedastic models. We perform some Monte Carlo studies to investigate the small sample properties of the GC method. The simulation results show that our method works well and performs better than alternative methods.

Keywords: Model Averaging; Model Selection; Asymptotic Optimality; Mallows’ Cp; Heteroskedastic error (search for similar items in EconPapers)
Pages: 20 pages
Date: 2011-04-20
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Published in Discussion paper series (2011), 139: 1-20

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Working Paper: Generalized Cp Model Averaging for Heteroskedastic Models (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:ota:busdis:10252/4544

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