Optimal Model Averaging of Varying Coefficient Models

We consider the problem of model averaging over a set of semiparametric varying coefficient models where the varying coefficients can be functions of continuous and categorical variables. We propose a Mallows model averaging procedure that is capable of delivering model averaging estimators with solid finite-sample performance. Theoretical underpinnings are provided, finite-sample performance is assessed via Monte Carlo simulation, and an illustrative application is presented. The approach is very simple to implement in practice and R code is provided in an appendix

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Year of publication:	2017
Authors:	Li, Cong
Other Persons:	Li, Qi (contributor) ; Racine, Jeffrey (contributor) ; Zhang, Daiqiang (contributor)
Publisher:	[2017]: [S.l.] : SSRN
Subject:	Modellierung \| Scientific modelling \| Schätztheorie \| Estimation theory

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