Modified SEE variable selection for varying coefficient instrumental variable models |
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| Affiliation: | 1. Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, via Ponzio 34/5, 20133, Milano, Italy;2. Dipartimento di Chimica, Materiali e Ingegneria Chimica “G. Natta”, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy;1. Department of Economics, University of Verona, Vicolo Campofiore 2, 37129 Verona, Italy;2. Institute for Environmental Decisions, ETH Zurich, Switzerland;3. ETH Zurich, Institute for Environmental Decisions, Universitätstrasse 22, 8096 Zurich, Switzerland;4. Bern University of Applied Sciences, School of Agricultural, Forest, and Food Sciences, Laenggasse 85, 3052 Zollikofen, Switzerland;5. University of Osnabrueck, Institute for Environmental Systems Research, Barbarastrasse 12, 49076 Osnabrück, Germany |
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| Abstract: | We consider the problem of variable selection for a class of varying coefficient models with instrumental variables. We focus on the case that some covariates are endogenous variables, and some auxiliary instrumental variables are available. An instrumental variable based variable selection procedure is proposed by using modified smooth-threshold estimating equations (SEEs). The proposed procedure can automatically eliminate the irrelevant covariates by setting the corresponding coefficient functions as zero, and simultaneously estimate the nonzero regression coefficients by solving the smooth-threshold estimating equations. The proposed variable selection procedure avoids the convex optimization problem, and is flexible and easy to implement. Simulation studies are carried out to assess the performance of the proposed variable selection method. |
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