In　this　paper,　we　present　a　variable　selection　procedure　by　combining　basis　function　approximations　with　SCAD　penalty　for　semiparametric　varying　coefficient　partially　linear　models.　The　proposed　procedure　simultaneously　selects　significant　variables　in　the　parametric　components　and　the　nonparametric　components.　With　appropriate　selection　of　the　tuning　parameters,　we　establish　the　consistency　of　this　procedure　and　the　oracle　property　of　the　regularized　estimators.　A　simulation　study　is　undertaken　to　assess　the　finite　sample　performance　of　the　proposed　variable　selection　procedure.　Crown　Copyright　(C)　2009　Elsevier　B.V.　All　rights　reserved.