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TITLE VC_PACK: Commands for the estimation of smooth varying coefficient models DESCRIPTION/AUTHOR(S) Nonparametric regressions are powerful statistical tools to model relationships between dependent and independent variables with minimal assumptions on the underlying functional forms. However, the added flexibility creates a curse of dimensionality, an induces a high computational cost in samples with even moderate sizes. As an alternative, semiparametric models that combine the flexibility of nonparametric regressions with the structure of standard models. VC_pack provides commands for the estimation of smooth varying-coefficient model (Hastie and Tibshirani, 1993, Journal of the Royal Statistical Society, Series B 55: 757–796), based on kernel regression methods, using a new set of commands within that aim to facilitate bandwidth selection and model estimation as well as create visualizations of the results. KW: semiparametric regression KW: nonparametric regression KW: smooth-varying coefficients KW: lpoly, npregress Author: Fernando Rios-Avila, Levy Economics Institute of Bard College, Blithewood-Bard College, Annandale-on-Hudson, NY Support: friosavi@levy.org After installation, type help kweight, vc_bsreg, vc_bwalt, vc_bw, vc_graph, vc_pack, vc_predict, vc_preg, vc_reg, and vc_test Requires: Stata version 14 INSTALLATION FILES (click here to install) _gkweight.ado _gvbin.ado _gwberr.ado kweight.sthlp vc_bsreg.ado vc_bsreg.sthlp vc_bw.ado vc_bwalt.ado vc_bwalt.sthlp vc_bw.sthlp vc_graph.ado vc_graph.sthlp vc_pack.sthlp vc_predict.ado vc_predict.sthlp vc_preg.ado vc_preg.sthlp vc_reg.ado vc_reg.sthlp vc_test.ado vc_test.sthlp vt_xtoy.ado ANCILLARY FILES (click here to get) STATA_Paper.do