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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