VC_PACK: Stata module for the estimation of smooth varying coefficient models

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.