Shrinkage estimation of the varying-coefficient model with continuous and categorical covariates

This paper studies shrinkage estimation of a general varying-coefficient model in Li and Racine (2010), with both continuous and categorical covariates. We propose a kernel least absolute shrinkage and selection operator (KLASSO) to implement estimation and variable selection for the model. We establish the estimation sparsity and oracle efficiency of the KLASSO estimator. We also provide a BIC-type criterion for tuning parameter selection and justify the model selection consistency. Simulation results suggest our method has a nice performance in terms of estimation errors and variable selection.