Semiparametric Bayesian Inference In Smooth Coefficient Models

  title={Semiparametric Bayesian Inference In Smooth Coefficient Models},
  author={Gary Koop and Gary. Koop and Justin L. Tobias},
We describe procedures for Bayesian estimation and testing in cross sectional, panel data and nonlinear smooth coefficient models. The smooth coefficient model is a generalization of the partially linear or additive model wherein coefficients on linear explanatory variables are treated as unknown functions of an observable covariate. In the approach we describe, points on the regression lines are regarded as unknown parameters and priors are placed on differences between adjacent points to… CONTINUE READING