This paper discusses random intercept selection within the context of semiparametric regression models with structured additive predictor (STAR). STAR models can deal simultaneously with nonlinear covariate effects and time trends, unit- or cluster-specific heterogeneity, spatial heterogeneity...

Structured additive regression (STAR) models provide a flexible framework for modeling possible nonlinear effects of covariates: They contain the well established frameworks of generalized linear models (GLM) and generalized additive models (GAM) as special cases but also allow a wider class of...

Quantile regression provides a convenient framework for analyzing the impact of covariates on the complete conditional distribution of a response variable instead of only the mean. While frequentist treatments of quantile regression are typically completely nonparametric, a Bayesian formulation...

The long-term impact of globalization, outsourcing, and technological change on workers is increasingly being studied by economists. At the nexus of labor economics, industry studies, and industrial organization, The Analysis of Firms and Employees presents new findings about these impacts by...