B1117
Title: Factor-augmented time-varying coefficents panel data models
Authors: Helga Wagner - Johannes Kepler University (Austria) [presenting]
Abstract: Regression models for panel data with time-varying effects in a Bayesian framework are considered. Shrinkage of regression effects and the process variances of the effects allow distinguishing between effects that are practically zero, constant or time-varying. Longitudinal dependence is considered by including a subject-specific random factor with weights that may also vary over time. The model is applied to analyse panel data on the annual incomes of mothers returning to the job market after maternity leave.
