Identification and estimation of dynamic random coefficient models

Speaker: Dr Wooyoung Lee

Affiliation: University of Technology Sydney

Online via Zoom: https://uqz.zoom.us/j/83774352533

Abstract

I study panel data linear models with predetermined regressors (e.g. lagged dependent variables) that allow the coefficients as well as the intercept to be individual-specific, permitting unobserved heterogeneity in the effects of regressors on the dependent variable. I show that the model is not point-identified in a short panel context but rather partially identified, and I characterize sharp identified sets of the mean, variance, and CDF of the coefficient distributions. The characterization is general, allowing discrete, continuous, and unbounded data. A computationally efficient estimation and inference procedure is proposed, based on a fast and precise global polynomial optimization algorithm. The method is applied to study lifecycle earnings dynamics in U.S. households in the Panel Study of Income Dynamics (PSID) dataset. The results suggest substantial unobserved heterogeneity in earnings persistence, which implies that households face different levels of earnings risk that lead to heterogeneity in their consumption and savings behaviors.

About the presenter's meeting

Dr Lee is happy to have (30-min) 1-to-1 meeting with our colleagues and graduate
students on the seminar day. Anyone who wants to meet with him can contact Dr Fu
Ouyang to book a time slot.