Research projects

Project CEMAPRE internal

TitleEstimating partial effects for nonlinear dynamic panel data models with unobserved individual heterogeneity
ParticipantsIsabel Proença (Principal Investigator)
SummaryThis project aims to contribute to the existent literature of dynamic nonlinear panel data models
twofold. First, dependent unobserved individual heterogeneity is considered in nonlinear dynamic
panel data models leading to endogeneity and consequently inconsistency in estimation of the usual
methods. Therefore, it proposes alternative procedures based on semiparametric approaches to obtain
consistent estimation. Second, it focuses on the estimation of partial effects and average partial
effects, exploring the issues addressed in Shang and Wooldridge (2016) in the particular class of
models considered here. Finally, the proposed methods are illustrated in empirical applications.

Shang, S., and Wooldridge, J. (2016). On Estimating Partial Effects after Retransformation.
Available at SSRN 2763307.