Research projects

Project CEMAPRE internal

TitleNonlinear panel data models with unobserved individual heterogeneity
ParticipantsIsabel Proença (Principal Investigator)
SummaryThis project aims to contribute to the existent literature of nonlinear panel data models in
twofold. First, dependent unobserved individual heterogeneity is considered in nonlinear panel data
models leading to endogeneity and consequently the need to find consistent estimation procedures.
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 used in empirical applications.

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