Econometric Methods for Nonlinear Panel Data Models
Type
applied research project
Start Date
August 30, 2005
End Date
August 30, 2005
Status
ongoing
Description
Common econometric methods for non-linear panel data models, such as the probit or the tobit model, are either difficult to compute or depend critically and in a non robust way on simplifying statistical assumptions, or even both.
The aim of our line of research is to find robust and almost efficient estimators that are still fairly easy to compute. We also considered to include external information in the process of estimation. To derive such types of estimators we developed in most cases some variant of a GMM estimator.
The aim of our line of research is to find robust and almost efficient estimators that are still fairly easy to compute. We also considered to include external information in the process of estimation. To derive such types of estimators we developed in most cases some variant of a GMM estimator.
Leader contributor(s)
Member contributor(s)
Bertschek, Irene
Breitung, Jörg
Laisney, Francois
Partner(s)
International collaboration: During the various phases of this project we cooperated and still cooperate with Irene Bertschek (ZEW, Mannheim), Jörg Breitung (Humboldt Universität, Berlin), and Francois Laisney (University of Strasbourg and ZEW, Mannheim).
Funder
Eprints ID
19472