Speaker: | Andrew Adrian Pua |
---|---|
Speaker Intro: |
Assistant Professor at Wang Yanan Institute for Studies in Economics (WISE) and Department of Statistics, School of Economics, Xiamen University |
Host: | |
Description: |
Researchers have applied linear panel data methods to estimate binary choice models while allowing for individual-specific unobserved heterogeneity and dynamics either to provide empirical findings or to demonstrate the robustness of their empirical results. This leads to IV/GMM/OLS estimation of a dynamic linear probability model (LPM) with fixed effects. In this paper, I give a set of pros and cons of this procedure using explicit analytical results, some simulations, and an empirical application. I find that this procedure should be treated with caution, especially in fixed- T settings. In large-T settings, existing procedures cannot be directly applied. As a consequence, I give guidance as to what choices researchers should make in both these settings. |
Time: | 2017-11-10(Friday)12:30-13:30 |
Venue: | N302, Econ Building |
Organizer: |