Identification and (Fast) Estimation of Large Nonlinear Panel Models with Two-Way Fixed Effects
We study a nonlinear two-way fixed effects panel model that allows for unobserved individual heterogeneity in slopes and flexibly specified link function. The former is relevant when the researcher is interested in the distributional causal effects of covariates, and the latter mitigates potential misspecification errors due to restrictions imposed on the link function. We show that the fixed effects parameters and the link function can be identified when both individual and time dimensions are large. We propose a novel iterative Gauss-Seidel estimation procedure that overcomes the practical challenge of dimensionality in the number of fixed effects when the dataset is large. We revisit two empirical studies in trade (Helpman et al., 2008) and innovation (Aghion et al., 2013), and find non-negligible unobserved dispersion in trade elasticity across countries and the effect of institutional ownership on innovation across firms. These exercises emphasize the usefulness of our method in capturing flexible heterogeneity in the causal relationship of interest that may have important implications for the subsequent policy analysis. This is joint work with Ao Wang (University of Warwick).
Date: 10 November 2023, 14:15 (Friday, 5th week, Michaelmas 2023)
Venue: Manor Road Building, Manor Road OX1 3UQ
Venue Details: Seminar Room A or https://zoom.us/j/93054414699?pwd=NEFiL2ZNc0t5N3ZIUTE2VEh5OXhZUT09
Speaker: Martin Mugnier (University of Oxford)
Organising department: Department of Economics
Part of: Nuffield Econometrics Seminar
Booking required?: Not required
Audience: Members of the University only
Editor: Shreyasi Banerjee