Simultaneous Spatial Panel Data Models with Common Shocks
76 Pages Posted: 8 Nov 2017 Last revised: 18 Mar 2022
Date Written: August, 2017
Abstract
I consider a simultaneous spatial panel data model, jointly modeling three effects: simultaneous effects, spatial effects and common shock effects. This joint modeling and consideration of cross-sectional heteroskedasticity result in a large number of incidental parameters. I propose two estimation approaches, a quasi-maximum likelihood (QML) method and an iterative generalized principal components (IGPC) method. I develop full inferential theories for the estimation approaches and study the trade-off between the model specifications and their respective asymptotic properties. I further investigate the finite sample performance of both methods using Monte Carlo simulations. I find that both methods perform well and that the simulation results corroborate the inferential theories. Some extensions of the model are considered. Finally, I apply the model to analyze the relationship between trade and GDP using a panel data over time and across countries.
Keywords: Panel data model, spatial models, Simultaneous equations system, Common shocks, Simultaneous effects, Incidental parameters, Maximum likelihood estimation, Principal components, High dimensionality, Inferential theory
JEL Classification: C13, C31, C33, C38, C51
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