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Simultaneous Spatial Panel Data Models with Common Shocks

Lina Lu

No RPA 17-3, Supervisory Research and Analysis Working Papers from Federal Reserve Bank of Boston

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 model; Simultaneous equations system; Common shocks; Simultaneous effects; Incidental parameters; Maximum likelihood estimation; Principal components; High dimensionality; Inferential theory (search for similar items in EconPapers)
JEL-codes: C13 C31 C33 C38 C51 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-geo, nep-ore and nep-ure
Date: 2017-08-09
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