Working Paper

Simultaneous Spatial Panel Data Models with Common Shocks


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: Simultaneous equations system; Maximum likelihood estimation; Inferential theory; Simultaneous effects; Panel data model; Principal components; Common shocks; Spatial model; Incidental parameters; High dimensionality;

JEL Classification: C13; C51; C33; C38; C31;

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Bibliographic Information

Provider: Federal Reserve Bank of Boston

Part of Series: Supervisory Research and Analysis Working Papers

Publication Date: 2017-08-09

Number: RPA 17-3

Pages: 75 pages