SMU SOE Seminar (Nov 29, 2018, 2-3:30pm): Dynamic Spatial Panel Data Models with Common Shocks

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ABSTRACT Real data often have complicated correlation over cross section and time. Modeling, estimating and interpreting the correlations in data are particularly important in economic analysis. This paper integrates several correlation-modeling techniques and propose dynamic spatial panel data models with common shocks to accommodate possibly complicated correlation structure over cross section and time. A large number of incidental parameters exist within the model. The quasi maximum likelihood method (ML) is proposed to estimate the model. Heteroskedasticity is explicitly estimated. The asymptotic properties of the quasi maximum likelihood estimator (MLE) are investigated. Our analysis indicates that the MLE has a non-negligible bias. We propose a bias correction method for the MLE. The simulations further reveal the excellent finite sample properties of the quasi-MLE after bias correction. Keywords: Panel data models, Spatial interactions, Common shocks, Cross-sectional dependence, Incidental parameters, Maximum likelihood estimation JEL Codes: C3; C13 Click here to view the paper. Click here to view the CV.
		PRESENTER Kunpeng Li Capital University of Economics and Business
		RESEARCH FIELDS Econometrics
		DATE: 29 November 2018 (Thursday)
		TIME: 2pm - 3.30pm
		VENUE: Meeting Room 5.1, Level 5 School of Economics Singapore Management University 90 Stamford Road Singapore 178903