SMU SOE Seminar (Dec 4, 2019): Panel Data Models with Potentially Misspecified Unknown Factors

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TOPIC:

PANEL DATA MODELS WITH POTENTIALLY MISSPECIFIED UNKNOWN FACTORS

ABSTRACT Panel data models with interactive fixed effects have been well investigated and applied since Pesaran (2006) and Bai (2009). However, not much effort has been made to generalise the unobservable factor structure and relax the corresponding assumptions. In this study, we investigate the consequences of misspecifying the property of unknown factors of a parametric panel data model. We show that the interactive fixed effects estimator still achieves the global minimum even when the properties of unknown factors are misspecified. From the point of view of principle component analysis, we formalize some advantages/disadvantages when regressors and factors possess different trending behaviours across time. Rather than treating the unobservable factor structure as a part of the error component, we notice that the factor structure should be considered at least as equivalently important as observable regressors when conducting regression analysis. Some rates of convergence and an asymptotic normality are established accordingly. In addition, we find that nonstationarity of the factors can help reduce the requirement of the sample size along the time dimension. We verify our findings through extensive simulation studies and investigate income elasticity of health care expenditure using data of OECD counties. Click here to view the CV.
		PRESENTER Bin Peng Deakin University
		RESEARCH FIELDS Panel Data Models
		DATE: 4 December 2019 (Wednesday)
		TIME: 4pm - 5.30pm
		VENUE: Meeting Room 5.1, Level 5 School of Economics Singapore Management University 90 Stamford Road Singapore 178903

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