SMU SOE Seminar (July 19, 2019): Robust and Efficient Sequential GEL and GMM Estimation and Tests with Martingale Differences

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TOPIC:

ROBUST AND EFFICIENT SEQUENTIAL GEL AND GMM ESTIMATION AND TESTS WITH MARTINGALE DIFFERENCES

ABSTRACT This paper considers sequential generalized empirical likelihood (GEL) with martingale differences and compare it with a corresponding sequential generalized method of moments (GMM) estimation and tests when there is a computationally simple pn-consistent estimator of nuisance parameters or the nuisance parameters can be eliminated with an estimating function of parameters of interest. As an initial estimate might have asymptotic impact on final estimates, we propose a general C(α)-type formulation to eliminate the impact. This formulation can be used in both the GEL and GMM frameworks to construct estimation and tests robust to initial estimates. The sequential approaches can save computational burden as the numbers of moments and parameters are reduced. The properly constructed robust sequential GEL (RSGEL) and robust sequential GMM (RSGMM) estimators of parameters of interest can be as efficient as corresponding joint GMM estimators. The RSGEL removes several higher order bias terms of the RSGMM. Our moment conditions at the true parameters are martingales, thus they cover some spatial and time series models. We investigate tests for parameter restrictions in RSGEL and RSGMM frameworks. Tests in the sequential frameworks can be locally as powerful as those in the joint moments estimation frameworks when the sequential estimators are efficient. Keywords: Sequential estimation, GMM, empirical likelihood, martingale differences, high order bias, efficiency, test. JEL Codes: C12, C13, C14, C18, C51. Click here to view the CV.
		PRESENTER Fei Jin Fudan University
		RESEARCH FIELDS Spatial Econometrics Econometric Theory Applied Econometrics
		DATE: 19 July 2019 (Friday)
		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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