JSM 2004 - Toronto

Abstract #301727

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Activity Number: 431
Type: Contributed
Date/Time: Thursday, August 12, 2004 : 10:30 AM to 12:20 PM
Sponsor: Business and Economics Statistics Section
Abstract - #301727
Title: Model Selection and Parameter Estimation for Dynamic Panel Data
Author(s): Dylan Small*+ and Tze Leung Lai
Companies: University of Pennsylvania and Stanford University
Address: 3514 Lancaster Ave., Apt. 416, Philadelphia, PA, 19104,
Keywords: dynamic panel data ; model selection
Abstract:

Panel data has important advantages over purely cross-sectional or time-series data in studying many economic phenomenona, because it contains information about both the intertemporal dynamics and the individuality of the entities being investigated. A commonly used class of dynamic models for panel studies identifies the parameters of interest through moment restrictions. Two important problems that arise in such models are the following: (1) it may not be clear a priori whether certain moment restrictions are valid; and (2) some of the moment restrictions may only "weakly" identify the parameters of interest, providing little information about these parameters and making inference based on conventional asymptotic theory misleading. A procedure based on empirical likelihood for choosing among possible estimators and selecting variables in this setting is developed. The advantages of the procedure over other approaches in the econometric literature are demonstrated through theoretical analysis and simulation studies.

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