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Activity Number: 94
Type: Topic Contributed
Date/Time: Monday, August 4, 2008 : 8:30 AM to 10:20 AM
Sponsor: Social Statistics Section
Abstract - #300812
Title: Estimating Dynamic Panel Data Models with Measurement Errors
Author(s): Shawn Ni*+ and Michael Podgursky
Companies: University of Missouri-Columbia and University of Missouri-Columbia
Address: Department of Economics, Columbia, MO, 65211,
Keywords: measurement errors ; school effect
Abstract:

A key difficulty in drawing inference of school effect from student test score gains is the fact that test scores are noisy measurements of students' academic achievements. In this paper we examine competing inferential methods of dynamic panel data models using noisy data. In particular, we consider a score-level model where the score of the current period depends on the score of the previous period. We compare Monte Carlo simulation results of estimators of these model and estimates using the student test score data of Missouri.

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Revised September, 2008