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MOMENT-BASED INFERENCE WITH STRATIFIED DATA

Published online by Cambridge University Press:  30 April 2010

Gautam Tripathi
Gautam Tripathi*
Affiliation:
University of Connecticut
*
*Address correspondence to Gautam Tripathi, Department of Economics, University of Connecticut-Storrs, 341 Mansfield Road, Unit 1063, Storrs, CT 06269; e-mail: gautam.tripathi@uconn.edu.
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Abstract

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Many data sets used by economists and other social scientists are collected by stratified sampling. The sampling scheme used to collect the data induces a probability distribution on the observed sample that differs from the target or underlying distribution for which inference is to be made. If this effect is not taken into account, subsequent statistical inference can be seriously biased. This paper shows how to do efficient semiparametric inference in moment restriction models when data from the target population are collected by three widely used sampling schemes: variable probability sampling, multinomial sampling, and standard stratified sampling.

Information

Type
ARTICLES
Information
Econometric Theory , Volume 27 , Issue 1: SPECIAL ISSUE ON EMPIRICAL LIKELIHOOD AND RELATED METHODS , February 2011, pp. 47 - 73
Copyright
Copyright © Cambridge University Press 2010

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