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Moment Based Inference with Stratified Data

Gautam Tripathi ()

No 2005-38, Working papers from University of Connecticut, Department of Economics

Abstract: Many datasets 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 is collected by three widely used sampling schemes: variable probability sampling, multinomial sampling, and standard stratified sampling.

Keywords: Empirical likelihood; Moment conditions; Stratified sampling. (search for similar items in EconPapers)
JEL-codes: C14 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: 2005-09, Revised 2007-01
Note: I thank the co-editors and two anonymous referees for comments that greatly improved this paper. I also thank Paul Devereux and seminar participants at several universities for helpful suggestions and conversations. Financial support for this project from NSF grant SES-0214081 is gratefully acknowledged.
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https://media.economics.uconn.edu/working/2005-38r.pdf Revised version (application/pdf)
https://media.economics.uconn.edu/working/2005-38.pdf Original version (application/pdf)

Related works:
Journal Article: MOMENT-BASED INFERENCE WITH STRATIFIED DATA (2011) Downloads
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