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Asymptotic inference from multi-stage samples [An article from: Journal of Econometrics]
Book Details
Author(s)D. Bhattacharya
PublisherElsevier
ISBN / ASINB000RR4782
ISBN-13978B000RR4789
AvailabilityAvailable for download now
MarketplaceUnited States 🇺🇸
Description
This digital document is a journal article from Journal of Econometrics, published by Elsevier in 2005. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
I develop a GMM-based framework for asymptotic inference to analyze data from surveys whose designs involve stratification and clustering. I set up the estimation problem, derive the appropriate asymptotic distribution theory as the number of clusters per stratum tends to infinity and compute asymptotic standard errors that are robust to sample-design effects. The analysis is then extended to nonparametric regression and to semiparametric estimation based on U-processes. Empirical illustrations are provided using consumption expenditure data from the complexly designed Indian national household survey.
Description:
I develop a GMM-based framework for asymptotic inference to analyze data from surveys whose designs involve stratification and clustering. I set up the estimation problem, derive the appropriate asymptotic distribution theory as the number of clusters per stratum tends to infinity and compute asymptotic standard errors that are robust to sample-design effects. The analysis is then extended to nonparametric regression and to semiparametric estimation based on U-processes. Empirical illustrations are provided using consumption expenditure data from the complexly designed Indian national household survey.
