Estimating underreporting of consumer expenditures using Markov latent class analysis

This paper examines reporting in specific consumer item categories (or commodities) and estimates expenditure underreporting due to survey respondents who erroneously report no expenditure in a category. Our approach for estimating underreporting errors is a two-step process. In the first step, a Ma...

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Main Authors: Clyde Tucker, Paul P. Biemer, Brian Meekins
Format: Article
Language:English
Published: European Survey Research Association 2011-07-01
Series:Survey Research Methods
Subjects:
Online Access:https://ojs.ub.uni-konstanz.de/srm/article/view/4624
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author Clyde Tucker
Paul P. Biemer
Brian Meekins
author_facet Clyde Tucker
Paul P. Biemer
Brian Meekins
author_sort Clyde Tucker
collection DOAJ
description This paper examines reporting in specific consumer item categories (or commodities) and estimates expenditure underreporting due to survey respondents who erroneously report no expenditure in a category. Our approach for estimating underreporting errors is a two-step process. In the first step, a Markov latent class analysis is performed to estimate the proportion of consumers in various subpopulations who fail to report their actual expenditure in a particular commodity. Once this proportion is estimated, the dollar value of the missing expenditure is estimated using the mean expenditure of those in that subpopulation that did report an expenditure. Finally, the estimates are evaluated and discussed in light of external data on expenditure underreporting.
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spelling doaj.art-7517425e788d4bc19a4ff2bf4fce494b2022-12-22T02:46:12ZengEuropean Survey Research AssociationSurvey Research Methods1864-33612011-07-015210.18148/srm/2011.v5i2.46244675Estimating underreporting of consumer expenditures using Markov latent class analysisClyde TuckerPaul P. Biemer0Brian MeekinsRTI InternationalThis paper examines reporting in specific consumer item categories (or commodities) and estimates expenditure underreporting due to survey respondents who erroneously report no expenditure in a category. Our approach for estimating underreporting errors is a two-step process. In the first step, a Markov latent class analysis is performed to estimate the proportion of consumers in various subpopulations who fail to report their actual expenditure in a particular commodity. Once this proportion is estimated, the dollar value of the missing expenditure is estimated using the mean expenditure of those in that subpopulation that did report an expenditure. Finally, the estimates are evaluated and discussed in light of external data on expenditure underreporting.https://ojs.ub.uni-konstanz.de/srm/article/view/4624underreporting errorconsumer price indexmissing datasurvey evaluation
spellingShingle Clyde Tucker
Paul P. Biemer
Brian Meekins
Estimating underreporting of consumer expenditures using Markov latent class analysis
Survey Research Methods
underreporting error
consumer price index
missing data
survey evaluation
title Estimating underreporting of consumer expenditures using Markov latent class analysis
title_full Estimating underreporting of consumer expenditures using Markov latent class analysis
title_fullStr Estimating underreporting of consumer expenditures using Markov latent class analysis
title_full_unstemmed Estimating underreporting of consumer expenditures using Markov latent class analysis
title_short Estimating underreporting of consumer expenditures using Markov latent class analysis
title_sort estimating underreporting of consumer expenditures using markov latent class analysis
topic underreporting error
consumer price index
missing data
survey evaluation
url https://ojs.ub.uni-konstanz.de/srm/article/view/4624
work_keys_str_mv AT clydetucker estimatingunderreportingofconsumerexpendituresusingmarkovlatentclassanalysis
AT paulpbiemer estimatingunderreportingofconsumerexpendituresusingmarkovlatentclassanalysis
AT brianmeekins estimatingunderreportingofconsumerexpendituresusingmarkovlatentclassanalysis