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https://doi.org/10.18148/srm/2011.v5i2.4624

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Estimating underreporting of consumer expenditures using Markov latent class analysis

Die Schätzung der ungenügenden Berichterstattung der Konsumausgaben mit Hilfe der latenten Klassenanalyse von Markov
[journal article]

Tucker, Clyde
Biemer, Paul P.
Meekins, Brian

Abstract

"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. The author's approach for estimating underreporting errors is a two-step process. In the first ... view more

"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. The author's 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." (author's abstract)... view less

Keywords
data; data capture; data organization; data acquisition; data quality; method; methodological research; data collection method; error; consumption; consumption behavior

Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods

Document language
English

Publication Year
2011

Page/Pages
p. 39-51

Journal
Survey Research Methods, 5 (2011) 2

ISSN
1864-3361

Status
Published Version; peer reviewed

Licence
Deposit Licence - No Redistribution, No Modifications


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© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.