Arbeitspapier
Finite Mixture Models for Linked Survey and Administrative Data: Estimation and Post-estimation
Researchers use finite mixture models to analyze linked survey and administrative data on labour earnings (or similar variables), taking account of various types of measurement error in each data source. Different combinations of error-ridden and/or error-free observations characterize latent classes. Latent class probabilities depend on the probabilities of the different types of error. We introduce a set of Stata commands to fit a general class of finite mixture models to fit to linked survey-administrative data We also provide post-estimation commands for assessment of reliability, marginal effects, data simulation, and prediction of hybrid earnings variables that combine information from both data sources.
- Sprache
-
Englisch
- Erschienen in
-
Series: IZA Discussion Papers ; No. 14404
- Klassifikation
-
Wirtschaft
Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
Survey Methods; Sampling Methods
Personal Income, Wealth, and Their Distributions
- Thema
-
linked survey and administrative data
measurement error
finite mixture models
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Jenkins, Stephen P.
Rios-Avila, Fernando
- Ereignis
-
Veröffentlichung
- (wer)
-
Institute of Labor Economics (IZA)
- (wo)
-
Bonn
- (wann)
-
2021
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:41 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Jenkins, Stephen P.
- Rios-Avila, Fernando
- Institute of Labor Economics (IZA)
Entstanden
- 2021
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