Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/236435 
Year of Publication: 
2021
Series/Report no.: 
IZA Discussion Papers No. 14404
Publisher: 
Institute of Labor Economics (IZA), Bonn
Abstract: 
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.
Subjects: 
linked survey and administrative data
measurement error
finite mixture models
JEL: 
C81
C83
D31
Document Type: 
Working Paper

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