Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/272835 
Autor:innen: 
Erscheinungsjahr: 
2022
Schriftenreihe/Nr.: 
cemmap working paper No. CWP23/22
Verlag: 
Centre for Microdata Methods and Practice (cemmap), London
Zusammenfassung: 
In empirical studies, the data usually don't include all the variables of interest in an economic model. This paper shows the identification of unobserved variables in observations at the population level. When the observables are distinct in each observation, there exists a function mapping from the observables to the unobservables. Such a function guarantees the uniqueness of the latent value in each observation. The key lies in the identification of the joint distribution of observables and unobservables from the distribution of observables. The joint distribution of observables and unobservables then reveal the latent value in each observation. Three examples of this result are discussed.
Schlagwörter: 
identification in observations
unobserved heterogeneity
latent variable model
measurement error model
JEL: 
C01
C14
Persistent Identifier der Erstveröffentlichung: 
Dokumentart: 
Working Paper

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