Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/272835 
Authors: 
Year of Publication: 
2022
Series/Report no.: 
cemmap working paper No. CWP23/22
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
Abstract: 
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.
Subjects: 
identification in observations
unobserved heterogeneity
latent variable model
measurement error model
JEL: 
C01
C14
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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