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The econometrics of unobservables: Applications of measurement error models in empirical industrial organization and labor economics
- Source :
- Journal of Econometrics. 200:154-168
- Publication Year :
- 2017
- Publisher :
- Elsevier BV, 2017.
-
Abstract
- This paper reviews the recent developments in nonparametric identification of measurement error models and their applications in applied microeconomics, in particular, in empirical industrial organization and labor economics. Measurement error models describe mappings from a latent distribution to an observed distribution. The identification and estimation of measurement error models focus on how to obtain the latent distribution and the measurement error distribution from the observed distribution. Such a framework is suitable for many microeconomic models with latent variables, such as models with unobserved heterogeneity or unobserved state variables and panel data models with fixed effects. Recent developments in measurement error models allow very flexible specification of the latent distribution and the measurement error distribution. These developments greatly broaden economic applications of measurement error models. This paper provides an accessible introduction of these technical results to empirical researchers so as to expand applications of measurement error models.
- Subjects :
- Economics and Econometrics
Labour economics
Observational error
Computer science
Applied Mathematics
05 social sciences
Nonparametric statistics
Latent variable
Mixture model
01 natural sciences
010104 statistics & probability
Conditional independence
0502 economics and business
Econometrics
Errors-in-variables models
Endogeneity
0101 mathematics
Hidden Markov model
Industrial organization
050205 econometrics
Subjects
Details
- ISSN :
- 03044076
- Volume :
- 200
- Database :
- OpenAIRE
- Journal :
- Journal of Econometrics
- Accession number :
- edsair.doi...........0f4c9119f909f2d0b9c711ceeac1efd8