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A comparative study on estimation methods to deal with the endogeneity in linear random-intercept models with an extension
- Publication Year :
- 2017
- Publisher :
- TAYLOR & FRANCIS LTD, 2017.
-
Abstract
- In this paper, we investigate estimation methods to deal with situations where random intercepts are associated to time-varying covariates in the context of linear mixed models. First, a review of previous ways to deal with this so-called endogeneity issue is presented, then a new method based on shared random effects is proposed. Simulation studies and an empirical example are utilized to assess the performance of our proposed method. It is shown that our new approach is more efficient than most competitors and is robust to the misspecification of the random-effects distributions. The authors advise no direct funding is associated with the research reported on this article.
- Subjects :
- Statistics and Probability
Applied Mathematics
05 social sciences
Context (language use)
Extension (predicate logic)
Random effects model
01 natural sciences
Generalized linear mixed model
0506 political science
010104 statistics & probability
Endogenous covariates
fixed-effect approach
longitudinal data
mixture strategy
random-effect approach
Modeling and Simulation
Covariate
050602 political science & public administration
Econometrics
Endogeneity
0101 mathematics
Statistics, Probability and Uncertainty
Estimation methods
Random intercept
Mathematics
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....948f5e1b347bd4a1f2c421b29f0c6613