Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/171836
Authors: 
Li, Guangjie
Year of Publication: 
2015
Citation: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Volume:] 3 [Year:] 2015 [Issue:] 3 [Pages:] 494-524
Abstract: 
We examine the relationship between consistent parameter estimation and model selection for autoregressive panel data models with fixed effects. We find that the transformation of fixed effects proposed by Lancaster (2002) does not necessarily lead to consistent estimation of common parameters when some true exogenous regressors are excluded. We propose a data dependent way to specify the prior of the autoregressive coefficient and argue for comparing different model specifications before parameter estimation. Model selection properties of Bayes factors and Bayesian information criterion (BIC) are investigated. When model uncertainty is substantial, we recommend the use of Bayesian Model Averaging to obtain point estimators with lower root mean squared errors (RMSE). We also study the implications of different levels of inclusion probabilities by simulations.
Subjects: 
dynamic panel data model with fixed effects
incidental parameter problem
consistency in estimation
model selection
bayesian model averaging
JEL: 
C52
C11
C13
C15
Persistent Identifier of the first edition: 
Creative Commons License: 
http://creativecommons.org/licenses/by/4.0/
Document Type: 
Article
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