A Correction Function Approach to Solve the Incidental Parameter Problem
AbstractFollowing Lancaster (2002), we propose a strategy to solve the incidental parameter problem. The method is demonstrated under a simple panel Poisson count model. We also extend the strategy to accomodate cases when information orthogonality is unavailable, such as the linear AR(p) panel model. For the AR(p) model, there exists a correction function to fix the incidental parameter problem when the model is stationary with strictly exogenous regressors. MCMC algorithms are developed for parameter estimation and model comparison. The results based on the simulated data sets suggest that our method could achieve consistency in both parameter estimation and model selection.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Cardiff University, Cardiff Business School, Economics Section in its series Cardiff Economics Working Papers with number E2009/6.
Length: 44 pages
Date of creation: Mar 2009
Date of revision:
Contact details of provider:
Postal: Aberconway Building, Colum Drive, CARDIFF, CF10 3EU
Phone: +44 (0) 29 20874417
Fax: +44 (0) 29 20874419
Web page: http://business.cardiff.ac.uk/research/academic-sections/economics/working-papers
More information through EDIRC
dynamic panel data model with fixed effect; incidental parameter problem; consistency in estimation; model selection; Bayesian model averaging; Markov chain Monte Carlo (MCMC);
Find related papers by JEL classification:
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-03-28 (All new papers)
- NEP-CMP-2009-03-28 (Computational Economics)
- NEP-ECM-2009-03-28 (Econometrics)
- NEP-ORE-2009-03-28 (Operations Research)
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Bruce Webb).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.