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A Correction Function Approach to Solve the Incidental Parameter Problem

Author

Listed:
  • Li, GuangJie

    () (Cardiff Business School)

  • Leon-Gonzalez, Roberto

Abstract

Following 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.

Suggested Citation

  • Li, GuangJie & Leon-Gonzalez, Roberto, 2009. "A Correction Function Approach to Solve the Incidental Parameter Problem," Cardiff Economics Working Papers E2009/6, Cardiff University, Cardiff Business School, Economics Section.
  • Handle: RePEc:cdf:wpaper:2009/6
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    More about this item

    Keywords

    dynamic panel data model with fixed effect; incidental parameter problem; consistency in estimation; model selection; Bayesian model averaging; Markov chain Monte Carlo (MCMC);

    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

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