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A Comparative Study for Estimation Parameters in Panel Data Model

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  • Youssef, Ahmed H.
  • Abonazel, Mohamed R.

Abstract

This paper examines the panel data models when the regression coefficients are fixed, random, and mixed, and proposed the different estimators for this model. We used the Mote Carlo simulation for making comparisons between the behavior of several estimation methods, such as Random Coefficient Regression (RCR), Classical Pooling (CP), and Mean Group (MG) estimators, in the three cases for regression coefficients. The Monte Carlo simulation results suggest that the RCR estimators perform well in small samples if the coefficients are random. While CP estimators perform well in the case of fixed model only. But the MG estimators perform well if the coefficients are random or fixed.

Suggested Citation

  • Youssef, Ahmed H. & Abonazel, Mohamed R., 2009. "A Comparative Study for Estimation Parameters in Panel Data Model," MPRA Paper 49713, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:49713
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    File URL: https://mpra.ub.uni-muenchen.de/49713/1/MPRA_paper_49713.pdf
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    References listed on IDEAS

    as
    1. Cheng Hsiao & M. Hashem Pesaran, 2004. "Random Coefficient Panel Data Models," CESifo Working Paper Series 1233, CESifo.
    2. Carlson, Rodney L, 1978. "Seemingly Unrelated Regression and the Demand for Automobiles of Different Sizes, 1965-75: A Disaggregate Approach," The Journal of Business, University of Chicago Press, vol. 51(2), pages 243-262, April.
    3. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
    4. Gendreau, Brian C & Humphrey, David Burras, 1980. "Feedback Effects in the Market Regulation of Bank Leverage: A Time-Series and Cross-Section Analysis," The Review of Economics and Statistics, MIT Press, vol. 62(2), pages 276-280, May.
    5. Murtazashvili, Irina & Wooldridge, Jeffrey M., 2008. "Fixed effects instrumental variables estimation in correlated random coefficient panel data models," Journal of Econometrics, Elsevier, vol. 142(1), pages 539-552, January.
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    Cited by:

    1. Abonazel, Mohamed R., 2016. "Generalized Random Coefficient Estimators of Panel Data Models: Asymptotic and Small Sample Properties," MPRA Paper 72586, University Library of Munich, Germany.
    2. Abonazel, Mohamed R., 2015. "How to Create a Monte Carlo Simulation Study using R: with Applications on Econometric Models," MPRA Paper 68708, University Library of Munich, Germany.

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    More about this item

    Keywords

    Panel Data Model; Random Coefficient Regression Model; Mixed RCR Model; Monte Carlo Simulation; Pooling Cross Section and Time Series Data; Mean Group Estimators; Classical Pooling Estimators.;
    All these keywords.

    JEL classification:

    • 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
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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