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Properties of Fixed Effects Dynamic Panel Data Estimators for a Typical Growth Dataset



This paper investigates the properties of dynamic panel data (DPD) estimators in the context of a typical growth dataset. Using Monte Carlo simulations, we compare the performance of various DPD estimators, namely the Anderson-Hsiao (AH) and Arellano-Bond's General Method of Moment (GMM) one-step and two- step estimators, using the least-square dummy variable (LSDV) as a benchmark. We arrive at three conclusions. First, LSDV produces biased estimates and the biases are significant even for a moderate-sized time dimension. Second, there is no immediately obvious choice to replace LSDV among the estimators considered here. For one, there is the bias-efficiency trade-off. In addition, differences in the characteristics of data influence the performances of the various estimators. Finally, serial correlations in the error terms, even at a low degree, can introduce significant biases to the estimations.

Suggested Citation

  • Arya B. Gaduh, 2002. "Properties of Fixed Effects Dynamic Panel Data Estimators for a Typical Growth Dataset," CSIS Economics Working Paper Series WPE062, Centre for Strategic and International Studies, Jakarta, Indonesia.
  • Handle: RePEc:sis:wpecon:wpe062

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    References listed on IDEAS

    1. M. Chatib Basri & Hal Hill, 2004. "Ideas, Interests and Oil Prices: The Political Economy of Trade Reform During Soeharto's Indonesia," The World Economy, Wiley Blackwell, vol. 27(5), pages 633-655, May.
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    Cited by:

    1. Eicher, Theo S. & Schreiber, Till, 2010. "Structural policies and growth: Time series evidence from a natural experiment," Journal of Development Economics, Elsevier, vol. 91(1), pages 169-179, January.
    2. Theo Eicher & Till Schreiber, 2010. "Institutions and Growth: Time Series Evidence from Natural Experiments," Working Papers UWEC-2007-15-P, University of Washington, Department of Economics.
    3. Stefan Sperlich & Yvonne Sperlich, 2012. "Growth and Convergence in South–South Integration Areas: Empirical Evidence," Research Papers by the Institute of Economics and Econometrics, Geneva School of Economics and Management, University of Geneva 12032, Institut d'Economie et Econométrie, Université de Genève.
    4. Karen Poghosyan & Evžen Kočenda, 2016. "Determinants of export sophistication: Evidence from Monte Carlo simulations," Working Papers 360, Leibniz Institut für Ost- und Südosteuropaforschung (Institute for East and Southeast European Studies).

    More about this item


    dynamic panel data estimators; economic growth; Anderson- Hsiao (AH); General Methods of Moment (GMM); least-square dummy variable (LSDV); Monte Carlo simulation.;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity
    • O5 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies


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