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A Dynamic “Fixed Effects” Model for Heterogeneous Panel Data

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  • Diana Weinhold

    (London School of Economics)

Abstract

This paper introduces a dynamic panel data model in which the intercepts and the coefficients on the lagged endogenous variables are specific to the cross section units, while the coefficients on the exogenous variables are assumed to be normally distributed across the cross section. Thus the model includes mixture of fixed coefficients and random coefficients, which I call the “MFR” model. The paper shows that this model has several desirable characteristics. In particular, the model allows for a considerable degree of heterogeneity across the cross section both in the dynamics and in the relationship between the independent and dependent variables. Estimation of the MFR model produces an estimate of the variance of the coefficients across the cross section units which can be used as a diagnostic tool to judge how widespread a relationship is and whether pooling of the data is appropriate. In addition, unlike LSDV estimation of dynamic panel models, the MFR model does not produce severely biased estimates when T is small.

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Bibliographic Info

Paper provided by EconWPA in its series Econometrics with number 0410003.

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Length: 18 pages
Date of creation: 05 Oct 2004
Date of revision:
Handle: RePEc:wpa:wuwpem:0410003

Note: Type of Document - pdf; pages: 18
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Web page: http://128.118.178.162

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Keywords: dynamic fixed effects panel data; heterogenous coefficients;

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  1. Kiviet, Jan F., 1995. "On bias, inconsistency, and efficiency of various estimators in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 68(1), pages 53-78, July.
  2. Ruth A. Judson & Ann L. Owen, 1997. "Estimating dynamic panel data models: a practical guide for macroeconomists," Finance and Economics Discussion Series 1997-3, Board of Governors of the Federal Reserve System (U.S.).
  3. Keane, Michael P & Runkle, David E, 1992. "On the Estimation of Panel-Data Models with Serial Correlation When Instruments Are Not Strictly Exogenous," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(1), pages 1-9, January.
  4. Hsiao, C. & Mountain, D.C. & Tsui, K.Y. & Chan, M.W.L., 1989. "Modeling Ontario Regional Electricity System Demand Using A Mixed Fixed And Random Coefficients Approach," Papers m8906, Southern California - Department of Economics.
  5. 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.
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Cited by:
  1. Andreas Dietrich, 2009. "Does Growth Cause Structural Change, or Is it the Other Way Round? A Dynamic Panel Data Analyses for Seven OECD Countries," Jena Economic Research Papers 2009-034, Friedrich-Schiller-University Jena, Max-Planck-Institute of Economics.
  2. Klasen, Stephan & Herzer, Dierk & Nowak-Lehmann D., Felicitas, 2007. "In search of FDI-led growth in developing countries," Proceedings of the German Development Economics Conference, Göttingen 2007 14, Verein für Socialpolitik, Research Committee Development Economics.
  3. Erkan Erdil & I. Hakan Yetkiner, 2004. "A Panel Data Approach for Income-Health Causality," Working Papers FNU-47, Research unit Sustainability and Global Change, Hamburg University, revised Apr 2004.
  4. A.R. Kemal & Abdul Qayyum & Muhammad Nadim Hanif, 2007. "Financial Development and Economic Growth: Evidence from a Heterogeneous Panel of High Income Countries," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 12(1), pages 1-34, Jan-Jun.
  5. Abdur R. Chowdhury, 2010. "External Debt and Growth in Developing Countries: A Sensitivity and Causal Analysis," Working Papers id:3151, eSocialSciences.
  6. Qayyum, Abdul & Siddiqui, Rehana & Hanif, Muhammad Nadim, 2004. "Financial Development and Economic Growth: Evidence from Heterogeneous Panel Data of Low Income Countries," MPRA Paper 23431, University Library of Munich, Germany.

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