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Bias Correction in the Dynamic Panel Data Model with a Nonscalar Disturbance Covariance Matrix

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  • Maurice J. G. Bun

    (University of Amsterdam)

Abstract

By using asymptotic expansion techniques approximation formulae are developed for the bias of ordinary and generalized Least Squares Dummy Variable (LSDV) estimators in dynamic panel data models. Earlier results on bias approximation in first-order stable dynamic panel data models are extended to higher-order dynamic models with general disturbance covariance structure. The focus is on estimation of both short- and long-run coefficients. The results show that proper modelling of the disturbance covariance structure is indispensable. The bias approximations are used to construct bias corrected estimators which are then applied to quarterly data from 14 European Union countries. Money demand functions for M1, M2 and M3 are estimated for the EU area as a whole for the period 1991:I-1995:IV. The empirical results show that in general plausible long-run effects are obtained by the bias corrected estimators. Moreover, bias correction can be substantial underlining the importance of more refined estimation techniques. Also the efficiency gains by exploiting the heteroscedasticity and cross-correlation patterns between countries are considerable.

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Bibliographic Info

Paper provided by Econometric Society in its series Econometric Society World Congress 2000 Contributed Papers with number 0511.

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Date of creation: 01 Aug 2000
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Handle: RePEc:ecm:wc2000:0511

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  1. Kiviet, Jan F. & Phillips, Garry D. A. & Schipp, Bernhard, 1995. "The bias of OLS, GLS, and ZEF estimators in dynamic seemingly unrelated regression models," Journal of Econometrics, Elsevier, Elsevier, vol. 69(1), pages 241-266, September.
  2. Carlo C. A. Winder & Martin M. G. Fase, 1998. "Wealth and the demand for money in the European union," Empirical Economics, Springer, Springer, vol. 23(3), pages 507-524.
  3. Pesaran, M. H. & Zhao, Z., 1998. "Bias Reduction in Estimating Long-run Relationships from Dynamic Heterogenous Panels," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge 9802, Faculty of Economics, University of Cambridge.
  4. Kiviet, Jan F. & Phillips, Garry D. A., 1994. "Bias assessment and reduction in linear error-correction models," Journal of Econometrics, Elsevier, Elsevier, vol. 63(1), pages 215-243, July.
  5. Kajal Lahiri, 2005. "Analysis of Panel Data," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, Agricultural and Applied Economics Association, vol. 87(4), pages 1093-1095.
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Cited by:
  1. Giovanni S.F. Bruno & Anna M. Falzoni & Rodolfo Helg, 2004. "Measuring the effect of globalization on labour demand elasticity: An empirical application to OECD countries," KITeS Working Papers, KITeS, Centre for Knowledge, Internationalization and Technology Studies, Universita' Bocconi, Milano, Italy 153, KITeS, Centre for Knowledge, Internationalization and Technology Studies, Universita' Bocconi, Milano, Italy, revised Feb 2004.
  2. Alexander Chudik & M. Hashem Pesaran, 2013. "Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors," Globalization and Monetary Policy Institute Working Paper, Federal Reserve Bank of Dallas 146, Federal Reserve Bank of Dallas.
  3. G. Everaert & L. Pozzi, 2004. "Bootstrap Based Bias Correction for Homogeneous Dynamic²² Panels," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium, Ghent University, Faculty of Economics and Business Administration 04/263, Ghent University, Faculty of Economics and Business Administration.
  4. Ilse Ruyssen & Gerdie Everaert & Glenn Rayp, 2014. "Determinants and dynamics of migration to OECD countries in a three-dimensional panel framework," Empirical Economics, Springer, Springer, vol. 46(1), pages 175-197, February.
  5. Everaert, Gerdie & Pozzi, Lorenzo, 2007. "Bootstrap-based bias correction for dynamic panels," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 31(4), pages 1160-1184, April.
  6. G. Everaert, 2009. "Using Backward Means to Eliminate Individual Effects from Dynamic Panels," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium, Ghent University, Faculty of Economics and Business Administration 09/553, Ghent University, Faculty of Economics and Business Administration.

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