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A Generalized Error Component Model with Heteroscedastic Disturbances

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  • Baltagi, Badi H
  • Griffin, James M

Abstract

This paper generalizes the one-way error component model from the homoskedastic to the heteroskedastic case. Unlike P. Mazodier and A. Trognon's (1978) heteroskedastic two-way error component model, an explicit form for V11/2 is obtained that allows the computation of generalized least squares as a simple modification of J. A. Hausman's (1978) procedure for the homoskedastic case. Two methods for estimating the variance components are proposed. The first estimates the variance components based on ordinary least squares and within residuals. The second uses the minimum norm quadratic unbiased estimation procedure suggested by C. R. Rao (1970). These methods are then applied to the estimation of gasoline demand for eighteen OECD countries over the period 1964-78. Copyright 1988 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

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Bibliographic Info

Article provided by Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association in its journal International Economic Review.

Volume (Year): 29 (1988)
Issue (Month): 4 (November)
Pages: 745-53

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Handle: RePEc:ier:iecrev:v:29:y:1988:i:4:p:745-53

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Cited by:
  1. Subal C. Kumbhakar, 1996. "Le ralentissement de la productivité des entreprises d'électricité au Texas : le rôle des marges, des rendements d'échelle et du progrès technique," Économie et Prévision, Programme National Persée, vol. 126(5), pages 77-89.
  2. Heshmati, Almas, 1994. "Estimating random effects production function models with selectivity bias: an application to Swedish crop producers," Agricultural Economics: The Journal of the International Association of Agricultural Economists, International Association of Agricultural Economists, vol. 11(2-3), December.
  3. Baltagi B-H. & Bresson G. & Pirotte A., 2004. "Joint LM test for homoskedasticity in a one-way error component model," Working Papers ERMES 0408, ERMES, University Paris 2.
  4. Shiu, Alice & Heshmati, Almas, 2006. "Technical Change and Total Factor Productivity Growth for Chinese Provinces: A Panel Data Analysis," Ratio Working Papers 98, The Ratio Institute.
  5. Heshmati, Almas & Kumbhakar, Subal C., 2010. "Technical Change and Total Factor Productivity Growth: The Case of Chinese Provinces," IZA Discussion Papers 4784, Institute for the Study of Labor (IZA).
  6. Badi H. Baltagi & Byoung Cheol Jung & Seuck Heun Song, 2008. "Testing for Heteroskedasticity and Serial Correlation in a Random Effects Panel Data Model," Center for Policy Research Working Papers 111, Center for Policy Research, Maxwell School, Syracuse University.
  7. Kouassi, Eugene & Mougoué, Mbodja & Sango, Joel & Bosson Brou, J.M. & Amba, Claude M.O. & Salisu, Afeez Adebare, 2014. "Testing for heteroskedasticity and spatial correlation in a two way random effects model," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 153-171.
  8. Chen, Kevin Z. & Meilke, Karl D. & Turvey, Calum, 1999. "Income risk and farm consumption behavior," Agricultural Economics: The Journal of the International Association of Agricultural Economists, International Association of Agricultural Economists, vol. 20(2), March.
  9. Bresson G. & Hsiao C. & Pirotte A., 2007. "Assessing the Contribution of R&D to Total Factor Productivity – a Bayesian Approach to Account for Heterogeneity And Heteroscedasticity," Working Papers ERMES 0708, ERMES, University Paris 2.
  10. Nilanjana Roy, 1999. "Is Adaptive Estimation Useful for Panel Models With Heteroskedasticity in the Unit-Specific Error Component? Some Monte Carlo Evidence," Econometrics Working Papers 9913, Department of Economics, University of Victoria.
  11. Baltagi, Badi H. & Song, Seuck Heun & Kwon, Jae Hyeok, 2009. "Testing for heteroskedasticity and spatial correlation in a random effects panel data model," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2897-2922, June.
  12. Eduardo Fé, 2012. "Instrumental variable estimation of heteroskedasticity adaptive error component models," Statistical Papers, Springer, vol. 53(3), pages 577-615, August.
  13. M. Giulietti & S. Mccorriston & P. Osborne, 2004. "Foreign direct investment in the UK: evidence from a disaggregated panel of the UK food sector," Applied Economics, Taylor & Francis Journals, vol. 36(7), pages 653-663.
  14. repec:ebl:ecbull:v:3:y:2008:i:75:p:1-10 is not listed on IDEAS
  15. Nilanjana Roy, 2002. "Is Adaptive Estimation Useful For Panel Models With Heteroskedasticity In The Individual Specific Error Component? Some Monte Carlo Evidence," Econometric Reviews, Taylor & Francis Journals, vol. 21(2), pages 189-203.
  16. Majumdar, Raju, 2012. "The role of secured debt in resolving agency conflicts and problems of asymmetric information: Indian evidence," MPRA Paper 37925, University Library of Munich, Germany.
  17. repec:ebl:ecbull:v:3:y:2003:i:15:p:1-4 is not listed on IDEAS

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