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Adaptive Estimation in the Panel Data Error Component Model with Heteroskedasticity of Unknown Form

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  • Li, Qi
  • Stengos, Thanasis

Abstract

The authors show that the adaptive estimation result for the heteroskedasticity of an unknown form time-series (or cross-section) model can be generalized to the panel data error components model. The authors give recursive transformations that change the error term of a random effects model and the first differenced error term of a fixed effects model into classical errors. They also propose a modified Breusch-Pagan test for testing the random individual effects. Monte Carlo evidence suggests that the proposed estimator performs adequately in small samples. Copyright 1994 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

Suggested Citation

  • Li, Qi & Stengos, Thanasis, 1994. "Adaptive Estimation in the Panel Data Error Component Model with Heteroskedasticity of Unknown Form," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(4), pages 981-1000, November.
  • Handle: RePEc:ier:iecrev:v:35:y:1994:i:4:p:981-1000
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    Cited by:

    1. Ximing Wu & Thanasis Stengos, 2005. "Partially adaptive estimation via the maximum entropy densities," Econometrics Journal, Royal Economic Society, vol. 8(3), pages 352-366, December.
    2. Georges Bresson & Cheng Hsiao & Alain Pirotte, 2011. "Assessing the contribution of R&D to total factor productivity—a Bayesian approach to account for heterogeneity and heteroskedasticity," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(4), pages 435-452, December.
    3. 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.
    4. 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.
    5. Yiguo Sun & Thanasis Stengos, 2008. "The absolute health income hypothesis revisited: a semiparametric quantile regression approach," Empirical Economics, Springer, vol. 35(2), pages 395-412, September.
    6. Alain Pirotte & Jean-Loup Madre, 2011. "Determinants of Urban Sprawl in France," Urban Studies, Urban Studies Journal Limited, vol. 48(13), pages 2865-2886, October.
    7. Baltagi, Badi H. & Bresson, Georges & Pirotte, Alain, 2006. "Joint LM test for homoskedasticity in a one-way error component model," Journal of Econometrics, Elsevier, vol. 134(2), pages 401-417, October.
    8. Baltagi, Badi H. & Jung, Byoung Cheol & Song, Seuck Heun, 2010. "Testing for heteroskedasticity and serial correlation in a random effects panel data model," Journal of Econometrics, Elsevier, vol. 154(2), pages 122-124, February.
    9. 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.
    10. Eduardo Fé, 2012. "Instrumental variable estimation of heteroskedasticity adaptive error component models," Statistical Papers, Springer, vol. 53(3), pages 577-615, August.
    11. Juhl, Ted & Sosa-Escudero, Walter, 2014. "Testing for heteroskedasticity in fixed effects models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 484-494.
    12. Badi H. Baltagi & Peter H. Egger & Michaela Kesina, 2016. "Firm‐Level Productivity Spillovers in China's Chemical Industry: A Spatial Hausman‐Taylor Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 214-248, January.
    13. You, Jinhong & Zhou, Xian & Zhou, Yong, 2010. "Statistical inference for panel data semiparametric partially linear regression models with heteroscedastic errors," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1079-1101, May.
    14. Platoni, Silvia & Barbieri, Laura & Moro, Daniele & Sckokai, Paolo, 2020. "Heteroscedastic stratified two-way EC models of single equations and SUR systems," Econometrics and Statistics, Elsevier, vol. 15(C), pages 46-66.
    15. Eduardo Fé Rodríguez, 2009. "Adaptive Instrumental Variable Estimation of Heteroskedastic Error Component Models," Economics Discussion Paper Series 0921, Economics, The University of Manchester.
    16. Platoni, Silvia & Sckokai, Paolo & Moro, Daniele, 2008. "Panel Data Estimation Techniques for Farm-level Data Model," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 44268, European Association of Agricultural Economists.

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