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Heteroskedasticity and Neglected Parameter Heterogeneity

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  • Zietz, Joachim

Abstract

The paper studies the consequences of neglecting parameter heterogeneity for the linear regression model and cross-sectional data. Monte-Carlo experiments are used to illustrate that neglected parameter heterogeneity typically leads to (a) regression coefficients that are economically meaningless and (b)significant test statistics for heteroskedasticity and, possibly non-normality. The paper concludes that evidence for heteroskedasticity should not routinely lead to the use of White's well-known heteroskedasticity-consistent variance covariance matrix estimator. If heteroskedasticity is caused by neglected parameter heterogeneity or other causes of heteroskedasticity, such as wrong functional form, White's estimator will not serve any useful purpose. Copyright 2001 by Blackwell Publishing Ltd

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Bibliographic Info

Article provided by Department of Economics, University of Oxford in its journal Oxford Bulletin of Economics & Statistics.

Volume (Year): 63 (2001)
Issue (Month): 2 (May)
Pages: 263-73

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Handle: RePEc:bla:obuest:v:63:y:2001:i:2:p:263-73

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Cited by:
  1. Joachim Zietz & Bobby Newsome, 2002. "Agency Representation and the Sale Price of Houses," Journal of Real Estate Research, American Real Estate Society, vol. 24(2), pages 165-192.
  2. Joachim Zietz, 2005. "Detecting Neglected Parameter Heterogeneity with Chow Tests," Working Papers 200503, Middle Tennessee State University, Department of Economics and Finance.
  3. Juhl, Ted & Sosa-Escudero, Walter, 2014. "Testing for heteroskedasticity in fixed effects models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 484-494.

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