Premium
Heteroskedasticity and Neglected Parameter Heterogeneity
Author(s) -
Zietz Joachim
Publication year - 2001
Publication title -
oxford bulletin of economics and statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.131
H-Index - 73
eISSN - 1468-0084
pISSN - 0305-9049
DOI - 10.1111/1468-0084.00220
Subject(s) - heteroscedasticity , econometrics , estimator , normality , statistics , linear regression , monte carlo method , variance (accounting) , mathematics , economics , accounting
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.