Abstract
Heteroskedasticity occurs when the error variances are no longer constant across observations, and its presence leads to inefficiency in OLS estimation. Tests for heteroskedaticity are presented, and methods for correcting for its presence are developed. Such methods are of en difficult to apply in multiple regression models and an alternative approach is suggested of continuing to use the OLS coefficient estimates but adjusting their standard errors to take into account any heteroskedasticity that might be present. The use of logarithms to mitigate heteroskedasticity is discussed, and an approach to discriminating between linear and logarithmic regression models is proposed.
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Notes
Halbert White, ‘A heteroskedasticity consistent covariance matrix estimator and a direct test of heteroskedasticity’, Econometrica 48 (1980), 817–838.
Steven M. Goldfeld and Richard E. Quandt, ‘Some tests for homoskedasticity’, Journal of the American Statistical Association 60 (1965), 539–547.
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© 2014 Terence C. Mills
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Mills, T.C. (2014). Heteroskedasticity. In: Analysing Economic Data. Palgrave Texts in Econometrics. Palgrave Macmillan, London. https://doi.org/10.1057/9781137401908_15
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DOI: https://doi.org/10.1057/9781137401908_15
Publisher Name: Palgrave Macmillan, London
Print ISBN: 978-1-349-48656-4
Online ISBN: 978-1-137-40190-8
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