Heteroscedasticity
Version 1.0.0 · Updated 2026-07-30
CORE DEFINITION
In regression analysis, the variance of the error term is not constant as the independent variable changes. For example, higher income individuals tend to have larger variability (dispersion) in their consumption expenditure.
SCAFFOLDING EFFECT
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Risk scales with size. In management, as organizational size (or wealth) increases, the unpredictability (variance) of its behavior often also increases. Do not apply the "certainty experience" of managing small teams to large teams; the range of fluctuation in large systems is of a completely different magnitude.
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Heteroscedasticity refers to the variance of regression residuals not being constant across levels of the independent variable, violating the classical OLS assumption of homoscedasticity, which can distort standard errors and significance tests. It is a common issue in cross-sectional data.
MINIMUM ACTION
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Homoscedasticity_and_heteroscedasticityverified
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