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Error terms are assumed to be spherical otherwise the OLS estimator is inefficient.
The OLS estimator remains unbiased, however.
Spherical errors occur when errors have both uniform variance ( homoscedasticity ) and are uncorrelated with each other.
Heteroskedacity occurs when the amount of error is correlated with an independent variable.
For example, in a regression on food expenditure and income, the error is correlated with income.
Low income people generally spend a similar amount on food, while high income people may spend a very large amount or as little as low income people spend.
Heteroskedacity can also be caused by changes in measurement practices.
For example, as statistical offices improve their data, measurement error decreases, so the error term declines over time.

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