One of the standard assumptions of the classical linear regression model

y i = β 0 + β 1 x i 1 + β 2 x i 2 + + β k x i k + ε ; i = 1 N

is that the variance of the error term (εi) is the same for all observations, that is Var(|x1i,x2i,,xki)=σ2. The assumption of a constant error variance is known as homoskedasticity and its failure is referred to as heteroskedasticity, or unequal variance. Heteroskedasticity is expressed as Var(|x1i,x2i,,xki)=σi2, where an i subscript on ...

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