– heteroskedastic error term causes the dependent variable to fluctuate in a way that the OLS estimation procedure attributes to the independent variable
• OLS tend to underestimate the standard error of the coefficients
– heteroskedasticity increases the variances of the estimates in a way that is masked by OLS estimates
• There is a battery of tests for heteroskedasticity
• We will derive two tests, both for the model
• Both are based on analysis of residuals
• OLS estimates are consistent even under heteroskedasticity
• This allows us to get consistent estimates of residuals, which represent correctly the stochastic error term
• Sometimes, simple visual analysis of residuals is sufficient to detect heteroskedasticity