Although heteroskedasticity does not produce biased OLS estimates, it leads to a bias in the variance-covariance matrix. This means that standard model testing methods such as t tests or F tests cannot be relied on any longer. This post provides an intuitive illustration of heteroskedasticity and covers the calculation of standard errors that are robust to it.
Data A popular illustration of heteroskedasticity is the relationship between saving and income, which is shown in the following graph.