However, OLS is inefficient, and leads to incorrect calculation of SEs. Variance of commodity future prices throughout the year. Variance of expenditure on food may be greater for rich people than poor people. Then, do OLS regression of e 2 on all of your X variables, their squares, and their cross-products. The square roots of the diagonals give you the HCSEs.
More specific corrections require insight into the exact form of the heteroscedasticity.
For example, if the variance of the disturbance terms depends entirely on income. Then , and . If , then . All of the assumptions of OLS now hold for this transformed relation, yielding . The most common test for autocorrelation is the Durbin-Watson test.