If you run a LM test for heteroskedasiticity and reject the null hypothesis,what should you conclude? A)at least one coefficients in the auxiliary regression is significantly different from zero,the assumption var(y_i. )= var(e_i)= $\sigma$²is unlikely to be true B)there is no evidence of heteroskedasticity,the assumption var(y_i. )= var(e_i)= $\sigma$²is most likely true C)there is heteroskedasticity present and it is correctly specified as tested D)there is heteroskedasticity,but it is not linear in the explanatory variables

Question

Quizplus · Accepted Answer

If the null hypothesis of the LM test is rejected, it means that there is evidence of heteroskedasticity. In this case, option A provides the correct conclusion that at least one coefficient in the auxiliary regression is significantly different from zero and the assumption of constant variance of the errors is unlikely to be true.

If You Run a LM Test for Heteroskedasiticity and Reject σ\sigmaσ

If You Run a LM Test for Heteroskedasiticity and Reject $\sigma$