INTRODUCTION TO ECONOMETRICS II ECO 306 NOUN 100
3.1.3.0 MAIN CONTENTS 3.1.3.1 Heteroscedasticity and Its Effects Gauss–Markov second conditions listed in the previous module states that the variance of the disturbance term in each observation should be constant. This sounds peculiar and needs a bit of explanation. The disturbance term in each observation has only one value, so what can be meant by its "variance The focus point of discussion here is, its potential behaviour before the sample is generated. So
when the model is written as; …[3.01]
Figure 1.1 Homoscedasticity [3.01]has in it the first two Gauss–Markov conditions stating that the disturbance terms
, ..., in the
nobservations are drawn from probability
distributions that have 0 mean and the same variance. Their actual values in the sample will sometimes be positive, sometimes negative, sometimes relatively far from 0,
sometimes relatively close, but there will be no a priori reason to anticipate a particularly erratic value in any given observation. To put it another way, the probability of
ureaching a given positive or negative value will be the same in all observations. This condition is known as homoscedasticity, which means "same dispersion.
