Sources of heteroscedasticity:

Heteroscedasticity, or unequal  variance, often occurs in cross-section data. For example,  let us consider the savings behaviour of households. We know that savings is relatively higher among households with higher income. It is also likely that the variance of savings among high-income families may be  larger  than the variance among low-income families. Low-income families do not have much to save, so they cannot differ much in their levels of  savings. High-income families, by contrast, exhibit wide ranges, from the miser who saves virtually all his income to  the spendthrift who saves virtually nothing. Secondly, there is more freedom of choice for high income families while low income families have to spend a major part of their income on consumption goods. Clearly, a cross-section  sample of data on savings and income behaviour  to estimate  an equation may  not  satisfy the homoscedasticity  assumption. More generally,  there is typically a problem  of heteroscedasticity in cross-section studies  in which there is a large variation in the size of  the entities for which data are obtained. These entities could be households with widely different income levels, firms with widely different scales of operation, and nations with widely different levels of output.

There could be several reasons for the presence of heteroscedasticity: There may be  certain outliers in  the data which would increase or decrease error variance. Secondly, the problem  of heteroscedasticity often arises because  the scale of a variable  varies enormously within the sample.