An alternative method to estimate income variance in cross-sectional data

A popular approach to estimating income variance in cross-sectional data is to use an aggregate method by categorizing sample observations into arbitrarily formed groups, taking into account some socio-economic attributes. This study proposes an alternative technique that can be used to estimate income variance from cross-sectional data. Results indicate that this multiplicative heteroskedastic feasible least squares estimation procedure is consistent and efficient, consumes less time and requires less manipulation of data.