Abstract
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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1431-1436 |
| Number of pages | 6 |
| Journal | Applied Economics Letters |
| Volume | 19 |
| Issue number | 15 |
| DOIs | |
| State | Published - Oct 2012 |
| Externally published | Yes |
Keywords
- aggregate approach
- cross-sectional data
- feasible generalized least squares
- income variance
- multiplicative heteroskedasticity
ASJC Scopus subject areas
- Economics and Econometrics