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

Hiroki Uematsu, Ashok Kumar Mishra and Rebekah Rachel Powell

Applied Economics Letters, 2012, vol. 19, issue 15, 1431-1436

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.

Date: 2012
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/13504851.2011.631887 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:apeclt:v:19:y:2012:i:15:p:1431-1436

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEL20

DOI: 10.1080/13504851.2011.631887

Access Statistics for this article

Applied Economics Letters is currently edited by Anita Phillips

More articles in Applied Economics Letters from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().