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

Hiroki Uematsu, Ashok Kumar Mishra, Rebekah Rachel Powell

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

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 languageEnglish (US)
Pages (from-to)1431-1436
Number of pages6
JournalApplied Economics Letters
Volume19
Issue number15
DOIs
StatePublished - Oct 2012
Externally publishedYes

Keywords

  • aggregate approach
  • cross-sectional data
  • feasible generalized least squares
  • income variance
  • multiplicative heteroskedasticity

ASJC Scopus subject areas

  • Economics and Econometrics

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