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

Author

Listed:
  • Hiroki Uematsu
  • Ashok Kumar Mishra
  • Rebekah Rachel Powell

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.

Suggested Citation

  • Hiroki Uematsu & Ashok Kumar Mishra & Rebekah Rachel Powell, 2012. "An alternative method to estimate income variance in cross-sectional data," Applied Economics Letters, Taylor & Francis Journals, vol. 19(15), pages 1431-1436, October.
  • Handle: RePEc:taf:apeclt:v:19:y:2012:i:15:p:1431-1436
    DOI: 10.1080/13504851.2011.631887
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