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  • Decomposition methods for income inequality measures, such as the Gini index and the members of the Generalised Entropy family, are widely applied. Most methods decompose income inequality into a between (explained) and a within (unexplained) part, according to two or more population subgroups or income sources. In this article, we use a regression analysis for a lognormal distribution of personal income, modelling both the mean and the variance, decomposing the variance as a measure of income inequality, and apply the method to survey data from Russia spanning the first decade of market transition (1992-2002). For the first years of the transition, only a small part of the income inequality could be explained. Thereafter, between 1996 and 1999, a larger part (up to 40%) could be explained, and ‘winner’ and ‘loser’ categories of the transition could be spotted. Moving to the upper end of the income distribution, the self-employed won from the transition. The unemployed were among the losers. (xsd:string)
?:contributor
?:dateModified
  • 2013 (xsd:gyear)
?:datePublished
  • 2013 (xsd:gyear)
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  • true (xsd:boolean)
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?:inLanguage
  • en (xsd:string)
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?:issn
  • 1736-8758 ()
?:issueNumber
  • 2 (xsd:string)
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?:name
  • Income Inequality Decomposition, Russia 1992-2002: Method and Application (xsd:string)
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?:publicationType
  • Zeitschriftenartikel (xsd:string)
  • journal_article (en)
?:reference
?:sourceInfo
  • GESIS-SSOAR (xsd:string)
  • In: Studies of Transition States and Societies, 5, 2013, 2, 21-34 (xsd:string)
rdf:type
?:url
?:urn
  • urn:nbn:de:0168-ssoar-365254 ()
?:volumeNumber
  • 5 (xsd:string)