Applying the decomposition of the foster and wolfson bipolarization index to earnings functions

Elena Bárcena-Martin, Jacques Silber

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

This chapter shows that the algorithm recently proposed to decompose the Foster and Wolfson bipolarization index by income sources (see Bárcena-Martin, Deutsch, & Silber, forthcoming) may be extended to break down wage bipolarization by its determinants. The chapter gives an empirical illustration comparing the determinants of wage bipolarization and inequality in various European countries in 2011, with a special focus on Portugal. In Portugal higher levels of education are the main source of bipolarization and inequality. Gender and working in the public sector are important determinants of bipolarization while age and having a temporary job are important determinants of inequality.

Original languageEnglish
Title of host publicationResearch on Economic Inequality
PublisherEmerald Group Publishing Ltd.
Pages63-88
Number of pages26
DOIs
StatePublished - 2018

Publication series

NameResearch on Economic Inequality
Volume26
ISSN (Print)1049-2585

Bibliographical note

Publisher Copyright:
© 2019 by Emerald Publishing Limited All rights of reproduction in any form reserved.

Keywords

  • Bipolarization
  • Earnings function
  • Foster and Wolfson polarization index
  • Income sources
  • Inequality
  • SILC data

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