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.
|Title of host publication||Research on Economic Inequality|
|Publisher||Emerald Group Publishing Ltd.|
|Number of pages||26|
|State||Published - 2018|
|Name||Research on Economic Inequality|
Bibliographical noteFunding Information:
Elena Bárcena-Martín gratefully acknowledges the financial support provided by the Spanish Ministry of Education through Grant ECO2015-63734-P (MINECO/FEDER). She also thanks the University of Málaga for its financial support. Both authors thank the referee and the editors of this volume for their helpful remarks.
© 2019 by Emerald Publishing Limited All rights of reproduction in any form reserved.
- Earnings function
- Foster and Wolfson polarization index
- Income sources
- SILC data