Chapter 4 Applying The Decomposition of the Foster and Wolfson Bipolarization Index to Earnings Functions

E. Bárcena-Martín, J. Silber
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Abstract

Abstract This chapter shows that the algorithm recently proposed to decompose the Foster and Wolfson bipolarization index by income sources (see Barcena-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.
第四章将Foster和Wolfson两极化指数的分解应用于盈余函数
摘要本章表明,最近提出的按收入来源分解Foster和Wolfson双极化指数的算法(见Barcena Martin,Deutsch,&Silber,即将出版)可以扩展到按其决定因素分解工资双极化。本章对2011年欧洲各国工资两极分化和不平等的决定因素进行了实证分析,并特别关注葡萄牙。在葡萄牙,较高的教育水平是两极分化和不平等的主要根源。性别和在公共部门工作是两极化的重要决定因素,而年龄和有临时工作是不平等的重要决定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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