Women in the Top of the Income Distribution – What Can We Learn From LIS-Data?

Roman Bobilev (), Anne Boschini and Jesper Roine

No 773, LIS Working papers from LIS Cross-National Data Center in Luxembourg

Abstract: We explore the extent to which LIS-data can be used to shed light on the presence of women in the top of the income distribution. We show developments of the share of women in top groups (P90-100 and P99-100) of the labour income distribution for 28 countries and, when possible, compare to outcomes when including capital incomes. These turn out not to matter much for the share of women in top groups with some important exceptions. Relating our findings to the existing evidence on women in the top of the income distribution based on aggregate tax data, we find that LIS-data give a relatively accurate picture of the basic findings. However, we also note that once we divide the top1 group further, samples quickly become too small to allow further study. For countries where data allows such analysis, we find that having a partner and having children are positively associated with being in top income groups for men, but negatively associated for women. However, time interactions suggest that these differences have decreased over time. Also, top income men are more likely to have partners who are not in the top of the income distribution while this is not the case for top income women. All these results are surprisingly consistent across country groups.

JEL-codes: D31 H20 J16 J31 (search for similar items in EconPapers)
Pages: 51 pages
Date: 2019-09
References: View references in EconPapers View complete reference list from CitEc
Citations:

Published in Italian Economic Journal (2019). https://doi.org/10.1007/s40797-019-00108-w

Downloads: (external link)
http://www.lisdatacenter.org/wps/liswps/773.pdf (application/pdf)

Related works:
Journal Article: Women in the Top of the Income Distribution: What Can We Learn From LIS-Data? (2020)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:lis:liswps:773

Access Statistics for this paper

More papers in LIS Working papers from LIS Cross-National Data Center in Luxembourg Contact information at EDIRC.
Bibliographic data for series maintained by Piotr Paradowski ().