Welfare measurement in labour supply models with nonlinear budget constraints

Ian Walker () and Ian Preston

Journal of Population Economics, 1999, vol. 12, issue 3, 343-361

Abstract: This paper is concerned with the measurement of individual welfare in labour supply models which allow for the impact of income taxation and income support schemes on labour supply decisions. The paper is motivated by the concern over the need to have measures which can be interpreted easily, which can be compared with net income, and which can be meaningfully aggregated. To illustrate the issues we use estimates of a discrete choice model of labour supply for United Kingdom lone mothers to compute alternative welfare measures which might be considered as having intuitive appeal to policy-makers. We compute welfare change based on these measures arising from a recent reform of the child support payments system.

Keywords: Welfare; measurement; ·; labour; supply; ·; lone; parents (search for similar items in EconPapers)
JEL-codes: C25 I30 I38 J22 (search for similar items in EconPapers)
Date: 1999-08-16
Note: Received: 25 February 1997/Accepted: 12 March 1998
References: Add references at CitEc
Citations: View citations in EconPapers (26)

Downloads: (external link)
http://link.springer.de/link/service/journals/00148/papers/9012003/90120343.pdf (application/pdf)
Access to the full text of the articles in this series is restricted

Related works:
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:spr:jopoec:v:12:y:1999:i:3:p:343-361

Ordering information: This journal article can be ordered from
http://www.springer. ... tion/journal/148/PS2

Access Statistics for this article

Journal of Population Economics is currently edited by K.F. Zimmermann

More articles in Journal of Population Economics from Springer, European Society for Population Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().