Ordinal Welfare Comparisons with Multiple Discrete Indicators: A First Order Dominance Approach and Application to Child Poverty
Channing Arndt (),
Roberta Distante (),
M. Azhar Hussain (),
Lars Peter Østerdal,
Pham Lan Huong and
Additional contact information
Pham Lan Huong: Central Institute for Economic Management (CIEM), Vietnam
Maimuna Ibraimo: Ministry of Planning and Development (MPD), Mozambique
No 11-13, Discussion Papers from University of Copenhagen. Department of Economics
We develop an ordinal method for making welfare comparisons between populations with multidimensional discrete well-being indicators observed at the micro level. The approach assumes that, for each well-being indicator, the levels can be ranked from worse to better; however, no assumptions are made about relative importance of any dimension nor about complementarity/substitutability relationships between dimensions. The method is based on the concept of multidimensional first order dominance. We introduce a rapid and reliable algorithm for empirically determining whether one population dominates another on the basis of available binary indicators by drawing upon linear programming theory. These approaches are applied to household survey data from Vietnam and Mozambique with a focus on child poverty comparisons over time and between regions.
Pages: 23 pages
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (20) Track citations by RSS feed
Downloads: (external link)
Journal Article: Ordinal Welfare Comparisons with Multiple Discrete Indicators: A First Order Dominance Approach and Application to Child Poverty (2012)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:kud:kuiedp:1113
Access Statistics for this paper
More papers in Discussion Papers from University of Copenhagen. Department of Economics ï¿½ster Farimagsgade 5, Building 26, DK-1353 Copenhagen K., Denmark. Contact information at EDIRC.
Bibliographic data for series maintained by Thomas Hoffmann ().