Arbeitspapier
Robust multidimensional welfare comparisons: One vector of weights, one vote
Many aspects of social welfare are intrinsically multidimensional. Composite indices at-tempting to reduce this complexity to a unique measure abound in many areas of economics and public policy. Comparisons based on such measures depend, sometimes critically, on how the di erent dimensions of performance are weighted. Thus, a policy maker maker may wish to take into account imprecision over composite index weights in a systematic manner. In this paper, such weight imprecision is parameterized via the -contamination framework of Bayesian statistics. Subsequently, combining results from polyhedral geometry, social choice, and theoretical computer science, an analytical procedure is presented that yields a provably robust ranking of the relevant alternatives in the presence of weight imprecision. The main idea is to consider a vector of weights as a voter and a continuum of weights as an electorate. The procedure is illustrated on recent versions of the Rule of Law and Human Development indices.
- Sprache
-
Englisch
- Erschienen in
-
Series: Nota di Lavoro ; No. 40.2013
- Klassifikation
-
Wirtschaft
Mathematical Methods
Optimization Techniques; Programming Models; Dynamic Analysis
Microeconomic Policy: Formulation, Implementation, and Evaluation
Social Choice; Clubs; Committees; Associations
General Welfare; Well-Being
- Thema
-
Multidimensional Welfare
Composite Index
ε-contamination
Polyhedral Geometry
Social Choice
Approximation Algorithms
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Athanassoglou, Stergios
- Ereignis
-
Veröffentlichung
- (wer)
-
Fondazione Eni Enrico Mattei (FEEM)
- (wo)
-
Milano
- (wann)
-
2013
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
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Objekttyp
- Arbeitspapier
Beteiligte
- Athanassoglou, Stergios
- Fondazione Eni Enrico Mattei (FEEM)
Entstanden
- 2013