Artikel
Contribution-based grouping under noise
Many real-world mechanisms are 'noisy' or 'fuzzy', that is the institutions in place to implement them operate with non-negligible degrees of imprecision and error. This observation raises the more general question of whether mechanisms that work in theory are also robust to more realistic assumptions such as noise. In this paper, in the context of voluntary contribution games, we focus on a mechanism known as 'contribution-based competitive grouping'. First, we analyze how the mechanism works under noise and what happens when other assumptions such as population homogeneity are relaxed. Second, we investigate the welfare properties of the mechanism, interpreting noise as a policy instrument, and we use logit dynamic simulations to formulate mechanism design recommendations.
- Sprache
-
Englisch
- Erschienen in
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Journal: Games ; ISSN: 2073-4336 ; Volume: 8 ; Year: 2017 ; Issue: 4 ; Pages: 1-23 ; Basel: MDPI
- Klassifikation
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Wirtschaft
Stochastic and Dynamic Games; Evolutionary Games; Repeated Games
Institutions: Design, Formation, Operations, and Impact
Equity, Justice, Inequality, and Other Normative Criteria and Measurement
- Thema
-
voluntary contributions
behavioral economics
noise
heterogeneity
mechanism design
welfare
efficiency
equality
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Nax, Heinrich H.
Murphy, Ryan O.
Duca, Stefano
Helbing, Dirk
- Ereignis
-
Veröffentlichung
- (wer)
-
MDPI
- (wo)
-
Basel
- (wann)
-
2017
- DOI
-
doi:10.3390/g8040050
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:45 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Nax, Heinrich H.
- Murphy, Ryan O.
- Duca, Stefano
- Helbing, Dirk
- MDPI
Entstanden
- 2017
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