Estimation of bankruptcy rules with a priori unions for establishing new systems of quotas
Loading...
Identifiers
Publication date
Advisors
Tutors
Editors
Journal Title
Journal ISSN
Volume Title
Publisher
Sociedad Española de Estadística e Investigación Operativa
Abstract
This paper addresses a sampling procedure for estimating extensions of the random arrival rule to those bankruptcy situations where there exist a priori unions. It is based on simple random sampling with replacement and it adapts an estimation method of the Owen value for transferable utility games with a priori unions, especially useful when the set of involved agents is sufficiently large. We analyse the theoretical statistical properties of the resulting estimator as well as we provide some bounds for the incurred error. Its performance is evaluated on two well-studied examples in literature where this allocation rule can be exactly obtained. Finally, we apply this sampling method to provide a new quota system for the milk market in Galicia (Spain) for checking the role of different territorial structures when they are taken as a priori unions. The resulting quotas estimator is also compared with two classical rules in bankruptcy literature.
Description
Bibliographic citation
Saavedra Nieves, A., & Saavedra Nieves, P. (2023). Estimation of bankruptcy rules with a priori unions for establishing new systems of quotas. BEIO, Boletín de Estadística e Investigación Operativa, 39(1).
Relation
Has part
Has version
Is based on
Is part of
Is referenced by
Is version of
Requires
Publisher version
https://www.seio.es/beio/estimation-of-bankruptcy-rules-with-a-priori-unions-for-establishing-new-systems-of-quotas/Sponsors
A. Saavedra-Nieves acknowledges the financial support of grant PID2021-124030NB-C32, funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”, and under grant Grupos de Referencia Competitiva ED431C 2021/24, funded by Consellería de Cultura, Educación e Universidades, Xunta de Galicia. P. Saavedra-Nieves also acknowledges the financial support of the Xunta de Galicia through the European Regional Development Fund (Grupos de Referencia Competitiva ED431C 2021/24) and of the Spanish Ministry of Science and Innovation through projects PID2020-118101GB-I00 and PID2020-116587GB-I00.
Rights
Attribution-NonCommercial-NoDerivatives 4.0 Internacional








