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Constrainedly fair job assignments under minimum wages

Andersson, Tommy LU ; Svensson, Lars-Gunnar LU and Yang, Z. (2010) In Games and Economic Behavior 68(2). p.428-442
Abstract
A number of jobs are to be assigned to a greater number of workers. While having to abide by the law of minimum wages, firms must determine who should be assigned which job and at what Salary. In Such situations fair (envy-free) allocations usually fail to exist. To cope with this Situation, this paper proposes a new concept of fairness, called constrained fairness. Among the set of constrainedly fair allocations, the so-called constrainedly fair and minimal allocations are of particular interest. The reason for this is that the salaries are not only compatible with the minimum wages; they are also optimal from the standpoint of cost-minimizing firms and the assignment of jobs is efficient from the viewpoint of workers. A convergent... (More)
A number of jobs are to be assigned to a greater number of workers. While having to abide by the law of minimum wages, firms must determine who should be assigned which job and at what Salary. In Such situations fair (envy-free) allocations usually fail to exist. To cope with this Situation, this paper proposes a new concept of fairness, called constrained fairness. Among the set of constrainedly fair allocations, the so-called constrainedly fair and minimal allocations are of particular interest. The reason for this is that the salaries are not only compatible with the minimum wages; they are also optimal from the standpoint of cost-minimizing firms and the assignment of jobs is efficient from the viewpoint of workers. A convergent dynamic procedure that identifies constrainedly fair and minimal allocations is proposed. Furthermore, strategic properties of the mechanism are derived, and two notions of efficiency are evaluated. (C) 2009 Elsevier Inc. All rights reserved. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Non-manipulability, Incentives, design, Dynamic mechanism, Constrained fairness, Minimum wages, Job assignment
in
Games and Economic Behavior
volume
68
issue
2
pages
428 - 442
publisher
0899-8256
external identifiers
  • wos:000275524500002
  • scopus:75349110211
ISSN
0899-8256
DOI
10.1016/j.geb.2009.09.010
language
English
LU publication?
yes
id
e1a0c39c-a885-42fe-ba24-0ba3ec95bc74 (old id 1588411)
date added to LUP
2010-04-20 15:42:17
date last changed
2018-05-29 11:27:27
@article{e1a0c39c-a885-42fe-ba24-0ba3ec95bc74,
  abstract     = {A number of jobs are to be assigned to a greater number of workers. While having to abide by the law of minimum wages, firms must determine who should be assigned which job and at what Salary. In Such situations fair (envy-free) allocations usually fail to exist. To cope with this Situation, this paper proposes a new concept of fairness, called constrained fairness. Among the set of constrainedly fair allocations, the so-called constrainedly fair and minimal allocations are of particular interest. The reason for this is that the salaries are not only compatible with the minimum wages; they are also optimal from the standpoint of cost-minimizing firms and the assignment of jobs is efficient from the viewpoint of workers. A convergent dynamic procedure that identifies constrainedly fair and minimal allocations is proposed. Furthermore, strategic properties of the mechanism are derived, and two notions of efficiency are evaluated. (C) 2009 Elsevier Inc. All rights reserved.},
  author       = {Andersson, Tommy and Svensson, Lars-Gunnar and Yang, Z.},
  issn         = {0899-8256},
  keyword      = {Non-manipulability,Incentives,design,Dynamic mechanism,Constrained fairness,Minimum wages,Job assignment},
  language     = {eng},
  number       = {2},
  pages        = {428--442},
  publisher    = {0899-8256},
  series       = {Games and Economic Behavior},
  title        = {Constrainedly fair job assignments under minimum wages},
  url          = {http://dx.doi.org/10.1016/j.geb.2009.09.010},
  volume       = {68},
  year         = {2010},
}