2015
DOI: 10.1016/j.jebo.2015.02.006
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Optimal sorting in group contests with complementarities

Abstract: openAccessArticle: Falsecover date: 2015-04-01pii: S0167-2681(15)00041-4Harvest Date: 2016-01-06 13:07:33issueName:Page Range: 311-311href scidir: http://www.sciencedirect.com/science/article/pii/S0167268115000414pubType

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Cited by 18 publications
(17 citation statements)
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References 21 publications
(27 reference statements)
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“…Provided the cost function of effort is not "too steep," Ryvkin (2011) theoretically shows that when within-group efforts are perfectly substitutable and the probability of winning is given by the lottery contest success function (CSF) (Tullock, 1980), the optimal sorting is the one that minimizes the variance in ability across groups, i.e., the most "balanced" sorting. Extending these results to group contests with arbitrary levels of within-group complementarity, Brookins, Lightle and Ryvkin (2015b) show that the optimal sorting may be either balanced or unbalanced, and depends on both the degree of complementarity of efforts within groups and steepness of the effort cost function.…”
Section: Related Literaturementioning
confidence: 88%
“…Provided the cost function of effort is not "too steep," Ryvkin (2011) theoretically shows that when within-group efforts are perfectly substitutable and the probability of winning is given by the lottery contest success function (CSF) (Tullock, 1980), the optimal sorting is the one that minimizes the variance in ability across groups, i.e., the most "balanced" sorting. Extending these results to group contests with arbitrary levels of within-group complementarity, Brookins, Lightle and Ryvkin (2015b) show that the optimal sorting may be either balanced or unbalanced, and depends on both the degree of complementarity of efforts within groups and steepness of the effort cost function.…”
Section: Related Literaturementioning
confidence: 88%
“…Since our article considers the optimal choice of a contest organizer, it is also related to the literature on optimal contests. These studies consider the problem of designing a contest in order to elicit maximum aggregate efforts from the contestants and suggest the various solutions in terms of the optimal number of the contestants(Fu and Lu [23]), the optimal type of group impact function(Lee and Song [31]), the optimal structure of the contest success function(Dasgupta and Nti [17], Epstein et al [21]), optimal reward systems (allocation of the prizes of the contest) (Cohen et al [13], Moldovanu et al [36]), the optimal information structure( Nti [39]), the optimal sorting of contestants (Ryvkin [43], Brookins et al [12]), and the optimal bias of contest rule(Franke et al [22]). To the best of our knowledge, however, none of them explores the case in which the maximum aggregate effort can be elicited by introducing a draw.…”
Section: Introductionmentioning
confidence: 99%
“…The non-cooperative level of production crucially depends on the domain of contributions. In standard models of the weakest-link public goods (Hirshleifer, 1983;Cornes, 1993;Cornes and Sandler, 1996;Baland and Platteau, 1997;Baland et al, 2007;Cornes and Hartley, 2007;Barbieri and Malueg, 2012;Brookins et al, 2015), each player is responsible only for a single task (single-task domains). In this paper, we instead study a common multiple-task domain.…”
Section: Introductionmentioning
confidence: 99%