Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/296421 
Year of Publication: 
2023
Citation: 
[Journal:] Theoretical Economics [ISSN:] 1555-7561 [Volume:] 18 [Issue:] 2 [Year:] 2023 [Pages:] 597-632
Publisher: 
The Econometric Society, New Haven, CT
Abstract: 
Matchings in a market may have varying degrees of compromise from efficiency, fairness, and or stability. A distance function allows to quantify such concepts or the (dis)similarity between any two matchings. There are a few attempts to propose such functions, however these are tailored for specific applications and ignore the individual preferences completely. In this paper, we construct a normative framework to quantify the difference between outcomes of market mechanisms in matching markets, while endogenizing the preferences of the individuals into the distance concept. Several conditions are introduced to capture natural and appealing behavior of such functions. We find a class of distance functions called \textit{scaled Borda distances}, which is the only class of distance functions that satisfies these conditions simultaneously.
Subjects: 
distance function
Matching markets
metrics
JEL: 
C78
D61
D63
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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