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A Marriage Market for Economists

Andersson, Ludvig LU (2019) NEKH02 20191
Department of Economics
Abstract
For a labor market, such as the one for economists, an employer often faces the diffi- culty of distinguishing attainable from unattainable candidates. Offers, rejections and the recruiting process overall is costly, and participants of the market need to choose who to pursue wisely. EconMatch is a site aiming to provide suggestions on what candidate is the best to pursue for a university, based on a matching algorithm and the market’s preferences. Some concerns, however, regarding EconMatch, the algo- rithm it is based on, its performance on the labor market and possibilities for strategic behavior have been expressed. However, the essay shows that potential strategic con- duct does not seem worthwhile because of how the algorithm is... (More)
For a labor market, such as the one for economists, an employer often faces the diffi- culty of distinguishing attainable from unattainable candidates. Offers, rejections and the recruiting process overall is costly, and participants of the market need to choose who to pursue wisely. EconMatch is a site aiming to provide suggestions on what candidate is the best to pursue for a university, based on a matching algorithm and the market’s preferences. Some concerns, however, regarding EconMatch, the algo- rithm it is based on, its performance on the labor market and possibilities for strategic behavior have been expressed. However, the essay shows that potential strategic con- duct does not seem worthwhile because of how the algorithm is constructed, and even less so when considering the non-binding property of the matching. Simulations show that market size seem to have a negative impact on the probability of achieving the highest preference match for candidates. This is likely due to competition and in- creasingly complex combinatorics. However, considering the algorithm in the bigger picture may be more appropriate. This essay proposes to consider EconMatch as a tool for communicating information, rather than a traditional matching assignment, thus, reducing asymmetric information and facilitating credible signaling. (Less)
Please use this url to cite or link to this publication:
author
Andersson, Ludvig LU
supervisor
organization
course
NEKH02 20191
year
type
M2 - Bachelor Degree
subject
keywords
EconMatch, Matching Theory, Strategy, Algorithm, Asymmetric Information
language
English
id
8980292
date added to LUP
2019-08-08 11:32:32
date last changed
2019-08-08 11:32:32
@misc{8980292,
  abstract     = {{For a labor market, such as the one for economists, an employer often faces the diffi- culty of distinguishing attainable from unattainable candidates. Offers, rejections and the recruiting process overall is costly, and participants of the market need to choose who to pursue wisely. EconMatch is a site aiming to provide suggestions on what candidate is the best to pursue for a university, based on a matching algorithm and the market’s preferences. Some concerns, however, regarding EconMatch, the algo- rithm it is based on, its performance on the labor market and possibilities for strategic behavior have been expressed. However, the essay shows that potential strategic con- duct does not seem worthwhile because of how the algorithm is constructed, and even less so when considering the non-binding property of the matching. Simulations show that market size seem to have a negative impact on the probability of achieving the highest preference match for candidates. This is likely due to competition and in- creasingly complex combinatorics. However, considering the algorithm in the bigger picture may be more appropriate. This essay proposes to consider EconMatch as a tool for communicating information, rather than a traditional matching assignment, thus, reducing asymmetric information and facilitating credible signaling.}},
  author       = {{Andersson, Ludvig}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{A Marriage Market for Economists}},
  year         = {{2019}},
}