Abstract
In this paper we introduce and study a model that considers the job market as a two-sided matching market, and accounts for the importance of social contacts in finding a new job. We assume that workers learn only about positions in firms through social contacts. Given that information structure, we study both static properties of what we call locally stable matchings, a solution concept derived from stable matchings, and dynamic properties through a reinterpretation of Gale-Shapley’s algorithm as myopic best response dynamics.
We prove that, in general, the set of locally stable matching strictly contains that of stable matchings and it is in fact NP-complete to determine if they are identical. We also show that the lattice structure of stable matchings is in general absent. Finally, we focus on myopic best response dynamics inspired by the Gale-Shapley algorithm. We study the efficiency loss due to the informational constraints, providing both lower and upper bounds.
A full version of this work appears in [2].
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Arcaute, E., Vassilvitskii, S. (2009). Social Networks and Stable Matchings in the Job Market. In: Leonardi, S. (eds) Internet and Network Economics. WINE 2009. Lecture Notes in Computer Science, vol 5929. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10841-9_21
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DOI: https://doi.org/10.1007/978-3-642-10841-9_21
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