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The Matching Function: A Unified Look into the Black Box

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Abstract

In this paper, we use tools from network theory to trace the properties of the matching function to the structure of granular connections between applicants and firms. We link seemingly disparate parts of the literature and recover existing functional forms as special cases. Our overarching message is that structure counts. For rich structures, captured by non-random networks, the matching function depends on whole sets rather than just the sizes of the two sides of the market. For less rich-random network-structures it depends on the sizes of the two sides and a few structural parameters. Structures characterized by greater asymmetries reduce the matching function's efficacy, while denser structures can have ambiguous effects on it. For the special case of the Erdös-Rényi network, we show that the way the network varies with the sizes of the two sides of the market determines if the matching function exhibits constant returns to scale, or even if it is of a specific functional form, such as CES.

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  • Georgios Angelis & Yann Bramoullé, 2023. "The Matching Function: A Unified Look into the Black Box," AMSE Working Papers 2315, Aix-Marseille School of Economics, France.
    • Handle: RePEc:aim:wpaimx:2315
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    1. Christopher A. Pissarides, 2000. "Equilibrium Unemployment Theory, 2nd Edition," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262161877, December.
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    3. Lange, Fabian & Papageorgiou, Theodore, 2020. "Beyond Cobb-Douglas: Flexibly Estimating Matching Functions with Unobserved Matching Efficiency," IZA Discussion Papers 13177, Institute of Labor Economics (IZA).
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