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The Matching Function: A Unified Look into the Black Box

Author

Listed:
  • Georgios Angelis

    (Bocconi University [Milan, Italy], IGIER)

  • Yann Bramoullé

    (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

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.

Suggested Citation

  • Georgios Angelis & Yann Bramoullé, 2023. "The Matching Function: A Unified Look into the Black Box," Working Papers hal-04136688, HAL.
  • Handle: RePEc:hal:wpaper:hal-04136688
    Note: View the original document on HAL open archive server: https://amu.hal.science/hal-04136688
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    References listed on IDEAS

    as
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    Bocconi University; IGIER; Bramoullé;
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