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A Field Study on Matching with Network Externalities

Author

Listed:
  • Mariagiovanna Baccara
  • Ayse Imrohoroglu
  • Alistair J. Wilson
  • Leeat Yariv

Abstract

We study the effects of network externalities within a protocol for matching faculty to offices in a new building. Using web and survey data on faculty's attributes and choices, we identify the different layers of the social network: institutional affiliation, coauthorships, and friendships. We quantify the effects of network externalities on choices and outcomes, disentangle the layers of the networks, and quantify their relative influence. Finally, we assess the protocol used from a welfare perspective. Our study suggests the importance and feasibility of accounting for network externalities in assignment problems and evaluates techniques that can be employed to this end. (JEL C78, C93, D62, D85, Z13)

Suggested Citation

  • Mariagiovanna Baccara & Ayse Imrohoroglu & Alistair J. Wilson & Leeat Yariv, 2012. "A Field Study on Matching with Network Externalities," American Economic Review, American Economic Association, vol. 102(5), pages 1773-1804, August.
    • Handle: RePEc:aea:aecrev:v:102:y:2012:i:5:p:1773-1804
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    6. Maria Gabriella Graziano & Claudia Meo & Nicholas C. Yannelis, 2020. "Shapley and Scarf housing markets with consumption externalities," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 22(5), pages 1481-1514, September.
    7. Wei, Liyuan & Yang, Yupin, 2022. "An empirical investigation of director selection in movie preproduction: A two-sided matching approach," International Journal of Research in Marketing, Elsevier, vol. 39(3), pages 888-906.
    8. Jeremy T. Fox, 2018. "Estimating matching games with transfers," Quantitative Economics, Econometric Society, vol. 9(1), pages 1-38, March.
    9. Juan D Carrillo & Saurabh Singhal, 2011. "Tiered Housing Allocation: an Experimental Analysis," Working Paper 8511, USC Lusk Center for Real Estate.
    10. Chen, Bo, 2021. "Labor market matching with ensuing competitive externalities in large economies," Mathematical Social Sciences, Elsevier, vol. 109(C), pages 12-17.
    11. Fisher, James C.D. & Hafalir, Isa E., 2016. "Matching with aggregate externalities," Mathematical Social Sciences, Elsevier, vol. 81(C), pages 1-7.
    12. Suguru Otani & Takuma Matsuda, 2023. "Unified Merger List in the Container Shipping Industry from 1966: A Structural Estimation of the Transition of Importance of a Firm's Age, Tonnage Capacity, and Geographical Proximity on Merger Decisi," Papers 2310.09938, arXiv.org, revised Nov 2023.
    13. Itai Ashlagi & Peng Shi, 2014. "Improving Community Cohesion in School Choice via Correlated-Lottery Implementation," Operations Research, INFORMS, vol. 62(6), pages 1247-1264, December.
    14. Ferrara, Gerardo & Kim, Jun Sung & Koo, Bonsoo & Liu, Zijun, 2021. "Counterparty choice in the UK credit default swap market: An empirical matching approach," Economic Modelling, Elsevier, vol. 94(C), pages 58-74.
    15. Linde, Sebastian & Siebert, Ralph B., 2023. "Exploring the incremental merger value from multimarket and technology arguments," International Journal of Industrial Organization, Elsevier, vol. 87(C).
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    19. Bo Chen, 2019. "Downstream competition and upstream labor market matching," International Journal of Game Theory, Springer;Game Theory Society, vol. 48(4), pages 1055-1085, December.

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    More about this item

    JEL classification:

    • D02 - Microeconomics - - General - - - Institutions: Design, Formation, Operations, and Impact
    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • D62 - Microeconomics - - Welfare Economics - - - Externalities
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments

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