Defining Geographic Markets Through Choice Sets: An Empirical Method Applied to Real Estate Brokerage

Adam Lindhe and Johan Orrenius ()
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Adam Lindhe: Royal Institute of Technology (KTH)
Johan Orrenius: Research Institute of Industrial Economics (IFN), Postal: Research Institute of Industrial Economics, Box 55665, SE-102 15 Stockholm, Sweden, https://www.ifn.se/en/researchers/ifn-researcher/johan-orrenius/

No 1558, Working Paper Series from Research Institute of Industrial Economics

Abstract: We introduce a choice-set approach to defining markets and a novel method to empirically recover geographic markets using machine learning, Spatial and Categorical Bayesian Clustering (SCBC). SCBC leverages the identity of the seller for each observation to capture market structures in a novel way that is not captured by purely distance-based methods. Applied to real estate agents in Stockholm (Sweden), SCBC classifies sales more accurately than the baseline K-means algorithm. Finally, we investigate the correct number of clusters and find that the optimal number of clusters is close to the validation set based on industry knowledge.

Keywords: Industrial organization; Competition policy; Market regulations (search for similar items in EconPapers)
JEL-codes: C60 D47 L10 (search for similar items in EconPapers)
Pages: 43 pages
Date: 2026-04-29
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Persistent link: https://EconPapers.repec.org/RePEc:hhs:iuiwop:1558

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