Abstract

Using machine learning techniques, we uncover an important number of dealers in the U.S. municipal bond market who focus on geographically adjacent states, a characteristic distinct from dealer centrality. These “specialized” dealers enjoy larger market shares in states with greater local ownership and in local bonds with more complex features. We also find that trades intermediated by these specialized dealers have significantly larger markups than those intermediated by national dealers. For the average retail trade, about two-thirds of the differential markup is attributed to rent, with the remaining third to the unique benefits of specialization. Only the latter matters for institution-sized trades. Together, these results suggest that specialized dealers possess some monopoly power yet also provide important differentiated services. Specialized dealers provide immediacy, reward customers with an allocation of new bond offerings, help customers overcome information frictions, and facilitate access to local investor clientele. The latter two account for the bulk of the specialization benefits. Over time, as transparency improves and local ownership declines, the average market share of specialized dealers decreases along with differential markups.

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• Keyword(s):
• finance 247
• machine learning 22

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