The U.S. Syndicated Loan Market: Matching Data
26 Pages Posted: 12 Dec 2018
Date Written: December 2018
We introduce a new software package for determining linkages between datasets without common identifiers. We apply these methods to three datasets commonly used in academic research on syndicated lending: Refinitiv LPC DealScan, the Shared National Credit Database, and S&P Global Market Intelligence Compustat. We benchmark the results of our match using results from the literature and previously matched files that are publicly available. We find that the company level matching is enhanced by careful cleaning of the data and considering hierarchical relationships. For loan level matching, a tailored approach based on a good understanding of the data can be better in certain dimensions than a more pure machine learning approach.
Keywords: bank credit, syndicated loans, probabilistic matching, company level matching, loan level matching
JEL Classification: C55, C88, E44, G21
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