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The U.S. Syndicated Loan Market: Matching Data
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 ...
Pipeline Risk in Leveraged Loan Syndication
Leveraged term loans are typically arranged by banks but distributed to institutional investors. Using novel data, we find that to elicit investors' willingness to pay, arrangers expose themselves to pipeline risk: They have to retain larger shares when investors are willing to pay less than expected. We argue that the retention of such problematic loans creates a debt overhang problem. Consistent with this, we find that the materialization of pipeline risk for an arranger reduces its subsequent arranging and lending activity. Aggregate time series exhibit a similar pattern, which suggests ...