Search Results
Working Paper
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 ...
Working Paper
Sentiment in Central Banks' Financial Stability Reports
Using the text of financial stability reports (FSRs) published by central banks, we analyze the relation between the financial cycle and the sentiment conveyed in these official communications. To do so, we construct a dictionary tailored specifically to a financial stability context, which assigns positive and negative connotations based on the sentiment conveyed by words in FSRs. With this dictionary, we construct a financial stability sentiment (FSS) index. Using a panel of 35 countries for the sample period between 2005 and 2015, we find that central banks' FSS indexes are mostly driven ...
Working Paper
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 ...
Discussion Paper
Constructing a Dictionary for Financial Stability
In this note, we explain in detail how we made word-level choices in our dictionary. In the note, we also consolidate our lessons from this process into a framework for thinking about dictionary construction.