Challenges in identifying interbank loans

Olivier Armantier and Adam Copeland

Economic Policy Review, 2015, issue 21-1, 17 pages

Abstract: Although interbank lending markets play a key role in the financial system, the lack of disaggregated data often makes the analysis of these markets difficult. To address this problem, recent academic papers focusing on unsecured loans of central bank reserves have employed an algorithm in an effort to identify individual transactions that are federal funds loans. The accuracy of the algorithm, however, is not known. The authors of this study conduct a formal test with U.S. data and find that the rate of false positives produced by one of these algorithms is on average 81 percent; the rate of false negatives is 23 percent. These results raise concerns about the information content of the algorithm's output.

Keywords: data quality; federal funds market (search for similar items in EconPapers)
JEL-codes: C81 G10 (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (4)

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