Challenges in Identifying Interbank Loans

17 Pages Posted: 22 Oct 2015

See all articles by Olivier Armantier

Olivier Armantier

Federal Reserve Bank of New York

Adam M. Copeland

Federal Reserve Bank of New York

Date Written: 2015

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: federal funds market, data quality

JEL Classification: C81, G10

Suggested Citation

Armantier, Olivier and Copeland, Adam M., Challenges in Identifying Interbank Loans (2015). Economic Policy Review, Issue 21-1, pp. 1-17, 2015. Available at SSRN: https://ssrn.com/abstract=2677548

Olivier Armantier (Contact Author)

Federal Reserve Bank of New York ( email )

33 Liberty Street
New York, NY 10045
United States

Adam M. Copeland

Federal Reserve Bank of New York ( email )

33 Liberty Street
New York, NY 10045
United States

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