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Evaluating the quality of fed funds lending estimates produced from Fedwire payments data

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Abstract

A number of empirical analyses of interbank lending rely on indirect inferences from individual interbank transactions extracted from payments data using algorithms. In this paper, we conduct an evaluation to assess the ability of identifying overnight U.S. fed funds activity from Fedwire payments data. We find evidence that the estimates extracted from the data are statistically significantly correlated with banks' fed funds borrowing as reported on the FRY-9C. We find similar associations for fed funds lending, although the correlations are lower. To be conservative, we believe that the estimates are best interpreted as measures of overnight interbank activity rather than fed funds activity specifically. We also compare the estimates provided by Armantier and Copeland (2012) to the Y-9C fed funds amounts.

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  • Anna Kovner & David R. Skeie, 2013. "Evaluating the quality of fed funds lending estimates produced from Fedwire payments data," Staff Reports 629, Federal Reserve Bank of New York.
  • Handle: RePEc:fip:fednsr:629
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    5. Olivier Armantier & Adam Copeland, 2012. "Assessing the quality of “Furfine-based” algorithms," Staff Reports 575, Federal Reserve Bank of New York.
    6. Dennis Kuo & David R. Skeie & James Vickery & Thomas Youle, 2013. "Identifying term interbank loans from Fedwire payments data," Staff Reports 603, Federal Reserve Bank of New York.
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    12. repec:zbw:bofrdp:2011_023 is not listed on IDEAS
    13. Q. Farooq Akram & Casper Christophersen, 2010. "Interbank overnight interest rates - gains from systemic importance," Working Paper 2010/11, Norges Bank.
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    Cited by:

    1. Luca Arciero & Ronald Heijmans & Richard Heuver & Marco Massarenti & Cristina Picillo & Francesco Vacirca, 2016. "How to Measure the Unsecured Money Market: The Eurosystem’s Implementation and Validation Using TARGET2 Data," International Journal of Central Banking, International Journal of Central Banking, vol. 12(1), pages 247-280, March.
    2. Abbassi, Puriya & Bräuning, Falk & Fecht, Falko & Peydró, José-Luis, 2014. "Cross-border liquidity, relationships and monetary policy: Evidence from the Euro area interbank crisis," Discussion Papers 45/2014, Deutsche Bundesbank.
    3. Thomas B. King & Kurt F. Lewis, 2020. "Credit Risk, Liquidity, and Lies," International Journal of Central Banking, International Journal of Central Banking, vol. 16(5), pages 219-267, October.
    4. S. Gabrieli & C.-P. Georg, 2014. "A network view on interbank market freezes," Working papers 531, Banque de France.
    5. Denbee, Edward & Julliard, Christian & Li, Ye & Yuan, Kathy, 2021. "Network risk and key players: A structural analysis of interbank liquidity," Journal of Financial Economics, Elsevier, vol. 141(3), pages 831-859.
    6. Puriya Abbassi & Falk Bräuning & Falko Fecht & José-Luis Peydró, 2017. "International financial integration, crises, and monetary policy: evidence from the euro area interbank crises," Working Papers 17-6, Federal Reserve Bank of Boston.
    7. Puriya Abbassi & Falk Brauning & Falko Fecht & José-Luis Peydró, 2017. "International Financial Integration, Crises and Monetary Policy: Cross-Border Interbank Lending During the Euro Crises," Working Papers 965, Barcelona School of Economics.
    8. Q. Farooq Akram & Casper Christophersen, 2017. "Pricing in the Norwegian Interbank Market – the Effects of Liquidity and Implicit Government Support," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(2), pages 165-204, April.
    9. Abbassi, Puriya & Bräuning, Falk & Fecht, Falko & Peydró, José-Luis, 2022. "Cross-border interbank liquidity, crises, and monetary policy," Journal of International Economics, Elsevier, vol. 139(C).

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    More about this item

    Keywords

    federal funds market; data quality; interbank loans; fed funds; Fedwire; Y-9C;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • E40 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - General
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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