IDEAS home Printed from https://ideas.repec.org/p/ssb/dispap/665.html
   My bibliography  Save this paper

How do banks' funding costs affect interest margins?

Author

Listed:

Abstract

We use a dynamic factor model and a detailed panel data set with quarterly accounts data on all Norwegian banks to study the effects of banks' funding costs on their retail rates. Banks' funds are categorized into two groups: customer deposits and long-term wholesale funding (market funding from private and institutional investors including other banks). The cost of market funding is represented in the model by the three-month Norwegian Inter Bank Offered Rate (NIBOR) and the spread of unsecured senior bonds issued by Norwegian banks. Our estimates show clear evidence of incomplete pass-through: a unit increase in NIBOR leads to an approximately 0.8 increase in bank rates. On the other hand, the difference between banks' loan and deposit rates is independent of NIBOR. Our findings are consistent with the view that banks face a downward-sloping demand curve for loans and an upward-sloping supply curve for customer deposits.

Suggested Citation

  • Arvid Raknerud & Bjørn Helge Vatne & Ketil Rakkestad, 2011. "How do banks' funding costs affect interest margins?," Discussion Papers 665, Statistics Norway, Research Department.
    • Handle: RePEc:ssb:dispap:665
    as

    Download full text from publisher

    File URL: https://www.ssb.no/a/publikasjoner/pdf/DP/dp665.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chan, K C, et al, 1992. "An Empirical Comparison of Alternative Models of the Short-Term Interest Rate," Journal of Finance, American Finance Association, vol. 47(3), pages 1209-1227, July.
    2. Paolo Angelini & Laurent Clerc & Vasco Cúrdia & Leonardo Gambacorta & Andrea Gerali & Alberto Locarno & Roberto Motto & Werner Roeger & Skander Van den Heuvel & Jan Vlček, 2015. "Basel III: Long-term Impact on Economic Performance and Fluctuations," Manchester School, University of Manchester, vol. 83(2), pages 217-251, March.
    3. Arvid Raknerud & Terje Skjerpen & Anders Rygh Swensen, 2010. "Forecasting key macroeconomic variables from a large number of predictors: a state space approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(4), pages 367-387.
    4. Chong, Beng Soon, 2010. "Interest rate deregulation: Monetary policy efficacy and rate rigidity," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1299-1307, June.
    5. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
    6. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
    7. Maudos, Joaquin & Fernandez de Guevara, Juan, 2004. "Factors explaining the interest margin in the banking sectors of the European Union," Journal of Banking & Finance, Elsevier, vol. 28(9), pages 2259-2281, September.
    8. André K. Anundsen & Eilev S. Jansen, 2011. "Self-reinforcing effects between housing prices and credit. Evidence from Norway," Discussion Papers 651, Statistics Norway, Research Department.
    9. Boris Hofmann & Paul Mizen, 2004. "Interest Rate Pass-Through and Monetary Transmission: Evidence from Individual Financial Institutions' Retail Rates," Economica, London School of Economics and Political Science, vol. 71, pages 99-123, February.
    10. Henrik Andersen & Sigbjørn Atle Berg & Eilev S. Jansen, 2008. "The dynamics of operating income in the Norwegian banking sector," Working Paper 2008/13, Norges Bank.
    11. Q. Akram & Casper Christophersen, 2013. "Norwegian Overnight Interbank Interest Rates," Computational Economics, Springer;Society for Computational Economics, vol. 41(1), pages 11-29, January.
    12. de Bondt, Gabe, 2002. "Retail bank interest rate pass-through: new evidence at the euro area level," Working Paper Series 136, European Central Bank.
    13. De Graeve, Ferre & De Jonghe, Olivier & Vennet, Rudi Vander, 2007. "Competition, transmission and bank pricing policies: Evidence from Belgian loan and deposit markets," Journal of Banking & Finance, Elsevier, vol. 31(1), pages 259-278, January.
    14. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 120(1), pages 387-422.
    15. Choi, In & Chul Ahn, Byung, 1998. "Testing the null of stationarity for multiple time series," Journal of Econometrics, Elsevier, vol. 88(1), pages 41-77, November.
    16. Choi, In, 1994. "Residual-Based Tests for the Null of Stationarity with Applications to U.S. Macroeconomic Time Series," Econometric Theory, Cambridge University Press, vol. 10(3-4), pages 720-746, August.
    17. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    18. Ho, Thomas S. Y. & Saunders, Anthony, 1981. "The Determinants of Bank Interest Margins: Theory and Empirical Evidence," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 16(4), pages 581-600, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Arvid Raknerud & Bjørn Helge Vatne, 2012. "The relation between banks' funding costs, retail rates and loan volumes: An analysis of Norwegian bank micro data," Working Paper 2012/17, Norges Bank.
    2. Arvid Raknerud & Bjørn Helge Vatne, 2013. "The relations between bank-funding costs, retail rates, and loan volumes. Evidence form Norwegian microdata," Discussion Papers 742, Statistics Norway, Research Department.
    3. Michiel van Leuvensteijn & Christoffer Kok Sørensen & Jacob A. Bikker & Adrian A.R.J.M. van Rixtel, 2013. "Impact of bank competition on the interest rate pass-through in the euro area," Applied Economics, Taylor & Francis Journals, vol. 45(11), pages 1359-1380, April.
    4. von Borstel, Julia & Eickmeier, Sandra & Krippner, Leo, 2016. "The interest rate pass-through in the euro area during the sovereign debt crisis," Journal of International Money and Finance, Elsevier, vol. 68(C), pages 386-402.
    5. Jaakko Sääskilahti, 2018. "Retail Bank Interest Margins in Low Interest Rate Environments," Journal of Financial Services Research, Springer;Western Finance Association, vol. 53(1), pages 37-68, February.
    6. Illes, Anamaria & Lombardi, Marco J. & Mizen, Paul, 2019. "The divergence of bank lending rates from policy rates after the financial crisis: The role of bank funding costs," Journal of International Money and Finance, Elsevier, vol. 93(C), pages 117-141.
    7. De Graeve, Ferre & De Jonghe, Olivier & Vennet, Rudi Vander, 2007. "Competition, transmission and bank pricing policies: Evidence from Belgian loan and deposit markets," Journal of Banking & Finance, Elsevier, vol. 31(1), pages 259-278, January.
    8. Ming-Hua Liu & Dimitris Margaritis & Zhuo Qiao, 2016. "The Global Financial Crisis and Retail Interest Rate Pass-Through in Australia," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 19(04), pages 1-32, December.
    9. Bennouna, Hicham, 2019. "Interest rate pass-through in Morocco: Evidence from bank-level survey data," Economic Modelling, Elsevier, vol. 80(C), pages 142-157.
    10. Matteo Barigozzi & Antonio M. Conti & Matteo Luciani, 2014. "Do Euro Area Countries Respond Asymmetrically to the Common Monetary Policy?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(5), pages 693-714, October.
    11. Mario Forni & Luca Gambetti & Luca Sala, 2014. "No News in Business Cycles," Economic Journal, Royal Economic Society, vol. 124(581), pages 1168-1191, December.
    12. Luke Hartigan & James Morley, 2020. "A Factor Model Analysis of the Australian Economy and the Effects of Inflation Targeting," The Economic Record, The Economic Society of Australia, vol. 96(314), pages 271-293, September.
    13. Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2022. "The global component of inflation volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 700-721, June.
    14. Jonas Krampe & Luca Margaritella, 2021. "Factor Models with Sparse VAR Idiosyncratic Components," Papers 2112.07149, arXiv.org, revised May 2022.
    15. Romain Houssa & Lasse Bork & Hans Dewachter, 2008. "Identification of Macroeconomic Factors in Large Panels," Working Papers 1010, University of Namur, Department of Economics.
    16. Piyachart Phiromswad & Takeshi Yagihashi, 2016. "Empirical identification of factor models," Empirical Economics, Springer, vol. 51(2), pages 621-658, September.
    17. Fabio Canova & Matteo Ciccarelli, 2009. "Estimating Multicountry Var Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(3), pages 929-959, August.
    18. Angelopoulos, Jason & Sahoo, Satya & Visvikis, Ilias D., 2020. "Commodity and transportation economic market interactions revisited: New evidence from a dynamic factor model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    19. Hwee Kwan Chow & Keen Meng Choy, 2009. "Analyzing and forecasting business cycles in a small open economy: A dynamic factor model for Singapore," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2009(1), pages 19-41.
    20. Ergemen, Yunus Emre & Rodríguez-Caballero, C. Vladimir, 2023. "Estimation of a dynamic multi-level factor model with possible long-range dependence," International Journal of Forecasting, Elsevier, vol. 39(1), pages 405-430.

    More about this item

    Keywords

    interest rates; NIBOR; pass-through; funding costs; bank panel data; dynamic factor model;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ssb:dispap:665. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: L Maasø (email available below). General contact details of provider: https://edirc.repec.org/data/ssbgvno.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.