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Modelling bank lending in the euro area: a nonlinear approach

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  • Leonardo Gambacorta
  • Carlotta Rossi

Abstract

This article investigates the possible nonlinearities in the response of bank lending to monetary policy shocks in the euro area. The credit market is modelled over the period 1985 to 2005 by means of an Asymmetric Vector Error Correction Model (AVECM) involving four endogenous variables (loans to the private sector, real Gross Domestic Product (GDP), lending rate and consumer price index) and one exogenous variable (money market rate). The main features of the model are the existence of two cointegrating equations representing the long-run credit demand and supply and the possibility for loading and lagged term coefficients to assume different values depending on the monetary policy regime (easing or tightening). The main result of this article is that the effect on credit, GDP and prices of a monetary policy tightening is larger than the effect of a monetary policy easing. This finding supports the existence of an asymmetric broad credit channel in the euro area.

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  • Leonardo Gambacorta & Carlotta Rossi, 2010. "Modelling bank lending in the euro area: a nonlinear approach," Applied Financial Economics, Taylor & Francis Journals, vol. 20(14), pages 1099-1112.
  • Handle: RePEc:taf:apfiec:v:20:y:2010:i:14:p:1099-1112
    DOI: 10.1080/09603101003781430
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    2. Tomas Konecny & Oxana Babecka-Kucharcukova, 2016. "Credit Spreads and the Links between the Financial and Real Sectors in a Small Open Economy: The Case of the Czech Republic," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(4), pages 302-321, August.
    3. Jung, Alexander, 2020. "An empirical analysis of loan supply and demand in the euro area," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 187-201.
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    5. Dobromił Serwa, 2012. "Banking crises and nonlinear linkages between credit and output," Applied Economics, Taylor & Francis Journals, vol. 44(8), pages 1025-1040, March.
    6. Mikael Juselius & Mathias Drehmann, 2020. "Leverage Dynamics and the Burden of Debt," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(2), pages 347-364, April.
    7. Paradiso, Antonio & Kumar, Saten & Lucchetta, Marcella, 2014. "Investigating the US consumer credit determinants using linear and non-linear cointegration techniques," Economic Modelling, Elsevier, vol. 42(C), pages 20-28.
    8. Bouvatier, Vincent & López-Villavicencio, Antonia & Mignon, Valérie, 2014. "Short-run dynamics in bank credit: Assessing nonlinearities in cyclicality," Economic Modelling, Elsevier, vol. 37(C), pages 127-136.
    9. Isakin, Maksim & Serletis, Apostolos, 2019. "Banking technology in a Markov switching economy," Journal of Macroeconomics, Elsevier, vol. 59(C), pages 154-168.
    10. Maria Grazia Miele, 2013. "The effects of capital requirements on real economy:a cointegrated VAR approach for US commercial banks," Working Papers 163, University of Rome La Sapienza, Department of Public Economics.
    11. Saten Kumar, 2016. "Is the US Consumer Credit Asymmetric?," Scottish Journal of Political Economy, Scottish Economic Society, vol. 63(2), pages 194-215, May.
    12. Di Giulio, Daniele, 2009. "Bank lending to the production sector: credit crunch or extra-credit?," MPRA Paper 26824, University Library of Munich, Germany.
    13. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2020. "Modelling Loans to Non-Financial Corporations within the Eurozone: A Long-Memory Approach," CESifo Working Paper Series 8674, CESifo.
    14. Mikael Juselius & Mathias Drehmann, 2015. "Leverage dynamics and the real burden of debt," BIS Working Papers 501, Bank for International Settlements.
    15. Kok, Christoffer & Rossi, Carlotta & Marqués-Ibáñez, David, 2009. "Modelling loans to non-financial corporations in the euro area," Working Paper Series 989, European Central Bank.
    16. Perevyshina, E. & Perevyshin, Y., 2015. "Evaluation of Credit Channel in Russia," Journal of the New Economic Association, New Economic Association, vol. 28(4), pages 96-110.

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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