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Modelling bank lending in the euro area: A non-linear approach

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  • Leonardo Gambacorta

    () (Banca d'Italia)

  • Carlotta Rossi

    () (Banca d'Italia)

Abstract

This paper investigates possible non-linearities in the response of bank lending to monetary policy shocks in the euro area. The credit market is modelled over the period 1985-2005 by means of an Asymmetric Vector Error Correction Model (AVECM) involving four endogenous variables (loans to the private sector, real 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 co-integrating 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 paper finds that the effect on credit, GDP, and prices of a monetary policy tightening is larger than the effect of a monetary policy easing. This result supports the existence of an asymmetric broad credit channel in the euro area.

Suggested Citation

  • Leonardo Gambacorta & Carlotta Rossi, 2007. "Modelling bank lending in the euro area: A non-linear approach," Temi di discussione (Economic working papers) 650, Bank of Italy, Economic Research and International Relations Area.
  • Handle: RePEc:bdi:wptemi:td_650_07
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    Cited by:

    1. 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.
    2. Borio, Claudio & Gambacorta, Leonardo, 2017. "Monetary policy and bank lending in a low interest rate environment: Diminishing effectiveness?," Journal of Macroeconomics, Elsevier, vol. 54(PB), pages 217-231.
    3. Dobromił Serwa, 2012. "Banking crises and nonlinear linkages between credit and output," Applied Economics, Taylor & Francis Journals, vol. 44(8), pages 1025-1040, March.
    4. 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.
    5. Juselius, Mikael & Drehmann, Mathias, 2016. "Leverage dynamics and the burden of debt," Research Discussion Papers 3/2016, Bank of Finland.
    6. Isakin, Maksim & Serletis, Apostolos, 2019. "Banking technology in a Markov switching economy," Journal of Macroeconomics, Elsevier, vol. 59(C), pages 154-168.
    7. 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.
    8. Saten Kumar, 2016. "Is the US Consumer Credit Asymmetric?," Scottish Journal of Political Economy, Scottish Economic Society, vol. 63(2), pages 194-215, May.
    9. Di Giulio, Daniele, 2009. "Bank lending to the production sector: credit crunch or extra-credit?," MPRA Paper 26824, University Library of Munich, Germany.
    10. 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.
    11. Mikael Juselius & Mathias Drehmann, 2015. "Leverage dynamics and the real burden of debt," BIS Working Papers 501, Bank for International Settlements.
    12. 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.
    13. 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.

    More about this item

    Keywords

    monetary policy transmission; credit market; credit view; asymmetries;

    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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