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Modelling loans to non-financial corporations in the euro area

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  • Kok, Christoffer
  • Rossi, Carlotta
  • Marqués-Ibáñez, David

Abstract

We model the determinants of loans to non-financial corporations in the euro area. Using the Johansen (1992) methodology, we identify three cointegrating relationships. These relationships are interpreted as the long-run loan demand, investment and loan supply equations. The short-run dynamics of loan demand for the euro area are subsequently modelled by means of a Vector Error Correction Model (VECM). We perform a number of specification tests, which suggest that developments in loans to non-financial corporations in the euro area can be reasonably explained by the model. We then use the estimated model to analyse the impact of permanent and temporary shocks to the policy rate on bank lending to nonfinancial corporations. JEL Classification: C32, C51

Suggested Citation

  • 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.
    • Handle: RePEc:ecb:ecbwps:2009989
    Note: 508948
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    Cited by:

    1. Alan Ahearne & Guntram B. Wolff, 2012. "The debt challenge in Europe," Working Papers 686, Bruegel.
    2. Grégory Levieuge, 2017. "Explaining and forecasting bank loans. Good times and crisis," Applied Economics, Taylor & Francis Journals, vol. 49(8), pages 823-843, February.
    3. Sophocles N. Brissimis & Eugenie N. Garganas & Stephen G. Hall, 2014. "Consumer credit in an era of financial liberalization: an overreaction to repressed demand?," Applied Economics, Taylor & Francis Journals, vol. 46(2), pages 139-152, January.
    4. Deryugina, Elena & Kovalenko, Olga & Pantina, Irina & Ponomarenko, Alexey, 2015. "Disentangling loan demand and supply shocks in Russia," BOFIT Discussion Papers 8/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
    5. Ruscher Eric & Wolff Guntram B., 2013. "Corporate Balance Sheet Adjustment: Stylized Facts, Causes and Consequences," Review of Economics, De Gruyter, vol. 64(2), pages 117-138, August.
    6. repec:pra:mprapa:40579 is not listed on IDEAS
    7. de Haan, Leo & van den End, Jan Willem, 2013. "Banks’ responses to funding liquidity shocks: Lending adjustment, liquidity hoarding and fire sales," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 152-174.
    8. Miroslav Plasil & Stepan Radkovsky & Pavel Rezabek, 2013. "Modelling bank loans to non-financial corporations," Occasional Publications - Chapters in Edited Volumes, in: CNB Financial Stability Report 2012/2013, chapter 0, pages 128-136, Czech National Bank.
    9. Bolt, Wilko & de Haan, Leo & Hoeberichts, Marco & van Oordt, Maarten R.C. & Swank, Job, 2012. "Bank profitability during recessions," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2552-2564.
    10. Di Giulio, Daniele, 2009. "Bank lending to the production sector: credit crunch or extra-credit?," MPRA Paper 26824, University Library of Munich, Germany.
    11. Krainer, Robert E., 2014. "Monetary policy and bank lending in the Euro area: Is there a stock market channel or an interest rate channel?," Journal of International Money and Finance, Elsevier, vol. 49(PB), pages 283-298.
    12. G.Levieuge, 2015. "the coherence and the predictive content of the French Bank Lending Survey’s indicators (in French)," Working papers 567, Banque de France.

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    More about this item

    Keywords

    bank credit; cointegration; error-correction model; euro area; non-financial corporations;
    All these keywords.

    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

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