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Modelling loans to non-financial corporations in the euro area

Author

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  • Christoffer Kok S�rensen

    (European Central Bank)

  • David Marqu�s Ib��ez

    (European Central Bank)

  • Carlotta Rossi

    (Bank of Italy)

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 using 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 non-financial corporations.

Suggested Citation

  • Christoffer Kok S�rensen & David Marqu�s Ib��ez & Carlotta Rossi, 2012. "Modelling loans to non-financial corporations in the euro area," Temi di discussione (Economic working papers) 857, Bank of Italy, Economic Research and International Relations Area.
    • Handle: RePEc:bdi:wptemi:td_857_12
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    Cited by:

    1. 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.
    2. 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.
    3. Alan Ahearne & Guntram B. Wolff, 2012. "The debt challenge in Europe," Working Papers 686, Bruegel.
    4. 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.
    5. Grégory Levieuge, 2017. "Explaining and forecasting bank loans. Good times and crisis," Applied Economics, Taylor & Francis Journals, vol. 49(8), pages 823-843, February.
    6. 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.
    7. Di Giulio, Daniele, 2009. "Bank lending to the production sector: credit crunch or extra-credit?," MPRA Paper 26824, University Library of Munich, Germany.
    8. 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).
    9. 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.
    10. repec:pra:mprapa:40579 is not listed on IDEAS
    11. 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.
    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

    loans to non-financial corporations; credit;

    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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