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The determinants of household credit in Spain

Author

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  • Fernando Nieto

    (Banco de España)

Abstract

This paper estimates a single-equation model to analyse the main explanatory factors behind changes in Spanish household credit, considering that the behaviour of its determinants is exogenous. According to the evidence reported, household borrowing is determined in the long run by real spending, gross wealth and the repayment term for outstanding credits, which have a positive influence, and by the cost of loans and the unemployment rate, the effect of which is of a negative sign. Developments in the short run are influenced by changes in long-term interest rates and in employment. The evidence offered suggests that, in general terms, the financing received by households over the period analysed is in line with what may be inferred from its determinants; however, the high volume of debt incurred entails greater exposure of the sector to unexpected changes in its income, in its wealth or in the cost of borrowing, especially in a setting in which floating-rate loans are increasingly significant.

Suggested Citation

  • Fernando Nieto, 2007. "The determinants of household credit in Spain," Working Papers 0716, Banco de España.
    • Handle: RePEc:bde:wpaper:0716
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    File URL: http://www.bde.es/f/webbde/SES/Secciones/Publicaciones/PublicacionesSeriadas/DocumentosTrabajo/07/Fic/dt0716e.pdf
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Barbara Cavalletti & Corrado Lagazio & Elena Lagomarsino & Daniela Vandone, 2020. "Consumer Debt and Financial Fragility: Evidence from Italy," Journal of Consumer Policy, Springer, vol. 43(4), pages 747-765, December.
    2. Jose Felix Izquierdo, 2017. "Modelos para los flujos de nuevo credito en España," Working Papers 17/09, BBVA Bank, Economic Research Department.
    3. Lim, Sung Soo & Bone, Matthew, 2022. "Optimism, debt accumulation, and business growth," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 97(C).
    4. Stefan Behrendt, 2016. "Taking Stock - Credit Measures in Monetary Transmission," Jena Economics Research Papers 2016-002, Friedrich-Schiller-University Jena.
    5. Lobna ABID & Zouari Dorra & Zouari Ghorbel Sonia, 2012. "Household indebtedness in Tunisia," E3 Journal of Business Management and Economics., E3 Journals, vol. 3(10), pages 341-350.
    6. repec:etr:series:v:3:y:2012:i:11:p:341-350 is not listed on IDEAS
    7. Barbara CAVALLETTI & Corrado LAGAZIO & Daniela VANDONE, 2008. "Il credito al consumo in Italia: benessere economico o fragilita’ finanziaria?," Departmental Working Papers 2008-24, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    8. V. A. Pankova, 2022. "Modeling the Dynamics of Retail Lending in Russia: a Relationship with the Dynamics of Household Savings, Incomes, and Expenses," Studies on Russian Economic Development, Springer, vol. 33(6), pages 723-735, December.
    9. Meniago, Christelle & Mukuddem-Petersen, Janine & Petersen, Mark A. & Mongale, Itumeleng P., 2013. "What causes household debt to increase in South Africa?," Economic Modelling, Elsevier, vol. 33(C), pages 482-492.
    10. Jose Maria Alvarez & Cristina Deblas & Jose Felix Izquierdo & Ana Rubio & Jaime Zurita, 2017. "The impact of European banking consolidation on credit prices," Working Papers 17/08, BBVA Bank, Economic Research Department.
    11. Lukáš Fiala, 2021. "Modelling of mortgage debt´s determinants: the case of the Czech Republic," FFA Working Papers 4.002, Prague University of Economics and Business, revised 15 Jan 2022.
    12. Lukáš Fiala, 2022. "Modelling Household Mortgage Debt: the case of the Czech Republic," Prague Economic Papers, Prague University of Economics and Business, vol. 2022(6), pages 443-463.

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    More about this item

    Keywords

    credit; household; error correction;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers
    • R20 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - General

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