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Analysis of the Impact of Borrower-Based Measures

Author

Listed:
  • Martin Cesnak

    (National Bank of Slovakia)

  • Jan Klacso

    (National Bank of Slovakia)

  • Roman Vasil

    (National Bank of Slovakia)

Abstract

The National Bank of Slovakia has been actively implementing borrower-based measures since 2014. In this paper we provide a cost-benefit analysis of these measures. DSTI measures affected mainly the riskiest borrowers with at most secondary education and lower income. Exemptions from DTI limits are provided mainly to borrowers with a higher volume of loans and higher education. LTV limits affected mainly younger borrowers up to 35 years old. The impact of respective measures was affected by front-loading, by the gradual tightening of the limits and by other legislative changes. The highest impact is estimated in 2019, when the volume of newly granted loans was lowered by 17% due to the measures. The estimated impact on residential real estate prices is relatively mild. The current coronavirus pandemic is the first period when systemic risks could have materialized after the implementation of the measures. Due to the possible loan payment deferral the number of loans defaulted has remained relatively low, therefore LTV measures have not been able to limit credit losses. On the other hand, DSTI measures have helped to mitigate credit risk. Households affected the most by the pandemic were those with an already high debt burden even before the outbreak of the crisis. These households have used loan payment deferral to a larger extent.

Suggested Citation

  • Martin Cesnak & Jan Klacso & Roman Vasil, 2021. "Analysis of the Impact of Borrower-Based Measures," Working and Discussion Papers OP 3/2021, Research Department, National Bank of Slovakia.
    • Handle: RePEc:svk:wpaper:1082
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    References listed on IDEAS

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    1. Martin Cesnak & Jan Klacso, 2021. "Assessing real estate prices in Slovakia - a structural approach," Working and Discussion Papers WP 3/2021, Research Department, National Bank of Slovakia.
    2. Kelly, Robert & McCann, Fergal & O’Toole, Conor, 2018. "Credit conditions, macroprudential policy and house prices," Journal of Housing Economics, Elsevier, vol. 41(C), pages 153-167.
    3. Federico Belotti & Silvio Daidone & Giuseppe Ilardi & Vincenzo Atella, 2013. "Stochastic frontier analysis using Stata," Stata Journal, StataCorp LP, vol. 13(4), pages 718-758, December.
    4. Andrej Cupák & Ján Klacso & Martin Suster, 2020. "Surveying the Impact of the Covid-19 Recession on the Financial Situation of Indebted Households," Working and Discussion Papers WP 6/2020, Research Department, National Bank of Slovakia.
    5. Kenneth Kuttner & Ilhyock Shim, 2012. "Taming the Real Estate Beast: The Effects of Monetary and Macroprudential Policies on Housing Prices and Credit," RBA Annual Conference Volume (Discontinued), in: Alexandra Heath & Frank Packer & Callan Windsor (ed.),Property Markets and Financial Stability, Reserve Bank of Australia.
    6. Mr. Malhar S Nabar & Mr. Ashvin Ahuja, 2011. "Safeguarding Banks and Containing Property Booms: Cross-Country Evidenceon Macroprudential Policies and Lessons From Hong Kong SAR," IMF Working Papers 2011/284, International Monetary Fund.
    7. Ms. Deniz O Igan & Mr. Heedon Kang, 2011. "Do Loan-To-Value and Debt-To-Income Limits Work? Evidence From Korea," IMF Working Papers 2011/297, International Monetary Fund.
    8. Jérôme Vandenbussche & Ursula Vogel & Enrica Detragiache, 2015. "Macroprudential Policies and Housing Prices: A New Database and Empirical Evidence for Central, Eastern, and Southeastern Europe," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(S1), pages 343-377, March.
    9. Elliot Anenberg & Aurel Hizmo & Edward Kung & Raven Molloy, 2019. "Measuring mortgage credit availability: A frontier estimation approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(6), pages 865-882, September.
    10. Gross, Marco & Población, Javier, 2017. "Assessing the efficacy of borrower-based macroprudential policy using an integrated micro-macro model for European households," Economic Modelling, Elsevier, vol. 61(C), pages 510-528.
    11. Mark Cassidy & Niamh Hallissey, 2016. "The Introduction of Macroprudential Measures for the Irish Mortgage Market," The Economic and Social Review, Economic and Social Studies, vol. 47(2), pages 271-297.
    12. Pavol Jurca & Ján Klacso & Eugen Tereanu & Marco Forletta & Mr. Marco Gross, 2020. "The Effectiveness of Borrower-Based Macroprudential Measures: A Quantitative Analysis for Slovakia," IMF Working Papers 2020/134, International Monetary Fund.
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    Cited by:

    1. Martin Cesnak, 2023. "Decomposition of retail loan growth," Working and Discussion Papers OP 1/2023, Research Department, National Bank of Slovakia.
    2. Martin Cesnak & Jan Klacso & Patrik Kupkovic & Andrej Moravcik & Stefan Rychtarik & Roman Vrbovsky, 2024. "Assessing Residential Real Estate prices in Slovakia: Possible Approaches and Indices," Working and Discussion Papers OP 1/2024, Research Department, National Bank of Slovakia.
    3. Hodula, Martin & Melecký, Martin & Pfeifer, Lukáš & Szabo, Milan, 2023. "Cooling the mortgage loan market: The effect of borrower-based limits on new mortgage lending," Journal of International Money and Finance, Elsevier, vol. 132(C).

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    More about this item

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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