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Assessing the impact of macroprudential measures: The case of the LTV limit in Lithuania

Author

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  • Tomas Reichenbachas

    (Bank of Lithuania)

Abstract

In this paper, we adopt a dual micro-and-macro simulation strategy to assess the impact of introducing (or changing) the LTV limit. Due to the nature of borrower-based macroprudential measures, to assess this impact we need to use borrower-level micro data. Tightening (or loosening) the LTV limit increases the share of borrowers constrained by the policy measure in question; thus, the overall impact depends on initial market conditions. We find that the introduction of an LTV limit of 85 % in 2011 had a modest short-term impact on economic activity because the new regulatory limit was non-binding for most borrowers at the time. We estimate that if the LTV limit would not have been introduced, the household loan portfolio would have grown on average 1.5 percentage points faster per year (over 2012-2014). This would have led to a 0.5 percentage point higher housing price growth and a 0.2 percentage point higher real GDP growth. When the macroprudential LTV limit is binding for a significant portion of borrowers, lowering the LTV limit at current market conditions has a much more pronounced effect. We show that if the LTV limit had been implemented at the end of 2004, it would have substantially helped in tempering the credit and housing boom, albeit at the cost of lowering economic growth.

Suggested Citation

  • Tomas Reichenbachas, 2020. "Assessing the impact of macroprudential measures: The case of the LTV limit in Lithuania," Bank of Lithuania Working Paper Series 80, Bank of Lithuania.
  • Handle: RePEc:lie:wpaper:80
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    References listed on IDEAS

    as
    1. Akinci, Ozge & Olmstead-Rumsey, Jane, 2018. "How effective are macroprudential policies? An empirical investigation," Journal of Financial Intermediation, Elsevier, vol. 33(C), pages 33-57.
    2. Cussen, Mary & O'Brien, Martin & Onorante, Luca & O'Reilly, Gerard, 2015. "Assessing the impact of macroprudential measures," Economic Letters 03/EL/15, Central Bank of Ireland.
    3. Zohair Alam & Mr. Adrian Alter & Jesse Eiseman & Mr. Gaston Gelos & Mr. Heedon Kang & Mr. Machiko Narita & Erlend Nier & Naixi Wang, 2019. "Digging Deeper--Evidence on the Effects of Macroprudential Policies from a New Database," IMF Working Papers 2019/066, International Monetary Fund.
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    Cited by:

    1. Barasinska, Nataliya & Ludwig, Johannes & Vogel, Edgar, 2021. "The impact of borrower-based instruments on household vulnerability in Germany," Discussion Papers 20/2021, Deutsche Bundesbank.

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    More about this item

    Keywords

    Financial stability; Macroprudential policy; Borrower-based macroprudential policy instruments; LTV limit;
    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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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