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In: IMF Working Paper No. 19/285
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In: Oxford Bulletin of Economics and Statistics, Band 81, Heft 4, S. 817-848
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In: ECB Working Paper No. 2004
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Working paper
In: ECB Working Paper No. 1569
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In: ECB Working Paper No. 1570
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In: IMF Working Paper No. 2023/009
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Working paper
In: Bank of Italy Temi di Discussione (Working Paper) No. 1137
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In: ECB Working Paper No. 2081
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In: ECB Working Paper No. 2088
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We develop an integrated micro-macro model framework that is based on household survey data for a subset of the EU countries that the Household Finance and Consumption Survey (HFCS) contains. The model can be used for conducting scenario and sensitivity analyses with regard to the factors that drive households' income and expenses as well as their asset values and hence the structure of their balance sheet. Moreover, we use it for the purpose of assessing the efficacy of borrower-based macroprudential instruments, namely loan-to-value (LTV) ratio and debt service to income (DSTI) ratio caps. The simulation results from the model can be attached to bank balance sheets and their risk parameters to derive the impact of the policy measures on their capital position. The model framework also allows quantifying the macroeconomic feedback effects that would result from the policy-induced reduction of demand for mortgage loans. The model allows answering the question as to which of the two measures – LTV or DSTI caps – are more effective, both with respect to their ability to reduce household loss rates as well as their impact on the economy.
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We develop a Mixed-Cross-Section Global Vector Autoregressive (MCS-GVAR) model for the 28 EU economies and a sample of individual banking groups to study the propagation of bank capital shocks to the economy. We conduct various simulations with the model to assess how capital ratio shocks influence bank credit supply and aggregate demand. We distinguish between contractionary and expansionary deleveraging scenarios and confirm the intuitive result that only when banks choose to achieve higher capital ratios by shrinking their balance sheets would economic activity be at risk to contract. The model can be used to establish ranges of impact estimates for capital-related macroprudential policy measures, including counter-cyclical capital buffers, systemic risk buffers, G-SIB buffers, etc., also with a view to assessing the cross-country spillover effects of such policy measures. We highlight the importance for macroprudential policy makers to give clear guidance to banks as to how certain macroprudential policy measures should be implemented – depending on what measure is considered, during which phase in the business cycle, and for what particular purpose.
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In: ESRB: Working Paper Series No. 2016/17
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Working paper