2015
DOI: 10.1016/j.jfs.2015.03.005
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Why is credit-to-GDP a good measure for setting countercyclical capital buffers?

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Cited by 32 publications
(18 citation statements)
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“…Thus, because the incurred loss model, with its backward-looking provisioning requirements, does not adequately recognize the weakening of lending standards and the build-up of credit risks that occur 11 Interestingly enough, as documented by Fonseca, Gonzalez and Pereira da Silva (2010), before Basel III banks tended to have capital buffers well above those required by regulators in order to protect themselves from abrupt swings in business cycles and asset valuation that would otherwise lead to either immediate penalties or balance sheet adjustments. 12 See Behn et al (2013), Alessi and Detken (2014), Bank of England (2014), Buncic and Melecky (2014), Drehman and Tsatsaronis (2014) and Jokivuolle, Pesola and Viren (2015) for a discussion.…”
mentioning
confidence: 99%
“…Thus, because the incurred loss model, with its backward-looking provisioning requirements, does not adequately recognize the weakening of lending standards and the build-up of credit risks that occur 11 Interestingly enough, as documented by Fonseca, Gonzalez and Pereira da Silva (2010), before Basel III banks tended to have capital buffers well above those required by regulators in order to protect themselves from abrupt swings in business cycles and asset valuation that would otherwise lead to either immediate penalties or balance sheet adjustments. 12 See Behn et al (2013), Alessi and Detken (2014), Bank of England (2014), Buncic and Melecky (2014), Drehman and Tsatsaronis (2014) and Jokivuolle, Pesola and Viren (2015) for a discussion.…”
mentioning
confidence: 99%
“…Country‐specific variables are: (a) the margins between lending and deposit rates to NFCs; (b) the sovereign bond spreads; (c) the sector's concentration ratio (i.e. the Herfindahl ratio); (d) loans to deposits as a measure of liquidity foreseen in the newly established regulatory framework; and (e) loans to GDP reflecting lending relative to economic activity (Jokivuelle, Pesola, & Viren, ). We also incorporate euro‐area variables, which enable us to reveal the similarities or the differences of the responses across countries.…”
Section: Data and Methodological Frameworkmentioning
confidence: 99%
“…Sorge and Virolainen (2006) used Real GDP growth, real interest rate and lagged 'excess' indebtedness 7 to predict corporate default rates. These three macroeconomic factors have been shown to explain fluctuations in loan loss to total loans ratios surprisingly well in an aggregate country level (Jokivuolle et al, 2015), which is why we also include them together with inflation in matrix Z to control for the macroeconomic environment generating loan repayment problems. In addition, dummy variables for cooperative and savings banks, and both country and year fixed effects are included in every model specification to account for differences across bank owner/business types and to control for possible country and time heterogeneity in reporting practises.…”
Section: Empirical Methodology and Research Hypothesesmentioning
confidence: 99%