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COUNTER-CYCLICAL PROVISIONS, ANAGERIAL DISCRETION AND LOAN GROWTH: THE CASE OF SPAIN by S. Carbó-Valverde and F. Rodríguez-Fernández. João A.C. Santos Federal Reserve Bank of New York
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COUNTER-CYCLICAL PROVISIONS, ANAGERIAL DISCRETION AND LOAN GROWTH: THE CASE OF SPAINbyS. Carbó-Valverde and F. Rodríguez-Fernández
João A.C. Santos
Federal Reserve Bank of New York
The views expressed here are those of the authors and not necessarily those of the Federal Reserve Bank of New York or the Federal Reserve System.
Procyclicality of loan-loss provisions: Following the implementation of statistical provisions, the expected negative relationship between loan-loss provisions and GDP growth should decrease over time.
Managerial discretion: Since loan-loss provisions depend upon the “true” credit risk of loans and not upon net operating income, the significance of any statistical relationship between loan-loss provisions and net operating income should diminish over time.
Excessive loan growth: In order for counter-cyclical provisions to be fully effective, they should provide incentives for banks to grant loans more carefully. So, lagged loan growth rates should be unable to explain current loan default rates.
LLP = a*GDPG +b*NOI + CONTROLS
LLP is the ratio of loan-loss provisions to total assets
GDPG is the GDP growth
NOI is net operating income
Hyp 1: If the coefficient a decreases following the implementation of the counter-cyclical provisions, this will contribute to reducing procyclicality, as suggested in hypothesis 1.
Hyp 2: Consistent with hypothesis 2, we would expect profit smoothing behavior if the coefficient of NOI is positive and significant.
NPLt = a1*LGt-1 + a2*LGt-2 + …. a1*LGt-12 + CONTROLS
NPL is the ratio of non performing loans to total loans
LG is the quarterly growth rate of loans
Hypo 3: If the high-order lags of the NPL variable are statistically significant and the low-order lags are not, this would suggest that bank managers relax credit quality as the time from the last downturn increases.
If the high-order lags of the NPL variable are statistically significant and the low-order lags are not, this would suggest that bank managers relax credit quality as the time from the last downturn increases.