Financial Fragility, Macroeconomic Shocks and Banks' Loan Losses: Evidence from Europe

Abstract

This paper tests the hypothesis that the more fragile a banking system is, the more likely it is to experience problems when an unexpected shock hits. The empirical framework where this test is conducted is a reduced form model, where macroeconomic factors explain banks' loan losses. The dependent variable is the ratio of net loan losses to lending in a panel comprising the banking sectors of nine sample countries. An econometric model is estimated on pooled annual data mostly covering the period from the early 1980s to 2002. There are three separate explanatory terms. Two of these include a surprise change both in incomes and real interest rates. Both form a separate cross-product term with lagged aggregate indebtedness. The lagged dependent variable is the third explanatory term possibly capturing the feedback effect from loan losses back to the real economy. The underlying macroeconomic account that this paper puts forward is that loan losses seem basically to be generated by strong adverse aggregate shocks under high exposure of banks to such shocks. The model has been used in connection with stress testing in the Bank of Finland.

What matters more for South African households’ debt repayment difficulties?

“…Insofar as the plans of economic agents are based on the current state of affairs, the economic outlook and expectations, any deviations from this state of affairs will affect the agents' economic plans (Pesola, 2007). For this study, the timing of events is crucial, thus, the variables depicting adverse events are derived from households' circumstances observed or self-reported during the 2002 and 2005 waves of the survey with the assumption that those circumstances will affect the repayment performance in the subsequent period (2006).…”

The role of macroeconomic determinants in credit risk measurement in transition country: Estonian example

“…It should be done at the expense of new debt obligations. Pesola (2001Pesola ( , 2005Pesola ( , 2007 proposes that the main reason for the increase of aggregated credit risk is the growing aggregated indebtedness. Together with the deterioration of macroeconomic factors it is impossible for borrowers to repay their existing financial obligation.…”

“…As a result, additional financing should not be supported by improved cash flow generated by new investments. Blaschke et al (2001), Bonfim (2009), Jimenez and Saurina (2006), Pesola (2001Pesola ( , 2005Pesola ( , 2007, Shanazarian and Asberg-Sommar (2008), and other authors concentrated mainly on the analysis of the influence of macroeconomic variables on the credit risk growth. Thereby, a research of the combine influence of macroeconomic variables, banking sector variables and microeconomic level variables, together with the rapid growth of aggregated indebtedness on the level of non-performing loans, can be treated as insufficient, especially in the case of a small country with an open economy.…”

“…It should be noted that endogenous variables in both types of models are presented as a ratio of two different parameters and can be interpreted as default rate, probability of default, default frequency measure, expected default frequency, etc., for example, Bonfim (2009), Gasha and Morales (2004), Jimenez and Saurina (2006), Quagliariello (2008, 2009), Meyer and Yeager (2001), and Pesola (2001Pesola ( , 2007.…”

“…The variable mainly used as a dependent variable is the quotient of non-performing loans to the aggregated loan portfolio, for example, Bonfim (2009), Gasha and Morales (2004), Jimenez and Saurina (2006), Meyer and Yeager (2001), and Pesola (2001Pesola ( , 2007. Instead of non-performing loans, the changes in non-performing loans or loan losses can be used, for example, Quagliariello (2008, 2009).…”