Relation between credit losses and macroeconomic factors in European banks
1University of Oulu, Oulu Business School, Department of Finance, Finance
|Online Access:||PDF Full Text (PDF, 1.5 MB)|
|Persistent link:|| http://urn.fi/URN:NBN:fi:oulu-201906192577
Oulu : J. Komulainen,
|Publish Date:|| 2019-06-19
|Thesis type:||Master's thesis
Credit loss modelling under IFRS standards has changed towards a more forward-looking approach. The new expected credit loss model allows using all relevant information that is available without undue cost, also forward-looking information. Macroeconomic factors provide this kind of easily available information and thus they can be utilized in the credit loss modelling. Hence, I apply a large set of macroeconomic variables in order to find those ones that help to estimate future credit losses. Bank-specific features are also likely to affect credit loss changes, so they are also considered in this thesis.
On a sample of 24 European countries and 202 banks, I examine the explanatory power of changes in macroeconomic variables on consequent credit losses. The empirical analysis is based on several pooled, fixed effects and logistic regression specifications. I also use stepwise regressions based on Akaike information criteria to select a set of relevant variables in the multivariate regression specification.
The univariate regression results suggest that important macroeconomic variables explaining the changes in credit losses of the following year are the house price index, gross fixed capital formation, the nominal long-term interest rate and the term spread. Based on the multivariate regression results, inflation, unemployment and bankruptcies are the most important macroeconomic variables and bank size is the most important bank-specific variable. Small banks typically suffer from greater credit loss increases than medium and large banks, but medium and large banks are more sensitive to economic fluctuations. In addition, commercial banks are more sensitive to the changes in the house price index and unemployment than savings banks whereas savings banks are more sensitive to the changes in the number of bankruptcies.
The results documented have valuable implication for the practical implementation of the credit loss models and estimating future credit losses. The findings can be especially exploited in European banks that follow IFRS standards and apply the expected credit loss model.
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