Empirical Economics

, Volume 54, Issue 3, pp 1187–1214 | Cite as

Leading indicators of non-performing loans in Greece: the information content of macro-, micro- and bank-specific variables

Article

Abstract

We examine the information content of a unique set of macroeconomic, bank-specific, market and credit registry variables as regards their ability to forecast non-performing loans using a panel data set of nine Greek banks. We distinguish between business, consumer and mortgage loans and investigate their differences with respect to their optimal predictors. The quasi-AIM approach (Carson et al. in Int J Forecast 27:923–941, 2010) is utilized in order to take into account heterogeneity across banks and minimize estimation uncertainty. In addition, we calculate a number of forecasting measures in order to take into account the policy makers’ preferences. We find that market variables, specifically the supermarket sales, confidence indices for the services and construction sector and the business sentiment index represent good forecasting variables for most categories of NPLs. In addition, industrial production is the optimal predictor for consumer NPLs and imports for business NPLs. Finally, bank-specific variables represent top-performing leading indicators for business NPLs. Our results have significant implications for stress-testing credit risk in a top-down manner and for supervisory and macro-prudential policy design.

Keywords

Credit risk Non-performing loans forecasting Disaggregation Panel data Stress testing 

JEL Classification

C53 G01 G21 

Notes

Acknowledgements

The authors would like to thank an anonymous reviewer and the editor for constructive criticism which improved significantly the quality of the paper. The usual disclaimer applies. The views expressed in this paper are those of the authors and do not necessarily reflect those of the Bank of Greece or the European Central Bank.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.Directorate-General StatisticsEuropean Central BankFrankfurt am MainGermany
  2. 2.Economic Analysis and Research DivisionBank of GreeceAthensGreece

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