Abstract
Given that the case of Greece may be viewed as an ideal laboratory to study both recession-induced effects and moral hazard aspects, the study focuses on jointly exploring the effects upon the formation of non-performing loans arising from either the inability or the “unwillingness to pay” behavior of obligors. It employs Vector Autoregression (VAR) and Vector Error Correction (VEC) techniques using aggregate macro data along with features of the legal and regulatory framework as the temporary suspension of foreclosures to capture the aforementioned determinants. The results suggest evidence that the unprecedented NPL formation was determined by the severe increase in unemployment, the recessionary shocks reflected in the time path of GDP, as well as some micro-behavioral impact related to strategic and tactical default. Also, business NPL is the most responsive to the phase of the cycle.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Akaike, H., (1973): “Information theory and an extension of the maximum likelihood principle”, In B. N. Petrov & F. Caski (Eds.), Proceedings of the Second International Symposium on Information Theory, p. 267–281.
Akaike, H., (1974): “A new look at the statistical model identification”, IEEE Transactions on Automatic Control, 19, p. 716–723.
Andritzky, J.R., (2014): “Resolving Residential Mortgage Distress: Time to modify?”, IMF Working Paper 14/226.
Babihuga, R., (2007): “Macroeconomic and Financial Soundness Indicators: An Empirical Investigation”, IMF Working Paper, p. 1–30.
Bank of Greece (2015): “Report on Monetary Policy 2014–2015”.
Bhutta, N., Dokko, J. and, H. Shan, (2010): “The Depth of Negative Equity and Mortgage Default Decisions”, Finance and Economics Discussion Series, Federal Reserve Board, Washington, D.C.
Bofondi, M., and, T. Ropele, (2011): “Macroeconomic determinants of bad loans: evidence from Italian banks”, Questioni di Economia e Finanza, Bank of Italy, No. 89.
Castro, V., (2013): “Macroeconomic determinants of the credit risk in the banking system: The case of the GIPSI”, Economic Modeling, 31, p. 672–83.
Dickey, D., and, W. Fuller, (1981): “Likelihood ratio statistics for autoregressive time series with a unit root”, Econometrica, 60, p. 423–33.
Espinoza, R., and, A. Prasad, (2010): “Nonperforming Loans in the GCC Banking Systems and their Macroeconomic Effects”, IMF Working Paper 10/224.
European Banking Authority (2014): “EBA FINAL draft Implementing Technical Standards on Supervisory reporting on forbearance and non-performing exposures under article 99(4) of Regulation (EU) No 575/2013”.
Fofack, H., (2005): “Nonperforming Loans in Sub-Saharan Africa: Causal Analysis and Macroeconomic Implications”, World Bank Policy Research Working Paper No. 3769.
Foote, C., Gerardi, K., and, P. S. Willen, (2008): “Negative equity and foreclosure: theory and evidence”, Federal Reserve Bank of Boston, Public Policy Discussion Papers, 3, p. 1–36.
Ghent, A.C., and, M. Kudlyak, (2010): “Recourse and Residential Mortgage Default: Theory and Evidence from the U.S. States”, Federal Reserve Bank of Richmond, Working Paper Series, 09-10R.
Goel, R. K. and, I. Hasan, (2011): “Economy-wide corruption and bad loans in banking: international evidence”, Applied Financial Economics, 21, p. 455–61.
Guiso, L., Sapienza, P., and, L. Zingales, (2013): “The determinants of attitudes towards strategic default on mortgages”, The Journal of Finance, 68(4), p. 1473–1515.
Immergluck, D. and, G. Smith, (2006b): “The Impact of Single-family Mortgage Foreclosures on Neighborhood Crime”, Housing Studies 21 (6), p. 851–866.
Immergluck, D., and, G. Smith, (2006a): “The External Cost of Foreclosure: The Impact of Single-Family Mortgage Foreclosures on Property Values”, Housing Policy Debate 17 (1), p. 57–79.
Jarque, C. M., and, Bera, A. K., (1987): “A test for normality of observations and regression residuals”, International Statistical Review, 55, p. 163–172.
Jimenez, G., and, J. Saurina, (2005): “Credit cycles, credit-risk, and prudential regulation”, Banco de España.
Johansen, S., (1991): “Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models”, Econometrica 59(6), p. 1551–1580.
Johansen, S., (1995): “Likelihood-Based Inference in Cointegrated Vector Autoregressive Models”, New York: Oxford University Press.
Kauko, K., (2014): “Do Bailouts Cause Moral Hazards or Franchise Value in Banking?”, Kyklos, 67, p. 82–92.
Kelejian, H. H., (1982): “An Extension of a Standard Test for Heteroskedasticity to a Systems Framework,” Journal of Econometrics, 20, p. 325–333.
Klein, N., (2013): “Non-Performing Loans in CESEE: Determinants and Impact on Macroeconomic Performance”, IMF Working Paper, 13/72.
Louzis, D., Vouldis, A., and, V. Metaxas, (2012): “Macroeconomic and bank-specific determinants of NPLs in Greece: A comparative study of mortgage, business and consumer loan portfolios”, Journal of Banking and Finance 36, p. 1012–1027.
Monokroussos, P., Thomakos, D. D., and, T. A. Alexopoulos, (2016): “High NPLs Ratio in Greece: Outcome of an unprecedented recession or the lending practices of domestic credit institutions in the pre-crisis era?”, Eurobank Greece Macro Monitor.
Nkusu, M., (2011): “Non-performing Loans and Macro financial Vulnerabilities in Advanced Economies”, IMF Working Paper 11/161.
Pesaran, H. H., and, Y. Shin, (1998): “Generalized Impulse Response Analysis in linear multivariate models”, Economics Letters, 58(1), p. 17–29.
Rajan, R., and, S.C. Dahl, (2003): “Non-performing Loans and Terms of Credit of Public Sector Banks in India: An Empirical Assessment”, Reserve Bank of India, 24(3).
Rissanen, J., (1978): “Modeling by shortest data description”, Automatica, 14, p. 465–471.
Salas, V., and, J. Saurina, (2002): “Credit Risk in Two Institutional Regimes: Spanish Commercial and Savings Banks”, Journal of Financial Services Research 22(3), p. 203–224.
Schwarz, G., (1978): “Estimating the dimension of a model”, Annals of Statistics, 6, p. 461–464.
Seiler, M.J., (2015): “The role of information uncertainty in the decision to strategically default”, Journal of Housing Economics, 27(C), p. 49–59.
White, B. T., (2010): “Underwater and not walking away: Shame, fear, and the social management of the housing crisis”, The University of Arizona, Discussion paper No. 09-35.
Zhu, S., and, R. K. Pace, (2015): “The influence of foreclosures on Borrowers’ default behavior”, Journal of Money, Credit and Banking, 45(6), p. 1205–1222.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 The Hellenic Bank Association
About this chapter
Cite this chapter
Kapopoulos, P., Argyropoulos, E., Zekente, KM. (2017). Financial Distress, Moral Hazard Aspects and NPL Formation Under a Long-Lasting Recession: Empirical Evidence from the Greek Crisis. In: Monokroussos, P., Gortsos, C. (eds) Non-Performing Loans and Resolving Private Sector Insolvency. Palgrave Macmillan Studies in Banking and Financial Institutions. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-50313-4_11
Download citation
DOI: https://doi.org/10.1007/978-3-319-50313-4_11
Published:
Publisher Name: Palgrave Macmillan, Cham
Print ISBN: 978-3-319-50312-7
Online ISBN: 978-3-319-50313-4
eBook Packages: Economics and FinanceEconomics and Finance (R0)