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Macroeconomic Determinants of NPLs Using an Extended Sample and Dominance Analysis

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Advances in Longitudinal Data Methods in Applied Economic Research (ICOAE 2020)

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Abstract

This chapter aims at revisiting the empirical literature on the determinants of Non-Performing Loans (NPLs) using an extended dataset of selected OECD countries (augmented by EU countries not yet members of the OECD) and the latest data available for “traditional” macroeconomic variables with the addition of variables only recently proposed and not yet adequately tested. We endeavor to measure the effect of these determinants, but even more so for specific variables for which no clear consensus exists in the preexisting literature as for the direction of their impact. Our panel data specifications performed quite well, allowing us to address two additional research questions; whether the recent financial/economic crisis has changed the magnitude of the impact of the determinants of NPLs while also quantifying the relative importance of each determinant using the analytical tool of Dominance Analysis. The macroeconomic approach we opt for regarding the determinants of NPLs explains a more than satisfactory part of the variability of the dependent variable, while the crisis seems, as expected, to have affected the magnitude of the impact for most of the regressors. Last but not least, the unemployment rate and the degree of financial intermediation are topping the list of most important determinants followed by lending rates.

The views expressed in this paper do not necessarily reflect those of the Hellenic Ministry of Finance.

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Notes

  1. 1.

    Throughout the paper, we will use this term as used in the source of our data (Worldbank) although the term Non-Performing Exposures is also widely used (if not more, e.g., for EU countries).

  2. 2.

    See Baltagi (2001) for a relevant analysis.

  3. 3.

    We should note here that because of computational complexity we chose only 5 out of 7 regressors to be included in the Dominance Analysis based on the estimated explanatory power of each one of them in previous specifications.

  4. 4.

    One could make a point in favor of tackling Structural Unemployment over the medium to long-run instead of trying to mitigate the effect of the cycle using countercyclical policies in the short run.

References

  • Anastasiou, D., Louri, H., & Tsionas, M. (2016, August). Determinants of non-performing loans: Evidence from Euro-area countries. Finance Research Letters, 18, 116–119

    Google Scholar 

  • Azen, R., & Budescu, D. V. (2003). Comparing predictors in multivariate regression models: An extension of dominance analysis. Journal of Educational and Behavioral Statistics, 31, 157–180.

    Article  Google Scholar 

  • Baltagi, B. H. (2001). Econometric analysis of panel data (2nd ed.). Chichester: Wiley.

    Google Scholar 

  • Beck, R., Jakubik, P., & Piloiu, A. (2013). Non-performing loans: What matters in addition to the economic cycle? ECB Working Paper Series, 1515.

    Google Scholar 

  • Berg, S., Forsund, F., & Jansen, E. (1992). Malmquist indices of productivity growth during the deregulation of Norwegian banking, 1980-89. Scandinavian Journal of Economics, 94, 211–228.

    Article  Google Scholar 

  • Berger, A. N., & De Young, R. (1997). Problem loans and cost efficiency in commercial banks. Journal of Banking & Finance, 21, 849–870.

    Article  Google Scholar 

  • Bernanke, B., Gertler, M., & Gilchrist, S. (1998). The financial accelerator in a quantitative business cycle framework. NBER Working Paper No. 6455.

    Google Scholar 

  • Bishop, J. A., Chakraborti, S., & Thistle, P. D. (1988). Large sample tests for absolute Lorenz dominance. Economics Letters, 26, 291–294.

    Article  Google Scholar 

  • Boudriga, A. N., Taktak, B., & Jellouli, S. (2009). Bank specific, business and institutional environment determinants of nonperforming loans: Evidence from MENA countries. In ERF 16th Annual Conference. Cairo.

    Google Scholar 

  • Castro, V. (2013). Macroeconomic determinants of the credit risk in the banking system: The case of the GIPSI. Economic Modelling, 31, 672–683.

    Article  Google Scholar 

  • Chen, T., & Fan, C. K. (2019). Non-performing loans and housing prices in Taiwan. Journal of Applied Finance & Banking, 9(6), 57–66.

    Google Scholar 

  • Čihák, M. (2007). Introduction to applied stress testing. IMF Working Paper 07/59.

    Google Scholar 

  • Espinoza, R., & Prasad, A. (2010). Non-performing loans in their GCC banking system and their macroeconomic effects. IMF Working Paper, Middle East and Central Asia Department, no.224.

    Google Scholar 

  • Fernandez de Lis, S., Martinez Pagιs, J., & Saurina, J. (2000). Credit growth, problem loans and credit risk provisioning in Spain, Banco de Espana. Working Paper 18.

    Google Scholar 

  • Fofack, H. (2005). Non-performing loans in sub-Saharan Africa: Causal analysis and macroeconomic implications. World Bank Policy Research Working Paper 3769.

    Google Scholar 

  • Glen, J., & Mondragón-Vélez, C. (2011). Business cycle effects on commercial bank loan portfolio performance in developing economies. International Finance Corporation, World Bank Group.

    Google Scholar 

  • Hughes, J. P., & Mester, L. J. (1993). A quality and risk-adjusted cost function for banks: Evidence on the ‘too-big-to-fail’ doctrine. The Journal of Productivity Analysis, 4, 293–315.

    Article  Google Scholar 

  • Jakubík, P., & Sutton, G. (2011, December). Thoughts on the proper design of macro stress tests. In BIS Papers chapters, macroprudential regulation and policy, Vol. 60, Bank for International Settlements (pp. 111–119).

    Google Scholar 

  • Jimenez, G., & Saurina, J. (2005, January). Credit cycles, credit risk, and prudential regulation. Banco de Espaρa.

    Google Scholar 

  • King, R. G., & Plosser, C. I. (1984). Money, credit, and prices in a real business cycle. American Economic Review, 74, 363–380.

    Google Scholar 

  • Kiyotaki, N., & Moore, J. (1997). Credit cycles. Journal of Political Economy, 105(2), 211–248. University of Chicago Press.

    Article  Google Scholar 

  • Klein, N. (2013). Non-performing loans in CESEE: Determinants and impact on macroeconomic performance. IMF Working Paper, WP/13/72.

    Google Scholar 

  • Lawrence, E. C. (1995). Consumer default and the life cycle model. Journal of Money Credit and Banking, 27, 939–954.

    Article  Google Scholar 

  • Louzis, D., Vouldis, A., & Metaxas, V. (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, 1012–1027.

    Article  Google Scholar 

  • Manz, F. (2019). Determinants of non-performing loans: What do we know? A systematic review and avenues for future research. Management Review Quarterly, 69, 351–389.

    Article  Google Scholar 

  • Nikolopoulos, K. I., & Tsalas, A. I. (2017). Non-performing loans: A review of the literature and the international experience. In P. Monokroussos & C. Gortsos (Eds.), Non-performing loans and resolving private sector insolvency: Experiences from the EU periphery and the case of Greece (pp. 47–68). Cham: Springer.

    Chapter  Google Scholar 

  • Nkusu, M. (2011). Nonperforming loans and macrofinancial vulnerabilities in advanced economies. IMF Working Paper 11/161.

    Google Scholar 

  • Pesaran, H., Schuermann, T., Treutler, M., & Weiner, S. (2006). Macroeconomic dynamics and credit risk: A global perspective. Journal of Money, Credit and Banking, 38(5), 1211–1261.

    Article  Google Scholar 

  • Quagliariello, M. (2007). Banks’ riskiness over the business cycle: A panel analysis on Italian intermediaries. Applied Financial Economics, 17, 119–138.

    Article  Google Scholar 

  • Rajan, R. (1994). Why bank credit policies fluctuate: A theory and some evidence. The Quarterly Journal of Economics, 109, 399–441.

    Article  Google Scholar 

  • Reinhart, C. M., & Rogoff, K. (2010). From financial crash to debt crisis. NBER Working Paper Series, No. 15795.

    Google Scholar 

  • Rinaldi, L., & Sanchis-Arellano, A. (2006). Household debt sustainability: What explains household non-performing loans? An empirical analysis. ECB Working Paper.

    Google Scholar 

  • Salas, V., & Saurina, J. (2002). Credit risk in two institutional regimes: Spanish commercial and savings banks. Journal of Financial Services Research, 22(3), 203–224.

    Article  Google Scholar 

  • Sfakianakis, G., Georgopoulos, D., & Papadogonas, T. (2016). A growth-enhancing policy mix against the crisis: Empirically evaluating potential ingredients. Empirical Economics Letters, 15(11), 1111–1117.

    Google Scholar 

  • Stern, G., & Feldman, R. (2004). Too big to fail: The hazards of Bank bailouts. Washington, DC: The Brookings Institution.

    Google Scholar 

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Author information

Authors and Affiliations

  1. National and Kapodistrian University of Athens and Hellenic Open University, Athens, Greece

    George Sfakianakis

  2. Hellenic Open University, Athens, Greece

    George M. Agiomirgianakis

  3. Hellenic Ministry of Finance and Hellenic Open University, Athens, Greece

    George Manolas

Authors
  1. George Sfakianakis
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  2. George M. Agiomirgianakis
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  3. George Manolas
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Correspondence to George Sfakianakis .

Editor information

Editors and Affiliations

  1. Laboratory of Applied Economics, Department of Economics, University of Western Macedonia, Kastoria, Greece

    Nicholas Tsounis

  2. Laboratory of Applied Economics, Department of Economics, University of Western Macedonia, Kastoria, Greece

    Aspasia Vlachvei

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Sfakianakis, G., Agiomirgianakis, G.M., Manolas, G. (2021). Macroeconomic Determinants of NPLs Using an Extended Sample and Dominance Analysis. In: Tsounis, N., Vlachvei, A. (eds) Advances in Longitudinal Data Methods in Applied Economic Research. ICOAE 2020. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-63970-9_20

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