A novel approach to estimating the debt capacity of European SMEs





debt capacity, financial distress, macroeconomic factors, financial constraints


Research background: The concept of debt capacity assumes that a maximum value of debt ratio exists that when exceeded triggers unfavourable consequences, such as drop in market value, default or a change in the business' creditworthiness. With the current state of the art there is a priori no theoretical assurance that such a specific value exists, or rather it is represented by an interval of values. Beyond that, our understanding of debt capacity is often limited to a theoretical approximation by firm-specific factors, while the context of macroeconomic factors, especially those critical for SMEs, is neglected.

Purpose of the article: The aim of this paper is to present a novel approach to estimating SMEs' debt capacity. Further, the aim is to answer the question of what firm-level and macroeconomy conditions lead to exhausting the SMEs' debt capacity and under what conditions a specific value of maximum debt capacity could be estimated.

Methods: To estimate the debt capacity, we suggest a use of an information entropy minimising heuristic and the Minimal Description Length Principle. In this approach, the observed feature space is categorised into several regions. In this case, such a region represents a set of firm- and macroeconomy-specific conditions forming the debt capacity of the SMEs. To the best of our knowledge, such an approach has not yet been used in debt capacity applications.

Findings & value added: We found out that the debt ratio itself provides little explanation of exhausted debt capacity, suggesting that high debt levels are compensated for by other factors. By using the suggested approach, a set of more than 100 different regions was analysed. It was found that in case of five regions (sets of conditions) the debt capacity is exhausted, as the high level of debt has significant distress consequences.


Download data is not yet available.


Agarwal, V., & Taffler, R. (2008). Comparison of the performance of market-based and accounting-based bankruptcy prediction models. Journal of Banking and Finance, 32(8), 1541–1551. doi: 10.1016/j.jbankfin.2007.07.014.

Almeida, H., & Campallo, M. (2007). Financial constraints, asset tangibility, and corporate investment. Review of Financial Studies, 20(5), 1429–1460. doi: 10.1093/ rfs/hhm019.

Almeida, H., Campello, M., & Weisbach, M. S. (2004). The cash flow sensitivity of cash. Journal of Finance, 59, 1777–1804. doi: 10.1111/j.1540-6261.2004.00679.x.

Azofra, V., Rodríguez-Sanz, J. A., & Velasco, P. (2020). The role of macroeconomic factors in the capital structure of European firms: How influential is bank debt? International Review of Economics and Finance, 69, 494–514. doi: 10.1016/j.iref.2020. 06.001.

Beaver, W. H. (1966). Financial ratios as predictors of failure. Journal of Accounting Research, 4, 71–111. doi: 10.2307/2490171.

Beck, T., Demirguc-Kunt, A., Laeven, L., & Maksimovic, V. (2006). The determi-nants of financing obstacles. Journal of International Money and Finance, 25(6), 932–952. doi: 10.1016/j.jimonfin.2006.07.005.

Bongini, P. Ferrando, A., Rossi, E., & Rossolini, M. (2021). SME access to market-based finance across Eurozone countries. Small Business Economics, 56, 1667–1697. doi: 10.1007/s11187-019-00285-z.

Bradley, A. P. (1997). The use of the area under the roc curve in the evaluation of machine learning algorithms. Pattern Recognition, 30(7), 1145–1159. doi: 10.1016/ S0031-3203(96)00142-2.

Brennan, M., & Schwartz, E. (1978). Corporate income taxes, valuation, and the problem of optimal capital structure. Journal of Business, 51, 103–114. doi: 10.1086/295987.

Brezingar-Masten, A., & Masten, I. (2012). CART-based selection of bankruptcy predictors for the logit model. Expert Systems with Applications, 39(11), 10153–10159. doi: 10.1016/j.eswa.2012.02.125.

Carreira, C., & Silva, F. (2010). No deep pockets: Some stylized empirical results on firms’ financial constraints. Journal of Economic Surveys, 24, 731–753. doi: 10.1111 /j.1467-6419.2009.00619.x.

Cathcart, L., Dufour, A., Rossi, L., &. Varotto, S. (2020). The differential impact of leverage on the default risk of small and large firms. Journal of Corporate Fi-nance, 60, 101541. doi: 10.1016/j.jcorpfin.2019.101541.

Catherine, S., Chaney, T., Huang, Z., Sraer, D., & Thesmar, D. (2022). Quantifying reduced-form evidence on collateral constraints. Journal of Finance, 77, 2143–2181. doi: 10.1111/jofi.13158.

Chava, S., & Jarrow, R. A. (2004). Bankruptcy prediction with industry effects. Review of Finance, 8, 537–569. doi: 10.1093/rof/8.4.537.

Civelek, M., Ključnikov, A., Fialova, V., Folvarčná, A., & Stoch, M. (2021). How innovativeness of family-owned SMEs differ depending on their characteris-tics?. Equilibrium. Quarterly Journal of Economics and Economic Policy, 16(2), 413–428. doi: 10.24136/eq.2021.015.

Civelek, M., & Krajčík, V. (2022). How do SMEs from different countries perceive export impediments depending on their firm-level characteristics? System ap-proach. Oeconomia Copernicana, 13(1), 55–78. doi: 10.24136/oc.2022.002.

Civelek, M., Krajčík, V., & Fialova, V. (2023). The impacts of innovative and com-petitive abilities of SMEs on their different financial risk concerns: System ap-proach. Oeconomia Copernicana, 14(1), 327–354. doi: 10.24136/oc.2023.009.

Cleary, S. (2006). International corporate investment and the relationships be-tween financial constraint measures. Journal of Banking & Finance, 30, 1559–1580. doi: 10.1016/j.jbankfin.2005.03.023.

De Moor, L., Wieczorek-Kosmala, M., & Blach, J. (2016). SME debt financing gap: The case of Poland. Transformations in Business & Economics, 15(39), 274–291.

Di Marco, L., & Nieddu, L. (2014). Trigger factors that influence bankruptcy: A comparative and exploratory study. Rivista Italiana di Economia Demografia e Statistica, 68(3/4), 191–198.

Dietsch, M., & Petey, J. (2004). Should SME exposures be treated as retail or cor-porate exposure? A comparative analysis of default probabilities and asset cor-relations in French and German SMEs. Journal of Banking & Finance, 28, 773–788. doi: 10.1016/j.jbankfin.2003.10.006.

Dougherty, J., Kohavi, R., & Sahami, M. (1995). Supervised and unsupervised discretization of continuous features. In A. Prieditis & S. Russell (Eds.). Ma-chine learning: Proceedings of the twelfth international conference. San Francisco: Morgan Kaufmann Publishers.

Ellouze, D., & Mnasri, K. (2020). Business group diversification, financial con-straints, and firm performance: The case of Tunisian group affiliated firms. Journal of Management and Governance, 24, 273–301. doi: 10.1007/s10997-019-0945 4-4.

Erdogan, A. I. (2018). Factors affecting SME access to bank financing: An inter-view study with Turkish bankers. Small Enterprise Research, 25, 23–35. doi: 10.1080/13 215906.2018.1428911.

Fayyad, U. M., & Irani, K. B. (1993). Multi-interval discretization of continuous-valued attributes for classification learning. In R. Bajcsy (Ed.). International joint conference on artificial intelligence. San Francisco: Morgan Kaufmann.

Fazzari, S., Hubbard, R., & Petersen, B. (1988). Financing constraints and corpo-rate investment. Brookings Papers on Economic Activity, 1, 141–195. doi: 10.2307/253 4426.

Filipe, S. F., Grammatikos, T., & Michala, D. (2016). Forecasting distress in European SME portfolios. Journal of Banking & Finance, 64, 112–135. doi: 10.1016/j.jbankf in.2015.12.007.

Frydman, H., Altman, E. I., & Kao, D. L. (1985). Introduction recursive partition-ing for financial classification: The case of financial distress. Journal of Finance, 40(1), 269–291. doi: 10.1111/j.1540-6261.1985.tb 04949.x.

Gilchrist, S., & Himmelberg, C. P. (1995). Evidence on the role of cash flow in investment. Journal of Monetary Economics, 36, 541–572. doi: 10.1016/0304-3932 (95)01223-0.

Gungoraydinoglu, A., & Öztekin, Ö. (2011). Firm- and country-level determinants of corporate leverage: Some new international evidence. Journal of Corporate Finance, 17(5), 1457–1474. doi: 10.1016/j.jcorpfin.2011.08.004.

Gupta, J., Gregoriou, A., & Healy, J. (2015). Forecasting bankruptcy for SMEs using hazard function: To what extent does size matter? Review of Quantitative Finance and Accounting, 45(4), 845–869. doi: 10.1007/s11156-014-0458-0.

Hahn, J., & Lee, H. (2005). Financial constraints, debt capacity, and the cross sec-tion of stock returns. Working paper, University of Washington and Korea Develop-ment Institute.

Hand, D. J., & Till, R. J. (2001). A simple generalisation of the area under the ROC curve for multiple class classification problems. Machine Learning, 45, 171–186. doi: 10.1023/A:1010920819831.

Hanley, J. A., & McNeil, B. J. (1982). The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology, 143(1), 29–36. doi: 10.114 8/radiology.143.1.7063747.

Hastie, T., Tibshirani, R., & Friedman, J. (2009). The elements of statistical learning: Data mining, inference, and prediction. New York: Springer-Verlag. doi: 10.1007 /978-0-387-84858-7.

Hess, D., & Immenkötter, P. (2014). How much is too much? Debt capacity and financial flexibility. CFR Working Paper, University of Cologne, Centre for Financial Research (CFR), 14-03.

Hosmer, D. W., & Lemeshow, S. (2000). Applied logistic regression. Wiley.

Jin, Y., Luo, M., & Wan, C. (2018). Financial constraints, macro-financing envi-ronment, and post-crisis recovery of firms. International Review of Economics and Finance, 55, 54–67. doi: 10.1016/j.iref.2018.01.007.

Karas, M., & Režňáková, M. (2021). The role of financial constraint factors in pre-dicting SME default. Equilibrium. Quarterly Journal of Economics and Economic Policy, 16(4), 865–889. doi: 10.24136/eq.2021.032.

Kennedy, P. (2005). Oh no! I Got the wrong sign! What should I do? Journal of Economic Education, 36(1), 77–92. doi : 10.3200/JECE.36.1.77-92.

Ključnikov, A., Civelek, M., Fialova, V., & Folvarčná, A. (2021). Organizational, local, and global innovativeness of family-owned SMEs depending on firm-individual level characteristics: evidence from the Czech Republic. Equilibrium. Quarterly Journal of Economics and Economic Policy, 16(1), 169–184. doi: 10.24136/ eq.2021.006.

Ključnikov, A., Civelek, M., Krajčík, V., Novák, P., & Červinka, M. (2022). Finan-cial performance and bankruptcy concerns of SMEs in their export deci-sion. Oeconomia Copernicana, 13(3), 867–890. doi: 10.24136/oc.2022.025.

Kjenstad, E. C., & Kumar, A. (2022). The effect of real estate prices on peer firms. Real Estate Economics, 50, 1022–1053. doi: 10.1111/1540-6229.12362.

Lee, C., Wang, C., Yin, C., & Choo, M. (2021). Do firm characteristics affect debt capacity? Evidence in CEO succession. Applied Economics, 53(48), 5567–5583. doi: 10.1080/00036846.2021.1925626.

Leary, M., & Roberts, M. (2010). The pecking order, debt capacity, and infor-mation asymmetry. Journal of Financial Economics, 95, 332–355. doi: 10.1016/j.jfineco. 2009.10.009.

Lemmon, M., & Roberts, M. (2010). The response of corporate financing and in-vestment to changes in the supply of credit. Journal of Financial and Quantitative Analysis, 45, 555–587. doi: 10.1017/S0022109010000256.

León-Gómez, A., Santos-Jaén, J. M., Ruiz-Palomo, D., & Palacios-Manzano, M. (2022). Disentangling the impact of ICT adoption on SMEs performance: The mediating roles of corporate social responsibility and innovation. Oeconomia Copernicana, 13(3), 831–866. doi: 10.24136/oc.2022.024.

Li, H., & Sun, J. (2009). Predicting business failure using multiple case-based rea-soning combines with support vector machine. Expert Systems with Applications, 36(6), 10085–10096. doi: 10.1016/j.eswa.2009.01.013.

Ling, C. X., & Zhang, H. (2002). Toward Bayesian classifiers with accurate probabilities. In M. S. Chen, P. S. Yu, & B. Liu (Eds). Advances in knowledge discovery and data mining. PAKDD 2002. Lecture notes in computer science. Berlin, Heidel-berg: Springer.

Marchica, M. T., & Mura, R. (2010). Financial flexibility, investment ability, and firm value: Evidence from firms with spare debt capacity. Financial Manage-ment, 39(4), 1339–1365. doi: 10.2139/ssrn.891562.

McGuinness, G., Hogan, T., & Powell, R. (2018). European trade credit use and SME survival. Journal of Corporate Finance, 49, 81–103. doi: 10.1016/j.jcorpfin.2017.12 .005.

Mulford, C. W., & Comiskey, E. E. (2002). The financial numbers game: Detecting creative accounting practices. New York: John Wiley & Sons.

Musso, P., & Schiavo, S. (2008). The impact of financial constraints on firm surviv-al and growth. Journal of Evolutionary Economics, 18, 135–149. doi: 10.1007/s00191-007-0087-z.

Myers, S. C. (1977). Determinants of corporate borrowing. Journal of Financial Economics, 5, 147–175. doi: 10.1016/0304-405X(77)90015-0.

North, D., Baldock, R., & Ekanem, I. (2010). Is there a debt finance gap relating to Scottish SMEs? A demand-side perspective. Venture Capital, 12(3), 173–192. doi: 10.1080/13691061003658670.

Psillaki, M., Tsolas, I. T., & Margaritis, M. (2010). Evaluation of credit risk based on firm performance. European Journal of Operational Research, 201(3), 873–881. doi: 10.1016/j.ejor.2009.03.032.

Shumway, T. (2001). Forecasting bankruptcy more accurately: A simple hazard model. Journal of Business, 74(1), 101–124. doi: 10.1086/209665.

Shyam-Sunder, L., & Myears, S. C. (1999). Testing static tradeoff against pecking order models of capital structure. Journal of Financial Economics, 51, 219–244. doi: 10.1016/S0304-405X(98)00051-8.

Stiglitz, J. E. (1972). Some aspects of the pure theory of corporate finance: Bank-ruptcies and takeovers. Bell Journal of Economics and Management Science, 3(2), 458–482. doi: 10.2307/3003033.

Tinoco, M. H., & Wilson, N. (2013). Financial distress and bankruptcy prediction among listed companies using accounting, market, and macroeconomic varia-bles. International Review of Financial Analysis, 30, 394–419. doi: 10.1016/j.irfa. 2013.02.013.

Tomášková, E., & Kaňovská, L. (2022). Impact of cooperation flexibility on innova-tion flexibility in SMEs. Equilibrium. Quarterly Journal of Economics and Economic Policy, 17(2), 533–566. doi: 10.24136/eq.2022.019.

Traczynski, J. (2017). Firm default prediction: A Bayesian model-averaging ap-proach. Journal of Financial and Quantitative Analysis, 52(3), 1211–1245. doi: 10.1017/S002210901700031X.

Ullah, B. (2020). Financial constraints, corruption, and SME growth in transition economies. Quarterly Review of Economics and Finance, 75, 120–132. doi: 10.1016/ j.qref.2019.05.009.

Welc, J. (2017). EBITDA vs. cash flows in bankruptcy prediction on the Polish capital market. European Financial and Accounting Journal, 12(2), 91–103. doi: 10.18267 /j.efaj.183.

West, B. T., Welch, K. B., & Gałecki, A. T. (2014). Linear mixed models. A practical guide using statistical software. New York: CRC Press.

Whited, T. M. (1992). Debt, liquidity constraints, and corporate investment: Evi-dence from panel data. Journal of Finance, 47, 1425–1460. doi: 10.1111/j.1540-6261.1992.tb04664.x.

Virglerova, Z., Ivanova, E., Dvorsky, J., Belas, J., & Krulický, T. (2021). Selected factors of internationalisation and their impact on the SME perception of the market risk. Oeconomia Copernicana, 12(4), 1011–1032. doi: 10.24136/oc.2021.033.

Zavgren, C. V. (1985). Assessing the vulnerability to failure of American industrial firms: Logistic analysis. Journal of Business Finance and Accounting, 12(1), 19–45. doi: 10.1111/j.1468-5957.1985.tb00077.x.




How to Cite

Karas, M., & Režňáková, M. (2023). A novel approach to estimating the debt capacity of European SMEs. Equilibrium. Quarterly Journal of Economics and Economic Policy, 18(2), 551–581. https://doi.org/10.24136/eq.2023.017