Designing an Optimal Model Regarding Early Warning System of Bankruptcy of Banks in Iran Application of Grounded Theory and Econometric Models

Document Type : Research Article

Authors

Department of Management, Rasht Branch, Islamic Azad University, Rasht, Iran

Abstract

In financial and banking system and macroeconomic conditions develop a comprehensive document for the banking early warning system (BEWS) for monetary and banking policy makers is important. The main objective of the present study is to design and estimate the native model regarding the early warning system of bankruptcy threshold of banks in Iran. Based on the strategy of Grounded Theory, the native model designed. Also, according to the optimization criteria, the optimal model was chosen. The methodology is mixed. In the qualitative part, information is obtained through in-depth interviews by guiding generalities and in a semi-structured way. In the quantitative part, the research hypotheses were tested using data from the panel data for a ten-year period (2011-2020). The results obtained in the qualitative part have shown that capital adequacy, bank competitiveness index and bank stability have been identified as indicators of bankruptcy threshold of banks (dependent variables). Nine variables were identified as explanatory variables. According to the criteria of the optimal model, the third model is the optimal model from the point of view of all the criteria. Moreover, the residual sum of squares of the third model is lower than the other two models. The Durbin-Watson value is much closer to 2, so it is a healthier model and it can be claimed that there is no correlation error in the error term. Finally, in the third model, the value of F statistic is much higher than other models.

Keywords

Main Subjects

References

Agnello, L., and Sousa, R. M. (2012). How do banking crises impact on income inequality?. Applied Economics Letters, 19(15), 1425-1429.
Ahmadian, A. (2015). Designing an early warning system to predict the time of exposure to bankruptcy of banks, Quarterly Journal of Applied Theories of Economics, 2(4), 119-144.
Ahmadian, A., and Gorji, M. (2017). Explanation of bankruptcy prediction model to identify healthy and at-risk banks, Scientific-research quarterly of Asset Management and Financing, 5(3), 1-18.
Ahmadian, A., and Heydari, H. (2016). Designing a quick warning system in the banking network, the 26th annual monetary and exchange policy conference, Tehran, Monetary and Banking Research Institute.
Almanidis, P., and Sickles, R. C. (2016). Banking crises, early warning models, and efficiency. In Advances in Efficiency and Productivity, Springer.
Atefifar, A., and Fathi, Z. (2020). Effective investigation of financial health indicators as symbols of banking financial crisis by using multivariate logit models (case study of listed banks), Financial Engineering and Securities Management Quarterly, 42, 361-333.
Babajide, A. A., Olokoyo, F. O., and Adegboye, F. B. (2015). Predicting bank failure in Nigeria using survival analysis approach. Journal of South African Business Research, 2015, 965940.
Bakeri, A., Rezazadeh, J., Haghighat, H., and Kordestani, G. (2020). A Resilience-Based Model for Performance Assessment of Companies Listed in Tehran Stock Exchange During Economic and Environmental Crisis. Environmental Energy and Economic Research, 4(2), 135-153.
Bats, J. V., Giuliodori, M., and Houben, A. C. (2022). Monetary policy effects in times of negative interest rates: What do bank stock prices tell us?. Journal of Financial Intermediation, 101003.
Bazargan, A. (2017). An introduction to qualitative and mixed research methods; Common Approaches in Behavioral Sciences. Tehran: Didar Publications.
Berg, A., and C. Pattillo. (1999). Predicting Currency Crises: The Indicator Approach and an Alternative. Journal of International Money and Finance, 18(4), 561-586.
Betz, F., Oprica, S., Peltonen, T. A., and Sarlin, P. (2014). Predicting distress in European banks. Journal of Banking and Finance, 45, 225-241.
Botta, A., Caverzasi, E., and Russo, A. (2022). When complexity meets finance: A contribution to the study of the macroeconomic effects of complex financial systems. Research Policy, 51(8), 103990.
Bouri, E., Demirer, R., Gabauer, D., and Gupta, R. (2022). Financial market connectedness: The role of investors’ happiness. Finance Research Letters, 44, 102075.
Candelon, B., Dumitrescu, E.-I., and Hurlin, C. (2014). Currency crises early arning systems: why they should be dynamic. International Journal of Forecast, 30(4), 1016-1029.
Chen, Q., Goldstein, I., Huang, Z., and Vashishtha, R. (2022). Bank transparency and deposit flows. Journal of Financial Economics, 146(2), 475-501.
Chen, T. H., Lee, C. C., and Shen, C. H. (2022). Liquidity indicators, early warning signals in banks, and financial crises. The North American Journal of Economics and Finance, 62, 101732.
Claessens, S., and Kose, M. A. (2013). Financial Crises: Explanations, Types, and Implications, IMF Working Paper, No WP/13/28.
Cole, R. A., and Wu, Q. (2009). Is hazard or probit more accurate in predicting financial distress? Evidence from US bank failures. Munich Personal RePEc Archive, Paper No. 29182.
Creswell, J.W., and Clark, V.L. (2007). Designing and conducting mixed methods research, Thousand Oaks. CA: SAGE publication.
Creswell, J. W., and Creswell, J. D. (2018). Research Design: Quantitative and Mixed Methods Approaches. CA: SAGE Publications.
Creswell, J.W. (2012). Educational research: Planning, conducting, and evaluating quantitative and qualitative research. 4th Edition. Boston: Pearson Publication
Danaeifard, H., and Emami, S. M. (2007). Qualitative Research Strategies: A Reflection on Grounded Theory. Management Thought, 1(2), 97-69.
Diamond, D., and Dybvig, P. (1983). Bank runs, liquidity, and deposit insurance. Journal of political Economy, 91(3), 401-419.
Dincer, N., Eichengreen, B., and Geraats, P. (2022). Trends in monetary policy transparency: further updates. International Journal of Central Banking, 18(1), 331-348.
Filippopoulou, C. H., Galariotis, E., and Spyrou, S. (2020). An early warning system for predicting systemic banking crises in the Eurozone: A logit regression approach. Journal of Economic Behavior and Organization, 172, 344-363.
Frankel, J. A., and Rose, A. K. (1996). Currency crashes in emerging markets: An empirical treatment. Journal of International Economics, 41(3-4), 351-366.
Frankel, J. A., and Saravelos, G. (2010). Are leading indicators of financial crises useful for assessing country vulnerability? Evidence from the 2008-09 global crisis (No. w16047). National bureau of economic research.
Fratzscher, M., and Bussiere, M. (2003). Towards a new early warning system of financial crises. In: Royal Economic Society Annual Conference (No. 81). Royal Economic Society.
Gerged, A. M., Marie, M., and Elbendary, I. (2022). Estimating the Risk of Financial Distress Using a Multi-Layered Governance Criterion: Insights from Middle Eastern and North African Banks. Journal of Risk and Financial Management, 15(12), 588.
Ghenimi, A., Chaibi, H., and Omri, M. A. B. (2017). The effects of liquidity risk and credit risk on bank stability: Evidence from the MENA region. Borsa Istanbul Review, 17(4), 238-248.
Gholizadeh, A., Falahshams, M., and Afsharkazemi, M. A. (2020). Designing a quick warning system for the occurrence of a financial crisis in the Tehran Stock Exchange with the approach of Logit and Probit models. Scientific Journal of Financial Science of Securities Analysis, 13(48), 135-148.
Glaser, B., and Strauss, A. (1967). The discovery of grounded theory. Chicago: Aldine Publishing Company.
Glaser, B. (1998). Doing grounded theory: Issues and discussions. CA: Sociology Press.
Glaser, B. (2013). What is grounded theory. Online at: http: //www.groundedtheory.com /what-is-gt.aspx
Glaser, B., Bailyn, L., Fernandez, W., Holton, J. A., and Levina, N. (2013). What Grounded Theory Is…. In: Academy of management proceedings, Briarcliff Manor, NY 10510: Academy of Management.
Hammond, P., Opoku, M. O., and Kwakwa, P. A. (2022). Relationship among corporate reporting, corporate governance, going concern and investor confidence: Evidence from listed banks in sub Saharan Africa. Cogent Business and Management, 9(1), 2152157.
Huang, Y., Kou, G., and Peng, Y. (2017). Nonlinear manifold learning for early warnings in financial markets. J. European Journal of Operational Research, 258, 692-702.
Ivičić, L., Kunovac, D., and Ljubaj, I. (2008). Measuring bank insolvency risk in CEE countries. In: The Fourteenth Dubrovnik Economic Conference.
Kaminsky, G., and Lizondo, S., and M. Reinhart. (1998). Leading Indicator of Currency Crises. IMF Staff Papers, 45, 1-48.
Kaminsky, G. L., and C. M. Reinhart. (1999). The Twin crises: The causes of banking and balance of payments problems. American Economic Review, 89 (3), 473-500.
Komeijani, A. (2015). The role of banking system in Iranian Economy. Role of public relations in the banking industry, Conference in Central Bank of Iran (In Persian).
Laser, F. H., and Weidner, J. (2022). Currency compositions of international reserves and the euro crisis. Open Economies Review, 33, 917-944.
Lepetit, L., and Strobel, F. (2015). Bank insolvency risk and Z-score measures: A refinement. Finance Research Letters, 13, 214-224.
Li, Z., Yang, C., and Huang, Z. (2022). How does the fintech sector react to signals from central bank digital currencies?. Finance Research Letters, 50, 103308.
Lin, X., and Peng, Y. (2022). Research on the early warning system of regional financial risk. International Journal of Industrial and Systems Engineering, 41(3), 404-415.
Mabkhot, H., and Al-Wesabi, H. A. H. (2022). Banks’ Financial Stability and Macroeconomic Key Factors in GCC Countries. Sustainability, 14(23), 15999.
Mahmoudinia, D., and Borhani, L. (2022). The Twin Crises in the Iranian Economy and Its Determination during 1980–2018. Iranian Economic Review, 26(1), 183-197.
Martin, D. (1977). Early warning of bank failure: A logit regression approach. Journal of banking and finance, 1(3), 249-276.
Mayes, D.G., and Hanno, S. (2014). The effectiveness of capital adequacy measures in predicting bank distress. Vienna: SUERF - The Europe. Money and Finance Forum.
Oppong, G.K., and Pattanayak, J.K. (2019). Does investing in intellectual capital improve productivity? Panel evidence from commercial banks in India, Borsa-Istanbul Review, (http://creativecommons.org/licenses/bync-nd/4.0/)
Patel, S., and Sarkar, A. (1998). Crises in Developed and Emerging Stock Markets. Federal Reserve Bank.
Radfar, H., Shahchera, M., and Sabouri, B. (2019). The simultaneous effect of liquidity risk and credit risk on the stability of banks admitted to the Tehran Stock Exchange, 7(27), 191-214.
Rastogi, S., and Kanoujiya, J. (2022). Corporate disclosures and financial distress in banks in India: the moderating role of competition. Asian Review of Accounting, 30(5), 691-712.
Sadeghi Sharif, J., Talebi, M., Alemtabriz, A. and Katouzian, M. (2018). Comparison of indicators for determining the financial crisis threshold of banks in the early warning system based on the factor of business cycles, Monetary and Banking Research Quarterly, 11(38), 501-534.
Sadeghi sharif, J., Talebi M., Alemtabriz A., and Katouzian M. (2018). Comparison of indicators for determining the financial crisis threshold of banks in the early warning system based on the factor of business cycles, Monetary and Banking Research Quarterly, 11(38), 534-501.
Sahajawala, R., and Bergh, P. Van den. (2014). Supervisory risk assessment and early warning systems. Basel committee on banking supervision working papers, No 4.
Samad, A., and Armstrong, V. S. (2022). Bootstrap-DEA management efficiency and early prediction of bank failure: Evidence from 2008-2009 US bank failures. Central Bank Review, 22(3), 119-127.
Seraj, S., and Taheri, M. (2011). Banking supervision based on the early warning system, using CAMEL ratios in the form of logit model, scientific research journal of monetary-banking research, 4(12), 45-70.
Shirinpour, M., Haji, G., Sarlak, A., and Alipour, H. (2022). Asymmetric Effects of Oil Price, Exchange Rate and Money Volume on Stock Returns of Tehran Stock Exchange. Environmental Energy and Economic Research, 7(1), S049.
Shumway, T. (2001). Forecasting bankruptcy more accurately: A simple hazard model. The journal of business, 74(1), 101-124.
Strauss, A., and Corbin, J. (1998). Basics of qualitative research: Grounded theory procedures and techniques, 2nd ed. Thousand Oaks, CA: SAGE Publication.
Tatom, J. (2012). Predicting failure in the commercial bank industry. Munchin Personal RePEc Archive, Paper No. 34608.
Thomson, J. B. (1991). Predicting bank failures in the 1980s. Federal Reserve Bank of Cleveland Economic Review, 27(1), 9-20.
Weibull, W. (2015). A statistical theory of the strength of materials. In: Ingeni¨ors Vetenskaps Akademien Handlingar, vol. 151. Stockholm: Generalstabens Litografiska Anstalts Forlag.
Whalen, G. (2016). A proportional hazards model of bank failure: An examination of its usefulness as an early warning tool, Federal Reserve Bank of Cleveland Economic Review. Quarter 1, 9-20.
Zaghdoudi, T. (2016). Bank failure prediction with logistic regression. International Journal of Economics and Financial Issues. 3(2), 537-543.
Environmental Energy and Economic Research
Volume 7, Issue 2
May 2023
Pages 1-20

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