IDEAS home Printed from https://ideas.repec.org/a/sae/globus/v22y2021i3p674-688.html

Looking Beyond the Financial Numbers: The Relationship Between Macroeconomic Indicators and the Likelihood of Financial Distress

Author

Listed:
  • Ammar Hafeez
  • Sujata Kar

Abstract

The current article aims to identify important macroeconomic variables that could indicate the likelihood of financial distress among 294 Indian firms included in the BSE 500 index. Twelve years of financial data and macroeconomic indicators were analysed through a logit model. The study applied a synthetic measure of financial distress adopted from Bhattacharjee and Han (2014, China Economic Review , 30 , 244–262.) which is based on the interest coverage ratio. A significant negative relationship is reported between the likelihood of financial distress among firms and three macroeconomic indicators, namely, the index of industrial production (IIP), exchange rate and a 10-year bond yield. Accordingly, the classification accuracy reported for the full, training and testing samples was 75.51, 79.49 and 70 per cent, respectively. With respect to theoretical contribution, the study has underlined the difference between financial distress and bankruptcy. An additional classification test was conducted wherein the harmonic mean based on the current dataset characteristics was the discriminating score. A prediction accuracy of 76.92 and 70 per cent with respect to the training and testing sample was reported.

Suggested Citation

  • Ammar Hafeez & Sujata Kar, 2021. "Looking Beyond the Financial Numbers: The Relationship Between Macroeconomic Indicators and the Likelihood of Financial Distress," Global Business Review, International Management Institute, vol. 22(3), pages 674-688, June.
    • Handle: RePEc:sae:globus:v:22:y:2021:i:3:p:674-688
    DOI: 10.1177/0972150918811716
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0972150918811716
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0972150918811716?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jia Liu, 2009. "Business Failures And Macroeconomic Factors In The Uk," Bulletin of Economic Research, Wiley Blackwell, vol. 61(1), pages 47-72, January.
    2. Filipe, Sara Ferreira & Grammatikos, Theoharry & Michala, Dimitra, 2016. "Forecasting distress in European SME portfolios," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 112-135.
    3. Carling, Kenneth & Jacobson, Tor & Linde, Jesper & Roszbach, Kasper, 2007. "Corporate credit risk modeling and the macroeconomy," Journal of Banking & Finance, Elsevier, vol. 31(3), pages 845-868, March.
    4. Lennox, Clive, 1999. "Identifying failing companies: a re-evaluation of the logit, probit and DA approaches," Journal of Economics and Business, Elsevier, vol. 51(4), pages 347-364, July.
    5. Loretta Fung, 2008. "Large real exchange rate movements, firm dynamics, and productivity growth," Canadian Journal of Economics, Canadian Economics Association, vol. 41(2), pages 391-424, May.
    6. Giesecke, Kay & Longstaff, Francis A. & Schaefer, Stephen & Strebulaev, Ilya, 2011. "Corporate bond default risk: A 150-year perspective," Journal of Financial Economics, Elsevier, vol. 102(2), pages 233-250.
    7. Arindam Bandyopadhyay, 2006. "Predicting probability of default of Indian corporate bonds: logistic andZ‐score model approaches," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 7(3), pages 255-272, May.
    8. Beaver, Wh, 1968. "Information Content Of Annual Earnings Announcements," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 6, pages 67-92.
    9. Robson, Martin T, 1996. "Macroeconomic Factors in the Birth and Death of U.K. Firms: Evidence from Quarterly VAT Registrations," The Manchester School of Economic & Social Studies, University of Manchester, vol. 64(2), pages 170-188, June.
    10. Scott, James, 1981. "The probability of bankruptcy: A comparison of empirical predictions and theoretical models," Journal of Banking & Finance, Elsevier, vol. 5(3), pages 317-344, September.
    11. Wu, Y. & Gaunt, C. & Gray, S., 2010. "A comparison of alternative bankruptcy prediction models," Journal of Contemporary Accounting and Economics, Elsevier, vol. 6(1), pages 34-45.
    12. David S. Jenkins & Gregory D. Kane & Uma Velury, 2009. "Earnings Conservatism and Value Relevance Across the Business Cycle," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 36(9-10), pages 1041-1058.
    13. Priyadarshi Dash, 2017. "Predicting Financial Crises: A Study of Asian Economies," Global Business Review, International Management Institute, vol. 18(5), pages 1262-1277, October.
    14. Kam, Amy & Citron, David & Muradoglu, Gulnur, 2008. "Distress and restructuring in China: Does ownership matter?," China Economic Review, Elsevier, vol. 19(4), pages 567-579, December.
    15. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 4, pages 71-111.
    16. Sunti Tirapat & Aekkachai Nittayagasetwat, 1999. "An Investigation of Thai Listed Firms' Financial Distress Using Macro and Micro Variables," Multinational Finance Journal, Multinational Finance Journal, vol. 3(2), pages 103-125, June.
    17. Figlewski, Stephen & Frydman, Halina & Liang, Weijian, 2012. "Modeling the effect of macroeconomic factors on corporate default and credit rating transitions," International Review of Economics & Finance, Elsevier, vol. 21(1), pages 87-105.
    18. Balcaen, Sofie & Ooghe, Hubert, 2006. "35 years of studies on business failure: an overview of the classic statistical methodologies and their related problems," The British Accounting Review, Elsevier, vol. 38(1), pages 63-93.
    19. Chae Woo Nam & Tong Suk Kim & Nam Jung Park & Hoe Kyung Lee, 2008. "Bankruptcy prediction using a discrete-time duration model incorporating temporal and macroeconomic dependencies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(6), pages 493-506.
    20. William H. Beaver & Maureen F. McNichols & Jung-Wu Rhie, 2005. "Have Financial Statements Become Less Informative? Evidence from the Ability of Financial Ratios to Predict Bankruptcy," Review of Accounting Studies, Springer, vol. 10(1), pages 93-122, March.
    21. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    22. David S. Jenkins & Gregory D. Kane & Uma Velury, 2009. "Earnings Conservatism and Value Relevance Across the Business Cycle," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 36(9‐10), pages 1041-1058, November.
    23. N. Crutzen & D. Van Caille, 2008. "The Business Failure Process. An Integrative Model of the Literature," Review of Business and Economic Literature, KU Leuven, Faculty of Economics and Business (FEB), Review of Business and Economic Literature, vol. 0(3), pages 287-316.
    24. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 18(1), pages 109-131.
    25. Richard E. Caves, 1998. "Industrial Organization and New Findings on the Turnover and Mobility of Firms," Journal of Economic Literature, American Economic Association, vol. 36(4), pages 1947-1982, December.
    26. Bhattacharjee, Arnab & Han, Jie, 2014. "Financial distress of Chinese firms: Microeconomic, macroeconomic and institutional influences," China Economic Review, Elsevier, vol. 30(C), pages 244-262.
    27. Arindam Bandyopadhyay, 2006. "Predicting probability of default of Indian corporate bonds: logistic and Z-score model approaches," Journal of Risk Finance, Emerald Group Publishing, vol. 7(3), pages 255-272, May.
    28. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure - Reply," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 4, pages 123-127.
    29. Frydman, Halina & Altman, Edward I & Kao, Duen-Li, 1985. "Introducing Recursive Partitioning for Financial Classification: The Case of Financial Distress," Journal of Finance, American Finance Association, vol. 40(1), pages 269-291, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Soumya Ranjan Sethi & Dushyant Ashok Mahadik, 2025. "Do Rising Climate Risks Signal Financial Trouble for Food and Agro Based Firms?," Sustainable Development, John Wiley & Sons, Ltd., vol. 33(6), pages 8599-8618, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mohammad Mahdi Mousavi & Jamal Ouenniche & Kaoru Tone, 2023. "A dynamic performance evaluation of distress prediction models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 756-784, July.
    2. Ashraf, Sumaira & Félix, Elisabete G.S. & Serrasqueiro, Zélia, 2020. "Development and testing of an augmented distress prediction model: A comparative study on a developed and an emerging market," Journal of Multinational Financial Management, Elsevier, vol. 57.
    3. Sanjay Sehgal & Ritesh Kumar Mishra & Ajay Jaisawal, 2021. "A search for macroeconomic determinants of corporate financial distress," Indian Economic Review, Springer, vol. 56(2), pages 435-461, December.
    4. Mohammad Mahdi Mousavi & Jamal Ouenniche, 2018. "Multi-criteria ranking of corporate distress prediction models: empirical evaluation and methodological contributions," Annals of Operations Research, Springer, vol. 271(2), pages 853-886, December.
    5. Christian Lohmann & Steffen Möllenhoff & Thorsten Ohliger, 2023. "Nonlinear relationships in bankruptcy prediction and their effect on the profitability of bankruptcy prediction models," Journal of Business Economics, Springer, vol. 93(9), pages 1661-1690, November.
    6. M. A. Lagesh & Maram Srikanth & Debashis Acharya, 2018. "Corporate Performance during Business Cycles: Evidence from Indian Manufacturing Firms," Global Business Review, International Management Institute, vol. 19(5), pages 1261-1274, October.
    7. Sumaira Ashraf & Elisabete G. S. Félix & Zélia Serrasqueiro, 2019. "Do Traditional Financial Distress Prediction Models Predict the Early Warning Signs of Financial Distress?," JRFM, MDPI, vol. 12(2), pages 1-17, April.
    8. Jessica Thacker & Debdatta Saha, 2025. "Financial Performance and Corporate Distress: Searching for Common Factors for Firms in the Indian Registered Manufacturing Sector," Computational Economics, Springer;Society for Computational Economics, vol. 65(6), pages 3841-3883, June.
    9. Serrano-Cinca, Carlos & Gutiérrez-Nieto, Begoña & Bernate-Valbuena, Martha, 2019. "The use of accounting anomalies indicators to predict business failure," European Management Journal, Elsevier, vol. 37(3), pages 353-375.
    10. Casado Yusta, Silvia & Nœ–ez Letamendía, Laura & Pacheco Bonrostro, Joaqu’n Antonio, 2018. "Predicting Corporate Failure: The GRASP-LOGIT Model || Predicci—n de la quiebra empresarial: el modelo GRASP-LOGIT," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 26(1), pages 294-314, Diciembre.
    11. Ilyes Abid & Farid Mkaouar & Olfa Kaabia, 2018. "Dynamic analysis of the forecasting bankruptcy under presence of unobserved heterogeneity," Annals of Operations Research, Springer, vol. 262(2), pages 241-256, March.
    12. Kumar, Rahul & Deb, Soumya Guha & Mukherjee, Shubhadeep, 2020. "Do words reveal the latent truth? Identifying communication patterns of corporate losers," Journal of Behavioral and Experimental Finance, Elsevier, vol. 26(C).
    13. Elena Gregova & Katarina Valaskova & Peter Adamko & Milos Tumpach & Jaroslav Jaros, 2020. "Predicting Financial Distress of Slovak Enterprises: Comparison of Selected Traditional and Learning Algorithms Methods," Sustainability, MDPI, vol. 12(10), pages 1-17, May.
    14. du Jardin, Philippe, 2015. "Bankruptcy prediction using terminal failure processes," European Journal of Operational Research, Elsevier, vol. 242(1), pages 286-303.
    15. Zhang, Xuan & Ouyang, Ruolan & Liu, Ding & Xu, Liao, 2020. "Determinants of corporate default risk in China: The role of financial constraints," Economic Modelling, Elsevier, vol. 92(C), pages 87-98.
    16. Paulo V. Carvalho & José D. Curto & Rodrigo Primor, 2022. "Macroeconomic determinants of credit risk: Evidence from the Eurozone," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2054-2072, April.
    17. Oliver Lukason & Art Andresson, 2019. "Tax Arrears Versus Financial Ratios in Bankruptcy Prediction," JRFM, MDPI, vol. 12(4), pages 1-13, December.
    18. Correia, Maria, 2025. "Accounting and corporate failure: the evolving role of accounting information in bankruptcy prediction," LSE Research Online Documents on Economics 128340, London School of Economics and Political Science, LSE Library.
    19. fernández, María t. Tascón & gutiérrez, Francisco J. Castaño, 2012. "Variables y Modelos Para La Identificación y Predicción Del Fracaso Empresarial: Revisión de La Investigación Empírica Reciente," Revista de Contabilidad - Spanish Accounting Review, Elsevier, vol. 15(1), pages 7-58.
    20. Koen W. de Bock, 2017. "The best of two worlds: Balancing model strength and comprehensibility in business failure prediction using spline-rule ensembles," Post-Print hal-01588059, HAL.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:globus:v:22:y:2021:i:3:p:674-688. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: http://www.imi.edu/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.