The Determinants of Financial Distress in Emerging Country: Empirical Evidence from Indonesia
Abstract
This research strives to foresee corporate financial distress by applying three different perspectives that cover firms’ internal and external conditions namely accounting-based, market-based and macroeconomic models. Financially distressed and non-distressed corporations are analyzed using binomial logistic regression. Seven different models are employed to observe the effects of ten independent variables on financial distress, as well as to predict more accurately the possibility of firms defaulting. By exploring 257 public corporations listed on the Indonesia Stock Exchange over 10 years and utilizing 2,570 observations, the main finding suggests that when the accounting, market, and macroeconomic models are combined, it provides a better understanding of corporate failure than either model. Moreover, the results also indicate five factors that significantly determine the likelihood of a company’s financial distress: liquidity, profitability, asset productivity, market capitalization, and leverage. Accordingly, companies should keep a close watch on their accounting ratios and market indicators carefully to avoid bankruptcy. This research contributes to the finance and economic literature by paving the way for the development of an alternative perspective for predicting corporate failure in emerging markets.
Keywords
Full Text:
PDFReferences
Agarwal, V. & Taffler, R. (2008). Comparing the performance of market-based and accounting-based bankruptcy prediction models. Journal of Banking & Finance, 32(8), pp. 1541–1551. https://doi.org/10.1016/j.jbankfin.2007.07.014
Agrawal, K. & Maheshwari, Y. (2016). Predicting Financial Distress: Revisiting the Option-Based Model. South Asian Journal of Global Business Research, 5(2), pp. 268–284. https://doi.org/10.1108/SAJGBR-04-2015-0030
Agustia, D., Muhammad, N. P. A., & Permatasari, Y. (2020). Earnings management, business strategy, and bankruptcy risk: Evidence from Indonesia. Heliyon, 6(2), e03317. https://doi.org/10.1016/j.heliyon.2020.e03317
Allen, D. E. & Powell, R. (2012). The Fluctuating Default Risk of Australian Banks. Australian Journal of Management, 37(2), pp. 297–325. https://doi.org/10.1177/0312896211432369
Altman, E. I. (1968). Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. Journal of Finance, 23(4), pp. 589–609. https://doi.org/10.2307/2978933
Altman, E. I. (2000). Predicting Financial Distress of Companies: Revisiting the Z-score and ZETA Models. Stern School of Business, New York University. https://doi.org/10.4337/9780857936080.00027
Altman, E. I., Haldeman, R. G., Narayanan, P. (1977). Zeta to analysis a new model to identify bankruptcy risk of corporations. Journal of Banking & Finance, 1(1), pp. 29–54. https://doi.org/10.1016/0378-4266(77)90017-6
Andrade, G., & Kaplan, S. (2002). How Costly is Financial (Not Economic) Distress? Evidence from Highly Leveraged Transactions that Became Distressed. Journal of Finance, 53, pp. 1443–1493. https://doi.org/10.1111/0022-1082.00062
Beaver, W. H. (1966). Financial Ratios as Predictors of Failure. Journal of Accounting Research, 4, pp.71–111. https://doi.org/10.2307/2490171
Byström, H. N. E. (2006). Merton unraveled: a flexible way of modeling default risk. The Journal of Alternative Investments, 8(4), pp. 39–47. https://doi.org/10.3905/jai.2006.627849
Dinh, D. V., Powell, R. J., & Vo, D. H. (2021). Forecasting corporate financial distress in the Southeast Asian countries: A market-based approach. Journal of Asian Economics, 74. https://doi.org/10.1016/j.asieco.2021.101293
Fadrul, F., & Ridawati, R. (2020). Analysis of Method Used to Predict Financial Distress Potential in Pulp and Paper Companies of Indonesia. International Journal of Economics Development Research, 1(1), pp. 57–69. https://doi.org/10.37385/ijedr.v1i1.29
Gu, X., Tam, P. S., Lei, C.K. (2021). The effects of inequality in the 1997–98 Asian crisis and the 2008–09 global tsunami: The case of five Asian economies. Journal of International Money and Finance, 110, 102306. https://doi.org/10.1016/j.jimonfin.2020.102306.
Gunathilaka, C. (2014). Financial Distress Prediction: A Comparative Study of Solvency Test and Z-Score models with reference to Sri Lanka. The IUP Journal of Financial Risk Management, 11(3), pp. 40-50.
Hillegeist, S. A., Keating, E. K., Cram, D. P., & Lundstedt, K. G. (2004). Assessing the Probability of Bankruptcy. Review of Accounting Studies, 9(1), pp. 5–34. https://doi.org/10.1023/B:RAST.0000013627.90884.b7
IDX (Indonesia Stock Exchange) Annual Report. (2022). Retrieved from: https://www.idx.co.id/tentang-bei/laporan-tahunan/
Khoja, L., Chipulu, M., & Jayasekera, R. (2019). Analysis of financial distress cross countries: Using macroeconomic, industrial indicators and accounting data. International Review of Financial Analysis, 66, 101379. https://doi.org/10.1016/j.irfa.2019.101379
Kristanti, F. T., Effendi, N., Herwany, A., & Febrian, E. (2016). Does Corporate Governance Affect the Financial Distress of Indonesian Companies? A Survival Analysis Using Cox Hazard Model with Time-Dependent Covariates. Advanced Science Letters, 22(12), pp. 4326–4329. https://doi.org/10.1166/asl.2016.8138
Mas’ud, I., & Srengga, R. M. (2015). Financial Ratio Analysis to Predict the Financial Distress Condition of Manufacturing Companies Listed on The Indonesia Stock Exchange. Jurnal Akuntansi Universitas Jember, 10(2), pp. 139. https://doi.org/10.19184/jauj.v10i2.1255
Mashudi, Himmati, R., Ardillah, F. R., & Sarasmitha, C. (2021). Financial Distress Prediction in Infrastructure, Utilities, and Transportation Sector Companies 2015-2020. Jurnal Keuangan dan Perbankan, 25(3), pp. 656–670. https://doi.org/10.26905/jkdp.v25i3.5858
Patunrui, K. I. A. & Yati, S. (2017). Analysis of Financial Distress Assessment Using the Altman Method (Z - Score) in Pharmaceutical Companies Listed on the Indonesia Stock Exchange During 2013-2015 Period. Jurnal Akuntansi, Ekonomi dan Manajemen Bisnis, 5(1), pp. 55-71. https://doi.org/10.30871/jaemb.v5i1.275
Permana, R. K., Ahmar, N., & Djaddang, S. (2017). Prediction of Financial Distress in Manufacturing Companies on the Indonesia Stock Exchange. Jurnal Bisnis dan Manajemen, 7(2), pp.149-166. https://doi.org/10.15408/ess.v7i2.4797
Pertiwi, D. A. (2018). The Effect of Financial Ratios, Growth, Company Size, and Inflation on Financial Distress in the Mining Sector Listed on the Indonesia Stock Exchange (IDX) for the 2012-2016 Period. Jurnal Ilmu Manajemen, 6(3), 359–366.
Pham Vo Ninh, B., Do Thanh, T., & Vo Hong, D. (2018). Financial Distress and Bankruptcy Prediction: An appropriate Model for Listed Firms in Vietnam. Economic Systems, 42(4), pp. 616–624. https://doi.org/10.1016/j.ecosys.2018.05.002
Radelet, S., Sachs, J., Cooper, R., & Bosworth, B. (1998). The East Asian Financial Crisis: Diagnosis, Remedies, Prospects. Brookings Papers on Economic Activity, 1998(1), 1-90. https://doi.org/10.2307/2534670
Rees, B., (1995). Financial Analysis. Prentice Hall, London.
Sehgal, S., Mishra, R. K., Deisting, F., & Vashisht, R. (2021). On the determinants and prediction of corporate financial distress in india. [Corporate financial distress in India]. Managerial Finance, 47(10), 1428-1447. https://doi.org/10.1108/MF-06-2020-0332
Springate, G. L. V. (1978). Predicting the Possibility of Failure in a Canadian Firm. Master of Business Administration Project (Unpublished). Simon Fraser University.
Tinoco, M. H., & Wilson, N. (2013). Financial distress and bankruptcy prediction among listed companies using accounting, market and macroeconomic variables. International Review of Financial Analysis, 30, pp. 394–419. https://doi.org/10.1016/j.irfa.2013.02.013
Tinoco, M. H., Holmes, P., & Wilson, N. (2018). Polytomous response financial distress models: The role of accounting, market and macroeconomic variables. International Review of Financial Analysis, 59, pp. 276–289. https://doi.org/10.1016/j.irfa.2018.03.017
Uğurlu, M., & Aksoy, H. (2006). Prediction of corporate financial distress in an emerging market: The case of Turkey. Cross Cultural Management: An International Journal, 13, pp. 277-295. doi: 10.1108/13527600610713396.
Wahyuni, S. F., Farisi, S., & Jufrizen. (2020). Determinants of financial distress in manufacturing sector companies registered on the Indonesia Stock Exchange. Jurnal Ekonomi Keuangan dan Manajemen 16(2), 286–298.
Yulitasari R. M, & Yulistina. (2019). The Effect of Financial Performance on Financial Distress in the Listed Cement Sector Companies 2012-2017. Jurnal Media Ekonomi, 24(2), 18–26. https://doi.org/10.32767/JURMEK.V24I2.565
Zhang, B. Y., Zhou, H., & Zhu, H. (2009). Explaining Credit Default Swap Spreads with the Equity Volatility and Jump Risks of Individual Firms. Review of Financial Studies, 22(12), pp. 5099–5131. https://doi.org/10.1093/rfs/hhp004
Zhou, F., Fu, L., Li, Z., Xu, J. (2022). The recurrence of financial distress: A survival analysis. International Journal of Forecasting. ISSN 0169-2070. https://doi.org/10.1016/j.ijforecast.2021.12.005.
Zmijewski, M. E. (1984). Methodological Issues Related to the Estimation of Financial Distress Prediction Models. Journal of Accounting Research, 22, pp. 59-82. https://doi.org/10.2307/2490859
DOI: https://doi.org/10.26905/jkdp.v26i4.7891
Refbacks
- There are currently no refbacks.
Jurnal Keuangan dan Perbankan (Journal of Finance and Banking)
Diploma Program of Banking and Finance, Faculty of Economics and Business, University of Merdeka Malang
Published by University of Merdeka Malang
Mailing Address:
2nd floor Finance and Banking Building, Jl. Terusan Raya Dieng No. 57 Malang, East Java, Indonesia
Phone: -
Email: [email protected]
This work is licensed under a Creative
Commons Attribution-ShareAlike 4.0