IDEAS home Printed from https://ideas.repec.org/a/cvv/journ5/v5y2018i4p321-336.html

Measurement of the effects of capital structure in enterprises on the probability of bankruptcy: A research on the enterprises traded in the BIST industrial index

Author

Listed:
  • Gökhan ÖZER
  • Ali Korhan ÖZEN

    (Bülent Ecevit University, Turkey)

Abstract

This study aims to measure the relationship between the Altman Z-Score, which is used to determine the financial failure of the enterprises, and the decisions on the capital structure. In other words, it has been tried to determine whether the capital structure has any effect on the risk of bankruptcy. In the scope of the research, 112 enterprises that continue their activities uninterruptedly and are traded on the industrial index between 2006 and 2014 have been examined. Panel data analysis has been utilized in order to examine the effect of capital structure on the financial failure and/or performance in the enterprises. Through the use of the Altman Z-Score (ZSCORE) which is an indicator of the risk of bankruptcy in the models formed based on the panel data analysis, a statistically negative and significant correlation has been found between the capital structure of the enterprises and the risk of bankruptcy. The leverage ratio (TBTV), which is considered as a variable that represents the capital structure, and thenon-debt tax shields (BDVK), which represent the control variable, have been used. In the correlation between the control variable and the ZSCORE, it has been found that the BDVK has not any significant effect on the ZSCORE and has not caused any increase in the total variance. The findings of this study indicate that the debt ratio in the enterprises causes an increase in financial failure, and they are also compatible with the validity of the trade-off theory.

Suggested Citation

  • Gökhan ÖZER & Ali Korhan ÖZEN, 2018. "Measurement of the effects of capital structure in enterprises on the probability of bankruptcy: A research on the enterprises traded in the BIST industrial index," Journal of Economics Library, EconSciences Journals, vol. 5(4), pages 321-336, December.
    • Handle: RePEc:cvv:journ5:v:5:y:2018:i:4:p:321-336
    as

    Download full text from publisher

    File URL: https://journals.econsciences.com/index.php/JEL/article/view/1776/1791
    Download Restriction: no
    File URL: https://journals.econsciences.com/index.php/JEL/article/view/1776
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Harlan D. Platt & Marjorie B. Platt, 2008. "Financial Distress Comparison Across Three Global Regions," JRFM, MDPI, vol. 1(1), pages 1-34, December.
    2. repec:bla:jfinan:v:43:y:1988:i:1:p:1-19 is not listed on IDEAS
    3. Huang, Guihai & Song, Frank M., 2006. "The determinants of capital structure: Evidence from China," China Economic Review, Elsevier, vol. 17(1), pages 14-36.
    4. Harris, Richard D. F. & Tzavalis, Elias, 1999. "Inference for unit roots in dynamic panels where the time dimension is fixed," Journal of Econometrics, Elsevier, vol. 91(2), pages 201-226, August.
    5. Kaddour Hadri, 2000. "Testing for stationarity in heterogeneous panel data," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 148-161.
    6. Deakin, Eb, 1972. "Discriminant Analysis Of Predictors Of Business Failure," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 10(1), pages 167-179.
    7. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 4, pages 71-111.
    8. Platt, Harlan D. & Platt, Marjorie B., 2006. "Understanding Differences Between Financial Distress and Bankruptcy," Review of Applied Economics, Lincoln University, Department of Financial and Business Systems, vol. 2(2), pages 1-17.
    9. 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.
    10. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    11. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    12. G. S. Maddala & Shaowen Wu, 1999. "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(S1), pages 631-652, November.
    13. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure - Reply," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 4, pages 123-127.
    14. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
    15. repec:bla:obuest:v:61:y:1999:i:0:p:631-52 is not listed on IDEAS
    16. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    Full references (including those not matched with items on IDEAS)

    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. Soo Young Kim, 2018. "Predicting hospitality financial distress with ensemble models: the case of US hotels, restaurants, and amusement and recreation," Service Business, Springer;Pan-Pacific Business Association, vol. 12(3), pages 483-503, September.
    2. T.G. Saji, 2018. "Financial Distress and Stock Market Failures: Lessons from Indian Realty Sector," Vision, , vol. 22(1), pages 50-60, March.
    3. 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.
    4. Mário S. Céu & Raquel M. Gaspar, 2023. "Financial Distress in European Vineyards and Olive Groves," Working Papers REM 2023/0266, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    5. Shilpa Shetty H. & Theresa Nithila Vincent, 2024. "Corporate Default Prediction Model: Evidence from the Indian Industrial Sector," Vision, , vol. 28(3), pages 344-360, June.
    6. Zhou, Fanyin & Fu, Lijun & Li, Zhiyong & Xu, Jiawei, 2022. "The recurrence of financial distress: A survival analysis," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1100-1115.
    7. Enrico Supino & Nicola Piras, 2022. "Le performance dei modelli di credit scoring in contesti di forte instabilit? macroeconomica: il ruolo delle Reti Neurali Artificiali," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2022(2), pages 41-61.
    8. Nagmi Moftah Aimer, 2020. "Renewable energy consumption, financial development and economic growth: Evidence from panel data for the Middle East and North African countries," Economics Bulletin, AccessEcon, vol. 40(3), pages 2058-2072.
    9. Youssef Zizi & Mohamed Oudgou & Abdeslam El Moudden, 2020. "Determinants and Predictors of SMEs’ Financial Failure: A Logistic Regression Approach," Risks, MDPI, vol. 8(4), pages 1-21, October.
    10. Thao Tran & Ngoc Hong Nguyen & Binh Thien Le & Nam Thanh Vu & Duc Hong Vo, 2023. "Examining financial distress of the Vietnamese listed firms using accounting-based models," PLOS ONE, Public Library of Science, vol. 18(5), pages 1-17, May.
    11. Ángel Beade & Manuel Rodríguez & José Santos, 2024. "Multiperiod Bankruptcy Prediction Models with Interpretable Single Models," Computational Economics, Springer;Society for Computational Economics, vol. 64(3), pages 1357-1390, September.
    12. Jaroslava Hlouskova & Martin Wagner, 2006. "The Performance of Panel Unit Root and Stationarity Tests: Results from a Large Scale Simulation Study," Econometric Reviews, Taylor & Francis Journals, vol. 25(1), pages 85-116.
    13. Sallahuddin Hassan & Zalila Othman & Mohd Zaini Abd Karim, 2011. "Private and Public Investment in Malaysia: A Panel Time-Series Analysis," International Journal of Economics and Financial Issues, Econjournals, vol. 1(4), pages 199-210.
    14. Hui Li & Ting Sun & Jinquan Zhang, 2024. "Prediction of corporate financial distress based on corporate social responsibility: New evidence from DANP, VWP and MEOWA weights methodologies," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(5), pages 4537-4565, December.
    15. Amin Jan & Maran Marimuthu & Muhammad Kashif Shad & Haseeb ur-Rehman & Muhammad Zahid & Ahmad Ali Jan, 2019. "Bankruptcy profile of the Islamic and conventional banks in Malaysia: a post-crisis period analysis," Economic Change and Restructuring, Springer, vol. 52(1), pages 67-87, February.
    16. Fayçal Mraihi, 2016. "Distressed Company Prediction Using Logistic Regression: Tunisian’s Case," Quarterly Journal of Business Studies, Research Academy of Social Sciences, vol. 2(1), pages 34-54.
    17. 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.
    18. Richard Oduro & Michael Amoh Aseidu, 2017. "A Model to Predict Corporate Failure in the Developing Economies: A Case of Listed Companies on the Ghana Stock Exchange," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(4), pages 1-5.
    19. Gharehgozli, Orkideh, 2021. "An empirical comparison between a regression framework and the Synthetic Control Method," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 70-81.
    20. Skare, Marinko & PORADA-ROCHON, Małgorzata, 2022. "The role of innovation in sustainable growth: A dynamic panel study on micro and macro levels 1990–2019," Technological Forecasting and Social Change, Elsevier, vol. 175(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

    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:cvv:journ5:v:5:y:2018:i:4:p:321-336. 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: Bilal KARGI (email available below). General contact details of provider: https://journals.econsciences.com/index.php/JEL .

    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.