Determinants of Financial Distress Using a Binary Approach: Evidence from Property and Real Estate Firms on the IDX (2014–2023)

Authors

  • Ida Ayu Fatmayuni Fakltas Ekonomi dan Bisnis, Universitas Slamet Riyadi, Surakarta, Jawa Tengah Author https://orcid.org/0009-0007-6408-3158
  • Rina Susanti Fakltas Ekonomi dan Bisnis, Universitas Slamet Riyadi, Surakarta, Jawa Tengah Author
  • Aditya Wardana Fakultas Ekonomi dan Bisnis, Universitas Pembangunan Nasional Veteran Yogyakarta, Sleman, DIY Author https://orcid.org/0009-0009-5325-6441

DOI:

https://doi.org/10.61994/equivalent.v4i1.1438

Keywords:

Financial distress, Profitability, Liquidity, Leverage, Asset efficiency, Cox regression

Abstract

The study explores factors that influence the probability of distress on IDX. The study focuses on property and real estate companies. The study measures distress, with a dummy variable, where 1 mark a distressed firm and 0 marks a healthy firm. I looked at profitability, liquidity, solvency and efficiency ratio as indicators. The study used a targeted sampling method to select 36 issuers observed from 2014 to 2023. I tested the relationship, between ratios and financial distress using a regression model. I see that the results show the profitability reduces the chance of the distress. I notice that when the profitability is higher the chance that a firm will face the distress goes down. I see that the liquidity raises the chance of the distress. I notice that when the liquidity is higher, in this sector the liquidity may point to working capital management. I find that the solvency does not change the chance of the distress. I find that the efficiency ratio does not change the chance of the distress either. I see that the findings show the profitability and the liquidity matter for predicting the distress, in the property and real estate industry. I find the study gives information for the investors the creditors and the regulators. The study helps the investors; the creditors and the regulators check the stability and find the warning signs.   

References

Abdioğlu, N. (2019). The Impact of Firm Specific Characteristics on The Relation Between Financial Distress And Capital Structure Decisions. Journal of Business Research - Turk, 11(2). https://doi.org/10.20491/isarder.2019.655

Altman, E. I., Iwanicz‐Drozdowska, M., Laitinen, E. K., & Suvas, A. (2017). Financial Distress Prediction in an International Context: A Review and Empirical Analysis of Altman’s Z‐ Score Model. Journal of International Financial Management & Accounting, 28(2), 131–171. https://doi.org/10.1111/jifm.12053

Amoa-Gyarteng, K. (2021). Corporate Financial Distress: The Impact of Profitability, Liquidity, Asset Productivity, Activity and Solvency. Journal of Accounting, Business and Management (JABM), 28(2). https://doi.org/10.31966/jabminternational.v28i2.447

Brigham, E. F., & Houston, J. F. (2019a). Fundamentals of Financial Management. In Cegage Learning (Vol. 34, Issue 5).

Brigham, E. F., & Houston, J. F. (2019b). Fundamentals of Financial Management. In Cengange Learning, Inc (Vol. 15e). Cengage Learning.

Brigham, E. F., & Houston, J. F. (2019c). Fundamentals of Financial Management 15 Edition. In Cengage Learning.

Ceylan, I. E. (2021). The Impact of Firm-Specific and Macroeconomic Factors on Financial Distress Risk: A Case Study from Turkey. Universal Journal of Accounting and Finance, 9(3), 506–517. https://doi.org/10.13189/ujaf.2021.090325

Chen, H. L. (2018). Development of a Stabled Corporate Bankruptcy Classification model: Evidence from Taiwan. International Journal of Economic Sciences, VII(1). https://doi.org/10.20472/es.2018.7.1.002

Çolak, M. S. (2021). A new multivariate approach for assessing corporate financial risk using balance sheets. Borsa Istanbul Review, 21(3). https://doi.org/10.1016/j.bir.2020.10.007

Crespí-Cladera, R., Martín-Oliver, A., & Pascual-Fuster, B. (2021). Financial distress in the hospitality industry during the Covid-19 disaster. Tourism Management, 85, 104301. https://doi.org/10.1016/j.tourman.2021.104301

Fatmayuni, I. A., Sri Dwi Ari Ambarwati, & Hendro Widjanarko. (2024). Determinant Financial Distress: Evidence Manufacture Company in Indonesia Stock Exchange 2018 – 2022. Accounting and Finance Studies, 4(1), 1–16. https://doi.org/10.47153/afs41.8502024

Gregova, E., Valaskova, K., Adamko, P., Tumpach, M., & Jaros, J. (2020). Predicting Financial Distress of Slovak Enterprises: Comparison of Selected Traditional and Learning Algorithms Methods. Sustainability, 12(10), 3954. https://doi.org/10.3390/su12103954

Hassan, E., Awais-E-Yazdan, M., Birau, R., & Paliu-Popa, L. (2023). Anticipating financial distress in monster sectors of Pakistan’s economy: an application of logit. Industria Textila, 74(3), 363–370. https://doi.org/10.35530/IT.074.03.2022105

Ibrahim, M. Z., & Azzam, ohsen E. A. Y. (2023). The Impact of Earnings Quality on the Corporate Financial Distress: Empirical Evidence from Egypt. المجلة العلمیة للدراسات والبحوث المالیة والتجاریة, 4(1), 37–67. https://doi.org/10.21608/cfdj.2023.258036

Isayas, Y. N. (2021). Financial distress and its determinants: Evidence from insurance companies in Ethiopia. Cogent Business & Management, 8(1). https://doi.org/10.1080/23311975.2021.1951110

Jensen, M. C., & Meckling, W. H. (1976). Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of Financial Economics, 3(4). https://doi.org/10.1016/0304-405X(76)90026-X

Kristanti, F. T., Rahayu, S., & Huda, A. N. (2016). The Determinant of Financial Distress on Indonesian Family Firm. Procedia - Social and Behavioral Sciences, 219, 440–447. https://doi.org/10.1016/j.sbspro.2016.05.018

Laskin, A. V. (2021). Measuring investor relations and financial communication: an empirical test of scales of public relations. Organicom, 18(35). https://doi.org/10.11606/issn.2238-2593.organicom.2021.183841

Liang, S.-Z., Hsu, M.-H., & Chou, T.-H. (2022). Effects of Celebrity–Product/Consumer Congruence on Consumer Confidence, Desire, and Motivation in Purchase Intention. Sustainability, 14(14), 8786. https://doi.org/10.3390/su14148786

Luu Thu, Q. (2023). Impact of earning management and business strategy on financial distress risk of Vietnamese companies. Cogent Economics & Finance, 11(1). https://doi.org/10.1080/23322039.2023.2183657

Roger Bougie, & Sekaran, U. (2016). Research Methods For Business: A Skill Building Approach, 7th Edition (7th ed.). Wiley.

Sehgal, S., Mishra, R. K., Deisting, F., & Vashisht, R. (2021). On the determinants and prediction of corporate financial distress in India. Managerial Finance, 47(10). https://doi.org/10.1108/MF-06-2020-0332

Spector, P. E. (2019). Do Not Cross Me: Optimizing the Use of Cross-Sectional Designs. Journal of Business and Psychology, 34(2). https://doi.org/10.1007/s10869-018-09613-8

Subramanyam, K. R. (2017). Financial Statement Analysis Eleventh Edition. In McGraw-Hill Education.

Tari, D. N. (2025). Tren IPO dalam 4 Dekade 1985-2025 di BEI, Emiten Makin Banyak Investor Makin Cuan. Market.Bisnis.Com.

Waqas, H., & Md-Rus, R. (2018). Predicting financial distress: Importance of accounting and firm-specific market variables for Pakistan’s listed firms. Cogent Economics & Finance, 6(1), 1545739. https://doi.org/10.1080/23322039.2018.1545739

Wruck, K. H. (1990). Financial distress, reorganization, and organizational efficiency. Journal of Financial Economics, 27(2). https://doi.org/10.1016/0304-405X(90)90063-6

Wu, J. (2022). An Empirical Study on Markowitz and Single Index Model. Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022), 648. https://doi.org/10.2991/aebmr.k.220307.461

Wu, S., Zhang, H., Tian, Y., & Shi, L. (2021). Financial Distress Warning: An Evaluation System including Ecological Efficiency. Discrete Dynamics in Nature and Society, 2021. https://doi.org/10.1155/2021/5605892

Zhu, L., Yan, D., Zhang, Z., & Chi, G. (2022). Financial Distress Prediction of Chinese Listed Companies Using the Combination of Optimization Model and Convolutional Neural Network. Mathematical Problems in Engineering, 2022. https://doi.org/10.1155/2022/9038992

Downloads

Published

2026-01-22

How to Cite

Fatmayuni, I. A., Susanti, R., & Wardana, A. (2026). Determinants of Financial Distress Using a Binary Approach: Evidence from Property and Real Estate Firms on the IDX (2014–2023). Equivalent : Journal of Economic, Accounting and Management, 4(1), 297-310. https://doi.org/10.61994/equivalent.v4i1.1438