ANALYSIS OF THE POSSIBILITY OF BANKRUPTCY IN MEDIUM-SIZED AGRIBUSINESS COMPANIES IN AP VOJVODINA

Bogdan Jocić; Dragan Milić; Vladislav Zekić; Dragana Novaković; Tihomir Novaković; Zoran Ilić

doi:10.59267/ekoPolj2402469J

Authors

Bogdan Jocić University of Novi Sad, Faculty of Agriculture, Novi Sad, Serbia https://orcid.org/0000-0002-1745-3255
Dragan Milić University of Novi Sad, Faculty of Agriculture, Novi Sad, Serbia https://orcid.org/0000-0003-0377-1540
Vladislav Zekić University of Novi Sad, Faculty of Agriculture, Novi Sad, Serbia https://orcid.org/0000-0002-7377-2402
Dragana Novaković University of Novi Sad, Faculty of Agriculture, Novi Sad, Serbia https://orcid.org/0000-0002-1924-6196
Tihomir Novaković University of Novi Sad, Faculty of Agriculture, Novi Sad, Serbia https://orcid.org/0000-0002-8405-3403
Zoran Ilić ECOVIS FinAudit doo Beograd, Serbia https://orcid.org/0000-0001-6955-6443

DOI:

https://doi.org/10.59267/ekoPolj2402469J

Keywords:

Altman Z’ scor, Kralicek Quick test, Springate model, agriculture, food industry

Abstract

In the context of a volatile economy marked by diverse global crises, it becomes imperative to proactively assess the potential insolvency among economic entities. This study focuses on medium-sized companies involved in agricultural and food production within the AP Vojvodina, spanning the time frame from 2018 to 2022. The primary objective is to assess the likelihood of bankruptcy within the observed companies, applying Altman’s modified Z score (Z’), Kralicek Quick test and the Springate model. The data utilized for this research are sourced from the financial reports of the observed companies. Based on the performed analysis, it can be concluded that the modified Altman’s Z’ score and the Springate model in most cases gave identical results on the occurrence of bankruptcy. Using the Kralicek Quick test, the solvency ratings are quite divergent. In the observed period, the possibility of bankruptcy was higher for agricultural companies compared to ones from the food industry.

Downloads

Download data is not yet available.

References

Alihodžić, A. (2013). Testing the Kralicek DF indicator application on the Belgrade Stock Exchange. Banking, 3, 70-95.

Altman, E. I. (1983). Corporate Financial Distress and Bankruptcy. Wiley

Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589-609. https://doi.org/10.1111/j.1540-6261.1968.tb00843.x

Altman, E. I., Danovi, A., Falini, A. (2013). Z-Score Models’ application to Italian companies subject to extraordinary administration. Journal of Applied Finance, 23(1): 128–137.

Angelova, R., & Stoyancheva, D. (2023). Digitalization, financial insolvency and bankruptcy risk forecasting of Bulgarian agricultural enterprises. Scientific Papers Series Management, Economic Engineering in Agriculture & Rural Development, 23(2).

Bencová, T., Boháčiková, A., Tóth, M., & Pindešová, D. (2021). Are Slovak farms financially healthier as a result of the Common Agricultural Policy of the European Union? In SHS Web of Conferences (Vol. 129, p. 09002). EDP Sciences.

Bernhardsen, E. (2001). A model of bankruptcy prediction (No. 2001/10). Working Paper. Available at: https://www.econstor.eu/bitstream/10419/209799/1/nb-wp2001-10.pdf (assesed 08.02.2024.).

Bordeianu, G. D., Radu, F., Paraschivescu, M. D., & Păvăloaia, W. (2011). Analysis models of the bankruptcy risk. Economy Transdisciplinarity Cognition, 14(1), 248-259.

Cîrciumaru, D. (2011). The Analysis of the bankruptcy risk for the Romanian companies. Case study: The food Industry. REVISTA ECONOMICĂ, 132.

Didenko, K., Meziels, J., and Voronova, I. (2012). Assessment of enterprises insolvency: challenges and opportunities. Economics and Management, 17(1), 69-76.

Grice J.S., Dugan M.T., (2001), The limitations of bankruptcy prediction models: Some cautions for the researchers. Review of Quantitative Finance and Accounting, 17.

Jakšić, D., Mijić, K., Zekić, S., Poljašević, J. (2015). Comparative profitability analysis of milk production companies to milk processing companies in Serbia. Custose@gronegocio on line, 11 (3), 206-226.

Karas, M., Reznakova, M., & Pokorny, P. (2017). Predicting bankruptcy of agriculture companies: Validating selected models. Polish Journal of Management Studies, 15(1), 110-120.

Katchova, A. L., Enlow, S. J. (2013). Financial Performance of Publicly Traded Agribusiness. Agricultural Finance Review, no. 73 (2013), pp. 58–73.

Khorasgani, A. (2011). Optimal accounting based default prediction model for the UK SMEs. Proceedings of ASBBS. ASBBS Annual Conference: Las Vegas, 18 (1), 149-168.

Kovács, S., Fróna, D., & Rózsa, A. (2020). ANALYSING THE SITUATION OF AGRICULTURAL ENTERPRISES IN LIQUIDATION BY MEANS OF BANKRUPTCY PREDICTION MODELS. SEA: Practical Application of Science, 8(1).

Kralicek, P. (2007). Income and asset analysis (quick test). Business management consulting, available at: http://www.kralicek.at/pdf/qr_druck.pdf (assesed 07.12.2023.).

Kuběnka, M. (2016). The strictness of traditional indicators for creditworthiness measuring, in The 10th International Days of Statistics and Economics, Conference Proceedings, Prague, September 8-10, Libuše Macáková, Melandrium, 985-995.

Maksimovic, V., & Phillips, G. (1998). Asset Efficiency and Reallocation Decisions of Bankrupt Firms. The Journal of Finance, 53 (5), pp. 1495-1532.

Milić, D., Tekić, D., Zekić, V., Novaković, T., Popov, M., & Mihajlov, Z. (2021). Bankruptcy prediction models for large agribusiness companies in AP Vojvodina. Economics of Agriculture, 68(3), 805-822.

Niemann M., Schmidt J.H., Neukirchen M., 2008, Improving performance of corporate rating prediction models by reducing financial ratio heterogeneity. Journal of Banking and Finance, 32.

Opler, T., & Titman, S. (1994). Financial Distress and Corporate Performance. Journal Of Finance, 49 (3), pp. 1015-1040.

Platt D.H., Platt M.B., 1990, Development of a Class of Stable Predictive Variables: The Case of Bankruptcy Prediction. Journal of Business Finance and Accounting, 17.

Rajin, D., Milenković, D., & Radojević, T. (2016). Bankruptcy prediction models in the Serbian agricultural sector. Economics of Agriculture, 63(1), 89-105.

Serbian Business Registers Agency: financial reports for observed companies, available at: https://fin.apr.gov.rs/JavnaPretraga (type name of companies in proper search bar, assessed 05.02.2024).

Statistical Office of the Republic of Serbia (SORS), (2018): Survey on the structure of agricultural holdings, Land, available at: https://publikacije.stat.gov.rs/G2019/Pdf/G20196003.pdf (assessed 12.02.2024).

Springate, Gordon L., “Predicting the Possibility of Failure in a Canadian Firm: Discriminant Analysis “, Unpublished Master of Business Administration Project, Simon Fraser University, (January 1978).

Sušický, J. (2011). Applicability of Bankruptcy Models at Agricultural Companies. Economic Studies & Analyses/Acta VSFS, 5(3).

Tekić, D., Mutavdžić, B., Novković, N., Novaković, T., & Vukelić, N. (2020). Analysis of the financial position of mill companies in Vojvodina. Journal on Processing and Energy in Agriculture, 24(3-4), 119-122.

Stoyancheva, D., & Angelova, R. (2023). Assessment of financial sustainability and risk of bankruptcy of agricultural enterprises in Bulgaria. In SHS Web of Conferences (Vol. 176, p. 03002). EDP Sciences.

Wu Y., Gaunt C., Gray S., 2010, A comparison of alternative bankruptcy prediction models. Journal of Contemporary Accounting and Economics, 6.

Zarei, S., Dadashi, I., i Akbari, M. A. (jul 2012). Localized distress prediction models in the economic environment of Iran. African Journal of Business Management, 6 (29), 8651-8658.

Zenzerović, R., & Peruško, T. (2006). Kratki osvrt na modele za predviđanje stečaja. Ekonomska istraživanja 19(2), 132–151. [in English: Short retrospection on bankruptcy prediction models (2006). Economic Research, 19(2), 132–151].