|Title:||The use of discriminant analysis in the assessment of municipal company's financial health|
Vol. 12, No 2, 2019
Published date: 06-2019 (print) / 06-2019 (online)
Economics & Sociology
ISSN: 2071-789X, eISSN: 2306-3459
Yuriy Fedkovych Chernivtsi National University
Yuriy Fedkovych Chernivtsi National University
|Keywords:||municipal company, financial health, multiple discriminant model, M-Score, CEE countries|
|JEL classification:||J23, E24, B59|
Decentralization processes in the CEE countries have stimulated the search for measures of financial health of municipal companies that would be comparable and understandable to a broad range of stakeholders. In this study, we have developed a five-factor discriminant model for assessing municipal company’s financial health (M-Score model) using data on 50 Ukrainian companies during 2014-2017. The final test sample consisted of 71 companies operating in Bulgaria, Croatia, Czech Republic, Poland, Romania and Ukraine. Our findings can be summarized as follows. First, the empirical model suggests that the equity-assets ratio, the current ratio, and the average accounts receivable turnover have both the highest discriminatory power and the greatest impact on the municipal company’s financial health. Secondly, we provide convincing evidence that the municipal company’s financial health does not depend on the region, but on the nature of its activity and the purpose of enterprise activity. In particular, water and energy utilities are generally financially unhealthy, and out of 45 so-called necessary enterprises, only 12 are classified as financially healthy. The company’s M-Score will help managers, lenders, investors, local authorities, and the public to answer the following questions: Can the company avoid financial default? What is its position at the local level? What is its place in the industry?
1. Alsaied, J. (2017). Identification of Key Drivers for Municipal Utility Performance. Pursuit – The Journal of Undergraduate Research at the University of Tennessee, 8(1), 1-16.
2. Altman, E.A. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589-609.
3. Altman, E. I, & Hotchkiss, E. (2006). Corporate financial distress and bankruptcy (3rd ed.). New York, NY: John Wiley & Sons, Inc.
4. Altman, E. A. (2013). Predicting Financial Distress of Companies: Revisiting the Z-Score and ZETA® Models. In A. R. Bell, C. Brooks, & M. Prokopczuk (Eds.) Handbook of Research Methods and Applications in Empirical Finance; 428-456. Cheltenham, UK and Nor
5. Beecher, J. A., Dreese, G. R., & Landers, J. R. (1992). Viability Policies and Assessment Models for Small Water Utilities. Columbus, OH: The National Regulatory Research Institute.
6. Cabaleiro, R., Bush, E., & Vaamonde, A. (2013). Developing a method to assessing the municipal financial health. The American Review of Public Administration, 43(6), 729-751. https://doi.org/10.1177/0275074012451523
7. Cornell University, INSEAD, & WIPO. (2018). The Global Innovation Index 2018: Energizing the World with Innovation (11th ed.). Ithaca, Fontainebleau, and Geneva.
8. Cruz, N.F., & Marques, R. C. (2011). Viability of municipal companies in the provision of urban infrastructure services. Local Government Studies, 37(1), 93-110. doi: 10.1080/03003930.2010.548551
9. Government Information Division. (2004). Special Study: Municipal Enterprise Activities. St. Paul, MN: Minnesota Office of the State Auditor. Retrieved July 25, 2018, from https://www.auditor.state.mn.us/reports/gid/2004/enterprise/enterprise_04_report.pd
10. Jordan, J. L. (1998). Evaluating water system financial performance and financing options. Georgia water series, 3, 1-23.
11. Kicina, R. (2017). Methodology for assessment of financial health of state-owned and municipality-owned companies. INEKO. Retrieved June 30, 2018, from http://viitorul.org/files/ineko/2018/MD_Methodology%20for%20assessment%20of%20financial%20health%20of%2
12. Klinefelter, J. R., & Klinefelter, T. A. (2015). Minimalist investor maximum profits. New York, NY: Page Publishing, Inc.
13. Lihonenko, L. O., Tarasyuk, M. V., & Khilenko, O. O. (2005). Antykryzove upravlinnya pidpryyemstvom [Anti-crisis management of the enterprise]. Kyiv, Ukraine: NTEU.
14. Matejova, L., Placek, M., Krcpek, M., Pucek, M., & Ochrana, F. (2014). Economies of Scale – Empirical Evidence from the Czech Republic. Procedia Economics and Finance, 12, 403-411. https://doi.org/10.1016/S2212-5671(14)00361-X
15. Mihalovic, M. (2016). Performance Comparison of Multiple Discriminant Analysis and Logit Models in Bankruptcy Prediction. Economics and Sociology, 9(4), 101-118. doi: 10.14254/2071-789X.2016/9-4/6
16. Piotroski, J. D. (2000). Value investing: The use of historical financial statement information to separate winners from losers. Journal of Accounting Research, 38, 1-41.
17. Rencher, A. C. (2002). Methods of Multivariate Analysis (2nd ed.). New York, NY: John Wiley & Sons, Inc.
18. Romanova, A. I. (2012). Metod diagnostiki rezultatov proizvodstvenno-khozyaystvennoy deyatelnosti predpriyatiy sfery zhilishchno-kommunalnykh uslug [The diagnostic method is a result of industrial and business enterprises of housing and communal services]
19. Tabachnick, B. G., & Fidell, L.S. (1989). Using Multivariate Statistics (2nd ed.). New York, NY: HarperCollins.
20. Vasina, N.V. (2012). Modelirovaniye finansovogo sostoyaniya selskokhozyaystvennykh organizatsiy pri otsenke ikh kreditosposobnosti [Modeling the financial condition of agricultural organizations in assessing their creditworthiness]. Omsk, Russia: NOU VPO
21. Wibowo, A., & Alfen, H.W. (2015). Predicting the Probability of Default for Municipal Water Utilities in Indonesia. Public Works Management and Policy, 20(4), 337-359. https://doi.org/10.1177/1087724X14558269
22. Wirick, D.W., Borrows, J.D., & Goldberg, S. (1997). Evaluating water utility financial capacity with ratio analysis and discounted cash flows. Columbus, OH: The National Regulatory Research Institute.