Advancing the multifactor model of Stochastic Frontier Analysis

Authors

DOI:

https://doi.org/10.15587/1729-4061.2021.235316

Keywords:

multifactor model, efficiency, stochastic method, bankruptcy, financial stability, panel data

Abstract

The concept of efficiency is important in economic science; at present, its role in every sector of the economy is growing. Evaluating an enterprise’s efficiency makes it possible to implement a correct and profitable strategy of resource allocation, which shows its potential level Given an annual increase in the number of bankrupt enterprises, the issue of estimating the efficiency of enterprises is relevant for both their owners and managers, as well as for creditors. There are various methods and models for estimating the performance of enterprises. This work has assessed the efficiency of enterprises in the industrial sector over the period of 2017‒2018. Stochastic Frontier Analysis is based on the stochastic model of production function. The classic SFA method is based on the production function of the company, which relates the volume of output to the volume of resources consumed. At the same time, the SFA model uses several inputs (volumes of resources consumed) and only one output parameter ‒ the volume of production.

In order to achieve more precise results, a given model has been modified. The model allows several key financial indicators to be taken into consideration as outputs at the same time, based on which the financial activities of the studied economic entities are assessed. The result of the work involving open sources has revealed how the efficiency of different enterprises in the same industry changes over several years. It is shown that the modified Stochastic Frontier Analysis model could be used to assess financial stability and predict bankruptcy.

Supporting Agency

  • Работа подготовлена при финансовой поддержке гранта РФФИ (проект № 20-31-90100).

Author Biographies

Arthur Mitsel, Tomsk State University of Control Systems and Radioelectronics; Tomsk Polytechnic University

Doctor of Technical Sciences, Professor

Department of Automated Control Systems

Department of Digital Technologies and Experimental Physics

Aliya Alimkhanova, Tomsk State University of Control Systems and Radioelectronics

Postgraduate Student

Department of Automated Control Systems

Marina Grigorieva, Tomsk State University of Control Systems and Radioelectronics

PhD, Associate Professor

Department of Automated Control Systems

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Published

2021-06-29

How to Cite

Mitsel, A., Alimkhanova, A., & Grigorieva, M. (2021). Advancing the multifactor model of Stochastic Frontier Analysis . Eastern-European Journal of Enterprise Technologies, 3(4 (111), 58–64. https://doi.org/10.15587/1729-4061.2021.235316

Issue

Vol. 3 No. 4 (111) (2021): Mathematics and Cybernetics - applied aspects

Section

Mathematics and Cybernetics - applied aspects

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Copyright (c) 2021 Arthur Mitsel, Aliya Alimkhanova, Marina Grigorieva

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