Determinants of agricultural companies’ financial performance: The experience of Poland, Slovakia and Ukraine

  • Received December 19, 2022;
    Accepted February 1, 2023;
    Published February 7, 2023
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/imfi.20(1).2023.10
  • Article Info
    Volume 20 2023, Issue #1, pp. 99-111
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This work is licensed under a Creative Commons Attribution 4.0 International License

The purpose of the study is to conduct a comparative analysis of the determinants affecting the financial performance of agricultural enterprises in Poland, Slovakia and Ukraine. As the main research method, panel data regression analysis was used to analyze data from 34 Polish, 123 Slovak, and 305 Ukrainian agricultural companies for the period 2017–2020. To analyze the links between financial performance measures and its determinants, nine models were developed based on three selected dependent variables (Return on Assets, Return on Equity, Return on Sales) in each of the countries studied. Seven independent variables were used, such as Leverage, Long-Term Debt to Assets, Short-Term Debt to Assets, Debt to Equity, Current Ratio, Asset Tangibility, Capital Intensity, and two control variables such as Size and Dummy variable for legal form. The most significant impact on the financial performance of agricultural enterprises has: for Polish enterprises – Return on Assets – Leverage and Asset Tangibility, Return on Equity – Debt to Equity and Dummy variable for legal form, Return on Sales – Current Ratio, Capital Intensity, and Size; for Slovak enterprises – Return on Assets – Current Ratio, Return on Equity – Debt to Equity, Return on Sales – Current Ratio, and Capital Intensity; for Ukrainian enterprises – Return on Assets – Leverage and Size, Return on Equity – Debt to Equity, and Current Ratio, Return on Sales – Capital Intensity.

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    • Table 1. Variable definitions, calculation and abbreviations
    • Table 2. Descriptive statistics (based on observations: 1:1 – 34:4 (Poland); 1:1 – 123:4 (Slovakia); 1:1 – 305:4 (Ukraine))
    • Table 3. Results of panel data estimate parameter selection for each of the models used
    • Table A1. Model 1-9 (ROA, ROE, ROS). OLS, FEM, REM, using the observations: 1-136 (Poland); 1-492 (Slovakia); 1-1220 (Ukraine)
    • Conceptualization
      Serhii Lehenchuk, Jitka Meluchová
    • Formal Analysis
      Serhii Lehenchuk, Nataliya Zdyrko, Volodymyr Voskalo
    • Methodology
      Serhii Lehenchuk
    • Project administration
      Serhii Lehenchuk
    • Software
      Serhii Lehenchuk, Lyudmyla Chyzhevska, Volodymyr Voskalo
    • Supervision
      Serhii Lehenchuk, Lyudmyla Chyzhevska
    • Writing – original draft
      Serhii Lehenchuk, Lyudmyla Chyzhevska, Jitka Meluchová
    • Writing – review & editing
      Serhii Lehenchuk, Lyudmyla Chyzhevska
    • Data curation
      Lyudmyla Chyzhevska, Jitka Meluchová, Volodymyr Voskalo
    • Funding acquisition
      Jitka Meluchová, Nataliya Zdyrko, Volodymyr Voskalo
    • Validation
      Jitka Meluchová, Nataliya Zdyrko, Volodymyr Voskalo
    • Visualization
      Jitka Meluchová, Nataliya Zdyrko, Volodymyr Voskalo
    • Investigation
      Nataliya Zdyrko, Volodymyr Voskalo
    • Resources
      Nataliya Zdyrko, Volodymyr Voskalo