Factors affecting the dividend policy of non-financial joint-stock companies in Ukraine

  • Received June 24, 2020;
    Accepted July 27, 2020;
    Published August 7, 2020
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/imfi.17(3).2020.04
  • Article Info
    Volume 17 2020, Issue #3, pp. 40-53
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This work is licensed under a Creative Commons Attribution 4.0 International License

Dividend policy, as part of corporate governance, is largely dependent on the institutional environment in which companies operate. The study aims to determine factors affecting dividend policy in the conditions of the Ukrainian underdeveloped stock market, legal insecurity of minority shareholders, high cost and concentration of capital. For this purpose, hypotheses about the impact of a company’s financial state, size, business risk, and ownership structure on dividend payments were tested using a sample of 58 Ukrainian non-financial public joint-stock companies and applying Interactive tree classification techniques (C&RT). The resulting classification model for predicting dividend decisions correctly classifies 92.86% of companies that paid dividends and 93.3% of companies that did not. The findings, based on the classification tree and importance scale, prove the hypothesis that companies in which individuals and institutional investors have a controlling interest are more likely to pay dividends than other non-state companies. The financial indicators accurately classify only those firms that do not pay dividends, and business risk does not affect classification accuracy at all. The paper substantiates the ways of using the study findings for economic regulation, protection of minority shareholders’ rights, and proliferation of modern corporate governance practices.

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    • Figure 1. Classification tree related to factors determining a dividend policy
    • Figure 2. Receiver operating characteristic for the dividend payment (Area under curve: 0.958333; Gini: 0.916667)
    • Figure 3. Importance plot
    • Table 1. Classification accuracy
    • Conceptualization
      Heorhiy Rohov
    • Formal Analysis
      Heorhiy Rohov, Nataliya Shulga
    • Methodology
      Heorhiy Rohov, Oleh Kolodiziev
    • Software
      Heorhiy Rohov
    • Writing – original draft
      Heorhiy Rohov, Oleh Kolodiziev, Nataliya Shulga
    • Data curation
      Oleh Kolodiziev, Tetiana Riabovolyk
    • Supervision
      Oleh Kolodiziev
    • Validation
      Oleh Kolodiziev, Tetiana Riabovolyk
    • Investigation
      Nataliya Shulga
    • Resources
      Nataliya Shulga, Tetiana Riabovolyk
    • Funding acquisition
      Mykhailo Krupka
    • Project administration
      Mykhailo Krupka
    • Visualization
      Mykhailo Krupka
    • Writing – review & editing
      Mykhailo Krupka, Tetiana Riabovolyk