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Factors affecting the inconsistency of dividend policy using dynamic panel data model

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  • Powell Gian Hartono

    (Satya Wacana Christian University
    STIE Jakarta International College)

  • Robiyanto Robiyanto

    (Satya Wacana Christian University)

Abstract

Dividend policy inconsistency is a rarely examined phenomenon that happens frequently and dominant. This research examines nine predictors that affect dividend policy inconsistency in manufacturing companies listed on the Indonesian Stock Exchange in 2013–2019. The developed hypotheses were tested using the dynamic panel data regression with FD-GMM and SYS-GMM techniques and three model specification tests. The results showed that profitability and lagged dividend are robust predictors of the two parameters estimated. Furthermore, of the seven unproven hypotheses, four predictors had a significant effect but different directions. Investment opportunity, company size, financial leverage, and company age are predictors proven in the SYS-GMM parameters estimated. These results are a proven predictor for practitioners to consider investors to obtain optimal returns and company management to formulate optimal dividend policies to support a stable and sustainable business. The research originality examined the predictors suspected of affecting dividend policy inconsistency with the relevant statistical tools.

Suggested Citation

  • Powell Gian Hartono & Robiyanto Robiyanto, 2023. "Factors affecting the inconsistency of dividend policy using dynamic panel data model," SN Business & Economics, Springer, vol. 3(2), pages 1-21, February.
    • Handle: RePEc:spr:snbeco:v:3:y:2023:i:2:d:10.1007_s43546-023-00431-6
    DOI: 10.1007/s43546-023-00431-6
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