Pay disparity, investment in internal control personnel, and a firm’s investment inefficiency: Korean evidence

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The purpose of this study is to investigate the relationship between pay disparity and a company’s investment inefficiency, and to explore the moderating influence of investment in internal control personnel on this relationship. The global concern over pay disparity has intensified as executive compensation soars to unparalleled heights, while employee wages remain static. Utilizing a fixed-effect regression model and analyzing 5,407 observations from Korean listed companies between 2018 and 2020, the study shows a positive association between pay disparity (coef = 0.034, p-value < 0.01) and investment inefficiency, with pay disparity increasing the level of investment inefficiency by fostering overinvestment. Furthermore, the study shows that the interaction term between pay disparity and quantitative (coef = –0.246, p-value < 0.01) and qualitative (coef = –2.104, p-value < 0.01) investments in internal control personnel is negative and significant, indicating that the positive link between pay disparity and investment inefficiency is lessened when there is a higher quantitative and qualitative investment in internal control personnel. By offering a more comprehensive understanding of the conflicting evidence about the impact of pay disparity and the role of investment in internal control personnel in moderating the negative effect of pay disparity on investment efficiency, this study contributes to the existing literature. The findings of the study suggest that companies aiming to minimize investment inefficiency should consider not only addressing pay disparity but also investing in internal control personnel.

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    • Table 1. Descriptive statistics
    • Table 2. Correlations (p-values below)
    • Table 3. Pay disparity and a firm’s investment inefficiency
    • Table 4. Role of human resource investment in IC on the association between pay disparity and investment inefficiency
    • Table 5. Additional analysis
    • Table A1. Variable definition
    • Conceptualization
      Inkyung Yoon, Dongjoon Choi
    • Data curation
      Inkyung Yoon
    • Formal Analysis
      Inkyung Yoon
    • Investigation
      Inkyung Yoon
    • Methodology
      Dongjoon Choi
    • Project administration
      Dongjoon Choi
    • Software
      Dongjoon Choi
    • Supervision
      Dongjoon Choi
    • Validation
      Dongjoon Choi
    • Resources
      Hansol Lee
    • Visualization
      Hansol Lee
    • Writing – original draft
      Hansol Lee
    • Writing – review & editing
      Hansol Lee