Impact of economic policy uncertainty on audit fees: Evidence from Chinese listed companies

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High economic policy uncertainty in China amplifies operational risks and managerial pressure for businesses while driving the demand for independent audits. However, previous studies have paid limited attention to the impact of economic policy uncertainty on audit fees. This study aims to examine the impact of economic policy uncertainty on audit fees and to test whether the internal control quality will moderate this association at the firm level. This study employs the economic policy uncertainty index to measure uncertainty. The paper examines 3,469 Chinese A-share listed companies from 2007 to 2020, using STATA 17 for fixed-effects regression on panel data. The results show a robust positive association between economic policy uncertainty and audit fees (β = 0.0302, p < 0.001). However, this association is weaker for companies with better internal control quality (β = –0.0229, p < 0.001), suggesting that effective internal controls can mitigate the impact of economic policy uncertainty on audit fees. Furthermore, the findings indicate that this positive association is weaker for state-owned companies compared to non-state-owned companies (β = –0.0170, p < 0.001). At the same time, the study does not establish a significant difference in the positive association between TOP 10 and non-TOP 10 accounting firms. This study examines the adverse effects of economic policy uncertainty from the perspective of audit fees. The results have implications for stakeholders, including the need for companies to establish effective internal controls and good government-business relationships and for governments to reduce economic policy uncertainty and increase transparency in their policies.

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    • Figure 1. Research framework
    • Table 1. Sample selection procedure
    • Table 2. Sample distribution by year and industry
    • Table 3. Descriptive statistics
    • Table 4. Pairwise correlations analysis
    • Table 5. Main regression analysis
    • Table 6. Moderating effect test
    • Table 7. Robustness check
    • Table 8. Heterogeneity analysis
    • Table A1. Variables and definition
    • Conceptualization
      Ming Cheng, Chonlavit Sutunyarak
    • Data curation
      Ming Cheng
    • Formal Analysis
      Ming Cheng, Chonlavit Sutunyarak
    • Investigation
      Ming Cheng, Chonlavit Sutunyarak
    • Methodology
      Ming Cheng, Chonlavit Sutunyarak
    • Software
      Ming Cheng
    • Validation
      Ming Cheng, Chonlavit Sutunyarak
    • Visualization
      Ming Cheng
    • Writing – original draft
      Ming Cheng
    • Writing – review & editing
      Ming Cheng, Chonlavit Sutunyarak
    • Project administration
      Chonlavit Sutunyarak
    • Resources
      Chonlavit Sutunyarak
    • Supervision
      Chonlavit Sutunyarak