<![CDATA[Introduction: This study aims to analyze the effect of tax risk, company age, and earnings management on cost of debt in infrastructure sector companies listed on the Indonesia Stock Exchange (IDX) during the period 2019 to 2023. The research addresses the inconsistency of previous findings and the unique characteristics of the infrastructure sector that make cost of debt a critical factor due to its capital-intensive nature and high dependence on external financing.Methods: The research adopts a quantitative approach using panel data regression analysis through EViews 12 software. The model is designed to test both direct and indirect effects between variables, particularly examining the simultaneous and partial influence of tax risk, company age, and earnings management on cost of debt. Data were collected from audited financial statements of infrastructure companies listed on IDX during the research period.Results: The results indicate that tax risk, company age, and earnings management simultaneously have a effect on cost of debt. However, individually, only company age shows a influence where more mature companies receive higher creditor confidence due to their established operational track record. In contrast, tax risk and earnings management do not show influence, reflecting the unique characteristics of the infrastructure sector with relatively stable tax structures and creditors' focus on objective information such as operational cash flows.Conclusion and suggestion: The findings emphasize the importance of company maturity in reducing information asymmetry between management and creditors in the infrastructure sector. While tax risk and earnings management did not show significant individual influence, the role of regulatory framework and capital-intensive characteristics remains crucial. The study contributes to strengthening Trade-Off Theory and Agency Theory in the infrastructure context. Future research is suggested to explore other potential factors such as credit rating, ownership structure, infrastructure project characteristics, and macroeconomic conditions to develop more robust predictive models for optimal financing decision-making and accurate risk assessment for creditors.]]>
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