The reciprocal effect of environmental, social, and governance (ESG) practices and tax aggressiveness in Indonesian and Malaysian companies
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DOIhttp://dx.doi.org/10.21511/ppm.23(1).2025.25
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Article InfoVolume 23 2025, Issue #1, pp. 339-351
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Creative Commons Attribution 4.0 International License
This study highlights the complexity of the relationship between sustainability performance, environment, social and governance (ESG) reporting, and tax aggressiveness, which is a critical concern amidst the increasing demands for corporate social accountability. Companies in Indonesia and Malaysia, especially those in the non-financial sector, face increasing regulatory pressure to meet ESG standards. This study uses 263 Indonesian and 311 Malaysian companies as samples because both countries are prominent emerging markets in Southeast Asia with fast-growing economies, diverse industries, and abundant natural resources. However, aggressive tax avoidance remains a common strategy to maintain financial flexibility. This study aims to examine whether companies with high ESG performance tend to reduce tax avoidance practices or use it as a strategy to cover ESG costs. Through 2SLS regression analysis on 2012–2021 data, the results show that ESG performance has a significant positive effect on tax aggressiveness, where companies with high ESG performance also tend to engage in tax avoidance to cover ESG costs. Conversely, tax aggressiveness positively affects ESG performance because companies increase ESG engagement to reduce reputational risks from aggressive tax practices. The simultaneous test found a reciprocal relationship between the two variables with an R² value of 29.4% for tax aggressiveness and 63.1% for ESG performance. This study suggests stricter regulations to reduce tax avoidance in companies with high ESG performance and provides insights for policymakers in Southeast Asia.
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JEL Classification (Paper profile tab)Q56, H26, M41, M48
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References28
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Tables5
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Figures0
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- Table 1. Definition and operationalization of the variables
- Table 2. Sample selection criteria
- Table 3. Descriptive statistics
- Table 4. Multiple regression results for model 1
- Table 5. Multiple regression results for model 2
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