Impact of Executive Compensation Structures on Firm Risk-Taking Behavior

Abstract

This study examines the impact of executive compensation structures on firm risk-taking behaviour in Indian manufacturing firms over the period 2015–2024. Grounded in agency theory and related incentive-based frameworks, the study investigates how different components of executive pay—including salary, bonus, stock options, and equity-based compensation—influence corporate risk decisions. Using secondary panel data from listed manufacturing firms, the analysis employs pooled OLS, fixed effects, and random effects models, along with Hausman specification tests, quantile regression, and robustness checks using alternative risk measures. The empirical findings reveal that incentive-based compensation, particularly stock options and equity-based pay, is positively and significantly associated with firm risk-taking across financial, market, and investment dimensions. In contrast, fixed salary is negatively associated with risk-taking, indicating a stabilising and risk-averse effect. Bonus compensation shows a moderate positive effect, primarily linked to short-term risk incentives. The results further indicate that corporate governance significantly moderates the compensation–risk relationship by constraining excessive risk-taking induced by incentive-based pay. Quantile regression results confirm heterogeneity in effects, with stronger impacts observed among high-risk firms. The study contributes to the literature by providing comprehensive evidence from an emerging economy context and highlighting the importance of compensation design in shaping managerial behaviour. The findings have important implications for corporate boards and policymakers in balancing incentive alignment with risk control to ensure sustainable firm performance.

Received: 2026-04-15 | Revised: 2026-06-24 | Accepted: 2026-06-26 | Published: 2026-06-30

Declarations

Competing interests: The authors declare no competing interests.

Data availability statement: Data will be made available on reasonable request from the corresponding author.

Funding: This research received no external funding.

Clinical Trial Number: Not Applicable.

Declaration of using generative AI: During the preparation of this work the author(s) used ChatGPT in order to correct the grammatical errors. After using this tool/service, the author(s) reviewed and edited the content as needed and take full responsibility for the content of the published article.

Author Contributions: S.S.: Conceptualization, methodology, writing—original draft preparation, writing—review and editing. All authors have read and agreed to the published version of the manuscript.