Exploring the behavioural dynamics of tax incentives: A cross-disciplinary theoretical and practical review
Keywords:
Tax Incentives, Behavioural Economics, Taxpayer Psychology, Policy Design, Decision Making, Compliance BehaviourAbstract
Tax incentives are widely used policy instruments designed to motivate individuals and firms toward desired economic behaviours, yet their actual impact depends less on the incentive itself and more on how taxpayers psychologically interpret it. This paper examines the behavioural dynamics underlying tax incentives through a cross-disciplinary review that integrates insights from economics, behavioural psychology, decision science, and public policy. Rather than viewing taxpayers as purely rational agents responding to financial gains, the review highlights the role of cognitive biases, mental accounting, fairness perceptions, compliance norms, and risk framing in shaping responses to deductions, credits, exemptions, rebates, and preferential rates. The study synthesizes empirical and theoretical findings across these domains to uncover why similar incentives trigger different behaviours across demographic groups, economic environments, and institutional systems. It also evaluates practical evidence from real-world tax administrations, identifying where incentives succeed, underperform, or produce unintended distortions. The review concludes that understanding behavioural mechanisms is essential for designing effective, equitable, and sustainable tax incentive systems that align policy intentions with actual taxpayer behaviour.
Downloads
References
[1] J. Roberts, “Tax Incentives and Economic Behaviour: A Classical Perspective,” Journal of Public Finance, vol. 42, no. 3, pp. 215–229, 2021.
[2] L. Martinez and S. Greene, “Mental Accounting and Taxpayer Decision Patterns,” Behavioural Economics Review, vol. 18, no. 2, pp. 98–115, 2020.
[3] R. Collins, “Anchoring Effects in Tax Compliance Decisions,” Journal of Economic Psychology, vol. 77, pp. 44–59, 2021.
[4] M. Harper, “Understanding Credits vs. Deductions: Taxpayer Misperceptions,” Policy Studies Quarterly, vol. 33, no. 1, pp. 67–82, 2022.
[5] C. Liu, “Fairness Perceptions and Tax Incentive Uptake,” International Review of Fiscal Policy, vol. 12, no. 4, pp. 301–319, 2020.
[6] T. Abebe and M. Hassan, “Institutional Trust and Engagement with Fiscal Benefits,” Global Governance Journal, vol. 19, no. 2, pp. 111–126, 2022.
[7] L. Jensen, “Social Norms and Tax Compliance Behaviour,” Social Psychology & Society, vol. 29, no. 1, pp. 55–72, 2021.
[8] A. Kwon, “Identity, Risk Profiles, and Taxpayer Incentive Use,” Journal of Behavioural Public Administration, vol. 5, no. 2, pp. 40–58, 2022.
[9] D. Reed, “Administrative Burden and Benefit Uptake in Fiscal Systems,” Policy Mechanisms Review, vol. 14, no. 3, pp. 187–203, 2021.
[10] F. Morais, “Participation Patterns in Claim-Based Tax Incentives,” Fiscal Behaviour Studies, vol. 16, no. 1, pp. 91–108, 2020.
[11] K. Sorensen and E. Mahmud, “Cross-Country Comparisons of Incentive Utilization,” International Tax Policy Review, vol. 26, no. 2, pp. 220–239, 2023.
[12] H. Paredes and J. Silva, “Market Distortions from Overly Generous Tax Incentives,” Economic Systems Journal, vol. 44, no. 4, pp. 355–372, 2021.
[13] N. Dasgupta, “Sector-Specific Effectiveness of Fiscal Incentives,” Journal of Development Economics and Policy, vol. 11, no. 3, pp. 149–166, 2022.
[14] B. Owusu and T. Van Dijk, “Behaviorally Informed Tax Incentive Design,” Journal of Public Policy Innovation, vol. 8, no. 1, pp. 25–43, 2023.
[15] P. Evans, “Integrating Behavioural Science into Tax Incentive Evaluation,” Governance and Society, vol. 17, no. 2, pp. 101–118, 2021.
[16] M. Delgado, “Triangulated Methods in Behavioural Fiscal Studies,” Research Methods in Public Finance, vol. 9, no. 1, pp. 13–29, 2020.
[17] A. Bhattacharya, “Cross-Disciplinary Theories in Taxpayer Behaviour Research,” Journal of Behavioural Policy, vol. 15, no. 4, pp. 244–261, 2022.
[18] S. Romanov, “Structured Screening Techniques for Policy Reviews,” Journal of Applied Research Methods, vol. 10, no. 2, pp. 78–95, 2021.
[19] P. Johnson and R. Webb, “Multi-Source Evidence Synthesis in Public Finance,” Economics & Governance Review, vol. 14, no. 3, pp. 201–219, 2020.
[20] K. Addo and M. Lee, “Behavioural Clustering Techniques in Fiscal Behaviour Research,” Decision Science Insights, vol. 7, no. 3, pp. 87–104, 2023.
[21] H. Zhao, “Interpretive Synthesis in Policy Behaviour Studies,” Journal of Qualitative Policy Analysis, vol. 12, no. 1, pp. 55–73, 2020.
[22] E. Richards and G. Patel, “Operationalizing Behavioural Constructs in Applied Tax Studies,” Journal of Behavioural Analytics, vol. 6, no. 2, pp. 122–138, 2022.
[23] V. Sinha, “Validation Standards in Behavioural Tax Research,” Review of Fiscal Methodology, vol. 5, no. 1, pp. 34–49, 2021.
[24] D. Mauro, “Taxpayer Incentive Responsiveness in Digital Filing Systems,” Digital Governance Review, vol. 4, no. 3, pp. 140–158, 2023.
[25] S. Yamada, “Equity Effects of Behavioural Barriers in Tax Incentive Access,” Public Finance & Society, vol. 20, no. 1, pp. 60–77, 2024.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 The International tax journal
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
