Tax compliance determinants: empirical evidence from Croatia
Abstract
Governments ensure majority of their revenues through taxes. If properly designed, taxation policies can be mechanisms of promoting sustainable economic development and inclusive economic growth. However, the main issue of government authorities remains achieving tax compliance among taxpayers. The question of noncompliance intersects different fields from public finance, law, ethics, and its complexity presents a challenge for the society in general.
This study aims to examine the influence of chosen economic and psychological determinants on tax compliance. In order to identify the determinants of taxpayers’ behaviour, a total of 862 questionnaires were administered and collected directly from Croatian taxpayers. Partial least squares structural equation modelling (PLS-SEM) was applied to analyse the survey data. The results suggest that social norms and tax morale influence taxpayers’ compliance significantly.
Overall, findings of this study contribute to the better understanding of tax compliance and its determinants in the context of a genuine paradigm shift in the field. This emphasizes the importance of including and exploring psychological determinants in tax compliance analysis.
Keyword : tax compliance, taxation policies, taxpayers’ behaviour, economic determinants, psychological determinants, PLS-SEM
How to Cite
Paleka, H., Karanović, G., & Badulescu, D. (2022). Tax compliance determinants: empirical evidence from Croatia. Technological and Economic Development of Economy, 28(6), 1915–1932. https://doi.org/10.3846/tede.2022.18130
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Górecki, M. A., & Letki, N. (2020). Social norms moderate the effect of tax system on tax evasion: Evidence from a large-scale survey experiment. Journal of Business Ethics. https://doi.org/10.1007/s10551-020-04502-8
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Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
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