Determinants of Tax Morale in Greece – UROP Spring Symposium 2024

Determinants of Tax Morale in Greece

Sophia Guo

Pronouns: she/her

Research Mentor(s): Antonios Koumpias
Research Mentor School/College/Department: Social Sciences, College of Arts and Sciences, University of Michigan-Dearborn / Other
Program:
Authors: Antonios Koumpias, Sophia Guo
Session: Session 5: 2:40 pm – 3:30 pm
Poster: 42

Abstract

The purpose of this paper is to analyze determinants of voluntary tax compliance, or tax morale, in Greece. Despite extensive literature identifying factors that are predictive of tax morale in developed and developing economies around the world, there is no evidence about Greece using canonical survey measures to this day. This study contributes the first estimate of determinants of tax morale in Greece using the standard survey dataset employed in the literature. We use information from the 7th wave of the World Value Survey that collected information on Greek individuals’ perceptions about tax compliance in 2017. We employ logistic regression to identify the association between individual-level demographics, socio-economic characteristics and institutional beliefs and a binary measure of high tax morale. Our findings are mainly in agreement with prior estimates in the literature identifying self-employed individuals as the least likely to voluntarily comply with their tax obligations. To uncover mechanisms driving our results, we investigate whether regional differences in the intensity of the negative economic adjustment of NUTS level-2 GDP influenced tax morale to find a modest and monotonic negative association of GDP reductions on tax morale. Our findings have important policy implications by shedding light on the characteristics of individuals who may be susceptible to non-compliance. These insights directly inform targeted strategies for tax audits and detect certain social beliefs that may require policy adjustment to promote and facilitate adherence to tax compliance norms.

Physical Sciences, Social Sciences

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