The Fiscal Citizenship Project

Fiscal Citizenship and Tax Compliance

Multidimensional Tax Compliance Attitude

Christoffer Bruns, Martin Fochmann, Peter N. C. Mohr & Benno Torgler

Citizen tax compliance significantly dictates governmental fiscal capacities. Recognizing this, understanding the determinants of tax compliance remains paramount. While existing literature frequently isolates and tests individual determinants such as audit likelihood, penalty structures, tax morale, and perceived fairness, an integrative, bottom-up approach addressing the spectrum of tax compliance attitudes has largely been overlooked. Addressing this gap, our study constructs a multidimensional Tax Compliance Attitude Inventory (TCAI) by harmonizing real taxpayer responses with established theoretical underpinnings. Through factor analysis, we delineate four pivotal factors: (i) morale, (ii) monetary benefit, (iii) deterrence, and (iv) authority. Notably, morale and deterrence emerge as consistent influencers of tax compliance. Embracing this multidimensionality, our cluster analysis demarcates two distinct taxpayer personas: (a) moralists and (b) rationalists. Our findings underscore that moralists consistently exhibit higher tax compliance than their rationalist counterparts. We further present a streamlined classification algorithm to operationalize the TCAI in new datasets, minimizing item count. This work serves as a seminal contribution, offering both academia and tax authorities a robust, quantitative tool to gauge tax compliance attitudes.

Efficient Verification of Tax Returns: Can the Government Group its Citizens Without Acting in a Discriminatory Manner?

Angelika Mohr, supervised by Ralf Schenke

A poorly functioning tax authority that is unable to secure compliance negatively impacts tax morale and Fiscal Citizenship. Tax authorities in many different countries thus use automated risk management systems to categorise taxpayers according to the risk associated with their tax return. This aims to increase the efficiency and accuracy of tax collection.

To prevent circumvention by taxpayers and tax advisors, these systems are highly confidential, and their exact workings are therefore hidden from the public eye. This creates a risk of real and perceived discrimination of certain taxpayers, including migrant groups. This risk is especially high if complex algorithms or machine learning technologies are employed, which might lead to hidden bias.

Automated risk management systems can improve the effectiveness of the tax administration by increasing the risk of detection, thus creating additional incentive for taxpayer cooperation, as well as increasing societal pressure on taxpayers to act in a compliant manner. In this way, these systems can help improve Fiscal Citizenship.

However, this may be counteracted if such systems were shown to involve real or perceived discrimination of certain groups of taxpayers, which negatively impacts tax morale. This may decrease Fiscal Citizenship especially among migrant groups, as they are minorities who are more likely to experience discrimination.

This doctoral thesis asks which safeguards must be put in place to prevent discrimination of individual taxpayers, especially in reference to German constitutional law. Are some inherent discriminatory risks of automated risk assessment legally acceptable? How can these systems be monitored effectively to ensure that they function correctly, both to protect taxpayers from discrimination and to allow tax authorities to collect the taxes owed as effectively as possible?