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Behavioural Insights in Action: Improving Tax Compliance Through Behaviourally Informed Training

Published online by Cambridge University Press:  13 February 2026

Yasen Dimitrov
Affiliation:
Department of Business Administration and Marketing, University of Insurance and Finance, Sofia, Bulgaria
Velina Hristova
Affiliation:
Department of Psychology, Sofia University ‘St. Kliment Ohridski’, Sofia, Bulgaria Institute for Population and Human Studies, Bulgarian Academy of Sciences, Sofia, Bulgaria
Ivo Vlaev*
Affiliation:
Behavioural and Implementation Science Interventions, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
*
Corresponding author: Ivo Vlaev; Email: vlaev@nus.edu.sg
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Abstract

This study examines whether behaviourally informed training can improve the effectiveness of phone-based tax debt collection in a public-sector setting. In collaboration with the Bulgarian National Revenue Agency, we implemented a two-day training programme for call centre agents focused on persuasion, negotiation and behavioural influence techniques derived from behavioural science and nudge theory. The impact of the intervention is assessed using descriptive comparisons of monthly aggregated debt-collection performance indicators before and after the training. We find that, following the intervention, trained agents achieved markedly better outcomes relative to pre-intervention periods, including an increase of approximately 20% in the total amount of debt collected over the subsequent three months and a higher rate of secured payment agreements. Notably, these improvements contrast with historical seasonal patterns that typically show a decline in collections during the same period. While the analysis is descriptive and does not permit definitive causal inference, the results provide strong indicative evidence that targeted behavioural training can enhance compliance outcomes in live, interpersonal interactions. The study contributes to the behavioural public policy and persuasion literatures by extending behavioural insights beyond written or digital nudges to real-time, conversational settings. From a practical perspective, the findings highlight the potential value of soft-skills and behavioural training for frontline public servants as a scalable and cost-effective tool for improving tax administration performance.

Information

Type
Findings from the Field
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2026. Published by Cambridge University Press.
Figure 0

Figure 1. Monthly debt repayment indicators before and after the behavioural training intervention, compared with the same calendar period in the previous year.

Notes: The figure displays monthly aggregated indicators of phone-based debt collection outcomes at the National Revenue Agency (NRA). Blue shades correspond to the benchmark period (November 2023–February 2024), while red shades correspond to the post-intervention period (November 2024–February 2025). Within each colour group, bars represent individual months. Arrows indicate the timing of the training intervention, which took place during the first two weeks of November 2024.
Figure 1

Figure 2. Debt repayment indicators during the four months before and after the intervention.

Notes: The figure displays monthly aggregated indicators of phone-based debt collection outcomes at the National Revenue Agency (NRA). Blue shades correspond to the pre-intervention period (July–October 2024), while red shades correspond to the post-intervention period (November 2024–February 2025). Within each colour group, bars represent individual months. Arrows indicate the timing of the training intervention, which took place during the first two weeks of November 2024.Outcomes shown include: (i) the proportion of contacted cases with full repayment; (ii) the proportion of full repayment among cases with any payment; (iii) full repayments as a share of total payments; and (iv) full repayments as a share of total outstanding debt. All values are calculated from monthly aggregated administrative data and are descriptive in nature; they are not adjusted for covariates and should not be interpreted as causal estimates. The comparison illustrates changes relative to the immediate pre-intervention trajectory.
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