ISSN: 1996-2207
Affiliations: Visiting Professor, University of Johannesburg
Source: Tydskrif vir die Suid-Afrikaanse Reg, Issue 3, 2025, p. 642-645
https://doi.org/10.47348/TSAR/2025/i3a14
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ISSN: 1996-2207
Affiliations: University of the Witwatersrand
Source: Tydskrif vir die Suid-Afrikaanse Reg, Issue 3, 2025, p. 646-648
https://doi.org/10.47348/TSAR/2025/i3a15
None
ISSN: 2709-8575
Affiliations: Docteur en sciences économiques, Data scientiste, Chef division analyse risques et suiviévaluation, Office Togolais des Recettes & Chercheur associé au CREAMO (Université de Lomé); Docteur en sciences économiques, Inspecteur des Douanes, Chef section brigade à la Division des Opérations Douanières de Kwadjoviakopé de l’Office Togolais des Recettes; Master en Statistiques & Mathématiques, Data scientiste, Chargé de l’analyse des risques et de la programmation fiscale, Office Togolais des Recettes
Source: African Multidisciplinary Tax Journal, Volume 5, Issue 1 (2025), p. 1–26
https://doi.org/10.47348/AMTJ/V5/i1a1
Customs fraud is an inherent phenomenon of customs administrations and is most often responsible for undermining customs revenue collection. In an attempt to combat this phenomenon, customs administrations, particularly in developing countries, often conduct extensive and unstructured audits. This is not conducive to the fluidity of international trade. The objective of this study is to analyse the extent to which the use of machine learning and mirror analysis improves the identification of customs fraud, while preserving the objective of revenue mobilisation. Using data from the Togolese Revenue Authority and COMTRADE, the findings indicate that mirror analysis and machine learning can better enhance customs fraud detection. To this end, the study recommends the use of these tools in fraud detection.
ISSN: 2709-8575
Affiliations: Manager, Research, Strategy and Statistics Division at the Eswatini Revenue Service; Research Fellow, Institute of Development Studies; Economic Analyst, Research, Strategy and Statistics Division at the Eswatini Revenue Service
Source: African Multidisciplinary Tax Journal, Volume 5, Issue 1 (2025), p. 27–50
https://doi.org/10.47348/AMTJ/V5/i1a2
This paper investigates corporate income tax (CIT) payment compliance among corporations in Eswatini, an underexplored area critical for revenue-constrained low and middle-income countries. Using a unique administrative dataset (2017–2022), we analyse factors driving timely and full tax payments. We combine descriptive analysis with a more robust Heckman selection model to address sample selection bias. Results show that, while 82% of filed returns included payments, only 55% were fully compliant, and 42% were late. Compliance was higher among larger firms and those in urban tertiary sectors, while smaller and rural firms frequently overpaid, potentially due to penalties. Electronic payments exhibited the highest compliance, whereas mobile and cash payments lagged. Regression analysis highlights company size, provisional tax filings and electronic payments as key compliance predictors. This study contributes to the tax compliance literature with actionable insights for revenue authorities, from the simplification of tax processes for smaller firms to the larger implementation of electronic tax payments.
ISSN: 2709-8575
Affiliations: Groupe de Recherche en Économie et Gestion [GREG], Université de Douala / École Supérieure des Sciences Economiques et Commerciales [ESSEC] de Douala, Douala-Cameroun; Université de Douala / École Supérieure des Sciences Economiques et Commerciales [ESSEC] de Douala, Douala-Cameroun; Université de Douala / École Supérieure des Sciences Economiques et Commerciales [ESSEC] de Douala, Douala-Cameroun, Centre de Recherche, d’Innovation et de Développement Agricoles (CARID), Douala-Cameroun
Source: African Multidisciplinary Tax Journal, Volume 5, Issue 1 (2025), p. 51–76
https://doi.org/10.47348/AMTJ/V5/i1a3
This study aims to demonstrate the impact of tax administration reforms on the mobilisation of direct and indirect taxes from non-natural resources. Out of 40 SSA countries. The assessed tax administration reforms are the establishment of a semi-autonomous revenue administration [SARA], a Large Business Collection Unit [LTU] and an Informal Sector Business Unit or strategy [ISU]. To this end, we use a seemingly unrelated regression [SURE] panel method on data from various sources. The results show that SARAs and LTUs positively impact the mobilisation of direct taxes. However, SARAs do not have an independent impact on indirect taxes and must be used alongside ISUs. ISUs have a positive impact on the mobilisation of indirect taxes. Reorganising tax administration in relation to taxpayers has a positive impact on tax revenue.