Tax Policy and SME Compliance in South Africa: Insight from Tax Practitioners
Bibliographic record
Abstract
Tax practitioners (such as accountants and bookkeepers) are important enablers of tax compliance. Taxpayers, particularly small businesses, look to tax practitioners for expert advice because of increasingly complex tax legislation. This study’s purpose was to examine tax practitioners’ perspectives on tax policy and SME compliance in South Africa. This study looks at the perspective of tax practitioners to extend information on tax policy and its effect on the tax compliance of SMEs. A total of 90% of companies in South Africa are classified as SMEs, which account for more than 80% of employment in the economy. Despite the importance of the SME sector in job creation, tax policies and the costs associated with them are major issues affecting the overall regulatory environment and they are identified as a major threat to SMEs’ growth. This study seeks to close this gap by examining practitioners’ perspectives on tax policy and SME compliance in South Africa. This study adopted a quantitative approach using a self-administered questionnaire which was emailed to a sample of 255 tax practitioners by using a link through QuestionPro, and this study applied descriptive statistics in analysing data. This study indicated that tax practitioners have sufficient experience and qualifications to prepare and handle tax matters for SMEs. This study demonstrated that SMEs register for taxes, file annual returns, and pay tax liability within the period stipulated by tax law. It further indicated that being tax-compliant has certain benefits for SMEs. This research is intended to assist tax authorities and the government in better creating measures to address the problem of tax compliance among SMEs in South Africa. This article adds to the body of knowledge because it uses the opinion of tax practitioners to extend debate on tax policy in tax compliance and its effect on the functioning of SMEs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".