Determinants of Tax Compliance: A Review of Factors and Conceptualizations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper aims at providing a review of the factors that determine taxpayer compliance from a social marketing point of view. Data was obtained from 18 empirical studies published between 1985 and 2012 from across the globe. The findings made several revelations. First, too many and different explanatory factors have been proposed in the literature making comparison of findings across several studies difficult. Second, several researchers proceed without a theoretical framework to help guide the selection of independent factors. Since the use of theory enhances understanding of the major factors that affect a phenomenon, this deficiency has left the tax literature without a meaningful convergence on the key determinants. Third, aggregate analysis showed that attitudinal, normative and subjective control variables were on the overall good predictors of tax compliance. The findings suggest the following implications for research and policy action. First, it is recommended that future studies should seek to develop a few theory based set of relevant determinants of tax compliance that can yield accurate predictions. Second, tax policy makers are advised to desist from exclusive use of the conventional coercive methods (subjective control factors) normally used to compel tax compliance; instead they should take a balanced approach to tax enforcement that will also encourage voluntary compliance through change of attitudes and norms.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it