A Longitudinal Assessment of Tax Reforms and National Income in Nigeria: 1971-2014
Bibliographic record
Abstract
This study assesses the impact of tax reforms on Nigeria’s national income over the period, 1971 to 2014. Using a variety of growth indicators signifying tax reforms, our regression model specified growth rate of national income (proxied by GDP) as a function of growth rates in these indicators. Diagnostic tests (F-statistics, Adjusted R-Square and Durbin-Watson) were carried out to ascertain the robustness of the parameter estimates. We found that tax reforms significantly improved national income and economic growth during the period of study, especially growth rates of value added tax and personal income tax. Our results show that growth rate of personal income tax has a positive significant effect on the national income and economic growth, while that of value added tax has a negative significant effect on growth of national income. The growth components of company income tax and petroleum profit tax are positive but not statistically significant. On the other hand, reforms in custom and excise duties were found to yield negative and statistically non-significant effect. The leading conclusions from these findings are: (1) strategic tax reforms significantly influence the behaviour of national income and GDP; (2) tax policy significantly fosters the growth of national income; and (3) policy makers, especially Ministry of Finance and Federal Inland Revenue Service and their state counterparts, should give requisite attention to tax policy issues, in the light of their obvious implications on growth of the national income and economic development.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".