Effects of Taxation as an Alternative to the Dwindling Oil Revenue in Nigeria
Bibliographic record
Abstract
The study investigated the effect of taxation as an alternative to the dwindling oil revenue in Nigeria for the period of 24 years covering 1994 to 2017; examine the effect of value added tax on economic growth in Nigeria; investigate the effect of petroleum profit tax on economic growth in Nigeria; determine the impact of company income tax on economic growth in Nigeria. The study employed Johansen cointegration and error correction model technique and specified real gross domestic product (RGDP) on petroleum profit tax (PPT), company income tax (CIT) and value added tax (VAT). The result of unit root test indicated that there is presence of stationarity among the variables at 2nd difference. The Johansen cointegration analysis indicated that there is a longrun relationship between tax variable and economic growth in Nigeria. However, the relationships between the variables were negatively related to economic growth in Nigeria. The ECM result was correctly signed and significant thereby incorporating the shortrun inconsistency in the model. However, the overparameterized error correction model result showed that the variables have short run association which effect can actually be felt in the long run. The result further showed that the short-run dynamics in the model has been corrected; giving the correctly signed and statistically significant ECM coefficient of about 48.73% increase. The result of parsimonious ECM showed that the ECM coefficients of the series is significant and correctly signed, thus validating the presence of long run relationship amidst the variables and that about 57.46% of the short run inconsistencies are corrected and incorporated into the long run dynamics, annually. Based on the result of the longrun cointegration, the study concluded that taxation have negative effects on economic growth in Nigeria but can impact positively if government give possible attention to it thereby serving as an alternative to the dwindling oil revenue. The study therefore recommended that government should ensure that taxation is properly managed in a manner that will accelerate economic growth, reduce inflation rate and generate employment in the country. The study further suggested that government should diversify the economy from being solely oil dependent, to other streams of income generation such as agriculture, solid minerals and gas, otherwise the ripple effect of our over reliance on crude export to the USA, will be devastating to the economy.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".