Implications of Non –productive and Productive Government Expenditure on Output and Employment: Evidence From Nigeria
Bibliographic record
Abstract
Nigerian government expenditure has been on an increasing trend over the years, and its contribution to sustainable economic development; promoting long-term output and employment has generated controversial issues in the literature. Against this background, this study analyses the impact of both productive and non-productive government expenditure on output and employment in Nigeria using the Vector Error Correction Model, The long-run equations for output and employment are established. The joint short and long-run causality was also investigated. The study shows a contrary result to theoretical predictions; Nigeria's long-run growth is not promoting by productive government expenditure. Furthermore, there is joint short and long-run causality between employment and government expenditure channels. Evidence from the output equation indicates no joint long and short-run causality. The implication of this result shows that government expenditure either productive or non-productive, has not improved the economy, although there is an increase in employment generation through the non-productive channel, which has not promoted broad-based growth. For the Nigerian government to improve the situation, the study recommends a critical assessment of public expenditure through the cost-benefit approach.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".