Fiscal and Monetary Policy for Decent Employment in Nigeria
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
The level of unemployment in Nigeria has risen persistently, increasing the risk of the non-achievement of the SDG goal 8 – decent work and economic growth. Economists have documented that monetary and fiscal policies are effective tools for influencing economic variables such as the unemployment rate. In this study, we attempt to investigate and compare how these tools affect unemployment level in Nigeria. This study comes at an important time in Nigeria when the economy just exited a recession and is still experiencing low production and rising unemployment. This study investigates the nexus between macroeconomic policies and unemployment using the Autoregressive Distributed Lag (ARDL) estimation technique. The study finds that government capital expenditure helps to reduce unemployment in the long run only. On the other hand, the currency in circulation and the real GDP help to reduce unemployment rate in both the short and the long run. The study recommends a policy mix, which proposes that government expenditure be judiciously employed, and simultaneously, the Central Bank of Nigeria (CBN) should regulate the supply of money into the economy to not trigger inflation and unemployment.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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