Bibliographic record
Abstract
The aim of this paper is to empirically investigates whether Sierra Leone fiscal policy is sustainability. In this regard, I employ different econometric methodologies used in the empirical literature to investigates the sustainability of fiscal policy. The empirical findings that emerged from this study are useful on one hand to creditors, serving as a guide for lending to the government, and, on the other hand to the government, cautioning policymakers to avoid public debt from exploding that could possibly lead to fiscal insolvency and/or debt distress. I start by testing for the stationarity properties of the primary balance, the necessary condition for a sustainable fiscal policy. The findings indicated that Sierra Leone fiscal policy is sustainable under the review period. Next, I test for cointegration relationship between government revenue and government expenditure, the alternative approach to test for a sustainable fiscal policy. On this note, I employ both the Dynamic Ordinary Least Square (DOLS) and the Johansen cointegration techniques. Both approaches confirmed the existence of a cointegration relationship between government revenue and government expenditure. The estimated cointegration coefficients show that fiscal policy during the review period is weakly sustainable and the cointegration between government spending and revenue is positive (but less than one) and statistically significant. This implies that for each percentage point of GDP increase in government expenditure, government revenues increase by less than one percentage point of GDP. Additionally, I proceeded to endogenously account for structural breaks in the cointegration relationship, which is relevant for Sierra Leone, a country that has witnessed significant changes over the years, including the Structural Adjustments Programme (SAP) in the 1980s, tax reforms in the 1990s and 2000s, etc. I found evidence of a significant structural break occurring in 1984. There also exists uni-directional causality running from government revenue to government expenditure. This causality result is in line with the tax-and-spend hypothesis as proposed by Friedman (1978).Finally, I estimate an error correction model and the error correction term shows that the speed of adjustment from the expenditure side works faster than that of the revenue side to correct the fiscal disequilibrium.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".