Impact of Climate Change on Budget Balance: Implications for Fiscal Policy in the ECOWAS Region
Bibliographic record
Abstract
The budget deficits of the Economic Community of West African States (ECOWAS) have been widening over the years. This study investigated the impact of climate change on budget balance and projected its implication for fiscal policy in ECOWAS countries. The two-step dynamic GMM method was applied for a balanced panel data of 14 countries from 2008 to 2018. The study found that rainfall is the only climate variable that increases budget deficits. Other macroeconomic variables: debt to GDP ratio and inflation were also responsible for the widening budget deficits. A major policy implication of this finding is that extreme and unpredictable rainfalls will distort the fiscal balance of ECOWAS countries by either reducing the revenue generation outlets or by raising expenditures. This will lead to more borrowing that will further widen the existing budget deficits through debt servicing, hence, making the respective governments to pay less attention on other sectors of the economy. Thus, ECOWAS countries need to expand their revenue generation sources either by creating an enabling environment for more businesses and investments to strive or by engaging in more foreign direct investment (FDI).
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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 | 0.000 | 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".