Determinants of Inflation in Somalia: An ARDL Approach
Bibliographic record
Abstract
This study delves into the effective management of inflation by analyzing its determinants, highlighting the importance of low inflation as an indicator of macroeconomic stability.The research explores the interplay between Broad Money Supply, Gross Domestic Product (GDP), and Exchange rate, within the framework of Somalia's inflation, using time series data from 1970 to 2010.An Autoregressive Distributed Lag (ARDL) model is employed to scrutinize short-and long-term elasticities.The findings reveal a strong, statistically significant, positive correlation between money supply and inflation over the long term; specifically, a modest 1% increase in money supply leads to a significant 39.35% rise in the inflation rate.Additionally, in the long run, a sizeable negative relationship between GDP and inflation is uncovered, suggesting that a 1% rise in GDP corresponds to a remarkable 261.17% decrease in the inflation rate.Granger causality tests expose a unidirectional influence-from exchange rate to inflation, money supply to exchange rate, and GDP to exchange rate.Hence, this study emphasizes the need for the Somali government to implement fiscally prudent measures that foster real GDP growth.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".