Ethiopia Economic Update, No. 8
Bibliographic record
Abstract
COVID-19 has severely affected Ethiopia, weakening its economic performance. Ethiopia has experienced a collapse in external demand since April 2020 due to COVID-19. While merchandise exports, excluding gold, increased by 5.8 percent overall in FY20, they declined by 4.1 percent during July-December 2020 (year-on-year). Exports of garments, textiles, and fruits and vegetables have been particularly hit since the onset of the pandemic. Both exports and imports of services, dominated by air transport, recorded negative growth in FY20. Remittances dropped by 10 percent in FY20, although they have rebounded during the first half of FY21. Merchandise imports, which were already on decline prior to COVID-19, dropped by 8 percent in FY20, contributing to the narrowing of the current account balance, estimated at about 4 percent of GDP. Meanwhile, foreign direct investment has been severely hit, with inflows declining by 20 percent in FY20, contributing to weakening reserve levels. Despite the severe impacts, Ethiopia grew at 6.1 percent in FY20, as the impact of the COVID-19 pandemic took place largely in the final quarter of the fiscal year. Phone survey data suggests that both firm revenue and household income are significantly depressed, which points to weakening domestic demand. The adverse impact of the COVID-19 pandemic on economic activity is expected to continue in FY21, prior to experiencing a rebound in FY22 and beyond. Further action is needed to ensure a resilient economic recovery. The Government of Ethiopia is to be commended for having kept advancing its Homegrown Economic Reform Agenda despite COVID-19. Implementing some complementary reforms will be key to ensuring a resilient recovery in the new COVID-19 normal.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.106 | 0.033 |
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".