Верна ли для Армении гипотеза роста на основе экспорта
Bibliographic record
Abstract
The presented study examines the relevant problems of Exportled growth hypothesis for Armenia. Aim. The study aims to check if the exportled growth hypothesis is valid for Armenia in term of 1998–2017 or not. Tasks. To achieve this aim, the authors examine the mechanism of the relationship between export and GDP. Methods. For this purpose the correlation analysis is performed, as well as the results of Grangercausality test are shown.For this analysis, quarterly data are chosen covering 1998:Q12017:Q4. The analysis is provided by Eviews 4. Results. The results show that there is a high correlation between export and GDP (0.81). We can state also that the export growth in any quarter causes GDP growth in the same quarter, after 2 quarters, and in the last quarter after 2 years. The GDP growth causes export growth lagged 2–7 periods. The results of the Grangercausality test show that for some period of time the rise in export causes the inflow of foreign currency, which also causes a rise in import. And finally, we revealed that there is a strong positive relationship between the import and GDP, and also we cannot reject the hypothesis “import does not cause GDP growth”. Conclusions. The analysis shows that the Exportled growth hypothesis is valid for Armenia. The identified mechanism of impact of export on economic growth is the following: export growth causes an inflow of additional foreign currency during 3 months, which causes local currency appreciation and in the next 9 months the growth of import (especially for import of capital goods and raw materials) could be caused. And finally, the outcome is the GDP growth during the next 3.5 years. It must be noted that this process is continuous, as GDP growth causes export growth in the next 7 quarters.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".