Heading For Low Dollarization
Bibliographic record
Abstract
The global background for the economic recovery of EDB member states has improved this year, in many ways due to rising oil prices and an improved economic growth outlook in the major centers of the global economy. Against the backdrop of improving regional trends in economic growth and mutual trade, we have revised our GDP growth forecasts for the EDB member states in 2017-2019. The appreciable acceleration of GDP growth in Russia beginning in the 2nd quarter of 2017 along with improvements in both foreign and domestic macroeconomic conditions have prompted an upgrade of our GDP growth forecast for 2017, from 1.4% to 1.7%. The preservation and continued improvement of external conditions for the Russian economy is shifting the balance of risks toward higher growth rates. Improvements in the Russian economic performance have delivered a boost to the economies of other EDB countries: the GDP growth forecasts for 2017 have been upgraded for Belarus, from 1.4% to 1.8%, Kyrgyzstan, from 3.7% to 4.0%, Tajikistan, from 6.2% to 7.2%, and Kazakhstan, from 3.4% to 3.7%. In the longer term, the biggest challenge for the global economy consists of the lingering imbalances that have contributed to crises over the past decade. They primarily include the high levels of inequality both within and among countries. The continuing paradox in the global economy is that the majority of countries that most need economic integration (such as the poorest nations or developing countries without access to the sea) are the most disadvantaged in terms of participation in regional or global economic unions or “clubs”. We focus particular attention on the dedollarization of the economies of EDB member states as yet another factor contributing to improvements in the regional economic environment. The level of dollarization has been declining this year in all EDB member states, in many ways due to the stabilization of exchange rates, lower inflation, improved economic activity and regained trust in the national currencies. Among the EDB member states, the most noticeable reductions in the level of dollarization (measured as the share of foreign currency deposits within the structure of the broad money supply) have been recorded in Belarus, Kazakhstan, and Kyrgyzstan (the level of dollarization was close to 30% by mid-2017 in Kyrgyzstan, Kazakhstan, and Russia). Such positive trends will contribute to a more effective monetary policy in the regional economies, more conducive conditions to support lower inflation, as well as conditions aiding stronger financial stability.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.014 | 0.018 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.084 | 0.032 |
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".