How monetary policy depresses economic growth in Russia and the Eurasian Economic Union
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The relatively successful overcoming by the Russian economy of 2021 with an increase in GDP of 4.3% and investment in fixed assets of 5.6% inspires cautious optimism associated with the ability of the system of state power in crisis periods to target managerial influences, mobilizing the resources required to correct the macroeconomic situation. Already in the middle of the year, the 2020 recession caused by the pandemic consequences has been overcome, and there were good reasons to expect this trend to continue in 2022. To reach the targets of the annual GDP growth of the Eurasian Economic Union by 5-5.5%, established by the Supreme Eurasian Economic Council (the level of the heads of the EAEU states), there are all possibilities: production capacities that are not loaded by a third, the resources of the common labor market of the EAEU are far from exhausted, the abundance of exported industrial raw materials and energy resources, the scientific and technical potential involved by barely a quarter. According to our estimates, the available production capacities and untapped resources allow increasing output by more than 8% per year, however, the tightening of the monetary policy pursued by the Bank of Russia and following the same restrictive paradigm of the central (national) banks of the partner countries of the Union do not allow subordinating the existing reserves to development goals and achieving faster growth rates.
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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 | 0.002 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it