The Construction of China Monetary Condition Index and Empirical Analysis of Economic Growth
Why this work is in the frame
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Bibliographic record
Abstract
Monetary Conditions Index,as a reflection of the degree of tightness of a country's monetary policy,was put forward by the Bank of Canada in 1994,arose the widespread attention of international society.From the first quarter of 1998 to third quarter 2011 among a total of 55 quarters,this paper selects real interest rates,the real effective exchange rate and the actual credit scale gap as explanatory variables,selects the gap between actual output and potential output as explanatory variables,uses a single equation estimation method,constructs the aggregate demand curve,uses the least square method to calculate the explanatory variable weight,studies Chinese actual monetary condition index.Through the analysis and comparison of China's exchange rate,interest rate,credit scale changes and macro economic growth relationship, the paper validates Chinese actual monetary condition index's explanation on the entity economic fluctuant.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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