Comparison of International Differences in the Volatility of Economic Growth and Non-Performing Loan Ratio: A Statistical Study Based on the Quantile Regression Model
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
What is the level of non-performing loans in China’s banking sector and in different countries? Has the relationship between economic growth and the non-performing loan ratio changed? Is there a difference in the effect of the economic growth of different economies on the rate of non-performing loans in the banking sector? This study analyzes the relationship between economic growth and the non-performing loan ratios and characteristics of 13 countries from 2005-2014 based on quantile regression models with panel data. The results showed that the relationship between economic growth and the non-performing loan ratio was positive before the financial crisis in 2008 but was negative after 2008. The non-performing loan ratio in Canada, Mexico, and the US was low before 2008 and high after 2008. The impact of economic growth on the non-performing loan ratio was more significant for countries with a high non-performing loan ratio than for countries with a low non-performing loan ratio.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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