Analysis on the Effect of Chinese Medical Reform Policy on Medical Listed Companies -- Empirical Analysis on Listed Companies’ Stocks Returns
Bibliographic record
Abstract
This paper studies the stock market reaction of medical reform policies to examine policies’ effect on the listed companies which invested in hospital. This paper applies the method of Event Study, finding out that the announcement of the new round of medical and health systemic reform in 2009, the key work for medical and health systemic reform and its detailed rules of implementation in 2010, and the setting of several specific goals to develop the private hospitals run by civilians in 2012, have taken increases of listed companies’ stocks returns (rate of return) by 2.95%, 4.64% and 4.92% separately. That means the whole market value rose by almost 55 billion, 128 billion, and 131 billion of RMB respectively. The empirical analysis results show that share price’s return rate of the listed companies which invested in hospital are significantly associated with industrial planning and supporting policies launched by the government. That is to say, Chinese government’s policy which began to encourage and guide civilian capital to develop the medical industry stimulated the medical and health industry effectively and significantly.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".