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Record W2799631207 · doi:10.5430/jms.v9n2p20

Analysis on the Effect of Chinese Medical Reform Policy on Medical Listed Companies -- Empirical Analysis on Listed Companies’ Stocks Returns

2018· article· en· W2799631207 on OpenAlexvenueno aff
Xiaoqian Fu

Bibliographic record

VenueJournal of Management and Strategy · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Systems and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)BusinessRenminbiFinanceEvent studyStock (firearms)Stock marketAbnormal returnListed companyRate of returnAccountingStock exchangeExchange rate

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score0.552

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.036
GPT teacher head0.327
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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