Statistical Analysis of the Effectiveness of the New Cooperative Medical Scheme in Rural China
Bibliographic record
Abstract
This study is aimed at evaluating the impact of China's New Cooperative Medical Scheme (NCMS) on the utilization of health service and health status. Using a large sample based on the China Health and Nutrition Survey (CHNS) data and both Instrument Variables and individual Fixed Effect methods to eliminate the potential endogeneity problem, we consistently found that being enrolled by NCMS reduces out-of-pockets expenditure of rural residents of China. There's also a weaker evidence that the enrollment increase the use of preventive health service. However, we found that Enrolled in NCMS neither improves health condition nor increases the utilization of preventive and formal health service. Key words: New Cooperative Medical Scheme; Health service; Rural residents; Statistical Analysis Resume: Cette etude vise a evaluer l'impact de la Chine Nouvelle cooperative medicale Scheme (SNGC) sur l'utilisation des services de sante et l'etat de sante. L'utilisation d'un large echantillon base sur la Sante de la Chine et la nutrition Enquete (ISC) des donnees et des variables instrumentales et individuels a la fois des methodes a effet fixe pour eliminer le probleme d'endogeneite, nous avons constamment trouve que etant inscrits par SNGC reduit out-of-poches des depenses des residents ruraux de la Chine. Il ya egalement une faible preuve que l'inscription d'accroitre l'utilisation des services de sante preventifs. Toutefois, nous avons constate que ni inscrits dans le SNGC ameliore l'etat de sante, ni l'augmentation de l'utilisation des services de sante preventifs et formelle. Mots cles: Nouveau systeme de cooperative medicale; Le service de sante; Les residents ruraux; D'analyse statistique
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".