Building a Set of Internationally Comparable Value of Statistical Life Studies: Estimates of Chinese Willingness to Pay to Reduce Mortality Risk
Bibliographic record
Abstract
This study is the eighth in a series of stated-preference studies designed to enhance the basis for international benefits transfer of value of statistical life (VSL) estimates. The series has fielded essentially similar stated-preference surveys in Canada, China, France, Italy, Japan, Mongolia, the United Kingdom, and the United States. This Chinese study estimates the willingness to pay for contemporaneous and future mortality risk reductions of residents of Shanghai, Jiujiang, and Nanning, China using a stated-preference payment-card survey. The pooled VSL for a contemporaneous reduction in annual mortality risk reduction of 5 in 10,000 is about 1.47 million 2009 yuan ($614,805 U.S. $2016), with income elasticities of 0.2 to 0.25. This VSL estimate is at the lower end of estimates from the eight countries, between those from Mongolia and Japan, and in the mid-range of estimates of willingness to pay (WTP) for mortality risk reductions as a percentage of household income. We find lower discount rates in the Mongolia, Japan, and China studies than in those fielded in North America or Europe. The study also explores the relative performance of dichotomous choice and stated-preference card elicitation methods in a middle income country setting and develops a computerized “payment card” that allows testing for anchoring. Implicit transfer elasticities across countries, calculated using the VSLs we estimate and each country’s income, relative to those of the United States, yields estimates of 0.88–0.95 for the lower income countries. These compare with the default assumption of 1.0 or assumed elasticities of 1.2 for developing countries.
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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) | 0.001 | 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) | 0.000 | 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".