Sensitivity of community values to economic valuation technique: Evidence and explanations
Bibliographic record
Abstract
Objective: To assess the sensitivity of stated preference results to valuation technique by comparing mean stated preference values attained from a discrete choice experiment (DCE) to those attained from willingness to pay questions (WTP). Methods: Representative general population postal survey of 3500 households in 16 local government areas of Victoria, Australia. The survey included a discrete choice experiment and willingness-to-pay questions for proposed changes to local maternal health services at three different levels of program effectiveness (4% reduction in postnatal depression, 2% reduction, and no change). Results: 43% of contacted households participated. WTP-based estimates of mean value of the program improvement were A$56, A$49 and A$43 for the three levels of program effectiveness. Corresponding DCE-based estimates were A$55, A$36 and A$16. Confidence intervals around estimates produced by these two valuation techniques overlap for the first two levels of program effectiveness, but mean estimates are statistically significantly different at the lowest level of effect. Discussion: Contingent valuation (when asked in a dichotomous-choice format) and DCE approaches have a common base in random utility theory and should produce similar welfare estimates of changes in the good or service described. However, very few studies exist that test the comparative results from contingent valuation and DCE studies and the available studies find mixed results. This paper adds to this limited empirical base and may shed more light on how and why different stated preference techniques yield different results. In this study, the values of a general population sample appear similar for the projected scenario (of a community-based public health program that results in a reduction in postnatal depression from 14% to 10%). However, the sensitivity of welfare estimates to the scale of program effectiveness offered differs significantly between approaches. This results in a statistically significant difference in the mean value attached to a scenario describing a less successful public health program.
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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 | 0.255 | 0.611 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".