A Censored Quantile Regression Analysis of Vegetable Demand: The Effects of Changes in Prices and Total Expenditure
Bibliographic record
Abstract
Many diseases are linked to dietary behavior. One major diet‐related risk factor is a low consumption of vegetables. The consumption may be increased through public policies. The effects on vegetable purchases of either removing the value added tax on vegetables or a general income support are investigated. Adverse health effects are most serious in households consuming low quantities of vegetables. Therefore, the effects on high‐ and low‐consuming households are estimated by using quantile regressions (QRs). Since many households did not purchase any vegetable during each survey period, censored as well as ordinary QRs are used. Our results suggest that the effects of the policy variables differ in different parts of the conditional distribution of vegetable purchases. None of the proposed policy options is likely to substantially increase vegetable purchases among low‐consuming households. Bon nombre de maladies découlent des habitudes alimentaires. La faible consommation de légumes constitue un important facteur de risque liéà l'alimentation. Cette consommation pourrait être accrue par l'instauration de politiques gouvernementales. Nous avons examiné les effets de l'abolition de la taxe sur la valeur ajoutée ou d'un soutien du revenu sur les achats de légumes. Les effets néfastes sur la santé sont plus graves chez les ménages qui consomment de faibles quantités de légumes. Nous avons donc estimé les effets chez les ménages à forte et à faible consommation de légumes à l'aide de régressions par quantile. Comme de nombreux ménages n'ont pas acheté de légumes au cours des périodes sondées, nous avons utilisé des régressions par quantile censurées et des régressions par quantile ordinaires. Nos résultats ont indiqué que les effets des variables concernant les politiques diffèrent dans différentes parties de la distribution conditionnelle des achats de légumes. Aucune des options politiques proposées ne semble susceptible d'accroître substantiellement les achats de légumes chez les ménages qui en consomment peu.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".