Information Asymmetries and Consumption Decisions in Organic Food Product Markets
Bibliographic record
Abstract
Organic agriculture is a rapidly growing segment of most developed agricultural economies around the world. To stimulate growth and circumvent supply‐side market failures that emerge when organic products are not segregated, governments have introduced regulations concerning the certification and labeling of organic food. While certification and labeling satisfy market demand for information provision, the introduction of these activities creates incentives for the mislabeling of conventional food as organic. Despite the incentives for, and the incidence of, mislabeling in organic food product markets, this issue has not been analyzed systematically. In fact, the possibility of mislabeling has been customarily neglected by economic studies of markets for credence goods in general. This paper addresses the issue of product type misrepresentation in organic food product markets and develops a model of heterogeneous consumers that examines the effect of mislabeling on consumer purchasing decisions and welfare. Analytical results show that, contrary to what is traditionally believed, while certification and labeling are necessary, they are not sufficient for alleviating failures in organic food product markets. The effectiveness of labeling depends on the level of product type misrepresentation. Consumer deception through mislabeling affects consumer trust in the labeling process and can have detrimental consequences for the market acceptance of organic products. When extensive mislabeling occurs, the value of labeling is undermined and the organic food market fails. L'agriculture biologique est un secteur qui prend rapidement de l'expansion dans la plupart des pays agricoles industrialisés. Pour stimuler la croissance de ce secteur et éviter les problèmes d'offre qui surviennent quand il n'y a pas ségrégation des denrées, les gouvernements ont adopté des règlements sur la certification et l'étiquetage des produits biologiques. Même s'ils satisfont la demande d'informations sur le marché, la certification et l'étiquetage ouvrent la porte à l'usage abusif du terme “biologique” sur l'étiquette des denrées ordinaires. Or, bien que les producteurs soient tentés d'utiliser le terme à tort et à travers et en dépit des incidences d'un tel comportement, le phénomène n'a jamais été analysé de manière méthodique. De fait, les analyses économiques sur le marché des denrées alimentaires, en général, négligent souvent la possibilité de fausses déclarations sur l'étiquette des produits. L'article que voici aborde ce problème sur le marché des aliments biologiques et propose un modèle qui tient compte des effets d'un étiquetage fallacieux sur les achats et le bien‐être de consommateurs hétérogènes. Les résultats de l'analyse indiquent que, contrairement à ce qu'on croit, la certification et l'étiquetage, bien que nécessaires, ne suffisent pas à atténuer les problèmes observés sur le marché des aliments biologiques. En effet, l'efficacité de l'étiquetage dépend du nombre de fausses déclarations. La déception qui résulte d'une fausse déclaration ébranle la confiance des consommateurs dans le système d'étiquetage, si bien que les produits biologiques sont mal accueillis sur le marché. Quand les fausses déclarations se multiplient, l'étiquette perd sa valeur et il devient impossible de commercialiser les denrées biologiques.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".