On estimating the cost of characteristics indices from consumer demand analysis
Bibliographic record
Abstract
Abstract. We examine the information content of relative equivalence scales using a multiperiod framework and argue that in the absence of Independence of Base (IB) these scales can be uniquely identified from demand analysis only when the transformations of preferences through time are the same for all household types, a property termed as Intertemporally Invariant Base (IIB) utility. Restrictions imposed by IIB on conditional demands are tested empirically and found rejected within the context of a rank‐3 demand system applied to individual household data drawn from the U.K. Family Expenditure Survey 1970–86. Welfare implications of false IIB assumptions are also empirically investigated. JEL Classification: D1 A propos de l’estimation du coût des indices caractéristiques à partir de l’analyse de la demande des consommateur. Ce mémoire examine le contenu informationnel des échelles d’équivalence relative en utilisant un cadre d’analyse sur plusieurs périodes, et suggère que, en l’absence d’une indépendance de la base (IB), ces échelles peuvent être identifiées d’une manière univoque seulement si les transformations de préférences dans le temps sont les mêmes pour tous les types de ménages. On nomme cette propriété utilité de base invariante dans le temps (IIB). Les restrictions vérifiables imposées par IIB sur les demandes conditionnelles sont vérifiées empiriquement et sont rejetées dans le contexte d’un système de demande de rang 3 appliqué aux données des ménages individuels dans une étude des dépenses des ménages de la Grande Bretagne 1970–86. Les implications de faux postulats IIB sont analysées empiriquement.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".