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Record W1896518323 · doi:10.1002/agr.21292

Do Inventories Have an Impact on Price Transmission? Evidence From the Canadian Chicken Industry

2012· article· en· W1896518323 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAgribusiness · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomics of Agriculture and Food Markets
Canadian institutionsDesjardinsCentre intégré de santé et de services sociaux de Chaudière-AppalachesUniversité Laval
Fundersnot available
KeywordsEconometricsEstimatorEconomicsElasticity (physics)Quadratic equationTransmission (telecommunications)InferencePrice elasticity of demandWholesale price indexPrice elasticity of supplyPrice levelMicroeconomicsMid priceStatisticsComputer scienceMathematicsMacroeconomicsTelecommunications

Abstract

fetched live from OpenAlex

ABSTRACT This paper investigates the influence of inventories in explaining the magnitude of price transmission. Using data from the Canadian chicken industry, a flexible non‐linear inference framework detects significant non‐linearities in the relationship between farm and wholesale prices. An empirical model is proposed to estimate a price transmission elasticity and a target inventory equation in the spirit of linear‐quadratic inventory models in the macroeconomics literature. A generalized method of moments estimator measures the impact of inventories on price transmission and accounts for the potential correlation between sales and wholesale prices. The price transmission elasticity is lower (higher) when inventories are above (below) the target level.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.068
GPT teacher head0.263
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it