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Record W2002675986 · doi:10.2202/1542-0485.1263

Evaluating Reforms in Canadian Chicken Marketing Mechanisms Using a Linear-Quadratic Inventory Model

2010· article· en· W2002675986 on OpenAlexaffabout
Abdessalem Abbassi, Jean‐Philippe Gervais

Bibliographic record

VenueJournal of Agricultural & Food Industrial Organization · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomics of Agriculture and Food Markets
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsEconomicsQuadratic equationEstimatorMicroeconomicsEconometricsGeneralized method of momentsIndustrial organizationPanel dataMathematicsStatistics

Abstract

fetched live from OpenAlex

Marketing institutions in supply managed industries are evolving due to broad globalization pressures. The output and sales decisions of chicken processing firms under two different pricing mechanisms are modeled using a linear-quadratic inventory model. Decision rules lead to structural equations that relate output and sales to their own lagged values, lagged inventories and lagged prices and cost indicators. A Generalized Method of Moments (GMM) estimator is applied to the system of equations. The null hypotheses no adjustment costs in processing and no role for inventories in marketing are rejected. We simulate the impacts of reforming the chicken pricing mechanism, moving from producers vs. processors bargaining to a formula-based price (referred to as “cost-plus"). Output in the industry is higher under the bargaining pricing system mostly because processors pay a lower price than under the “cost-plus" mechanism. Simulations reveal that producers' expected profits are lower on average under the bargaining system than under “cost-plus." Moreover, the “cost-plus" system reduces the variability of profits.

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.

How this classification was reachedexpand

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)0.003
metaresearch head score (Gemma)0.002
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 score0.160
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.067
GPT teacher head0.250
Teacher spread0.183 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2010
Admission routes2
Has abstractyes

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