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Record W2040260839 · doi:10.1002/agr.20216

Trade implications of price discrimination in a domestic market

2010· article· en· W2040260839 on OpenAlexaboutno aff
Nobunori Kuga, Nobuhiro Suzuki, Harry M. Kaiser

Bibliographic record

VenueAgribusiness · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomics of Agriculture and Food Markets
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsPoolingPrice discriminationRelative priceStylized factRevenueDomestic marketProduct (mathematics)International economicsInternational tradeMicroeconomicsMacroeconomics

Abstract

fetched live from OpenAlex

Abstract This study examines how domestic price discrimination between fluid and manufacturing milk influences dairy trade. Two types of dairy models are used for the study. The first one is a stylized mathematical model which is used to explore the relative trade effects of domestic price discrimination accompanied with revenue pooling mechanism versus border measures in dairy product markets. The second one is a partial equilibrium, multiple‐region model of dairy policy and trade, which is used to see the empirical implication of domestic price discrimination for six major dairy producers. The analytical results identify the trading status as the key to determine the relative trade effects. While domestic price discrimination is always less trade distorting than border measures in a net‐importer case, the relative trade distortiveness depends on the export volume in a net exporter case. The theoretical possibility that domestic price discrimination is more trade distorting than border measures is found when the ratio of dairy export to domestic manufacturing milk consumption is very high. The results also indicate that while the both support measures increase dairy export, domestic price discrimination may place greater economic burden on fluid milk consumers and less economic burden on tax payers than border measures. In addition, the results imply that domestic price discrimination schemes can be effective trade protective measures for Canada, Japan and the United States, where the schemes are currently being implemented. © 2010 Wiley Periodicals, Inc.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.764
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.214
Teacher spread0.199 · 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

Citations1
Published2010
Admission routes1
Has abstractyes

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