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Record W7095213961

Harvard University

2010· article· en· W7095213961 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFranchising Strategies and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsProduct (mathematics)Exchange rateRelative priceRetail salesMarkup languageSupply chainMeasure (data warehouse)
DOInot available

Abstract

fetched live from OpenAlex

Relative cross-border retail prices, in a common currency, comoves closely with the nominal exchange rate. Using a data set with product level retail prices and wholesale costs for a large grocery chain operating in the U.S. and Canada, we decompose this variation into relative wholesale costs and relative markup components. We find that the correlation of the nominal exchange rate with the real exchange rate is mainly driven by changes in relative wholesale costs, arguably the most tradable component of a retailer’s costs. We then measure the extent to which national borders impose additional costs that segment markets across countries. We show that retail prices respond to changes in wholesale costs in neighboring stores within the same country but not to changes in wholesale costs in a neighboring store located across the border. In addition, we find a median discontinuous change in retail and wholesale prices of 24 percent at the international border. By contrast, the median discontinuity is 0 percent for state and provincial boundaries.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.377
Threshold uncertainty score0.537

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.6230.405

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 head0.006
GPT teacher head0.164
Teacher spread0.158 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2010
Admission routes1
Has abstractyes

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