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Record W3123578918 · doi:10.24149/gwp215

Geographic Barriers to Commodity Price Integration: Evidence from US Cities and Swedish Towns, 1732-1860

2014· preprint· en· W3123578918 on OpenAlexafffund
Mario J. Crucini, Gregor W. Smith

Bibliographic record

VenueFederal Reserve Bank of Dallas, Globalization and Monetary Policy Institute Working Papers · 2014
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsQueen's University
FundersSocial Sciences and Humanities Research Council of CanadaNational Science Foundation
KeywordsCommodityConvergence (economics)Dispersion (optics)Price dispersionEconomicsEconomic geographyInternational economicsGeographyEconometricsMacroeconomicsMarket economy

Abstract

fetched live from OpenAlex

We study the role of distance and time in statistically explaining price dispersion for 14 commodities from 1732 to 1860. The prices are reported for US cities and Swedish market towns, so we can compare international and intranational dispersion. Distance and commodity-specific fixed effects explain a large share -roughly 60% -of the variability in a panel of more than 230,000 relative prices over these 128 years. There was a negative "ocean effect": international dispersion was less than would be predicted using distance, narrowing the effective ocean by more than 3000 km. Price dispersion declined over time beginning in the 18th century. This process of convergence was broad-based, across commodities and locations (both national and international). But there was a major interruption in convergence in the late 18th and early 19th centuries, at the time of the Napoleonic Wars, stopping the process by two or three decades on average.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.065
GPT teacher head0.265
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.

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

Citations2
Published2014
Admission routes2
Has abstractyes

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