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DOES THE LAW OF ONE PRICE (LOP) HOLDS IN THE INTERNATIONAL BARLEY MARKETS

2021· article· en· W3210568265 on OpenAlexaboutno aff
Sanusi Mohammed Sadiq, Prakarsh Singh, Muhammad Makarfi Ahmad

Bibliographic record

VenueAgricultural Social Economic Journal · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsLaw of one priceEconomicsMarket integrationUnit rootGranger causalityMarket microstructureCointegrationInternational economicsFinancial economicsMid priceMonetary economicsPrice levelEconometricsMacroeconomicsOrder (exchange)

Abstract

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A price time-series data of barley for a period of 49 years (1970-2019) sourced from the FAO database was used to determine the horizontal market integration of barley among some selected major market players in barley trade in the world. The chosen markets are Australia, Canada, Iran, Turkey and the USA based on the availability of up-to-date large span data. The collected data were analyzed using inferential statistics- unit root tests, co-integration tests, unrestricted vector autoregressive model, Granger causality test and impulse response function. The empirical evidence showed that the law of one price (LOP) exists among the selected markets i.e. there is perfect price communication among the markets in the long run, thus highly integrated. Besides, Australian and Canadian markets established a long-run equilibrium, thus have a stable price in the long run. Furthermore, the import and export hubs of barley in the trade are Canadian, USA and Turkey markets while Iranian and Australian markets are large consumer markets. The empirical evidence showed Canadian and USA markets to be the major players in the trade while the Australian market is a follower in the trade. All the selected markets have promising future prices with a little inflationary trend which will owe to supply fluctuation. The reinforcement of physical infrastructure, the use of ICTs and well-defined consistent agricultural policy/market initiatives would thus lead to the global creation of a single uniform economic market for barley.

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)0.002
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0040.005
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.017
GPT teacher head0.215
Teacher spread0.198 · 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 source (direct Gemma or distilled Codex), 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".

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Citations1
Published2021
Admission routes1
Has abstractyes

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