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Record W2557739864 · doi:10.3844/ajabssp.2016.148.156

An Empirical Analysis of Supply Response of Rubber in Malaysia

2016· article· en· W2557739864 on OpenAlex
Ghulam Mustafa, Ismail Abd Latif, Henry Egwuma

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Agricultural and Biological Sciences · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsNutrasource
FundersUniversiti Putra Malaysia
KeywordsEconomicsIncentiveFertilizerNatural rubberAgricultural economicsError correction modelEconometricsRelative priceMicroeconomicsCointegrationAgronomy

Abstract

fetched live from OpenAlex

Supply response of rubber to changes in economic incentives is analysed using co-integration approach. Time series data is taken for the period 1990 to 2014 and the vector error correction model framework has been applied. The empirical results confirmed the existence of a unique long-run equilibrium relationship among planted acreage, the relative price of rubber and price of fertilizer. Further, the estimates suggested that rubber supply is significantly influenced by the relative price of rubber and the price of fertilizer. The estimated short-and long-run elasticities of acreage with respect to relative price are respectively 0.04 and 0.77, while the short-and long-run elasticities of acreage with respect to fertilizer price are -0.20 and -0.28 respectively. The study recommends the design of an appropriate economic incentive structure to stimulate output and hence the income of farmers.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.266

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.059
GPT teacher head0.259
Teacher spread0.200 · 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