MétaCan
Menu
Back to cohort
Record W3083002145 · doi:10.5430/rwe.v11n5p246

Factors Affecting Product Supply in the Domestic Agrarian Market in Azerbaijan

2020· article· en· W3083002145 on OpenAlexvenueno aff
Sugra Humbatova, Natig Gadim‒Oglu Hajiyev

Bibliographic record

VenueResearch in World Economy · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Socioeconomic and Political Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsAgrarian societyCointegrationDomestic marketUnit rootEconometric modelAgricultureProduct (mathematics)Unit root testVolatility (finance)EconometricsInternational tradeMathematics

Abstract

fetched live from OpenAlex

The purpose of the study was to study, analyze, evaluate and forecast the factors affecting the formation of product supply in the domestic agrarian market. Socio-economic aspects of the factors influencing the growth of product supply in agrarian market in the country were considered for the purpose of the research. Statistical and econometric analysis was carried out by the method of generalization, grouping, systematic approach, the role and place of factors influencing the growth of product supply in agrarian market. The methodology used is based on econometric analysis of time series. The first step involves the formation of an order of integration of variables included in the model and utilizing several unit root tests such as the Augmented Dickey-Fuller (ADF), Phillips-Perron (PP) and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) tests. The cointegration approach is based on the ARDL model and the boundary test. The relative volatility of some indicators, which indirectly depends on oil prices, has led to some limitations in the study. The originality of the research is a complex statistical and econometric analysis of the factors influencing the increase of product supply in the domestic agricultural market, and the scientific novelty is the determination of the dependence of product supply in the agricultural sector on government support, including investment. The application of the article in the development of this section on the impact of agricultural supply on food security is of practical importance.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.261
Threshold uncertainty score0.879

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.123
GPT teacher head0.335
Teacher spread0.212 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueResearch in World EconomySame topicGlobal Socioeconomic and Political DynamicsFrench-language works237,207