MétaCan
Menu
← Back to cohort
Record W2795668799 · doi:10.5539/ijef.v10n5p105

Impact of Morocco-ECOWAS Economic Relations on Economic Growth in Morocco: An Analysis Using the ARDL Model

2018· article· en· W2795668799 on OpenAlexvenueno aff
Hidaya EL Khattabi, Mohamed Karim

Bibliographic record

VenueInternational Journal of Economics and Finance · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsForeign direct investmentEconomicsPer capitaInternational economicsInternational tradeOrder (exchange)Investment (military)Distributed lagMacroeconomicsPolitical science

Abstract

fetched live from OpenAlex

Over the last decade, Morocco has undertaken numerous reforms in order to successfully integrate itself into the global economy in general, and Africa in particular, with the aim of diversifying and strengthening its competitive export potential.In fact, the analysis of trade relations between Morocco and ECOWAS reveals an increasing volume of trade, reflecting a continuous dynamization of their commercial relations. A similar trend is observed in foreign direct investment, which has been growing steadily over the last few years, reflecting Morocco’s desire to become a major player in the development of the African continent.The analysis of Morocco’s trade opening and foreign direct investment (FDI) in ECOWAS on Morocco’s economic growth, using ARDL (Autorégressive distribution Lag) modelling, shows that Moroccan foreign direct investment to ECOWAS has a significant impact on its GDP per capita in the short and long term. With regard to bilateral trade between the two partners, no long-term equilibrium relationship could be established due to the still low weight of trade volumes.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.170
Threshold uncertainty score0.338

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.002
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 head0.060
GPT teacher head0.279
Teacher spread0.219 · 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".

Quick stats

Citations3
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Economics and Finance→Same topicGlobal trade and economics→French-language works237,207→