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Record W2576365312 · doi:10.5539/ijef.v9n2p159

Economic Growth and Total Factor Productivity in Lebanon

2017· article· en· W2576365312 on OpenAlex
Wadad Saad

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Economics and Finance · 2017
Typearticle
Languageen
FieldComputer Science
TopicEconomic Growth and Development
Canadian institutionsnot available
FundersCentre National de la Recherche Scientifique
KeywordsOpenness to experienceTotal factor productivityDistributed lagEconomicsForeign direct investmentProductivityPrivate sectorInvestment (military)EconometricsMacroeconomicsMonetary economicsEconomic growth

Abstract

fetched live from OpenAlex

This study investigates empirically the determinants of economic growth and total factor productivity in Lebanon over the period 1980-2014. To do so, we firstly estimate the total factor productivity in a growth accounting framework. Secondly, an Autoregressive Distributed Lag (ARDL) modeling approach has been applied to examine the relationship between economic growth and some macroeconomic variables such as foreign direct investment, openness, claims on private sector, and official development assistance. Then we consider modeling the effects of these macroeconomic determinants on TFP through an ARDL model. Findings of the regression analysis suggest the presence of a statistically significant relationship between economic growth and the variables involved in this study except for claims on private sector which appears to be insignificant. The results of TFP model show a significant relationship with claims on private sector and openness on one hand and insignificant link with the direct foreign investment and official development assistance on the other hand.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.624
Threshold uncertainty score0.292

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.013
GPT teacher head0.221
Teacher spread0.208 · 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