Causality between Economic Growth, Export, and External Debt Servicing: The Case of Lebanon
Bibliographic record
Abstract
The econometric relationship between external public debt, exports and economic growth in Lebanon has been rarely examined. This study empirically investigates the relationship between economic growth, exports and external debt of Lebanon through an econometric analysis over the period 1970-2010 with the inclusion of a fourth macroeconomic variable that is the exchange rate. The exports were introduced in the model to test the export-led growth hypothesis for Lebanon. We explore this relationship using the vector error correction models (VECM) and we employ Granger causality technique in order to investigate the presence of causality among these variables. The results show that both short run and long run relationships exist among these variables. Moreover, the finding suggests, i) bidirectional Granger causality between GDP and external debt servicing, ii) unidirectional Granger causality that runs from external debt to exports, iii) unidirectional causality running from exports to economic growth, and iv) unidirectional causality running from exchange rate to economic growth.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".