The Monetary Approch to Balance of Payments and Exchange Rate Equilibrium Determination with an Empirical Application to the Case of Algeria
Bibliographic record
Abstract
The aim of this paper is to explain the exchange rate by using the fundamental determinants of cointegration techniques to search if there is a long-term relationship between exchange rate and fundamentals of the Algerian economy. For this purpose we applied the model of the monetary approach of the balance of payments to the Algerian economy. We based in this study in Edward model That’s takes into account all external factors (terms of trade, external debt ...) and internal factors (government expenditure, budget deficit, money supply ...) for the determination of real exchange rate equilibrium, and we takes in consideration two variables, domestic credit, and international reserve, as they are the most important in monetary approach to balance of payments. The results of our study are summarized in the following point: The variable international reserve has a positive sign (the expected sign is positive) that allowed us to conclude that an increase in international reserve unit will result in an appreciation of the exchange rate of 9.60*10-12 %. The domestic credit has a positive influence on real exchange rate (the expected sign is negative), that allowed us to conclude that an increase in domestic credit unit will result in an appreciation of the exchange rate of 9.41*10-10 %. This result contradicts in the economy theory.
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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 | 0.003 | 0.013 |
| 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 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".