Determinants of Money Demand in Algeria: An Empirical Study Using Cointegration and Error Correction Model
Bibliographic record
Abstract
This investigation aims primarily to estimate the determinants of the demand function of money in its broad sense, in Algeria during the period 1980-2017. To accomplish this study, Cointegration and Error Correction Model (ECM) have been used. Thus, these tests proved the no stationary of time series which led us to apply the cointegration tests, so in the end we estimate the model with error correction. The results of this estimation show that the importance of determinants of money demand in the short and long term are ordered as follows: real income, the velocity of circulation of money (VM2) in the short and long term, the long-term exchange rate; in the short term its importance diminishes in favor of inflation, which has a decisive effect on the demand for money in the short term. The findings reveal that the money demand function is insensitive to the interest rate, which explains why speculation is generally regarded as a less important reason in Algeria.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".