The Effectiveness of Monetary Policy And Money Demand Function Stability In A Developing Economy: Empirical Evidence from the State of Kuwait
Bibliographic record
Abstract
A stable money demand function plays a vital role in the analysis of macroeconomics, especially in the planning and implementation of monetary policy.This paper aims to examine the stability and behavior of the money demand function in Kuwait during two different periods. Where the first period extent between the first quarter of the year 1980 until the fourth quarter of the year 1998, which represents the political instability in the Arabian Gulf area. The second period between the first quarter of the year 1999 until the second quarter of the year 2018, and this period represents the political stability in the State of Kuwait. Hence, the real money balances (M1) is used by the error-correction models (ECM) technique to explain the short-run stability and behavior of M1, where ordinary least squares (OLS) technique is used to explain the stability and the behavior of M1 in long-run. The function of demand for money for Kuwait, whether short-term or long-term, is stable between the first quarter of the year 1999 and the second quarter of 2018, as well as stability in the full data between the first quarter of 1980 and the second quarter of 2018, which means that monetary policy is effective during these periods according to the estimated results of these functions.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.001 | 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".