Does the Money Multiplier Hold in Pacific Island Countries? The Case of Papua New Guinea
Bibliographic record
Abstract
This is the first study to systematically assess the significance of the standard money multiplier vis-à-vis the bank credit transmission channel in the case of Pacific Island Economies, focusing on Papua New Guinea. The vector autoregressive model comprising six variables—interest rate, inflation rate, loans, deposits, reserve money, and real output—was estimated using quarterly data for the period 1980q1 to 2017q4. We applied the ordinary least squares (OLS) method to estimate the system of vector autoregressions (VARs). The estimation was conducted for the full and sub-sample periods. From the impulse response functions generated, the results suggest that the money multiplier does not hold and that the transmission to bank credit appears weak. It seems that the ability of the Central Bank to make loanable funds available through its conduct of monetary policy may not enhance private sector credit. On the other hand, there appears to be a significant and positive association between bank deposits and credit, suggesting that bank deposits and credit are endogenous and demand driven.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".