VECTOR AUTOREGRESSION EVIDENCE ON MONETARISM: A FOCUS ON SOME DEVELOPING ECONOMIES IN SOUTH ASIA
Bibliographic record
Abstract
The objective of this paper is to test the validity of two views of monetarism in Bangladesh, India, and Pakistan. A Structural Vector Autoregressive (SVAR) model is developed and the objective is accomplished by conducting Granger causality tests and estimating variance decompositions and impulse response functions. The first view of monetarism that changes in the quantity of money cause, lead and are positively related to changes in prices at least in the medium to long time horizon is supported in Bangladesh, India, and Pakistan. The second view of monetarism that changes in the quantity of money cause, lead and are positively related to changes in output at least in the short to medium time horizon is not supported. The implication of such a result is that an expansionary monetary policy only fuels prices with insignificant effects on output. It supports the view of real business cycle theorists who postulate that policy changes only affect prices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.007 |
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 teacher head, 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".