A study on the relationship between money supply and inflation in Vietnam from 2005 to 2021
Bibliographic record
Abstract
The study examines the relationship between money supply and inflation in Vietnam in the period of 2005-2021. The relationship between money supply and inflation is addressed in economic theories and models and has been studied by many experts in different economies in different periods. To examine the relationship between money supply and inflation in Vietnam in the period of 2005-2021, the research team collected data on money supply and inflation rate, then analyzed this relationship during three periods of 2005-2011, 2012-2019 and 2019-2021. Next, the research team collected data on money supply (MS - total means of payment) and consumer price index (CPI), quarterly data from the first quarter of 2005 to the fourth quarter of 2021 and uses Eviews 8 software for analyzing. The research team uses a linear regression model to evaluate the impact of money supply growth (GMS) on consumer price index (CPI), a variable representing the inflation rate, of Vietnam during the research period. The model results support the view that money supply growth and past inflation are among the factors affecting inflation in Vietnam. From the research results and the actual money supply, the money supply growth rate as well as the inflation rate in Vietnam during the research period, the research team makes some policy recommendations to achieve the targets of supporting economic recovery, controlling inflation, stabilizing the macro-economy in Vietnam after the Covid-19 pandemic.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".