Current account dynamics: A SVAR analysis when the country‐specific shocks are correlated at leads
Bibliographic record
Abstract
Abstract The assumption of no correlation of the structural shocks as Blanchard and Quah's identification (BQ) assumes is not suitable when central banks, through discretionary policies or inflation targeting regimes, affect the output growth among other goals. In this study, we analyze the present value model of the current account (PVM) using a three‐SVAR specification and a modified BQ to identify three structural shocks: country‐specific permanent, country‐specific temporary, and global, but allowing the correlation of the domestic ones. Using Australia, Canada, Norway, and the UK, we find that those shocks are correlated and are less volatile than BQ would assume they are. The PVM predictions that hold are: (i) a positive (no) response in the current account to a country‐specific temporary (global) shock; and (ii) with the exception of Australia, there is no response in the current account to a country‐specific permanent shock. In addition, for all countries, the country‐specific temporary shock dominates current account changes but does not dominate net output growth fluctuations, which was a puzzle identified by a prior study. The role of the shock is enhanced by the modified BQ, but even with this enhancement, it still does not hold the most significant role in output variations, as indicated by PVM.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".