THE SHOCKS REDUCING EFFECT OF FLEXIBLE EXCHANGE RATE SYSTEMIN THE GLOBAL FINANCIAL CRISIS PROCESS: A COMPARATIVEANALYSIS
Bibliographic record
Abstract
Especially, many developed and developing economies has made transition into a flexible exchange rate system since 1990s. It is accepted that flexible exchange rates allow countries to be flexible in monetary policies against external shocks in economy literature. In this study, taking sample countries which are adopted flexible exchange rate system, shock absorption properties of flexible exchange rate system are investigated in the 2008 global crisis process. With the help of VAR structural analysis, the context of Japan, Canada, Korea and Turkey economies have been examined. The study was examined by separating two subtopic parts which are pre crisis and post crisis periods. According to the survey results, the reducing effects of exchange rate on the demand shocks were seen in Japan and Turkey in the pre-crisis period, for Canada in the post crisis period. There is a reducing effect of exchange rates on supply shocks in Japan and Turkey after the global crisis period. On the other hand, the reducing effect of exchange rate on shocks was not observed in South Korea. In addition, the data obtained from variance decomposition of reel exchange rates shows that the shock effects of exchange rates are higher than the reducing effects of exchange rates
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".