Economic integration and the exchange rate regime: how damaging are currency crises? : [This Version: October 2003]
Bibliographic record
Abstract
We use consumer price data for 205 cities/regions in 21 countries to study PPP deviations before, during and after the major currency crises of the 1990s. We combine data from industrialized nations in North America (Unites States, Canada and Mexico), Europe (Germany, Italy, Spain and Portugal), Asia (Japan and South Korea), and Oceania (Australia and New Zealand) with corresponding data from emerging market economies in South America (Argentina, Bolivia, Brazil, Columbia) and Asia (India, Indonesia, Malaysia, Philippines, Taiwan, Thailand). By doing so, we confirm previous results that both distance and border explain a significant amount of relative price variation across different locations. We also find that currency attacks had major disintegration effects by considerably increasing these border effects and by raising within-country relative price dispersion in emerging market economies. These effects are found to be quite persistent since relative price volatility across emerging markets today is still significantly larger than a decade ago.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".