Empirics of currency crises: A duration analysis approach
Bibliographic record
Abstract
Abstract This paper empirically analyzes the origins of currency crises for a group ofOECDeconomies from 1970 through 1998. We apply duration analysis to examine how the probability of a currency crisis depends on the length of non‐crisis periods, contagion channels, and macroeconomic fundamentals. Our findings confirm the negativeduration dependenceof a currency crisis—the likelihood of speculative attack sharply increases at the beginning of non‐crisis periods and then declines over time until it abruptly rises again. The results also indicate the hazard of a crisis increase with high values of the volatility of unemployment rates, inflation rates, contagion factors—which mostly work through trade channels, unemployment rates, real effective exchange rate, trade openness, and size of economy. To address concerns regarding validity of the identified crisis episodes, we exploit crisis episodes that are identified by a more objective approach based on the extreme value theory. Our results are robust under various specifications including two different crisis event sets that are identified on monthly and quarterly basis.
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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 | 0.011 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".