Weathering the financial crisis : good policy or good luck?
Bibliographic record
Abstract
The macroeconomic performance of individual countries varied markedly during the 2007-09 global financial crisis. While China's growth never dipped below 6% and Australia's worst quarter was no growth, the economies of Japan, Mexico and the United Kingdom suffered annualised GDP contractions of 5-10% per quarter for five to seven quarters in a row. We exploit this cross-country variation to examine whether a country's macroeconomic performance over this period was the result of pre-crisis policy decisions or just good luck. The answer is a bit of both. Better-performing economies featured a better-capitalised banking sector, lower loan-to-deposit ratios, a current account surplus, high foreign exchange reserves and low levels and growth rates of private sector credit-to-GDP. In other words, sound policy decisions and institutions reduced their vulnerability to the financial crisis. But these economies also featured a low level of financial openness and less exposure to US creditors, suggesting that good luck played a part.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".