The Financial Crisis: Lessons for the Next One
Bibliographic record
Abstract
The massive and multifaceted policy responses to the financial crisis and Great Recession — ranging from traditional fiscal stimulus to tools that policymakers invented on the fly — dramatically reduced the severity and length of the meltdown that began in 2008; its effects on jobs, unemployment, and budget deficits; and its lasting impact on today’s economy. Without the policy responses of late 2008 and early 2009, we estimate that: The peak-to-trough decline in real gross domestic product (GDP), which was barely over 4%, would have been close to a stunning 14%; The economy would have contracted for more than three years, more than twice as long as it did; More than 17 million jobs would have been lost, about twice the actual number. Unemployment would have peaked at just under 16%, rather than the actual 10%; The budget deficit would have grown to more than 20 percent of GDP, about double its actual peak of 10 percent, topping off at $2.8 trillion in fiscal 2011. Today’s economy might be far weaker than it is — with real GDP in the second quarter of 2015 about $800 billion lower than its actual level, 3.6 million fewer jobs, and unemployment at a still-dizzying 7.6%. We estimate that, due to the fiscal and financial responses of policymakers (the latter of which includes the Federal Reserve), real GDP was 16.3 % higher in 2011 than it would have been. Unemployment was almost seven percentage points lower that year than it would have been, with about 10 million more jobs. To be sure, while some aspects of the policy responses worked splendidly, others fell far short of hopes. Many policy responses were controversial at the time and remain so in retrospect. Indeed, certain financial responses were deeply unpopular, like the bank bailouts in the Troubled Asset Relief Program (TARP). Nevertheless, these unpopular responses had a larger combined impact on
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.011 | 0.020 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.011 | 0.015 |
| Insufficient payload (model declined to judge) | 0.027 | 0.005 |
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".