Understanding the Roots of the US Subprime Crisis and its Subsequent Effects
Bibliographic record
Abstract
In this paper we provide an overview of the roots, first manifestations and further developments of the US subprime crisis and explain the securitization process by emphasizing especially the mortgage securitization process. Some explanations for the ongoing financial crisis are also offered. We continue with a presentation of the US real estate sector and its main indicators. Finnally, we investigate the relationship between home mortgages growth and gross domestic product in the United States using quarterly observations for the two variables, covering the 2002-2008 time period. We find that curret GDP is explained both by its own lagged value and by previous quarter change in home mortgages. A unidirectional Granger causality from home mortgages to the gross domestic product is also attested. We can therefore report that a significant decrease in borrowing leads to an equally significant decrease in house prices and causes a future economic slowdown, reflected by a decrease in the gross domestic product.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".