High house prices may be global systemic risk
Bibliographic record
Abstract
Subject The rise in global house prices. Significance In the first quarter of 2015, the global house price index, aggregating prices in 52 countries, was at about the same level as in early 2007, according to IMF data. This recovery has occurred in a period of wage gains in most emerging markets (EMs), but little or no growth in household income across most advanced economies. Living costs excluding housing have stagnated and interest rates have been exceptionally low. Yet US interest rates are rising now and global prices are unlikely to keep falling beyond 2016, while many EMs have slumped into recession. As households are hit by more adverse trends, property markets and the related sectors will be affected. Impacts The EM house price boom will be curbed by slowing income growth and weaker economic prospects. High house-prices-to-household-income ratios and household debt might require the introduction of macroprudential tools. The US housing market will stay affordable compared to its long-term average and to Europe's.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.043 | 0.006 |
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".