Low Interest Rates and Housing Booms: the Role of Capital Inflows, Monetary Policy and Financial Innovation
Bibliographic record
Abstract
A number of OECD countries experienced an environment of low interest rates and a rapid increase in real house prices and residential investment during the past decade.Different explanations have been suggested for the housing boom: expansionary monetary policy, capital inflows due to a global savings glut and excessive financial innovation combined with inappropriately lax financial regulation.In this study we examine the effects of these three factors on the housing market.We estimate a panel VAR for a sample of OECD countries and identify monetary policy and capital inflows shocks using sign restrictions.To explore how the effects of these shocks change with the structure of the mortgage market and the degree of securitization, we allow the VAR coefficients to vary with mortgage market characteristics.Our results suggest that both types of shocks have a significant and positive effect on real house prices, real credit to the private sector and residential investment.The response of housing variables to both types of shocks is stronger in countries with more developed mortgage markets.The amplification effect of mortgage-backed securitization is particularly strong for capital inflows shocks.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".