The Influence of Monetary Policy on Real Estate Market as a Potential Catalyst for Economic Crisis
Bibliographic record
Abstract
The thesis focuses on the influence of target interest rates set by central banks to stimulate property markets, in particular on the impact of these rates on real estate pricing and the subsequent bubbles in the housing market. In my work I analyse panel data portraying the quarterly performance of 29 European states from early 2000 till the end of second quarter of 2015. In the first part I investigate the influence of interest rates on property prices and find out that a one percentage point decrease of the target interest rate by the central bank resulted in a rise of 0.897 points in the house price index. In the second part I evaluate the impact of this instrument on the creation of a housing bubble, which is represented by the indicator of housing price sustainability. I estimate that an decrease in interest rates by one percentage point is concomitant with a increase of growth of the price bubble by 0,28 %. I thus validate my hypotheses on the negative correlation between the aforementioned variables.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.001 |
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".