Factoral impact of house prices in Bulgaria: cross-spectral analysis
Bibliographic record
Abstract
The subject of research in this publication is the market house prices. They represent the real selling prices of dwellings (flats) free of charges, commissions, lawyers' fees and property transfer costs, whereas the house price index assesses the overall relative change in house prices in the current quarter compared to the previous one. The aim of this study is to assess the direction and intensity of the dependence between house prices and selected macro indicators such as the average gross monthly salary, monetary supply and the size of mortgage loans. The study period is from 2000 to 2018. The methodology is based on an analysis of the impact of the macro indicators on house price changes and on cross-spectral analysis to measure the degree of correspondence between their periodic components. The survey results show a statistically significant correlation between house prices and the macro indicators of money supply and mortgage loans. There is a close correlation between the periodic components of market house prices and the macro indicators. Matching wavelengths at which the phase spectrum measuring the degree of their correlation receives relatively low values is observed to be at a length of nine years.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".