Monitoring 15 years of residential house price development in Hungary with the help of the FHB House Price Index
Bibliographic record
Abstract
The working paper presents the development of the housing market in Hungary between 1998 and 2013 through the history of the FHB House Price Index. For computing the FHB House Price Index FHB applied the hedonic method. At its first publication in 2009 the Index was based on actual transaction data of residential real estate collected from the year of 1998 from appr. 1,000,000 residential properties located in appr. 3,200 municipalities. The source of data include the valuation records of FHB Mortgage Bank, as well as the buying - selling transaction database purchased from NAV, the national tax authority. Since its first publication the Index is updated on a quarterly basis. The average index value in 2000 was 100 later it peaked at 200,7 in the first quarter of 2008. The 15 years of the housing price history were divided into 4 significantly different eras. When analysing the development of the housing market, relations between selected macroeconomic and financial environment indicators , money market and credit market indices and other data of the housing market were also taken into consideration.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".