Bibliographic record
Abstract
Official Statistics on housing prices are a one of the relatively new segments of prices statistics, developed in the wake of the data gaps underlined by the last economic and financial crisis. Official European statistics need to abide to the highest standards of quality and harmonisation across countries. Eurostat and the National Statistical Institutes (NSIs) released the official harmonised HPIs in the beginning of 2013. Initially only indices on total housing price developments were published. However, users requested a breakdown into price developments for existing dwellings and for new ones. In parallel to further work on developing a methodological framework (with the Handbook on Residential Property Price Indices) and improvements of the data quality (starting from data sources for transactions, to data validation and index compilation) Eurostat worked with the NSIs on preparing the ground for this additional breakdown. Since autumn 2014 the split in new and existing dwellings has been made available both for annual and quarterly data. The quarterly data series start in 2005 and are disseminated with a timeliness of one quarter after the reference quarter. Today, HPI published by Eurostat are used for several policy purposes: for monetary policy assessments of price signals, for financial stability purposes as a soundness indicator and also to monitor macroeconomic imbalances: The deflated house price index (nominal HPI deflated by the index of private household consumption) is one of the fourteen MIP Scoreboard indicators used in the Alert Mechanism Reports. For complementing the information on price evolution and for supporting the analysis of housing markets, Eurostat started to work together with the NSIs to collect data on turnover. Furthermore, this was a request of the ECOFIN in order to further enrich the PEEIs (Principal European Economic Indicators). The publication of an index capturing the total value of transactions was launched in December 2015. The annual series are available for 18 EU Member States and going back to 2010. The publication of HPIs for EU countries going back often to 2000 together with the indices on turnover are a reliable source of data for better understanding the evolution of housing markets during the tumultuous period of the last decade and its implications for the present and future.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".