A Proposal for a Residential Housing Price Index in Cyprus Through Analysis of Transaction-Based Data and Comparison With Existing Indices
Why this work is in the frame
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Bibliographic record
Abstract
This research suggests improvements to the macroeconomic housing indices of a thin real estate market, such as that of Cyprus, by testing various index construction methods with transaction-based data. Authors employ around 80% of the total number of apartment transfers documented at the Department of Lands and Surveys (DLS) of Cyprus, spanning from the first quarter of 2015 to the second quarter of 2022. They utilize this data to generate comprehensive indices at both the national and district levels. Authors studied, analyzed, and identified the deficiencies of the DLS database and tested the sample with six different methods. Log-linear time dummy hedonic models were found to explain the variation of prices better than other methods, mainly due to their ability to handle the diversity of properties in terms of location and physical characteristics and proposed techniques to deal with the issues of the standard time dummy (STD) and rolling time dummy (RTD) methods, regarding index revisions and low transaction volume during periods of downturns, respectively. Furthermore, a hybrid dependent variable of actual and appraised prices, that is, the accepted price, extracts explicit significantly better statistical measures. Additionally, the overall model fit was enhanced by introducing locality dummy variables and, through different combinations of attributes, captured the optimal results per district. Eventually, when the introduced transaction-based indices were compared to the corresponding existing published indices, which are based on non-actual data, we saw some resemblances, but overall, there were wide deviations.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it