Hedonic Modeling for a Growing Housing Market: Valuation of Apartments in Complexes
Bibliographic record
Abstract
The share of apartment complexes in housing stock of major cities in the developing world has been increasing. They represent a different housing submarket whose growing importance necessitates further research. Using survey data on transaction records of real estate agents, we employ a hedonic pricing model to explore the factors influencing apartment prices in the Metropolitan Izmit area. The site of a major reconstruction effort following a strong earthquake, Izmit has been in the forefront of the changes taking place in the Turkish real estate sector in particular, and in urban housing in general. We aim to get better estimates by focusing the study on apartment complexes in Metropolitan Izmit, the major submarket in the area. The results reveal that structural characteristics of an apartment as well as amenities provided in an apartment complex are important determinants of price. Air quality and proximity to a good public school have a major effect on price as well. The findings suggest that the submarket could be segmented further geographically.
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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 | 0.000 |
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 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".