Decomposing Residential Resale House Prices into Structure and Land Components
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The use of hedonic regression models on the sales of detached housing units is widespread in the real estate literature. However, these models do not address the need to decompose the sale price into structure and land components. For many purposes, it is necessary to obtain separate estimates for the price and quantity of housing structures and the land that these structures sit on. The builder’s model accomplishes this decomposition but it takes a producer’s perspective and requires an exogeneous structure price index. In the present paper, a consumer approach to the decomposition problem is taken and this “new” approach to the decomposition problem does not require the use of an exogenous building price index. The paper uses data on sales of detached houses in Richmond, British Columbia in order to implement the new approach. The property price indexes generated by the new approach are compared to the corresponding indexes generated by a traditional time dummy hedonic regression model. The traditional hedonic regression approach does generate reasonable overall property price indexes, but the two approaches do not generate similar land and structure subindexes.
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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 | 0.000 | 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 it