The 'Green’ Premium in Israel: Measuring the Effects of Environmental Certification on Housing Prices
Bibliographic record
Abstract
‘Green’ building initiatives have led to the emergence of market-based policy approaches in a number of countries. Many of these have taken the form of environmental certification for buildings. A number of studies have examined the additional construction costs involved in achieving ‘green’ certification, and these studies suggest that they are relatively low, around 2% on average. Evidence is accumulating, however, that the "green premium" – or the extra cost that homebuyers pay to purchase a property in a certified green building – is systematically higher than this. This study aims to identify the nature and scale of the "green premium" in Israel, based on a novel comparative calculation method developed to examine how much ‘green’ building certification raises an apartment's price. We also examine how economically profitable it is to purchase a 'green' apartment for the homebuyer and for the Israeli economy overall. Finally, through a case study in Tel Aviv, we shed light on how the implementation of environmentally certified housing may lead to gentrification.
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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".