Opportunities and risks in the residential sector during a green transition: House prices, energy renovations and rising energy prices
Bibliographic record
Abstract
Transitioning to a low-carbon economy implies both risks and opportunities in the Danish housing sector, which accounts for one fourth of Denmark's CO2 emissions. We study the heterogeneous impacts on house prices of rising energy prices and energy renovations by combining micro-level data on sales and housing characteristics with data from the official mandatory energy rating reports. We find that higher energy prices reduce the prices of houses without district heating mainly in rural areas. Most renovations will not increase sales prices enough to cover the costs. Those renovations whose price effect will cover the costs have a lower-than-average impact on CO2 emissions, are cheap, and typically concern houses located in and around towns and mid-sized cities and other areas with a higher population density and well-developed road networks connected to towns and cities. We conclude that while opportunities for profitable energy renovations are concentrated in these areas, transitional risks are instead associated with peripheral rural areas, where both the exposure to rising energy prices and the risk of financing renovations is highest.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".