Energy Performance of Rented Dwelling: If You Can Dream It…
Bibliographic record
Abstract
The energy performance of rented dwellings is a crucial aspect of energy policy in the Walloon region in Belgium, where one quarter of households are tenants on the private market. The paper deals with the imperfect information problem that concerns the energy performance certificates (EPCs) and its impact on rental market. Four aspects of the problem reported in the literature are discussed, namely: 1) different energy evaluations of the same dwelling; 2) performance gap between theoretically estimated and real energy consumption; 3) insufficient coverage of the rental market by EPCs; 4) often weak appreciation of official EPCs on the rental market. The originality of the paper is that it compares the official EPC labels with the labels reported by tenants in a recent survey (N=2.892). While an existing EPC is often unknown for tenants, their awareness depends on the households’ socio-economic characteristics. Four groups of tenants are distinguished: those with correct answers, “dreamers” overestimating their energy performance, “complainers” underestimating their energy performance, and “indifferent” tenants who don’t know the existing label. The differences between groups are analyzed with descriptive statistics and a discrete choice model. According to the hedonic regression, the impact of an official EPC on housing rents varies for households with different perceptions of energy performance. In particular, the “dreamers” more severely penalize the worst energy classes, while the “indifferent” tenants a bit undervalue good EPCs and a bit overvalue bad EPCs. The indifference concerning the EPC slows down a progressive introduction of the impact of the energy performance on a residential rental market. In a policy context, the availability of a clear information on EPC for all tenants is an important condition of the functioning of the residential rental market in a manner that stimulates the renovation of old housing stock and the maintenance of high energy standards.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".