Setting the Standard: Commercial Electricity Consumption Responses to Energy Codes
Bibliographic record
Abstract
The adoption rate of building energy standards in the US has been increasing since the mid- 1990s as a result of the Energy Policy Act of 1992 (EPAct). However, most of the evidence on the energy savings that accrue from commercial building energy standards is based on engineering simulations, which do not account for realized behavior once a standard is actually adopted. This paper uses plausibly exogenous variation in commercial building energy standard adoptions, combined with a unique state-level dataset on electricity consumption, energy prices, and the prevalence of “plus-utilities” tenancy contracts in commercial buildings, to estimate the realized electricity consumption response to commercial energy codes. The results suggest that in states with a large fraction of post-EPAct new construction under a code, per capita commercial electricity consumption is lower by about 13%. In addition, a one percentage point increase in the rate of tenancy contracts where tenants pay directly for energy utilities is associated with a 1% decrease in per capita electricity demand. The realized energy savings are less than half of predicted simulated savings.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".