Exploring the Effects of Municipal Land and Building Policies on Apartment Size in New Residential Construction in Sweden
Bibliographic record
Abstract
New residential construction in many countries with rapid urban growth is often interrelated with smaller housing units being built. Sweden is not an exception. It is of interest to investigate the driving forces behind this tendency. Our presumption is that municipal land price policies and building permit regulations might play a certain role in this process. Contrary to previous studies that focus on the number of new dwelling units in housing construction, our purpose is to analyze the average size of new housing units and the factors that affect it on an aggregate level. We apply seemingly unrelated regressions for analysis of the average apartment size in new residential construction in the three largest metropolitan regions in Sweden as a function of the changes in population, apartment rent and prices, mortgage interest rates, land prices, and building permits per capita as a proxy for regulation. The unbalanced panel dataset includes the period between 1998 and 2017 and covers both the rental and the housing cooperative sectors. The analysis demonstrates that land prices and building policies along with market fundamentals are the underlying factors that affect the average size of an apartment in new residential construction in Sweden.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".