Do Open Sewers Lead to a Reduction in Housing Prices? Evidence from Rawalpindi, Pakistan
Bibliographic record
Abstract
In this study, we use the Hedonic property value method to estimate how a disamenity, bad odor from an open sewer system, affects housing prices in the city of Rawalpindi in Pakistan. We provide estimates of the benefits of converting the open system into a closed sewer system. We find that house rents decrease by approximately 10% if there is an open sewer (nali) by the house. House rents also increase for homes located further away from the main open drain (Nala Lai) - e.g. a house located 400 meters away from the main open drain enjoys a 12 percent increase in rent because of its distance. Sewer smell has a depressing effect on rent in those areas where smell remains constant throughout the day. The results suggest that residents are willing to pay to be away from bad odor emanating from the open sewerage system. City planners need to take this into account and consider installing sewerage pipes in open sewer areas, which would change the nature of Nala Lai from a disamenity to an amenity.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".