THE PERFORMANCE OF MUNICIPAL WATER UTILITIES: EVIDENCE ON THE ROLE OF OWNERSHIP
Bibliographic record
Abstract
There is growing concern about the operations of the municipal agencies responsible for supplying potable water and treating sewage, spurred by (1) difficulties of maintaining aging capital stocks in times of tightening fiscal constraints, (2) the water pollution generated by these agencies, (3) problems associated with service quality and reliability, and (4) the recognition of the role played by utilities in allocating scarce water resources. These concerns have lead to a heightened scrutiny of these agencies with increased interest in reforming their operations. In particular, this has focused on an examination of whether the ownership of water utilities is a factor explaining their behavior and whether changing their ownership will lead to improvements in their operations. The purpose of this paper was to critically assess what is known regarding the relationship between the ownership and performance of municipal water utilities. There are a number of theoretical arguments that support the prediction that privately owned water utilities will out-perform comparable publicly funded utilities. These arguments draw on property-rights and public choice theories and principle agent models in order to emphasize the difficulty that governments have in monitoring and providing proper incentives for utility managers. Empirical evidence was obtained from the United States, the United Kingdom, and France based on a variety of performance indicators. These data revealed that there was no compelling evidence of private utilities outperforming public utilities or that privatizing water utilities leads to improvements in performance.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".