The economics of seemingly abundant resource : efficient water pricing in Vancouver, Canada
Bibliographic record
Abstract
Current North American water pricing practices are inefficient because they are based on average utility expenditures rather than marginal costs and because they typically neglect factors such as the cyclicity of demands, the time of consumption and the value of the water resource. Despite strong criticisms of these practices (Hirshleifer, DeHaven and Milliman, 1960; Pearse, 1985) and the presence of well articulated theoretical models of efficient pricing alternatives (eg., peak-load pricing) no empirical study has been done to document the magnitude of the efficiency gains from altering water prices. A simulation program computes the impact upon a representative water utility's output and deficit and upon aggregate consumer surplus of a move from current practice to efficient prices. The program is based on the estimated costs of supply and demand for water for the city of Vancouver, Canada. A time series of quarterly observations for the period 1975-1986 is used to estimate short and long run marginal costs. The estimated cost structure of the utility is also used to test for optimal employment of its fixed factors: water in storage and capital. Cross-sectional data sets are used to estimate market demands for residential and industrial users. The estimation results indicate that long run marginal cost exceeds short run costs by a large margin and that there is some evidence of over-capitalization by the utility. Water demands are seen to be inelastic for indoor and outdoor residential consumption but are elastic for industrial consumption. Simulation results show that a move to seasonally differentiated pricing (with an annual charge calculated to recoup the resulting deficit) raises aggregate surplus by approximately 4%. Conversely, a move from current practice to Ramsey prices leads to a decrease in aggregate consumer surplus of approximately 13%.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".