Applied Environmental Economics: Bridging the divide between policy and theory within the context of recycling, macro-level environmental indicators, and water trading
Bibliographic record
Abstract
By focusing upon a range of topics and utilising a range of techniques, this Thesis provides a review of a range of issues related to successful environmental economics policy prescriptions. How and why certain policies are selected will be crucial to making effective policy prescriptions and this is the central focus of this Thesis. Spanning from a review of a policy prescription that was not followed to the development of a model that is applied to the review of a policy proposal; examples of policy failure, policy success, and policy prescriptions are at the core of the discussion throughout. With an appraisal of policy-making on a local level, the case of recycling and the household charge for waste collection is reviewed using data from municipalities in New South Wales, Australia. This analysis shows that without an adequate pricing scheme, different levels of the household charge for waste collection across municipalities have little association with different levels of recycling. An appraisal of intergovernmental agreements (including the Montreal Protocol) follows and finds that evidence points to an induced policy response, rather than the Environmental Kuznets Curve relationship. While declines in emissions cannot be solely attributed to the timing of the targets prescribed, the Montreal Protocol was associated with notable emission reductions. The last area of research covers a range of issues surrounding water trading between agricultural firms. Chapter four introduces a distinctive and innovative agent based model built to provide projections of trading that allow for: - the constraint of transaction costs, - the mixture of firms within the trading scheme, - out of equilibrium market operation, and – a range of crop water demands. This model is then utilised to gauge the impact of the implementation of a ‘Network Trading Scheme’ which has the aim of reducing the impact of transaction costs on otherwise viable trades.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.015 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".