Political Costs and the Challenge of Tradable Environmental Allowance Markets
Bibliographic record
Abstract
Traditional accounts of tradable environmental allowance markets focus on the economics of their operation and the instrumental costs of their design, such as the definition, monitoring, and enforcement of rights. Less attention has been given to the role of political costs in influencing whether these market-based mechanisms get enacted at all, and their form and fate if they do. These costs help to explain the divergence between strong theoretical arguments in favor of tradable environmental allowance markets and their more limited real world success. This Article analyzes how costs arising from the political process-that is, costs to politicala ctors of pursuing particularp olicies-affect the decision to advance tradable market-based environmental policies, and whether these policies are sustained. This Article does so through an examination of two tradable environmental allowance markets established in New Zealand: one governing fisheries and another regulating greenhouse gas emissions. The political acceptability of these environmental markets was affected by internal and external influences, including wider economic reforms, policy entrepreneurs, and failure of other policy options. Moreover, both policies have faced post-enactment political challenges that have threatened to undermine their design. New Zealand's experience suggests that tradable environmental allowance markets have limited political range, making them vulnerable to policy failure or manipulation and, though they can be successful in certain political environments, they are unlikely to form the basis of wide ranging environmental policy reform.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".