Cost Efficiency in BMP Adoption: Aspects of Conservation Auctions and Spatial Targeting
Bibliographic record
Abstract
Improving water quality by inducing agricultural producers to implement Beneficial Management Practices (BMPs) is one of the top environmental concerns in Canada and worldwide. Conservation auctions can be a cost-effective mechanism to achieve this goal. The first two papers in this thesis focus on analyzing the performance of conservation auctions depending on various characteristics of the underlying BMPs. The last paper presents an optimization model and compares the social optimum to various agri-environmental government programs including conservation auction. The first paper shows that not all BMPs are created equal, and conservation auctions can perform well if the potential BMPs’ cost has low heterogeneity and the corresponding supply curve is flat, especially at the beginning. In our study area, the cost curves of structural BMPs (run-off ponds and wetland restoration) exhibit low cost heterogeneity. On the other hand, the cost curves of non-structural BMPs (permanent perennial cover and conservation tillage) exhibit high cost heterogeneity because they are affected by the profitability of the land to a larger degree. Fortunately, the typical “hockey-stick” shape environmental abatement curve is an ideal candidate to use in conservation auctions. The second paper shows that if there is a diminishing marginal rate between BMP adoptions in close proximity, ignoring this so called “subadditivity” can significantly reduce the effectiveness of conservation auctions. The paper offers a potential solution by incorporating this diminishing marginal rate into the bid ranking and winner selection process. The technique was tested in the laboratory, and resulted in significant auction performance improvements if the subadditivity was present between neighbouring producers. The paper also shows that separately analyzing bidding and participation decisions for a conservation auction can lead to biased estimates; and hence, bidding behaviour should be analyzed in a selection model setting. The third paper applies a binary integer programming model to estimate the maximum achievable pollution abatement and the optimal BMP adoption pattern with a given budget in a small watershed on the Canadian Prairies. The model incorporates the notion of diminishing marginal returns between BMP adoptions on the same agricultural field. While ignoring these interdependencies between BMPs can lead to efficiency losses, the magnitude of the loss is considerably lower than efficiency loss resulting from typical restrictions in agri-environmental programs, such as size and payout limitations. As obtaining the necessary cost and abatement assessment to carry out such optimization can be costly, a conservation auction can be used instead. The paper estimates the performance of a potential conservation auction assuming rent seeking level equivalent to what was observed by bidders in the second paper. The result shows that even if the auction ignores the interdependencies between BMP adoptions, it can be highly effective. However, the effectiveness of conservation auctions deteriorate to a large extent if the market structure is less than ideal. Having separate conservation auctions for each BMP type, or imposing size and total payment restriction hinders the performance to a large extent.
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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 | 0.006 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".