The Impact of Output Based Allocations on the Carbon Tax and Policy: Measuring the Effective Tax Rates on Marginal Costs
Bibliographic record
Abstract
As the global climate challenge intensifies, countries are working to reduce the adverse effects caused by an increasing amount of Greenhouse gas (GHG) emissions. In 1997, the Kyoto Protocol was signed in an agreement that global warming is happening due to GHG emissions and industrialized countries commit to reducing GHG emissions according to their individual targets (United Nations 2021). Canada has been progressive in climate accountability plans. Under the Paris Agreement, Canada is committed to carbon net-zero by 2050 (Environmental and Natural Resources Canada 2021). As one of the largest energy producers in North America, Alberta introduced its first carbon tax regulation in 2007, the Specified Gas Emitters Regulation (SGER). The SGER introduced the concept of output based allocations in Canada and has been a model for the concept in other provinces and the federal government. As policies to reduce emissions are imposed, such as carbon taxes, concerns over the competitiveness of energy intensive production in industrialized countries rise. Carbon emissions can relocate in response to country specific policies, a phenomenon known as carbon leakage. Evidence suggests that overall global emissions have not declined with GHG emission policies introduced in industrialized countries as carbon leakage occurs to undermine the efficacy of the Kyoto Protocol’s anticipation (Babiker 2005). Output based allocations (OBAs) have been introduced as a solution to prevent carbon leakage and preserve firm competitiveness. OBAs are intended to reduce the side-effects of strengthening the environmental regulations while at the same time preserving the incentives to reduce emissions. Carbon border adjustment is another method intended to relieve the issues of carbon leakage. It adds import tariffs to specific products based on the carbon footprint and provides an export subsidy for domestic exporters. It effectively inhibits domestic producers’ offshoring due to the increasing stringency of the carbon regulatory environment. In this study, we will review background information around the emission regulations impacting Canada and Alberta. We will provide simulation analysis on output based allocations (OBAs) regarding effective tax rates on marginal costs (McKenzie, Mintz, and Scharf 1997). The results indicate that OBAs disrupt the correlation between energy input and effective tax rates on marginal costs (ETRMC), and therefore, promote energy production under a carbon tax.
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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 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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".