Old Wine in New Bottles: Are Carbon Tariffs International Trade Barriers? an Empirical Study of the Impact of Carbon Tariffs on Chinese Agricultural Products
Bibliographic record
Abstract
AbstractThis paper explains the reason for and the significance of tariffs. It discusses the effects of tariffs on agricultural trade: reduction of export volume, increase in export prices, decline in domestic output, deterioration of trade conditions, and reduced social welfare. The findings are based on the results of an empirical test using the Global Trade Analysis Project GTAP model and a RunGTAP software simulation analysis of the effects of tariffs on China's agricultural product exports. The results are discussed and recommendations for their application are provided.Keywords: Carbon tariffs; GTAP model; trade balance; low economy, green agricultural technology, environmental protection, social welfare; trade barriersJEL Codes: Q37IntroductionThe term carbon tariff was first put forward in January 2007 by the then French President, Jacques Chirac (France Tells US, 2007). Currently, some developed nations are advocating the collection of certain taxes or tariffs on commodities that are high in energy consumption and C02 emission in order to meet the requirements of the Kyoto Protocol. The General Assembly of the United Nations Climate Change Conference in Copenhagen and the Cancun Climate Change Conference have shifted the international community towards a consensus on the development of a low-carbon global economy.Globally, there have been no examples of tariffs on agricultural products, but some European countries, such as Sweden, Denmark, and Italy, have attempted to impose a tax within their own countries. Additionally, since July 2008, the province of British Columbia, Canada, introduced a tax, which stipulated that in the first year, 10 Canadian dollars per ton of emissions would be levied, followed by five more dollars in each year thereafter. By 2012, the tax levy would increase to 30 Canadian dollars per ton of emissions (Stern, 2007). At the same time, some developing countries, such as South Africa, moved to collect emission tax on industry production. On June 26, the U.S. approved the Clean Energy Security Act. According to the Act, beginning in 2020 the U.S. will impose high tariffs on emissions-intensive imported products that do not meet the standards of U.S. emissions. The bill specifies aluminum, iron and steel, cement, and chemical products (Xianliang 2009). It is worth noting that the EU launched the Emissions Trading Scheme in January 2005. Initially, it applied only to energy, steel, and other industrial sectors, but in 2008, the EU adopted a new bill pertaining to the aviation industry. As a result, beginning January 1, 2012, all incoming airlines were levied aviation emissions taxes (Lingyun, Junkai & Xing 2010).Among the new issues in environmental protection, the tariff has become a hot topic in the international arena. Some countries have recently developed tariff acts, while some international organizations have proposed tariffs that are applicable to international trade rules. Obviously, the tariff is an international political and economic issue. However, it is overlain by the complex strategic distribution of benefits. Although it can be assumed that tariffs will be in place in the near future, their practical application is still under discussion (Blyth, Bunn, Kettunen, & Wilson, 2009).Similarities and Differences Between Conventional Trade Restrictions and Carbon TariffsSimilar to conventional tariffs, the tariff has all the characteristics of common tariffs. Traditional tariffs can be classified by different criteria. For instance, they are classified as export tariffs, import tariffs, specific duty tariffs, ad valorem tariffs, and so on (Hillman & Bullard 1978). The tariff is a kind of import tariff. Carbon tariffs, in the case of certain fiscal revenues, have a role in protecting the environment to form part of fiscal tariffs and protective tariffs. …
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".