Abstract
The calculation of trade-embodied air pollution (TEAP) and its economic losses can be reasonably used to assess the impact of transboundary air pollution. However, these air pollutants, which are associated with international trade, can be easily ignored due to their concealment. Based on this, the global multiregional input‒output model (MRIO) is used to quantify the volume of five air pollutants that are embodied in the trade of 20 countries from 2000 to 2016. Then, the shadow price of trade-embodied air pollution (SPTEAP) and the elasticity of factor substitution (EFS) are both calculated by applying the translog production function. Finally, impulse response analysis is used to study the dynamic impact of EFS on the SPTEAP. The main conclusions are as follows: (1) All countries experienced a mass transfer of TEAP, among which China and the USA are the developing and developed countries with the largest amount of TEAP transfers, respectively. (2) The SPTEAP and EFS vary greatly among countries, and these values are generally higher in developed countries than in developing countries. The relationship between the three EFSs can be expressed as \({e}_{AE}<{e}_{LE}{<e}_{KE}\) in all countries, thus indicating that improving the technological level of a country is the best solution for reducing the TEAP in that country while incurring the lowest cost and the least difficulty. (3) Over the long run, the increase in \({e}_{KE}\) and \({e}_{LE}\) reduces the SPTEAP. Conversely, an increase in \({e}_{AE}\) increases the SPTEAP. Therefore, policymakers should weigh these three factors according to the fluctuation of the SPTEAP and constantly adjust the allocation structure and ratio of these factors to maximize the benefits of transboundary air pollution governance.
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This work was supported by the National Natural Science Foundation of China (Grant Nos. 72104235 and 71974188), and Key Project of Jiangsu Social Science Fund (Grant No. 23GLA006).
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Appendix
Appendix
Appendix 1 Sectors classification
No | Eora26 | Public classification system code | Sectors under public classification system |
|---|---|---|---|
1 | Agriculture | AGRF | Agriculture, Forestry, Hunting and Fisheries |
2 | Fishing | ||
3 | Mining and Quarrying | MINQ | Mining and Quarrying |
4 | Food and Beverages | FOOD | Food Products, Beverages and Tobacco |
5 | Textiles and Wearing Apparel | CLTH | Textiles, Leather and Wearing Apparel |
6 | Wood and Paper | WOOD | Wood, Paper and Publishing |
7 | Petroleum, Chemical and Non-Metallic Mineral Products | PETC | Petroleum, Chemical and Non-Mental Mineral Products |
8 | Metal Products | METP | Metal and Metal Products |
9 | Electrical and Machinery | ELMA | Electrical Equipment and Machinery |
10 | Transport Equipment | TREQ | Transport Equipment |
11 | Other Manufacturing | MANF | Manufacturing and Recycling |
12 | Recycling | ||
13 | Electricity, Gas and Water | ELGW | Electricity, Gas and Water |
14 | Construction | CNST | Construction |
15 | Maintenance and Repair | TRAD | Trade |
16 | Wholesale Trade | ||
17 | Retail Trade | ||
18 | Hotels and Restraurants | ||
19 | Transport | TRNS | Transport |
20 | Post and Telecommunications | POST | Post and Telecommunications |
21 | Finacial Intermediation and Business Activities | BANS | Financial Intermediation, Business Activities |
22 | Public Administration | PAEH | Public Administration, Education, Health, Recreational and Other Services |
23 | Education, Health and Other Services | ||
24 | Private Households | ||
25 | Others | ||
26 | Re-export and Re-import |
Appendix 2 Country and region classification
No | Abbreviation | Specific countries and regions |
|---|---|---|
1 | USA | America |
2 | CAN | Canada |
3 | RUS | Russia |
4 | IND | India |
5 | CHN | Chinese Mainland |
6 | East Asia | Hong Kong, Macao, Taiwan, Japan, South Korea |
7 | Southeast Asia | Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand, Vietnam |
8 | EU | Austria, Belgium, Bulgaria, Croatia, Cyprus, The Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, The Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden |
9 | Non-EU | Albania, Andorra, Belarus, Bosnia and Herzegovina, Iceland, Kazakhstan, Kyrgyzstan, Liechtenstein, Monaco, Montenegro, Norway, Moldova, San Marino, Serbia, Switzerland, Tajikistan, Macedonia, Turkey, Turkmenistan, Soviet Union, Ukraine, Uzbekistan, Britain, Bermuda, Greenland |
10 | Middle East and North Africa | Algeria, Bahrain, Egypt, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Libya, Morocco, Palestine, Oman, Qatar, Saudi Arabia, Syria, Tunisia, The United Arab Emirates, Yemen |
11 | Sub-Saharan Africa | Angola, Benin, Botswana, Burkina Faso, Burundi, Cameroon, Cape Verde, Central African Republic, Chad, Congo (Brazzaville), Cote d’Ivoire, Democratic Republic of the Congo, Djibouti, Eritrea, Ethiopia, Gabon, Gambia, Ghana, Guinea, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritania, Mauritius, Mozambique, Namibia, Niger, Nigeria, Rwanda, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, Somalia, South Africa, South Sudan, Sudan, Eswatini Togo, Trinidad and Tobago, Uganda, Tanzania, Zambia, Zimbabwe |
12 | Rest of Asia | Afghanistan, Armenia, Azerbaijan, The People’s Republic of Bangladesh, Bhutan, North Korea, Georgia, Maldives, Mongolia, Nepal, Pakistan, Sri Lanka |
13 | Latin America | Antigua and Barbuda, Argentina, Aruba, Bahamas, Barbados, Belize, Bolivia, Brazil, British Virgin Islands, Cayman Islands, Chile, Columbia, Costa Rica, Cuba, Dominican Republic, Ecuador, El Salvador, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Papua New Guinea, Paraguay, Peru, Suriname, Uruguay, Venezuela |
14 | Australia | Australia, Fiji, French Polynesia, New Caledonia, New Zealand, Samoa, Vanuatu |
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Diao, B., Wang, Y., Dong, F. et al. Can factor substitution reduce the shadow price of air pollution embodied in international trade? A worldwide perspective. Environ Sci Pollut Res 31, 7092–7110 (2024). https://doi.org/10.1007/s11356-023-31447-y
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DOI: https://doi.org/10.1007/s11356-023-31447-y