Whether trade liberalization resulting from mega free trade agreements, such as the Regional Comprehensive Economic Partnership (RCEP), will have an impact on the environment is the subject of ongoing debate and remains an empirical matter. In this paper, we contribute to the debate on the relation between trade and the environment by considering the case of the RCEP and examining whether it will increase or decrease greenhouse gas (GHG) emissions. We measure the impact of the RCEP on GHG emissions using the Global Trade Analysis Project (GTAP) model and the GTAP CO2 and non-CO2 emissions databases. Our results suggest that the RCEP is likely to “increase” the total amount of GHG emissions in the 16 RCEP members and the world.
The Regional Comprehensive Economic Partnership (RCEP) is an Association of Southeast Asian Nations (ASEAN)-centered proposal for a regional free trade area, which would initially include the ten ASEAN member states and six other countries with existing Free Trade Agreements (FTAs) with ASEAN, including Australia, China, India, Japan, the Republic of Korea, and New Zealand. Leaders from ASEAN and ASEAN’s FTA partners instigated the RCEP negotiations at the East Asia Summit in Phnom Penh, Cambodia in November 2012 [
The RCEP is one of several so-called “mega-FTAs”, including the FTAAP (Free Trade Area of the Asia Pacific), the TPP (Trans-Pacific Partnership), the TTIP (Transatlantic Trade and Investment Partnership), and the JCKFTA (Japan-China-Korea Free Trade Agreement). Together, the 16 RCEP participants account for almost half of the world’s population, nearly 30 percent of global GDP, and more than a quarter of world exports [
However, whether trade liberalization resulting from mega-FTAs, such as the RCEP, will have an impact on the environment is the subject of ongoing debate and remains an empirical matter. While some existing studies address the economic impact of the RCEP [
In this paper, we contribute to the debate on the relation between trade and the environment by considering the case of the RCEP and examining whether it will increase or decrease greenhouse gas (GHG) emissions. We do this by measuring the impact of the RCEP on GHG emissions using the Global Trade Analysis Project (GTAP) model and the GTAP’s CO2 and non-CO2 emissions databases.
It is common to employ the GTAP model to provide a quantitative assessment of the economic impact of the RCEP. This is a computable general equilibrium (CGE) model developed for trade analysis by the GTAP [
To facilitate comparison with other mega-FTAs (including the TPP, FTAAP, and JCKFTA), we combine the 129 countries and regions in GTAP 9 into 27 regions. We retain the original 57 industries in the database.
Our scenario assumes the complete removal of all import tariffs among the RCEP members. However, it is unlikely that the RCEP would remove all import tariffs across all sectors among the RCEP participants. In so doing, our scenario provides an upper bound of the possible economic impact of the RCEP.
Given the limitations of the available data, we focus only on GHG emissions as the form of environmental load. We employ the GTAP CO2 emissions database and GTAP non-CO2 emissions database to measure the impact of the RCEP on GHG emissions. These databases therefore enable us to measure not only CO2 emissions, but also non-CO2 emissions, including methane (CH4), nitrous oxide (N2O), and fluorinated GHGs (or F-gases) (namely, tetrafluorocarbon, hydrofluorocarbons, and sulfur hexafluoride).
The GTAP 9 CO2 emissions database details emissions resulting only from the combustion of fossil fuels, with the levels of CO2 emissions calculated by multiplying the amount of fuel consumed by emission coefficients [
The GTAP 9 non-CO2 emissions database provides the emissions data for three major non-CO2 gases (CH4, N2O, and F-gases) [
Region | Sector | Sector | |||
---|---|---|---|---|---|
1 | Japan | 1 | Paddy rice | 30 | Wood products |
2 | Korea | 2 | Wheat | 31 | Paper products, publishing |
3 | China | 3 | Cereal grains necd | 32 | Petroleum, coal products |
4 | Indonesia | 4 | Vegetables, fruit, nuts | 33 | Chemicals |
5 | Malaysia | 5 | Oil seeds | 34 | Mineral products necd |
6 | Philippines | 6 | Sugar cane, sugar beet | 35 | Ferrous metals |
7 | Singapore | 7 | Plant-based fibers | 36 | Metals necd |
8 | Thailand | 8 | Crops necd | 37 | Metal products |
9 | Vietnam | 9 | Cattle | 38 | Motor vehicles and parts |
10 | Cambodia | 10 | Animal products necd | 39 | Transport equipment necd |
11 | Laos | 11 | Raw milk | 40 | Electronic equipment |
12 | Brunei | 12 | Wool, silkworm cocoons | 41 | Machinery and equipment necd |
13 | Other ASEANa | 13 | Forestry | 42 | Manufactures necd |
14 | India | 14 | Fishing | 43 | Electricity |
15 | Australia | 15 | Coal | 44 | Gas manufacture, distribution |
16 | New Zealand | 16 | Oil | 45 | Water |
17 | United States | 17 | Gas | 46 | Construction |
18 | Canada | 18 | Minerals necd | 47 | Trade |
19 | Mexico | 19 | Meat: cattle, sheep, goats, horse | 48 | Transport necd |
20 | Peru | 20 | Meat products necd | 49 | Sea transport |
21 | Chile | 21 | Vegetable oils and fats | 50 | Air transport |
22 | Hong Kong | 22 | Dairy products | 51 | Communication |
23 | Taiwan | 23 | Processed rice | 52 | Financial services necd |
24 | Russia | 24 | Sugar | 53 | Insurance |
25 | EU27 | 25 | Food products necd | 54 | Business services necd |
26 | ROW1b | 26 | Beverages and tobacco products | 55 | Recreation and other services |
27 | ROW2c | 27 | Textiles | 56 | Pub Admin/Defence/Health/Education |
28 | Wearing apparel | 57 | Dwellings | ||
29 | Leather products |
a. Other ASEAN includes Myanmar and Timor-Leste. b. ROW1 includes rest of Asian economies. c. ROW2 includes rest of the world. d. nec means not elsewhere classified.
liberalization, the 16 participants are likely to experience a positive average impact of the RCEP on real GDP, total exports, and total imports, which increase by 0.19%, 2.95%, and 5.19%, respectively. In contrast, non- RCEP economies other than Russia are likely to experience a negative impact on real GDP. In percentage terms, the increase in Vietnam is the highest across GDP (0.91%), and the increases in Cambodia are the highest across total exports (8.96%) and total imports (10.31%).
By way of a comparison, reference [
Real GDP | Total export | Total import | |
---|---|---|---|
16 RCEP members | 0.19 | 2.95 | 5.19 |
Japan | 0.15 | 1.39 | 6.19 |
Korea | 0.73 | 3.31 | 6.63 |
China | 0.09 | 3.55 | 4.46 |
Indonesia | 0.06 | 2.66 | 3.90 |
Malaysia | 0.37 | 1.94 | 4.25 |
Philippines | 0.08 | 2.52 | 1.62 |
Singapore | 0.06 | 0.45 | 1.95 |
Thailand | 0.39 | 3.05 | 6.53 |
Vietnam | 0.91 | 0.64 | 10.20 |
Cambodia | 0.56 | 8.96 | 10.31 |
Laos | 0.36 | 5.32 | 8.31 |
Brunei | 0.08 | −0.33 | 1.84 |
Other ASEANa | 0.06 | 6.99 | 3.18 |
India | 0.41 | 8.32 | 5.07 |
Australia | 0.11 | 0.99 | 6.09 |
New Zealand | 0.05 | 0.66 | 2.15 |
United States | −0.01 | 0.71 | −1.04 |
Canada | −0.01 | 0.32 | −0.14 |
Mexico | −0.01 | 0.27 | −0.03 |
Peru | −0.00 | 0.16 | −0.54 |
Chile | −0.01 | 0.24 | −0.26 |
Hong Kong | −0.00 | −0.01 | −0.77 |
Taiwan | −0.04 | −0.44 | −1.71 |
Russia | 0.01 | 0.24 | −0.60 |
EU27 | −0.01 | 0.23 | −0.26 |
ROW1b | −0.06 | 0.21 | −1.15 |
ROW2c | −0.02 | 0.05 | −0.51 |
a. Other ASEAN includes Myanmar and Timor-Leste. b. ROW1 includes rest of Asian economies. c. ROW2 includes rest of the world.
As shown in
Japan | China | India | Australia | United States | EU27 | |
---|---|---|---|---|---|---|
Farm output | −7.96 | 0.19 | −0.41 | 11.82 | −0.46 | −0.03 |
Paddy rice | −29.51 | 1.55 | 1.57 | 32.90 | −1.40 | 2.22 |
Wheat | −4.26 | −0.60 | 0.70 | −5.95 | 0.69 | 0.05 |
Cereal grains neca | −0.53 | 0.75 | 7.65 | 43.07 | −0.69 | −0.07 |
Vegetables, fruit, nuts | −0.87 | 0.65 | −0.06 | −0.19 | −0.44 | 0.04 |
Oil seeds | −13.03 | 1.23 | −11.71 | −1.04 | −1.19 | −0.15 |
Sugar cane, sugar beet | −2.10 | −6.07 | 0.72 | 12.55 | 0.04 | −0.01 |
Plant-based fibers | 2.01 | 0.27 | 3.35 | −3.90 | −0.21 | −0.69 |
Crops neca | −3.14 | 10.47 | −1.42 | −5.62 | −0.11 | 0.01 |
Cattle | −13.17 | 0.25 | 0.13 | 14.83 | −0.59 | 0.20 |
Wool, silkworm cocoons | 1.14 | −27.39 | 1.23 | 91.83 | −8.89 | −24.38 |
Electricity | 0.39 | −0.07 | 0.20 | −0.26 | −0.00 | −0.00 |
a. nec means not elsewhere classified.
from the paddy rice sector is the second most significant increase rate of all sectoral output changes in China (1.55%) and the third most significant increase rate in Australia (32.90%). Electricity sector output, one of the largest sources of CO2 emissions, increases in Japan, India, and decreases in China, Australia, the US, and the EU.
Regarding the ASEAN + 6 FTA, reference [
In other findings, the total CO2 emissions of the 16 RCEP members and the world will increase by 7.08 Mt CO2 eq. (0.06%) and 10.38 Mt CO2 eq. (0.04%), respectively, and the total non-CO2 emissions of the 16 RCEP members and the world will increase by 12.24 Mt CO2 eq. (0.23%) and 14.72 Mt CO2 eq. (0.12%), respectively. Among the non-RCEP members, the total GHG emissions of the US will decrease by 0.23 Mt CO2 eq. (less than 0.01%), while those of the EU will increase by 6.55 Mt CO2 eq. (0.14%).
We next focus on the results for the individual economies. In terms of CO2 emissions, Japan and Korea will experience the greatest and the third greatest increase of all the economies, with the sum of its increases in CO2 emissions (5.59 Mt CO2 eq. and 4.14 Mt CO2 eq.) almost equaling the increase across all 16 RCEP members (7.08 Mt CO2 eq.) and the world (10.38 Mt CO2 eq.).
In terms of non-CO2 emissions for the individual economies, Australia will experience the greatest increase (11.92 Mt CO2 eq.), which is almost equal to the increase across all 16 RCEP members (12.24 Mt CO2 eq.). In percentage terms, New Zealand has the highest rate of increase in non-CO2 emissions (5.00%), while the Philippines has the largest rate of decrease (−3.45%).
CO2 | Non-CO2 | GHG | ||||
---|---|---|---|---|---|---|
16 RCEP members | 7.08 | (0.06) | 12.24 | (0.23) | 19.32 | (0.11) |
Japan | 5.59 | (0.54) | −2.69 | (−2.97) | 2.90 | (0.26) |
Korea | 4.14 | (0.83) | 0.18 | (0.35) | 4.32 | (0.78) |
China | −0.86 | (−0.01) | 2.64 | (0.10) | 1.78 | (0.02) |
Indonesia | −1.45 | (−0.37) | −0.60 | (−0.18) | −2.05 | (−0.29) |
Malaysia | −0.49 | (−0.24) | −0.20 | (−0.39) | −0.69 | (−0.27) |
Philippines | 0.07 | (0.09) | −2.78 | (−3.45) | −2.71 | (−1.70) |
Singapore | 0.43 | (0.65) | 0.22 | (2.81) | 0.65 | (0.88) |
Thailand | −0.10 | (−0.04) | 2.68 | (2.02) | 2.58 | (0.69) |
Vietnam | 1.57 | (1.24) | −0.60 | (−0.41) | 0.97 | (0.35) |
Cambodia | 0.41 | (8.61) | −0.43 | (−1.47) | −0.02 | (−0.06) |
Laos | 0.11 | (5.66) | −0.20 | (−1.67) | −0.10 | (−0.68) |
Brunei | −0.06 | (−0.72) | −0.04 | (−0.83) | −0.10 | (−0.76) |
Other ASEANb | 0.02 | (0.21) | 0.79 | (0.76) | 0.81 | (0.72) |
India | −2.07 | (−0.12) | −0.76 | (−0.06) | −2.83 | (−0.09) |
Australia | −0.28 | (−0.07) | 11.92 | (4.46) | 11.64 | (1.80) |
New Zealand | 0.05 | (0.16) | 2.12 | (5.00) | 2.17 | (2.90) |
United States | −0.17 | (−0.00) | −0.06 | (−0.01) | −0.23 | (−0.00) |
Canada | 0.19 | (0.04) | −0.57 | (−0.35) | −0.38 | (−0.06) |
Mexico | −0.02 | (−0.01) | −0.53 | (−0.30) | −0.55 | (−0.09) |
Peru | 0.04 | (0.08) | −0.03 | (−0.07) | 0.01 | (0.01) |
Chile | 0.16 | (0.20) | −0.05 | (−0.18) | 0.10 | (0.10) |
Hong Kong | 0.17 | (0.20) | 0.00 | (−0.04) | 0.17 | (0.19) |
Taiwan | −1.38 | (−0.56) | −0.05 | (−0.28) | −1.43 | (−0.54) |
Russia | −0.32 | (−0.02) | 0.32 | (0.04) | 0.00 | (−0.00) |
EU27 | 4.23 | (0.12) | 2.32 | (0.21) | 6.55 | (0.14) |
ROW1c | 0.09 | (0.03) | −0.41 | (−0.08) | −0.32 | (−0.04) |
ROW2d | 0.31 | (0.01) | 1.55 | (0.04) | 1.86 | (0.02) |
World | 10.38 | (0.04) | 14.72 | (0.12) | 25.10 | (0.06) |
a. Figures in parentheses are percentage deviations from the initial period. b. Other ASEAN includes Myanmar and Timor-Leste. c. ROW1 includes rest of Asian economies. d. ROW2 includes rest of the world.
relatively few sectors emit these GHGs. In terms of CO2 emissions, non-agricultural sectors appear in the top five sectors. Four of six economies in
In terms of work elsewhere, reference [
Japan | CO2 | CH4 | N2O | |||||
---|---|---|---|---|---|---|---|---|
Electricity | 1.84 | (0.40) | Paddy rice | −1.05 | (−15.21) | Paddy rice | −0.30 | (−29.51) |
Mineral products necb | 0.48 | (2.06) | Cattle | −0.51 | (−15.29) | Cattle | −0.26 | (−15.21) |
Ferrous metals | 0.47 | (1.16) | Raw milk | −0.20 | (−12.06) | Raw milk | −0.06 | (−11.76) |
Air transport | −0.28 | (−1.90) | Animal products necb | −0.06 | (−1.35) | Crops necb | −0.03 | (−3.14) |
Petroleum, coal products | 0.21 | (0.78) | PADHEc | 0.01 | (0.14) | Animal products necb | −0.02 | (−1.15) |
China | CO2 | CH4 | N2O | |||||
Mineral products necb | 1.81 | (0.32) | Paddy rice | 1.16 | (0.99) | Vegetables, fruit, nuts | 1.07 | (0.65) |
Chemicals | −1.73 | (−0.65) | Cattle | 0.78 | (0.43) | Cattle | 0.45 | (0.43) |
Ferrous metals | −1.00 | (−0.24) | Wool, silkworm cocoons | −0.41 | (−27.39) | Animal products necb | 0.39 | (0.62) |
Electricity | −1.00 | (−0.02) | PADHEc | −0.38 | (−0.10) | Paddy rice | 0.36 | (1.55) |
Textiles | 0.61 | (2.60) | Animal products necb | 0.26 | (0.58) | Crops necb | 0.17 | (10.47) |
India | CO2 | CH4 | N2O | |||||
Electricity | −2.04 | (−0.21) | Paddy rice | 1.71 | (1.72) | Oil seeds | −1.54 | (−11.70) |
Vegetable oils and fats | −0.46 | (−43.18) | PADHEc | −0.84 | (−0.48) | Cereal grains necb | 0.60 | (7.65) |
Chemicals | 0.44 | (0.98) | Oil seeds | −0.62 | (−11.70) | Crops necb | −0.52 | (−1.41) |
Mineral products necb | −0.38 | (−0.39) | Cattle | −0.32 | (−0.12) | Plant-based fibers | 0.34 | (3.35) |
Transport necb | 0.36 | (0.24) | Cereal grains necb | 0.31 | (7.65) | Wheat | 0.23 | (0.70) |
Australia | CO2 | CH4 | N2O | |||||
Electricity | −0.50 | (−0.26) | Cattle | 8.68 | (17.78) | Cattle | 5.50 | (17.72) |
Wool, silkworm cocoons | 0.48 | (91.86) | Cereal grains necb | 1.46 | (27.57) | Cereal grains necb | 2.33 | (29.23) |
Air transport | −0.44 | (−2.07) | Wheat | −0.98 | (−10.26) | Wheat | −1.42 | (−9.78) |
Metals necb | −0.21 | (−1.79) | Vegetables, fruit, nuts | −0.59 | (−5.71) | Vegetables, fruit, nuts | −0.80 | (−5.14) |
Ferrous metals | −0.19 | (−4.69) | Plant-based fibers | −0.45 | (−8.66) | Plant-based fibers | −0.63 | (−8.32) |
United States | CO2 | CH4 | N2O | |||||
Air transport | 1.49 | (0.41) | Cattle | −0.80 | (−0.78) | Cattle | −0.40 | (−0.77) |
Transport necb | 0.65 | (0.10) | Coal | 0.17 | (0.22) | Cereal grains necb | −0.25 | (−0.69) |
Chemicals | 0.20 | (0.18) | Raw milk | −0.15 | (−0.44) | Oil seeds | −0.18 | (−1.18) |
Ferrous metals | 0.18 | (0.49) | Animal products necb | −0.12 | (−0.44) | Chemicals | 0.09 | (0.17) |
Sea transport | 0.15 | (0.37) | Paddy rice | −0.06 | (−0.79) | Animal products necb | −0.08 | (−0.40) |
EU27 | CO2 | CH4 | N2O | |||||
Sea transport | 2.64 | (1.63) | Cattle | 0.21 | (0.20) | Cattle | 0.09 | (0.20) |
Transport necb | 1.95 | (0.29) | Raw milk | −0.15 | (−0.22) | Raw milk | −0.05 | (−0.22) |
Air transport | 0.96 | (0.49) | Transport necb | 0.14 | (0.29) | Wool, silkworm cocoons | −0.03 | (−24.38) |
Petroleum, coal products | 0.19 | (0.15) | Coal | 0.12 | (0.25) | Oil seeds | −0.02 | (−0.15) |
Mineral products necb | −0.17 | (−0.21) | Paddy rice | 0.09 | (1.84) | Petroleum, coal products | 0.01 | (0.17) |
a. Figures in parentheses are percentage deviations from the initial period. b. nec means not elsewhere classified. c. PADHE is PubAdmin/Defence/Health/Education.
Regarding CH4 emissions, we observe a significant increase in the volume of emissions in the cattle sector in Australia (8.68 Mt CO2 eq.), whereas in percentage terms CH4 emissions from the cattle sector decreased most significantly in Japan (−15.29%). These particular results mainly arise because of the large increase in output from the cattle sector in Australia and the large decrease in output from the cattle sector in Japan, as shown in
As for N2O emissions, we identify a significant increase in emissions from the cattle sector in Australia (5.50 Mt CO2 eq.), while in percentage terms the decrease in these same emissions is the second largest in Japan (−15.21%). Once again, these results are due to the large increase in output from the cattle in Australia and the large decreases in output from the cattle sector in Japan, as shown in
For both CH4 and N2O emissions, three or more of the top five emitting sectors in each economy are farm sectors. Worldwide in 2005, while CO2 emissions are concentrated in the energy sector, agriculture accounts for the largest share of non-CO2 emissions [
In this paper, we contribute to the debate on the relation between trade and the environment by considering the case of the RCEP and examining whether it will increase or decrease GHG emissions. To respond to this important research question, we measure the impact of the RCEP on GHG emissions using the GTAP model and the GTAP CO2 and non-CO2 emissions databases. Our scenario assumes the complete removal of all import tariffs among the RCEP members.
The results in terms of economic impact show that the 16 RCEP participants are likely to experience a positive effect on real GDP. In contrast, non-RCEP economies other than Russia are likely to experience a negative impact on real GDP. Further, farm output will tend to decline in Japan and the US and increase in Australia. The output of the electricity sector, one of the largest sources of CO2 emissions, will tend to increase in Japan and India, and decrease in China, Australia, the US, and the EU.
As for our main research question, the GHG emission impact results show that the RCEP is likely to “increase” the total amount of GHG emissions in the 16 RCEP members and the world. We observe increases in the amount of CO2 emissions in the non-agricultural sectors in each economy, and a substantial increase in the amount of CH4 and N2O emissions in the Australian cattle sector.
Finally, we briefly note the limitations of our study as a means of informing future research. In our model, we did not include the changes in environmental policy that may also result from the RCEP. In addition, because of limitations in the available data, we included only CO2, CH4, N2O, and F-gases as GHG emissions.
This work was supported by JSPS KAKENHI Grant Numbers JP26252036, JP16H06202.
Hirokazu Akahori,Daisuke Sawauchi,Yasutaka Yamamoto, (2016) The Regional Comprehensive Economic Partnership and Its Potential Impact on Greenhouse Gas Emissions. Journal of Environmental Protection,07,1183-1191. doi: 10.4236/jep.2016.79105