In order to answer the third and fourth research questions of our study, we apply the first and the second stages of the EIA method on the trade policy described above. The main purposes of this work are to examine: (i) a product group/sector whose production will likely increase as a result of the CPTPP in Vietnam, (ii) how the change in the sector production leads to the change in energy consumption and CO2 emissions, and (iii) opportunities to reduce and control energy consumption
and CO2 emissions as a result of the production change in Vietnam.
(i) Identification of the Product Group that is Likely to Increase as a Result of CPTPP in
Vietnam
Revealed Comparative Advantage Index
The traditional trade indicators including export partner share, export product share, and the RCA index will be analysed to provide information on the product groups that Vietnam has comparative advantage in exporting to other CPTPP member countries
.
The RCA index is defined as the share of a product group in one country’s exports divided by that product group’s share in world trade. The RCA index is a useful indicator in determining countries’ comparative advantages (Nguyen, 2011). The standard RCA index is calculated as:
/
/ /
ij ij wj ij wj
RCA x x
x x(4.10)
wj
x
is the world’s exports of commodity j;ij
x
is country i’s total exports; wjx
is the world’s total exports.A value of RCA greater than 1 broadly suggests a revealed comparative advantage for the country in sector j. This occurs when the share of that commodity in the country’s exports exceeds its share in the reference group exports. The factors that contribute to the movement in RCA are economic, structural change, improved world demand and trade specialisation (Le, 2010; Nguyen, 2011).
An RCA index can be calculated for a specific sector or for a group of countries (Irshad & Xin, 2017). The RCA index in our study is calculated as:
𝑅𝐶𝐴𝑗;𝑡 = (𝑥𝑗;𝑡𝑥 𝑗;𝑡;𝐶𝑃𝑇𝑃𝑃 ⁄ ) (∑ 𝑥𝑗;𝑡∑ 𝑥 𝑗;𝑡;𝐶𝑃𝑇𝑃𝑃 ⁄ ) (4.11)
where 𝑅𝐶𝐴𝑗;𝑡 is the comparative advantage index in the export of commodity j from Vietnam to CPTPP member countries in year t; 𝑥𝑗;𝑡is Vietnam’s export of commodity j in year t;
𝑥𝑗;𝑡;𝑇𝑃𝑃𝐴is the export of CPTPP member countries of commodity j in year t; ∑ 𝑥𝑗;𝑡 is Vietnam’s total exports in year t; ∑ 𝑥𝑗;𝑡;𝑇𝑃𝑃𝐴 is CPTPP’s total exports in year t.
Based on Hinloopen and van Marrewijk’s (2001) study, the RCA index is classified into four categories (Nguyen, 2011):
- 0 < RCA < 1: Products without comparative advantage.
- 1 < RCA < 2: Products with weak comparative advantage.
- 2 < RCA < 4: Products with medium comparative advantage.
- 4 < RCA: Products with strong comparative advantage.
Regional Orientation Index
After determining the product group in which Vietnam has comparative advantage in exports, we then calculate the regional orientation index for that product. The regional orientation index helps to determine whether Vietnam’s export of that product is more oriented toward the CPTPP region than other destinations. This index can be combined with the RCA index to examine which product group experiences trade diversion as a result of the CPTPP in Vietnam (Plummer et al., 2010).
𝑅𝑒𝑔𝑖𝑜𝑛𝑎𝑙 𝑂𝑟𝑖𝑒𝑛𝑡𝑎𝑡𝑖𝑜𝑛𝑐𝑔𝑟 =
𝑋𝑐𝑔𝑟/𝑋𝑐𝑟
𝑋𝑐𝑔−𝑟/𝑋𝑐−𝑟 (4.12)
where Xcgr = exports of good g by country c to region r;
Xcr = total exports of country c to region r;
Xcg−r = exports of good g by country c to countries outside region r;
Xc−r = total exports of country c to countries outside region r.
The orientation index of textile exports from Vietnam to CPTPP member countries is calculated as follows:
𝑅𝑒𝑔𝑖𝑜𝑛𝑎𝑙 𝑂𝑟𝑖𝑒𝑛𝑡𝑎𝑡𝑖𝑜𝑛𝑉𝑁−𝑡𝑒𝑥𝑡𝑖𝑙𝑒−𝐶𝑃𝑇𝑃𝑃 =
𝑋𝑉𝑁−𝑡𝑒𝑥𝑡𝑖𝑙𝑒−𝐶𝑃𝑇𝑃𝑃/𝑋𝑉𝑁−𝐶𝑃𝑇𝑃𝑃
𝑋𝑉𝑁−𝑡𝑒𝑥𝑡𝑖𝑙𝑒−𝑅𝑜𝑊/𝑋𝑉𝑁−𝑅𝑜𝑊 (4.13)
where
XVN−textile−CPTPP = exports of textiles from Vietnam to CPTPP member countries;
XVN−CPTPP = total exports of Vietnam to CPTPP member countries;
XVN−textile−RoW = exports of textiles from Vietnam to the rest of the world;
XVN−RoW = total exports of Vietnam to the rest of the world.
The data on export partner shares from Vietnam to CPTPP member countries from 1990 to 2015 are obtained from the World Integrated Trade Solution. The data on the RCA index from Vietnam to CPTPP member countries from 2000 to 2015 are retrieved from the World Bank’s World Trade Indicators.
(ii) Identification of the Likely Environmental Impacts due to Economic Changes
The second stage of the analysis is identification of possible environmental impacts due to the economic changes of product group from the CPTPP in Vietnam identified in Stage 1. For this purpose, our study follows the procedure that is proposed by EIA procedures of the Canadian trade policy guideline16 . A set of questions based on the descriptive method is modified according to the
proposed EIA guideline procedures of Canada for the specific purposes of our study (the impact of the CPTPP on Vietnam’s environment), including:
Question 1: Will the CPTPP lead to an increase or decrease in the production of a specific product in Vietnam?
Question 2: How will the increase in the production of the product as a result of the CPTPP affect input requirements (energy consumption) and outputs (CO2 emissions) in Vietnam?
16 The Canadian trade policy EIA framework and guideline are retrieved from:
Question 3: What does the literature identify about the energy demand and CO2 emissions of the
economic change of the product in Vietnam?
Question 4: Is there any movement in technology transfer among CPTPP member countries? Are these environmentally friendly or unfriendly technologies?
Question 5: How does the CPTPP regulate environmental protection during the production of the product?
In order to answer these questions, we follow the “sectoral approach” by analysing the statistical data for the product group that is more likely to increase in production as a result of the CPTPP; then we use the descriptive method to analyse the text of the CPTPP, and examine the existing domestic regulations to protect the environment during the production activities in Vietnam.
4.3
Chapter Summary
The chapter presents the data specification, the empirical model estimation method and the EIA method on trade policy to answer the research questions of our study.
We use an empirical model in Research question two to address the short-run and long-run impacts of trade openness, economic development and energy use on CO2 emissions. This empirical model
has been applied by researchers such as Ang (2008), Halicioglu (2009), Jalil and Mahmud (2009), Tan et al. (2014) for the cases in Malaysia, Singapore and China. Our model will provide a comprehensive quantitative assessment on the short-run and long-run relationships between economic
development, trade openness, energy consumption and environmental impact in Vietnam. The advanced estimation technology, ARDL, is applied to avoid the spurious interaction among the variables and to overcome the stationarity of the time series data in the study model. Further, the ARDL and ECM models help to capture the dynamic effects of trade openness on CO2 emissions.
To answer research questions three and four, we first analyse trade statistical data, including export partner shares, export product shares and the Revealed Comparative Advantage index to examine the export pattern of Vietnam to CPTPP member countries. Next, we apply the Environmental Impact Assessment method on trade policy to screen and scope potential effects of trade openness on Vietnam’s environment.
The data on export partner shares and export product shares from Vietnam to CPTPP member countries from 1990 to 2015 are obtained from the World Integrated Trade Solution. The data on the RCA index from Vietnam to CPTPP member countries from 2000 to 2015 are retrieved from the World Bank’s World Trade Indicators. Time series data which include real per capita GDP, energy use,
CO2 emissions and the trade openness ratio are obtained from the World Bank’s World Development