Impact of Regional Economic Integration in East Asia

Abstract

The current study evaluates the economy wide impact of trade liberalization in the ASEAN region along with China, Japan and Korea (ASEAN + 3) by the year 2020 using the GTAP framework. The study also assesses the environmental impact of the trade liberalization in the region focusing on the seven environmental indicators (CO₂, CH₄, N₂O, BOD, COD, Suspended Solid and Industrial Waste). The result shows that the countries under agreement (ASEAN + 3) will benefit with increased output, expansion of trade and welfare due to trade reforms. Further, the integration will increase the global welfare, although the regions not under agreement in the world will show a decline in output growth. Vietnam will be gaining with the highest output growth among the ASEAN region; however, the impact on the environment would not be favourable. The environmental impact reveals a mixed outcome for participating countries under the agreement. The paper provides useful insight in pursuing greater trade liberalization among the countries under the study.

Keywords:

• Free trade agreement
• East and South East Asia
• GTAP
• scenario
• environment

JEL Classifications:

• F15
• F18
• C68

Acknowledgements

Authors gratefully acknowledge the Institute for Global Environmental Strategies Japan (IGES), and the contribution of the other country partners of the project. Authors would like to express their gratitude to Ministry of Environment Japan (MOEJ), and UNEP for their financial support. Finally authors are indebted to Prof. Debesh Chakraborty (Department of Economics, Jadavpur University, Calcutta, India) for his valuable comments and constructive suggestions. The usual disclaimer applies.

Notes

¹At the Ninth ASEAN Summit in Bali in October 2003, ASEAN leaders have agreed to establish an ASEAN Economic Community (AEC) by 2020. The AEC is one of three pillars (the other two being the ASEAN Security Community and the ASEAN Socio-cultural Community) that make up the ASEAN Community as declared by ASEAN leaders in the Bali Concord II. In line with the ASEAN Vision 2020, it is envisaged that the AEC will be a single market and production base with free flow of goods, services, investments, capital and skilled labour (Hew, 2006).

²East Asia includes the People's Republic of China, Hong Kong, Macau, Mongolia, Japan, the Republic of Korea, North Korea, Taiwan. South East Asia includes ten ASEAN countries. For the current study, we consider a combination of countries from both Asia, thus named as East and South East Asia. For our analysis we focus primarily on six countries: Japan, China, the Republic of Korea, Thailand, Indonesia, and Vietnam.

³For details see Congjie and Dongping (2007), Vietnam Environment Monitor (2004), ESCAP (2006), Thailand Country Report (2001) and Indonesia's no 1 waste technology, management and solution event (2008) www.waste.indowater.com.

⁴Published BOD data were collected from the World Bank (2006), Development Data Group for China. The data collected from the World Bank source only covered industrial water pollution: i.e. organic water pollution. In this case we compared the World Bank data with the data supplied by other countries under study. The World Bank covers only 25% (approximately) of the reported BOD estimate from other countries (Japan, Korea). So the data for China has been scaled up accordingly. Unfortunately, the available source data is for total BOD only and the data source does not provide a sectoral distribution of the BOD. For the agricultural sector various options have been considered. We tried to incorporate additional information into the BOD and COD emissions from the agriculture sector. The harvest area of the various crops was used to estimate the BOD release from the agricultural sectors (Paddy rice, Wheat, Cereal grains nec, Vegetables, fruit, nuts, Oil seeds, Sugar cane and sugar beet, Plant-based fibres, Crops nec) in China. The BOD and COD from the agriculture sectors in China were estimated as follows: the harvested area per crop multiplied by the BOD and COD release per hectare of Thailand. For the livestock sector some additional modifications were used. Instead of harvested area we have considered the production quantity per BOD and COD release for Bovine cattle, sheep and goats, horses and Animal products nec. For the forestry and fishery sectors, we have estimated the BOD and COD release on the basis of production quantity (ton). The data were collected from the FAO statistics (Prodstat Foresstat and Fishstat) for the year 2001. For the rest of the sectors, BOD release was estimated following Thailand pattern and COD collected from the Environmental Yearbook of China.

⁵Due to the paucity of Industrial waste data for Indonesia, we use the average environmental coefficient of Thailand and Vietnam.

⁶Post simulation utility is the level of utility obtained after the trade scenario exercise is carried out.

⁷Equivalent variation (EV) is a measure of how much more money a consumer would pay before a price increase to avert the price increase. John Hicks is attributed with introducing the concept of equivalent variation.

⁸Efficiency gain – when a country participates in a free trade region, it may gain due to trade creation and either may gain or lose due to trade diversion. The former has a positive effect on welfare because the removal of tariffs within the region allows the country to allocate its resources more efficiently in production. The country can import the goods that it formerly produced inefficiently under a tariff from member countries that are more efficient producers (Caves & Jones, 1981).

⁹To update the environmental coefficients, we considered the past behaviour of the emission. We prepared 1995 and 2001 emission coefficient, to calculate the growth of the emission coefficients. Data on both industrial output and GHG emissions (CO₂, CH₄ and N₂O) have been obtained to estimate the GHG emission coefficients (57 sectors) for the year 1995 and 2001. The change in the growth of these sectoral emission coefficients over these periods was used to estimate the coefficients for the year 2010, 2015 and 2020. For the years 2001–2010, it is assumed that the emission coefficient growth rate of the period (1995–2001) across the countries, while the half of the above growth rate has been considered for 2010–2015. For the period 2015–2020, we considered one fourth of the emission growth of 2010–2015. This moderate adjustment for coefficient growth has been considered by assuming a fair degree of technological improvement during this period. The method used to update the BOD, COD, SS coefficients was different from GHG emission coefficients. The coefficient reduction of 10% and 15% for the period 2001–2010 has been considered for Japan and the Republic of Korea in the agricultural and non-agricultural sectors respectively. While for the other four developing countries – China, Indonesia, Vietnam and Thailand – the considered reductions are 2.5% and 5%. The same linear reduction for coefficient growth of BOD, COD and SS is taken for consideration for 2010–2015 and 2015–2020. The difference between the countries is set for the technological advancement. We used the historical data to update industrial waste, like GHG emissions. The difference was that the average coefficient growth changes were applied for all sectors instead of having individual sector growth rates due to the non-availability of the data at sectoral level. But we assume the coefficient growth of the agricultural sector will be half that of the non-agricultural sector.