Analysis of the Role of Tariff Concessions in East Asia

Abstract

While many studies focus on the impact of trade agreements, the literature has not focused on the extent of their implementation, in terms of the aspects agreed upon therein. In this article, we identify the past achievements of economic partnership agreements (EPAs) in the East Asian region in terms of tariff removals and suggest room for further economic benefits from trade liberalisation in the region. Second, we incorporate the HS6-level tariff concession dataset, which distinguishes between tariff removals agreed in these EPAs in East Asia but not yet implemented, from existing overall tariffs in 2011, in the Global Trade Analysis Project (GTAP) Database, which only incorporates enforced tariff reductions through the base-year applied tariffs. To analyse future trade integration, we include commitments that are not yet implemented. This allows us to analyse partial versus full enforcement of tariff concession commitments. Our results suggest that taking those commitments into account matters economically in East Asia.

JEL Classification: D58, F13, F14, F15, F17

Keywords

International Trade Tariff Concessions East Asia GTAP Free Trade Agreements Policy Analysis

1. Introduction

The movements of several regional trade agreements (RTAs) and bilateral free trade agreements (FTAs) have accelerated since the beginning of 2013 in the Asia-Pacific region. Negotiations on the China–Japan–Korea FTA (CJKFTA) and the Regional Comprehensive Economic Partnership (RCEP) were launched in November 2012. The Trans-Pacific Partnership (TPP) negotiation was concluded in 2015, and despite the withdrawal of the USA in January 2017, a new Comprehensive and Progressive Agreement for TPP (CPTPP) was signed between the remaining 11 members in March 2018.

There have been several studies on the impacts of East Asian integration employing computable general equilibrium (CGE) model simulations, including Kawasaki (2015), Itakura and Lee (2012) and Petri, Plummer and Zhai (2012). However, there is not much focus in the literature on the extent to which these agreements have later been implemented, in terms of the aspects agreed upon therein. This is an emerging key issue for assessing the economic impacts of mega-RTAs, given the number of bilateral and sub-regional agreements existing in the regions.

The United States International Trade Commission (USITC) conducted a comprehensive study in this regard reporting the likely impact of the TPP on the US economy in May 2016 (United States International Trade Commission, 2016). It used the tariff reduction scheduling data for TPP countries in the Market Access Map (MAcMap) by the International Trade Centre (ITC)¹ prepared for the Global Economic Partnership Agreements (EPAs)² Research Consortium.³ Those tariff data developments have been extended applying to other EPAs and would be expected to contribute to further studies. That said, while there have been several studies on RTAs, few focus on the extent of tariff reductions that have actually taken place and those being scheduled in the future.

We aim at filling this gap in the literature. We identify the past achievements of EPAs in the East Asian region in terms of tariff removals and suggest future room for further economic benefits from trade liberalisation in the region. Our unique contribution to this literature lies in both an accurate assessment of past achievements in tariff reductions and in analysing the future gains from trade liberalisation, as compared to the imperfect analysis that is widely done without accounting for tariff reduction schedules. In the second section that follows, after a brief look at Asian regionalism, tariff concessions in Asian EPAs are described by countries and sectors comparing the initial and final levels of tariff protections. The second section presents CGE model simulations, estimating the income gains from tariff reductions according to RCEP, based on the baseline developed in this article incorporating the tariff reduction schedules of existing EPAs. The article concludes with the fourth section.

2. Descriptive Evidence

2.1 Asian Regionalism

East Asia has been a world growth centre for decades, and the unprecedented development of its production networks particularly in the manufacturing sector has been progressing since the 1990s. East Asian countries, especially China and the Association of Southeast Asian Nations (ASEAN) member countries, have individually adopted aggressive trade and investment-related policies in order to attract foreign direct investment and to utilise the globalising market forces for achieving higher economic growth. Although these policies were not necessarily well coordinated among the countries at the beginning, intensive effort towards regional economic integration in the form of EPAs has gradually developed since the 2000s, partially due to the stalled World Trade Organization (WTO) Doha Round.

As presented in Figure 1, in 2000, there were only two EPAs among the East Asia countries, namely the Australia–New Zealand Closer Economic Relations Trade Agreement (ANZCERTA) and the ASEAN Free Trade Area (AFTA), whereas there were 30 EPAs in this region in 2015. This includes several bilateral EPAs as well as five ASEAN+1 EPAs: the ASEAN–China FTA (ACFTA) enforced in 2005, the ASEAN–Korea FTA (AKFTA) in 2007, the ASEAN–Japan Comprehensive Economic Partnership (AJCEP) in 2008, the ASEAN–India FTA (AIFTA) in 2010 and the ASEAN–Australia–New Zealand FTA (AANZFTA) in 2010. In addition to these existing EPAs, the ASEAN-10 and the six FTA partners of the ASEAN are currently engaged in the RCEP negotiations, with a view to further strengthening a legal framework for securing de facto economic integration in the region. Finally, China, Japan and Korea have been negotiating a possible FTA (CJK FTA) since 2013.

Looking from a different angle, 115 out of 120 possible combinations of bilateral agreements in East Asia have been concluded or implemented in the past. In other words, more than 95 per cent of bilateral combinations between East Asian countries have already been linked by FTAs. The remaining five combinations⁴ also have either bilateral or plurilateral EPAs under negotiation, such as the CJK FTA and RCEP after the TPP negotiation concluded in October 2015.⁵

Figure 1

Source: Authors’ compilation from various WEB sites.

On the other hand, as explained in the following section, this does not necessarily mean that these EPAs have resulted in a complete elimination of tariffs among the member countries. It is not unusual for a country to fail to achieve a 100 per cent level of tariff elimination in an EPA negotiation due to politico-economic reasons. No matter how many partners a country enters into EPAs with, if the ratio of liberalised items is limited, then the economic gains from EPAs are likely to fall short of expectations. Therefore, it should be emphasised that the conclusion of FTAs alone does not automatically bring economic benefits to member countries.

2.2 Tariff Concessions

We incorporate the tariff concession dataset in the Global Trade Analysis Project (GTAP) database, which distinguishes the tariff removals agreed to in these EPAs in East Asia but not implemented yet, from the existing overall tariffs in the benchmark year. The standard GTAP Database incorporates all in-force tariff reductions that have been included in the agreements; however, significant liberalisation still has to be implemented. We have quantified the actual tariff removals in East Asian EPAs at the HS6 levels. These will be aggregated to the GTAP sectoral level, to arrive at a GTAP-consistent tariff dataset that contains actually implemented tariffs in East Asia. This is suggested to be taken as the actual baseline for policy simulations in the future.

By using a product-level preferential tariff dataset, we construct a new GTAP-compatible dataset of tariff concessions under existing East Asian EPAs. The level of tariff concessions for each sector to which a country is willing to commit is measured by the conventional level of the tariff-elimination index (i.e., the share of duty-free tariff lines for a sector after the transition period).

It should be noted that the original tariff data have some inconsistencies across EPAs and countries for two reasons. First, some EPAs employ the HS2002 version of tariff classification in the agreement texts, whereas others employ the HS2007 version, depending on the timing of the negotiation. Second, as the most-detailed tariff classifications (HS 8-10 digit) are not internationally standardised and are autonomously defined by each country, the total number of tariff lines at the HS 8–10-digit level varies from one country to another.

In order to make our data comparable across countries and EPAs, we first compute the share of duty-free tariff lines at the HS 6-digit level and then convert all the HS2002-based tariff data into HS2007-based data, using a correspondence table provided by the World Integrated Trade Solution (WITS) website.⁶ Finally, the data are aggregated to the GTAP sectoral level in order to implement our simulations.

The data on preferential tariffs used in this article are mainly taken from the ERIA (Economic Research Institute for the Association of ASEAN and East Asia) preferential tariff dataset (Kuno, 2011; Kuno, Fukunaga, & Kimura, 2015), which covers 56 country-level⁷ tariff schedules under the five existing ASEAN+1 FTAs: the AANZFTA, the ACFTA, the AIFTA, the AJCEP and the AKFTA. This is supplemented with data on tariff commitments under the ASEAN Trade in Goods Agreement (ATIGA), which are taken from the ASEAN Secretariat website, as well as tariff data on some of Japan’s bilateral EPAs. We have incorporated all the RTAs that include one or more of these 27 East Asian regions.

East Asian EPAs have ‘substantially covered’ almost all commodities for tariff reductions, ranging from around 80 per cent in India to 100 per cent in Singapore, Australia and New Zealand (Table 1).

Table 1
Tariff Concessions in East Asian EPAs: Number of Commodities

(%)

Importers Ave.^* Exporters

BRN KHM IDN LAO MYS PHL SGP THA VNM AUS CHN IND JPN KOR NZL

BRN 98.2 – 99.2 99.2 99.2 99.2 99.2 99.2 99.2 99.2 99.3 98.4 86.2 98.2 99.2 99.3

KHM 94.6 98.5 – 98.5 98.5 98.5 98.5 98.5 98.5 98.5 90.8 90.2 88.5 85.3 91.0 90.8

IDN 93.5 98.8 98.8 – 98.8 98.8 98.8 98.8 98.8 98.8 94.7 92.5 52.1 92.2 92.1 94.7

LAO 84.3 80.0 80.0 80.0 – 80.0 80.0 80.0 80.0 80.0 93.1 97.7 80.3 86.8 90.1 93.1

MYS 96.3 98.9 98.9 98.9 98.9 – 98.9 98.9 98.9 98.9 97.6 93.7 80.9 95.0 93.0 97.6

PHL 89.9 99.1 99.1 99.1 99.1 99.1 – 99.1 99.1 99.1 96.1 92.8 82.2 97.7 90.0 96.1

SGP 100.0 100.0 100.0 100.0 100.0 100.0 100.0 – 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

THA 97.2 99.8 99.8 99.8 99.8 99.8 99.8 99.8 – 99.8 98.9 93.8 78.6 96.6 95.3 98.9

VNM 82.5 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 – 95.4 93.2 79.9 95.4 91.2 95.4

AUS 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 – n.a. – n.a. n.a. n.a.

CHN 95.1 95.1 95.1 95.1 95.1 95.1 95.1 95.1 95.1 95.1 n.a. – – – n.a. n.a.

IND 78.9 78.9 78.9 78.9 78.9 78.9 78.9 78.9 78.9 78.9 – – – n.a. n.a. –

JPN 93.7 89.5 93.6 94.2 93.6 94.6 95.2 93.4 94.7 94.6 n.a. – n.a. – – –

KOR 92.2 92.2 92.2 92.2 92.2 92.2 92.2 92.2 92.2 92.2 n.a. n.a. n.a. – – n.a.

NZL 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 n.a. n.a. – – n.a. –

			(%)
BRN	98.2	–	99.2	99.2	99.2	99.2	99.2	99.2	99.2	99.2	99.3	98.4	86.2	98.2	99.2	99.3
KHM	94.6	98.5	–	98.5	98.5	98.5	98.5	98.5	98.5	98.5	90.8	90.2	88.5	85.3	91.0	90.8
IDN	93.5	98.8	98.8	–	98.8	98.8	98.8	98.8	98.8	98.8	94.7	92.5	52.1	92.2	92.1	94.7
LAO	84.3	80.0	80.0	80.0	–	80.0	80.0	80.0	80.0	80.0	93.1	97.7	80.3	86.8	90.1	93.1
MYS	96.3	98.9	98.9	98.9	98.9	–	98.9	98.9	98.9	98.9	97.6	93.7	80.9	95.0	93.0	97.6
PHL	89.9	99.1	99.1	99.1	99.1	99.1	–	99.1	99.1	99.1	96.1	92.8	82.2	97.7	90.0	96.1
SGP	100.0	100.0	100.0	100.0	100.0	100.0	100.0	–	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0
THA	97.2	99.8	99.8	99.8	99.8	99.8	99.8	99.8	–	99.8	98.9	93.8	78.6	96.6	95.3	98.9
VNM	82.5	75.6	75.6	75.6	75.6	75.6	75.6	75.6	75.6	–	95.4	93.2	79.9	95.4	91.2	95.4
AUS	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0	–	n.a.	–	n.a.	n.a.	n.a.
CHN	95.1	95.1	95.1	95.1	95.1	95.1	95.1	95.1	95.1	95.1	n.a.	–	–	–	n.a.	n.a.
IND	78.9	78.9	78.9	78.9	78.9	78.9	78.9	78.9	78.9	78.9	–	–	–	n.a.	n.a.	–
JPN	93.7	89.5	93.6	94.2	93.6	94.6	95.2	93.4	94.7	94.6	n.a.	–	n.a.	–	–	–
KOR	92.2	92.2	92.2	92.2	92.2	92.2	92.2	92.2	92.2	92.2	n.a.	n.a.	n.a.	–	–	n.a.
NZL	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0	n.a.	n.a.	–	–	n.a.	–

Source: Authors’ estimates.

Note: *Averages of RCEP countries for ASEAN countries and ASEAN countries for non-ASEAN countries (same in the following tables).

2.3 Countries’ Tariff Protection

2.3.1 Initial Tariff Protection

To maintain consistency with the year of calibration of the GTAP model, we stay with the 2011 tariff data for descriptive purposes. The tariff data come from ITC: they are documented on ITC’s website⁸ and also in Bouët, Decreux, Fontagné, Jean and Laborde (2008) and Guimbard, Jean, Mimouni and Pichot (2012) which also discuss the methodological aspects of aggregating tariff data. Our year of interest is not the most recent, but it gives a closed picture of the actual situation (see Table 2). Some countries might have, however, undertaken some changes in trade policies which may have led to a decrease (a global increase is unlikely, but possible) of their applied tariff.

Table 2
Bilateral AVEs of Average Applied Tariffs, 2011

(%)

Importers Ave.^* Exporters

BRN KHM IDN LAO MYS PHL SGP THA VNM AUS CHN IND JPN KOR NZL

BRN 2.7 – 1.3 4.3 1.1 3.0 3.4 2.1 5.6 0.5 2.6 3.9 0.4 8.0 2.3 1.8

KHM 11.6 14.2 – 6.5 13.9 11.7 11.1 15.6 12.7 12.9 10.8 10.1 8.3 16.5 11.1 11.2

IDN 2.1 0.0 0.0 – 0.0 0.2 0.3 0.2 1.3 1.8 4.6 1.2 3.7 7.2 1.4 4.4

LAO 8.6 2.6 15.2 5.7 – 3.8 3.4 20.0 6.9 3.1 7.6 10.2 16.2 19.8 24.7 6.3

MYS 3.8 1.8 8.0 1.7 0.1 – 1.3 1.0 1.6 4.0 2.6 3.6 4.4 8.9 6.4 2.6

PHL 2.1 0.0 0.4 0.0 0.0 0.1 – 0.0 2.8 20.3 1.1 0.9 7.9 2.0 1.3 0.9

SGP 0.0 0.0 0.0 0.0 0.0 0.0 0.0 – 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

THA 7.4 0.1 14.0 8.9 2.9 5.7 10.1 6.2 – 9.1 3.1 6.8 7.8 8.8 6.2 8.5

VNM 6.3 0.0 5.1 3.2 0.5 3.0 2.7 7.4 3.9 – 3.5 7.5 8.6 5.2 6.8 4.8

AUS 0.3 0.0 0.0 2.1 0.0 0.2 0.1 0.0 0.0 0.1 – n.a. – n.a. n.a. n.a.

CHN 1.5 0.0 2.7 1.4 1.8 1.0 0.2 0.4 2.4 4.6 n.a. – – – n.a. n.a.

IND 17.9 0.1 39.9 31.6 0.1 20.3 5.9 4.0 9.1 11.3 – – – n.a. n.a. –

JPN 1.4 0.0 0.2 0.3 0.6 0.3 1.2 3.1 4.3 1.0 n.a. – n.a. – – –

KOR 4.0 2.3 10.9 1.8 0.4 2.1 4.2 1.2 12.7 10.2 n.a. n.a. n.a. – – n.a.

NZL 0.7 0.0 0.0 1.7 0.0 0.9 1.4 0.0 1.5 2.6 n.a. n.a. – – n.a. –

	(%)
BRN	2.7	–	1.3	4.3	1.1	3.0	3.4	2.1	5.6	0.5	2.6	3.9	0.4	8.0	2.3	1.8
KHM	11.6	14.2	–	6.5	13.9	11.7	11.1	15.6	12.7	12.9	10.8	10.1	8.3	16.5	11.1	11.2
IDN	2.1	0.0	0.0	–	0.0	0.2	0.3	0.2	1.3	1.8	4.6	1.2	3.7	7.2	1.4	4.4
LAO	8.6	2.6	15.2	5.7	–	3.8	3.4	20.0	6.9	3.1	7.6	10.2	16.2	19.8	24.7	6.3
MYS	3.8	1.8	8.0	1.7	0.1	–	1.3	1.0	1.6	4.0	2.6	3.6	4.4	8.9	6.4	2.6
PHL	2.1	0.0	0.4	0.0	0.0	0.1	–	0.0	2.8	20.3	1.1	0.9	7.9	2.0	1.3	0.9
SGP	0.0	0.0	0.0	0.0	0.0	0.0	0.0	–	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
THA	7.4	0.1	14.0	8.9	2.9	5.7	10.1	6.2	–	9.1	3.1	6.8	7.8	8.8	6.2	8.5
VNM	6.3	0.0	5.1	3.2	0.5	3.0	2.7	7.4	3.9	–	3.5	7.5	8.6	5.2	6.8	4.8
AUS	0.3	0.0	0.0	2.1	0.0	0.2	0.1	0.0	0.0	0.1	–	n.a.	–	n.a.	n.a.	n.a.
CHN	1.5	0.0	2.7	1.4	1.8	1.0	0.2	0.4	2.4	4.6	n.a.	–	–	–	n.a.	n.a.
IND	17.9	0.1	39.9	31.6	0.1	20.3	5.9	4.0	9.1	11.3	–	–	–	n.a.	n.a.	–
JPN	1.4	0.0	0.2	0.3	0.6	0.3	1.2	3.1	4.3	1.0	n.a.	–	n.a.	–	–	–
KOR	4.0	2.3	10.9	1.8	0.4	2.1	4.2	1.2	12.7	10.2	n.a.	n.a.	n.a.	–	–	n.a.
NZL	0.7	0.0	0.0	1.7	0.0	0.9	1.4	0.0	1.5	2.6	n.a.	n.a.	–	–	n.a.	–

Source: ITC’s MAcMap database, trade weighted average, %. Authors’ calculations.

We present here the trade-weighted average tariffs (in ad valorem equivalent, hereafter AVE, i.e., a percentage) applied by each concerned country to its partners. The column ‘AVE’ refers to the average applied tariff that each ASEAN country applies to all its regional partners and to the average tariff applied by each of the six remaining countries to the ASEAN-10 (e.g., Australia applies a 0.3% average tariff to the ASEAN-10). To provide an overview of trade preferences within those countries, we also provide a table with the same structure, displaying the most favoured nation (MFN) tariff rates (see Table A1).

Countries belonging to the region are rather heterogeneous in terms of development and their tariff patterns classically reproduce what is observed at the world level: developed countries are less protectionist than developing countries. Australia (0.34%), New Zealand (0.74%) and Japan (1.38%) apply the lowest level of tariffs to ASEAN countries.

According to the trade structure and the level of initial tariff, average protection varies across partners for a given importer. Thus, the country that faces the highest protection when exporting to Australia is Indonesia (2.1%). The other Australian partners face very low average tariffs (less than 0.2% in average). Protection in New Zealand exhibits little variance from free trade (from which Brunei, Cambodia, Lao and Singapore benefit) to 2.6 per cent applied to Vietnamese products. Japan applies low tariffs to its ASEAN neighbours, excepting Thailand which faces a 4.3 per cent average tariff.

China applies a fairly low level of protection to its ASEAN partners: 1.5 per cent. Only Thailand (2.4%), Cambodia (2.7%) and Vietnam (4.6%) encounter average duties that are greater than 2 per cent. India (17.9%) and Korea (4%) are globally more protectionist than their ASEAN partners. India remains the most protectionist country in the region, even if, since the mid-2000s, it has considerably reduced its custom duties. Cambodia is the ASEAN country that has the most limited market access to China (39.9%), followed by Indonesia (31.6%) and Malaysia (20.3%).

Regarding the ASEAN countries, those applying high duties inside the ASEAN block are CVLM, that is, Cambodia (11.6%), Lao (8.6%) and Vietnam (6.3%),⁹ as a result of their longer tariff dismantlement schedule within the ASEAN-10, due to their lower level of development. Malaysia applies an average tariff of 3.8 per cent to its regional partners. The remaining ASEAN countries apply intra-ASEAN tariffs that are lower on average. Their openness to the ‘Six’ is also limited, some countries being very protectionist, as Cambodia, Lao or Thailand. Thus, bilateral levels of protection are asymmetrical, witnessing the progresses that can be made on the reciprocity of the EPAs: ASEAN countries apply higher average tariffs to Australia, China, Japan and New Zealand than their counterparts. Lastly, in 2011, Singapore appeared as an extreme case as it completely opened itself to all its partners in the region.

2.3.2 Final Tariff Protection Within the EPAs

Tariffs dismantlement within the ASEAN and EPAs is still ongoing. Merging the information on the remaining products whose duties still need to be removed within this framework, as explained in the first section, and actual tariffs make it possible to compute the final tariff level, product by product, for each bilateral relationship.

The full implementation of EPAs produces a different picture of the average protection in the region and between countries. Table 3 provides an overview of the situation in 2025, that is, once all commitments are implemented.

Table 3
Bilateral Average AVEs of Applied Tariffs after EPAs’ Implementation

(%)

Importers Ave.^* Exporters

BRN KHM IDN LAO MYS PHL SGP THA VNM AUS CHN IND JPN KOR NZL

BRN 0.5 – 0.0 0.0 0.0 0.1 0.0 0.4 0.0 0.0 0.3 2.1 0.1 0.7 0.1 0.4

KHM 3.9 0.0 – 0.1 0.4 0.3 0.1 5.3 2.2 4.7 6.2 3.1 2.1 12.3 8.2 5.8

IDN 0.9 0.0 0.0 – 0.0 0.1 0.3 0.1 1.3 1.8 0.9 0.9 3.1 1.8 0.9 0.6

LAO 6.0 1.7 14.6 4.7 – 2.9 2.1 19.3 6.2 2.5 2.0 0.8 13.1 14.3 23.1 0.5

MYS 1.4 0.0 8.0 0.9 0.0 – 1.1 0.5 0.8 2.9 1.1 1.3 2.8 1.8 3.4 0.4

PHL 1.7 0.0 0.4 0.0 0.0 0.1 – 0.0 2.8 20.3 0.4 0.8 5.3 1.1 0.6 0.2

SGP 0.0 0.0 0.0 0.0 0.0 0.0 0.0 – 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

THA 2.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 – 0.9 0.1 1.3 4.9 4.2 1.3 0.8

VNM 2.9 0.0 4.8 2.3 0.4 2.2 1.9 7.2 3.2 1.8 2.2 3.5 1.6 3.2 0.9

AUS 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 – n.a. – n.a. n.a. n.a.

CHN 1.2 0.0 2.7 1.3 1.8 0.8 0.1 0.3 2.0 2.9 n.a. – – – n.a. n.a.

IND 15.2 0.1 39.4 29.0 0.0 17.4 1.6 2.0 5.6 7.0 – – – n.a. n.a. –

JPN 0.9 0.0 0.1 0.3 0.4 0.3 0.6 2.9 2.6 0.5 n.a. – n.a. – – –

KOR 2.3 0.0 4.4 0.5 0.2 0.6 2.8 0.4 10.8 6.2 n.a. n.a. n.a. – – n.a.

NZL 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 n.a. n.a. – – n.a. –

																(%)
BRN	0.5	–	0.0	0.0	0.0	0.1	0.0	0.4	0.0	0.0	0.3	2.1	0.1	0.7	0.1	0.4
KHM	3.9	0.0	–	0.1	0.4	0.3	0.1	5.3	2.2	4.7	6.2	3.1	2.1	12.3	8.2	5.8
IDN	0.9	0.0	0.0	–	0.0	0.1	0.3	0.1	1.3	1.8	0.9	0.9	3.1	1.8	0.9	0.6
LAO	6.0	1.7	14.6	4.7	–	2.9	2.1	19.3	6.2	2.5	2.0	0.8	13.1	14.3	23.1	0.5
MYS	1.4	0.0	8.0	0.9	0.0	–	1.1	0.5	0.8	2.9	1.1	1.3	2.8	1.8	3.4	0.4
PHL	1.7	0.0	0.4	0.0	0.0	0.1	–	0.0	2.8	20.3	0.4	0.8	5.3	1.1	0.6	0.2
SGP	0.0	0.0	0.0	0.0	0.0	0.0	0.0	–	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
THA	2.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	–	0.9	0.1	1.3	4.9	4.2	1.3	0.8
VNM	2.9	0.0	4.8	2.3	0.4	2.2	1.9	7.2	3.2		1.8	2.2	3.5	1.6	3.2	0.9
AUS	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	–	n.a.	–	n.a.	n.a.	n.a.
CHN	1.2	0.0	2.7	1.3	1.8	0.8	0.1	0.3	2.0	2.9	n.a.	–	–	–	n.a.	n.a.
IND	15.2	0.1	39.4	29.0	0.0	17.4	1.6	2.0	5.6	7.0	–	–	–	n.a.	n.a.	–
JPN	0.9	0.0	0.1	0.3	0.4	0.3	0.6	2.9	2.6	0.5	n.a.	–	n.a.	–	–	–
KOR	2.3	0.0	4.4	0.5	0.2	0.6	2.8	0.4	10.8	6.2	n.a.	n.a.	n.a.	–	–	n.a.
NZL	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	n.a.	n.a.	–	–	n.a.	–

Source: ITC’s MAcMap database, trade weighted average, %. Authors’ calculations.

Comparing the initial and final levels of tariffs allows us to evaluate the tariff liberalisation that will occur in those agreements. Tariff concessions in East Asian EPAs have not always been substantially high enough in terms of average tariff rates (Table 4) and would be much more effective than the number of commodities (Table 1).

Table 4

Tariff Concessions in East Asian EPAs: Tariff Rates

																(%)
Importers	Ave.^*	Exporters
Importers	Ave.^*	BRN	KHM	IDN	LAO	MYS	PHL	SGP	THA	VNM	AUS	CHN	IND	JPN	KOR	NZL
BRN	80.3	–	100.0	99.8	100.0	97.3	100.0	78.8	100.0	100.0	87.5	46.4	69.0	91.7	93.8	80.8
KHM	66.6	100.0	–	98.8	97.1	97.4	99.3	66.0	82.4	63.4	42.9	68.9	74.8	25.2	26.7	48.3
IDN	57.5	–	–	–	–	70.0	0.0	56.3	3.8	0.0	79.7	26.1	16.3	74.8	38.5	87.5
LAO	30.3	36.4	4.2	16.1	–	23.2	37.3	3.3	9.1	19.0	73.8	92.0	19.1	27.6	6.3	92.7
MYS	63.4	100.0	1.1	43.6	100.0	–	11.6	56.7	46.8	27.0	58.8	65.0	36.0	79.6	46.5	85.7
PHL	17.8	–	0.0	–	–	0.0	–	0.0	0.0	0.0	62.2	7.7	33.8	45.2	55.8	81.2
SGP	–	–	–	–	–	–	–	–	–	–	–	–	–	–	–	–
THA	73.5	100.0	100.0	99.7	99.7	99.8	100.0	100.0	–	90.4	98.1	81.1	36.7	52.3	78.5	90.5
VNM	54.4	0.0	5.7	28.3	12.5	28.6	29.1	3.5	19.0	–	50.1	71.2	59.7	70.3	52.4	81.8
AUS	100.0	100.0	–	100.0	–	100.0	100.0	–	100.0	100.0	–	n.a.	–	n.a.	n.a.	n.a.
CHN	21.2	–	1.5	9.2	0.6	19.2	45.5	32.4	17.2	35.5	n.a.	–	–	–	n.a.	n.a.
IND	15.2	16.7	1.2	8.5	60.0	14.2	73.2	49.9	38.1	37.6	–	–	–	n.a.	n.a.	–
JPN	34.1	–	62.5	19.4	37.7	12.5	52.4	8.9	40.3	49.0	n.a.	–	n.a.	–	–	–
KOR	41.7	100.0	59.4	71.8	54.1	72.8	34.7	70.1	15.2	39.6	n.a.	n.a.	n.a.	–	–	n.a.
NZL	100.0	–	–	100.0	–	100.0	100.0	–	100.0	100.0	n.a.	n.a.	–	–	n.a.	–

Source: ITC’s MAcMap database, trade weighted average, %. Authors’ calculations.

On the ASEAN countries’ side, tariff protection decreases greatly when taking into account all commitments (except for Singapore which is already fully opened). Cambodia reduces spectacularly its average tariffs by more than 7.5 percentage points (hereafter pp), that is to say the average level is almost reduced by a factor of 3. This country becomes very open to its ASEAN neighbours (except Singapore which still faces a more than 5 per cent average tariff when exporting to Cambodia). Thailand is also another country that experiences a large decrease in its tariff protection (from 7.4% to 2.0%). Brunei also reduces significantly its tariffs and stabilises its average protection to 0.5 per cent within the region. By implementing more ambitious commitments, Indonesia becomes more liberalised than the Philippines: both countries start with the same level of average protection (2.1%), but Indonesia ends with less than 1 per cent level, whereas the level of protection of Philippines is 1.7 per cent. Lao remains the most protectionist country in the ASEAN: its average protection is 6 per cent after a decline of 2.6 per cent. Vietnam more than halves its average protection (from 6.3% to 2.9%) and applies a reasonable level of average custom duties, but it also remains a country that faces high tariffs when exporting to its partners (such as Cambodia, Indonesia, Philippines or Thailand).

Regarding the external six partners, Australia and New Zealand, which apply very low initial duties to the ASEAN countries, now become completely open to them. The openness is also important for Korea (from 4.0% to 2.3%) and Japan (from 1.4% to 0.9%). The ambition is moderated for India: average applied tariff remains high (15.2%) but undergoes a decrease by 2.7 per cent. Finally, China offers less additional openness to the ASEAN countries (−0.3 %) but applies fairly low custom duties to its ASEAN partners (1.2%) after implementation of its commitments. Asymmetries between the ASEAN countries and their partners decrease along with the implementation of existing commitments. Except for India, the ASEAN countries remain more protected, vis-à-vis the ‘six’, than the opposite.

Finally, removing of tariff peaks (see Table A2) is not that ambitious once commitments have been implemented. Indeed, even if only 7,801 duty lines continue to exhibit an ad valorem equivalent of applied tariffs over 30 per cent, Cambodia dramatically cuts its tariff peaks as there remain only 1,006 of such tariffs; so does Thailand (from 1,946 to 314), Vietnam (from 1,339 to 669) and, to a lesser extent, Brunei (from 255 to 129) and Lao (from 1,320 to 956). Other countries’ commitments are less ambitious: some countries almost do not cut or remove these tariffs (e.g., Indonesia or Malaysia), and the Philippines does not cut any of its tariff peaks. On the ASEAN partners’ side (China, India, Japan and Korea), the ambition is moderated. Lastly, Australia and New Zealand have removed the few they had.

2.4 Sectoral Tariff Protection

The average protection applied within ASEAN-10 and their EPA partners was 3.4 per cent in 2011. The relatively low average hides, however, a heterogeneous average sectoral tariff protection. Within the region, agricultural trade is more protected on average (15.8%) than industrial trade (2.4%). However, some countries present variations: Australia and New Zealand protect their industry more (0.3% and 0.8%, respectively) than their agricultural sectors (0.1% and 0.4%, respectively). This remains an exception at the world level, agriculture being generally protected by higher custom duties (especially specific tariffs or tariff rate quotas) than industry, so this is witness to the important competitive advantages these two countries have in these sectors.

Still in 2011, the other ASEAN10 partners follow the classical pattern observed worldwide: they clearly protect their agriculture with substantial custom duties. India (73.2% in agriculture, 4.9% in Non-agricultural Market Access [NAMA], i.e., industrial products) and Korea (41.6% and 1.9%, respectively) highly defend their internal markets, followed by Japan (18.5% and 0.2%, respectively). China is relatively the more-open countries, as its average tariff in agriculture is equal to 8.7 per cent (versus 0.8% in industry).

Protection within the ASEAN-10 is more homogenous: the average tariff in industry is half its level in agriculture, as for Brunei the ratio of its average agricultural tariff to average industrial tariff is 2.3, Indonesia (2.9), Thailand (2.5) and Malaysia (2.1). Lao (1.5) and Vietnam (1.7) exhibit even lower differences between these two sectors. Finally, Cambodia’s tariffs do not offer large variability at this sectoral level of aggregation, but as stated above, in Australia and New Zealand, the agriculture market is more open than its industrial one: both these countries apply, on average, 11.6 per cent in industry and 11.1 per cent in agriculture.

Finally, even if a part of the tariffs has already been removed (witnessed by the preferential margins observable when comparing MFN tariffs and applied tariffs, see Table A2), the countries still highly protect a group of sensitive products. The number of tariff peaks (i.e., we choose an arbitrary value of the ad valorem equivalent of 30% to define tariff peaks; other values can also be found in the literature [50%, 100%] or on international organisation websites) is as high as 23,436 (on 656,349 duty lines, once we exclude products for which MFN duty is nil); 10,416 relate to the agricultural sector and non-agricultural market access has 13,020 of such tariffs. Cambodia is the country which uses these most frequently (13,328 duty lines, of which 10,052 are for industrial products). Australia and New Zealand have a few (respectively, 8 and 3, all of them applied to manufactured products). Other details can be found in the Annex.

The first important thing to notice in Table 5 is the ambitious liberalisation measures exhibited by the EPAs: average tariff will go down by 49 per cent (from 3.4% in 2011 to 1.7% once EPAs are implemented). Among the 43 GTAP sectors, 31 see their average tariffs being reduced by more than a half; five sectors experience a decline of between 25 per cent and 50 per cent, and only seven are liberalised by less than a quarter.

Table 5
Average AVEs of Applied Tariffs in 2011 and After EPAs’ Implementation, by GTAP Sectors

GTAP Code Sector Applied 2011 Applied 2025 Delta

gdt Gas manufacture and distribution 0.0 0.0 –100

oil Oil 0.5 0.0 –100

wol Wool. Silk-worm cocoons 2.2 0.0 –100

c_b Sugar cane and sugar beet 0.2 0.0 –100

gas Gas 0.2 0.0 –100

col Coal 0.6 0.0 –99.9

for Forestry 2.4 0.1 –95.8

ele Electronic equipment 0.4 0.0 –92.5

wap Wearing apparel 8.8 0.7 –92.2

oap Animal products NEC 3.8 0.4 –90.1

wht Wheat 6.0 0.7 –87.6

omn Minerals NEC 0.3 0.0 –87.6

nfm Metals NEC 1.1 0.1 –87.2

fmp Metal products 5.2 0.7 –86.6

ppp Paper products. Publishing 2.4 0.4 –83.6

ome Machinery and equipment NEC 2.5 0.4 –82.3

omf Manufactures NEC 3.8 0.8 –79.0

cmt Meat: Cattle, sheep, goats and horses 8.4 1.8 –78.6

tex Textiles 5.7 1.7 –70.5

osd Oil seeds 5.9 1.8 –69.0

mil Dairy products 4.0 1.3 –67.3

otn Transport equipment NEC 3.3 1.1 –67.2

ctl Cattle, sheep, goats and horses 2.5 0.8 –66.7

nmm Mineral products NEC 4.0 1.4 –63.8

pfb Plant-based fibers 0.0 0.0 –63.7

lea Leather products 6.1 2.2 –63.6

fsh Fishing 1.9 0.7 –63.1

crp Chemical, rubber and plastic products 2.9 1.1 –62.4

i_s Ferrous metals 5.5 2.1 –62.0

lum Wood products 3.1 1.4 –56.5

gro Cereal grains NEC 5.1 2.5 –51.0

ofd Food products NEC 7.5 3.8 –48.7

mvh Motor vehicles and parts 12.9 7.6 –40.7

p_c Petroleum and coal products 1.2 0.8 –33.7

pdr Paddy rice 11.4 8.0 –29.5

omt Meat products NEC 8.4 6.2 –26.1

v_f Vegetables, fruit and nuts 12.1 9.5 –21.6

b_t Beverages and tobacco products 22.6 19.2 –15.2

ocr Crops NEC 12.4 10.5 –14.8

pcr Processed rice 39.9 34.8 –12.9

sgr Sugar 15.8 14.3 –9.7

vol Vegetable oils and fats 25.6 25.1 –2.1

ely Electricity 0.5 0.5 0

ALL 3.4 1.7 –49.0

GTAP Code	Sector	Applied 2011	Applied 2025	Delta
gdt	Gas manufacture and distribution	0.0	0.0	–100
oil	Oil	0.5	0.0	–100
wol	Wool. Silk-worm cocoons	2.2	0.0	–100
c_b	Sugar cane and sugar beet	0.2	0.0	–100
gas	Gas	0.2	0.0	–100
col	Coal	0.6	0.0	–99.9
for	Forestry	2.4	0.1	–95.8
ele	Electronic equipment	0.4	0.0	–92.5
wap	Wearing apparel	8.8	0.7	–92.2
oap	Animal products NEC	3.8	0.4	–90.1
wht	Wheat	6.0	0.7	–87.6
omn	Minerals NEC	0.3	0.0	–87.6
nfm	Metals NEC	1.1	0.1	–87.2
fmp	Metal products	5.2	0.7	–86.6
ppp	Paper products. Publishing	2.4	0.4	–83.6
ome	Machinery and equipment NEC	2.5	0.4	–82.3
omf	Manufactures NEC	3.8	0.8	–79.0
cmt	Meat: Cattle, sheep, goats and horses	8.4	1.8	–78.6
tex	Textiles	5.7	1.7	–70.5
osd	Oil seeds	5.9	1.8	–69.0
mil	Dairy products	4.0	1.3	–67.3
otn	Transport equipment NEC	3.3	1.1	–67.2
ctl	Cattle, sheep, goats and horses	2.5	0.8	–66.7
nmm	Mineral products NEC	4.0	1.4	–63.8
pfb	Plant-based fibers	0.0	0.0	–63.7
lea	Leather products	6.1	2.2	–63.6
fsh	Fishing	1.9	0.7	–63.1
crp	Chemical, rubber and plastic products	2.9	1.1	–62.4
i_s	Ferrous metals	5.5	2.1	–62.0
lum	Wood products	3.1	1.4	–56.5
gro	Cereal grains NEC	5.1	2.5	–51.0
ofd	Food products NEC	7.5	3.8	–48.7
mvh	Motor vehicles and parts	12.9	7.6	–40.7
p_c	Petroleum and coal products	1.2	0.8	–33.7
pdr	Paddy rice	11.4	8.0	–29.5
omt	Meat products NEC	8.4	6.2	–26.1
v_f	Vegetables, fruit and nuts	12.1	9.5	–21.6
b_t	Beverages and tobacco products	22.6	19.2	–15.2
ocr	Crops NEC	12.4	10.5	–14.8
pcr	Processed rice	39.9	34.8	–12.9
sgr	Sugar	15.8	14.3	–9.7
vol	Vegetable oils and fats	25.6	25.1	–2.1
ely	Electricity	0.5	0.5	0
ALL		3.4	1.7	–49.0

Source: ITC’s MAcMap database, trade weighted average, %. Authors’ calculations.

On the 31 most liberalised sectors, the tariffs on five of them are completely removed (−100%). However, these sectors have initially a very little average protection and concern mainly energy-related products. Two other sectors are also fully liberalised in this case: the sector ‘Wool’ whose initial average tariff is not very high (2.2%) and ‘sugar cane’ (0.2%).

Among the sectors with a significant drop in protection and with an initial relatively important average tariff are those related to the textile industry—see the tariffs removed: the ‘Wearing apparel’ sector starts with an 8.8 per cent average tariff that is reduced by −92.2 per cent, the ‘textiles’ sector is protected by a 5.7 per cent tariff that will be substantially reduced (−70.5%), and the ‘Leather products’ (6.1% in 2011) will see its average protection declining by 63.1 per cent. Some agricultural sectors are also significantly liberalised. This is particularly the case for ‘Animal products NEC’ (3.8% in 2011, −90.1% after EPAs’ implementation), ‘wheat’ (6%, −87.6%) and ‘white meat’ (8.4%, −78.6%).

However, the least significant declines also concern agricultural products, especially sectors in which initial protection was strongest. The ‘processed rice’ sector, for example, which has an initial protection of almost 40 per cent, will still be highly protected after the implementation of the EPAs (the variation corresponds to 12.9%), as will ‘vegetable oils and fats’ (25.6%, −2.1%), ‘tobacco and alcohol’ (22.6% −15.2%) and ‘sugar’ products (15.8%, −9.7%).

While we show and discuss some statistics on the frequency of peak tariffs, we employ the complete dataset on tariffs at the tariff line level, aggregate it to the HS6 level and then concord it to the GTAP sectors using correspondence tables.

3. Scenarios and Simulations

3.1 The Framework of a Computable General Equilibrium Model

Using our specific dataset, we compare the economic impacts of partial versus complete implementation of the tariff reductions agreed to in the East Asian EPAs. The GTAP model as well as the GTAP database are utilised to estimate the impacts of tariff reductions. The GTAP model is a standard CGE model of global trade. In the static version of the GTAP model, production factors—capital and labour—and productivity are exogenous.

In this article, two dynamic aspects of trade liberalisation are studied in the model simulations modifying the static version of the GTAP model. First, the dynamic aspects of capital formation are incorporated. Capital accumulation and growth effects are introduced, linking an induced increase in income, savings and investment in turn to capital stock. The external balance is also endogenously determined assuming the expected rate of return on capital is equalised among regions through international capital movement. On the other hand, labour supply is still exogenous. Labour could move across sectors within economies, but the total quantity of labour is fixed by the economies. The international movement of labour is not taken into account and the rates of change in wage rates may vary across regions.

Second, pro-competitive productivity improvement effects are also incorporated, assuming that total factor productivity of domestic industries increases according to lower import prices weighted by the ratio of imports to total production. That said, the trade framework has maintained an Armington model, in which products are differentiated at the country level but not firm level; those are implemented in the Melitz model which introduces firms’ heterogeneity.

3.2 Scenarios

The current GTAP Database (version 9.0, documented in Narayanan, Aguiar, & McDougall, 2015) consists of 57 disaggregated sectors and 140 economies. In this article, as shown in Table 6, economies are aggregated into 27 regions. The RCEP countries are disaggregated individually, except for Myanmar where data are not available.¹⁰ Commodities are aggregated into 22 sectors in accordance with the medium classifications of standard national accounts.

Table 6
Geographical and Sectoral Aggregations

Countries and Regions
Commodities

JPN Japan RIC Rice

CHN China GRA Grains

KOR Korea MET Bovine cattle, sheep and goat products

HKG Hong Kong, China MIL Dairy products

TWN Chinese Taipei SGR Sugar

BRU Brunei B_T Beverages and tobacco products

IDN Indonesia OAF Other primary

MYS Malaysia OPF Other processed foods

PHL Philippines MNG Mining

SGP Singapore TXL Textiles and wearing apparel

THA Thailand CHM Chemical products

VNM Vietnam MTL Metals

KHM Cambodia MVH Motor vehicles and parts

LAO Laos OTN Other transport equipment

IND India ELE Electronic equipment

AUS Australia OME Other machinery and equipment

NZL New Zealand OMF Other manufacturing

USA US CNS Construction

CAN Canada EGW Electricity, gas and water

MEX Mexico T_T Transportation

CHL Chile OSP Other private services

PER Peru OSG Public services

RUS Russia

EUM EU

OAO Other Asia

OAM Other America

ROW Rest of the world

Countries and Regions	Commodities
CHN	China	GRA	Grains
KOR	Korea	MET	Bovine cattle, sheep and goat products
HKG	Hong Kong, China	MIL	Dairy products
TWN	Chinese Taipei	SGR	Sugar
BRU	Brunei	B_T	Beverages and tobacco products
IDN	Indonesia	OAF	Other primary
MYS	Malaysia	OPF	Other processed foods
PHL	Philippines	MNG	Mining
SGP	Singapore	TXL	Textiles and wearing apparel
THA	Thailand	CHM	Chemical products
VNM	Vietnam	MTL	Metals
KHM	Cambodia	MVH	Motor vehicles and parts
LAO	Laos	OTN	Other transport equipment
IND	India	ELE	Electronic equipment
AUS	Australia	OME	Other machinery and equipment
NZL	New Zealand	OMF	Other manufacturing
USA	US	CNS	Construction
CAN	Canada	EGW	Electricity, gas and water
MEX	Mexico	T_T	Transportation
CHL	Chile	OSP	Other private services
PER	Peru	OSG	Public services
RUS	Russia
EUM	EU
OAO	Other Asia
OAM	Other America
ROW	Rest of the world

Source: Authors’ compilation based on GTAP Data Base version 9.0.

The latest GTAP Database was released in May 2015; however, its base year remains 2011. The benchmark data used in this study were updated to 2015, downloaded from the website of the International Monetary Fund.

We have simulated two scenarios of unilateral import tariff reductions by East Asian countries and their trade partners in the region. The first one is a stylised one where import tariffs which existed in 2011 would fully be removed. The second one looks at a reduction in import tariffs based on existing East Asian EPAs discussed above.

3.3 Results

The economy-wide impacts of tariff reductions will largely be determined by the magnitude of those reductions. The more tariffs are reduced, the more imports are boosted, domestic production could be replaced and real income and consumption stimulated by lower import costs. The overall impacts of unilateral tariff reductions would generally be expected to result in improvements in economic welfare at the macro level.

Theoretical studies have argued possible negative impacts of tariff reductions from a deterioration of terms of trade. Additional demand for imported goods caused by lower import prices in domestic markets would result in higher prices of goods in international markets. However, quantitative studies using conventional CGE model simulations have generally shown that those negative impacts would be more than offset by the positive dynamic effects of capital formation and technology improvement discussed above, in addition to the static gains of more efficient resource allocations.

Estimated income gains from full tariff removals by East Asian countries are shown in Table 7 by the source country of imports, the magnitudes varying widely among ASEAN countries reflecting the differences in initial tariff rates discussed above. The other six countries (Australia, China, India, Japan, Korea and New Zealand) would gain less than the AESAN countries. In contrast, income gains from the remaining tariff reductions according to the East Asian EPAs (Table 8) would generally be limited, except in the smaller East Asian countries as a result of a major implementation of existing EPAs until 2011. The ratios of income gains with the remaining tariff reductions according to the existing East Asian EPAs relative to those by full tariff removals are shown in Table 9. It is indicated in Figure 2 that those are more or less proportional to the rates of tariff concessions in terms of the trade-weighted average tariff rates (Table 4) rather than those at the tariff line levels (Table 1).

Table 7
Changes in Equivalent Variations According to Tariff Removals

(% of GDP)

Importers Ave. Exporters

BRN KHM IDN LAO MYS PHL SGP THA VNM AUS CHN IND JPN KOR NZL

BRN 3.77 – 0.00 0.06 0.00 0.19 0.00 1.93 0.23 0.00 0.01 0.54 0.12 0.32 0.36 0.00

KHM 8.65 0.00 – 0.01 0.00 0.21 0.00 0.21 1.86 1.45 0.01 4.10 0.09 0.11 0.60 0.01

IDN 0.52 0.00 0.00 – 0.00 0.00 0.00 0.16 0.01 0.01 0.02 0.06 0.04 0.19 0.03 0.00

LAO 1.43 0.00 0.00 0.00 – 0.00 0.00 0.01 0.52 0.05 0.01 0.85 0.01 –0.02 0.00 0.00

MYS 2.39 0.00 0.00 0.00 0.00 – 0.13 0.19 0.05 0.04 0.01 0.70 0.05 0.77 0.43 0.01

PHL 8.63 0.00 0.00 0.00 0.00 0.00 – 0.96 0.05 0.37 0.34 2.03 0.86 1.97 2.05 0.00

SGP 0.00 0.00 0.00 0.00 0.00 0.00 0.00 – 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

THA 5.58 0.00 0.02 0.33 0.02 0.46 0.24 0.49 – 0.23 0.06 1.84 0.19 1.38 0.29 0.01

VNM 3.66 0.00 0.01 0.02 0.00 0.02 0.00 0.14 0.00 – 0.02 2.35 0.17 0.16 0.77 0.00

AUS 0.01 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 – n.a. – n.a. n.a. n.a.

CHN 0.03 0.00 0.00 0.00 0.00 0.01 0.00 0.02 0.01 0.00 n.a. – – – n.a. n.a.

IND 0.87 0.00 0.00 0.53 0.00 0.22 0.00 0.04 0.03 0.05 – – – n.a. n.a. –

JPN 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 n.a. – n.a. – – –

KOR 0.63 0.00 0.00 0.13 0.00 0.01 –0.01 0.04 0.16 0.31 n.a. n.a. n.a. – – n.a.

NZL 0.05 0.00 0.00 0.01 0.00 0.01 0.00 0.00 0.02 0.01 n.a. n.a. – – n.a. –

															(% of GDP)
BRN	3.77	–	0.00	0.06	0.00	0.19	0.00	1.93	0.23	0.00	0.01	0.54	0.12	0.32	0.36	0.00
KHM	8.65	0.00	–	0.01	0.00	0.21	0.00	0.21	1.86	1.45	0.01	4.10	0.09	0.11	0.60	0.01
IDN	0.52	0.00	0.00	–	0.00	0.00	0.00	0.16	0.01	0.01	0.02	0.06	0.04	0.19	0.03	0.00
LAO	1.43	0.00	0.00	0.00	–	0.00	0.00	0.01	0.52	0.05	0.01	0.85	0.01	–0.02	0.00	0.00
MYS	2.39	0.00	0.00	0.00	0.00	–	0.13	0.19	0.05	0.04	0.01	0.70	0.05	0.77	0.43	0.01
PHL	8.63	0.00	0.00	0.00	0.00	0.00	–	0.96	0.05	0.37	0.34	2.03	0.86	1.97	2.05	0.00
SGP	0.00	0.00	0.00	0.00	0.00	0.00	0.00	–	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00
THA	5.58	0.00	0.02	0.33	0.02	0.46	0.24	0.49	–	0.23	0.06	1.84	0.19	1.38	0.29	0.01
VNM	3.66	0.00	0.01	0.02	0.00	0.02	0.00	0.14	0.00	–	0.02	2.35	0.17	0.16	0.77	0.00
AUS	0.01	0.00	0.01	0.00	0.00	0.00	0.00	0.00	0.00	0.00	–	n.a.	–	n.a.	n.a.	n.a.
CHN	0.03	0.00	0.00	0.00	0.00	0.01	0.00	0.02	0.01	0.00	n.a.	–	–	–	n.a.	n.a.
IND	0.87	0.00	0.00	0.53	0.00	0.22	0.00	0.04	0.03	0.05	–	–	–	n.a.	n.a.	–
JPN	0.10	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.10	0.00	n.a.	–	n.a.	–	–	–
KOR	0.63	0.00	0.00	0.13	0.00	0.01	–0.01	0.04	0.16	0.31	n.a.	n.a.	n.a.	–	–	n.a.
NZL	0.05	0.00	0.00	0.01	0.00	0.01	0.00	0.00	0.02	0.01	n.a.	n.a.	–	–	n.a.	–

Source: Authors’ simulations.

Table 8

Changes in Equivalent Variations According to EPAs Tariff Reductions

															(% of GDP)
Importers	Ave.	Exporters
Importers	Ave.	BRN	KHM	IDN	LAO	MYS	PHL	SGP	THA	VNM	AUS	CHN	IND	JPN	KOR	NZL
BRN	1.39	–	0.00	0.04	0.00	0.10	0.00	0.28	0.20	0.00	0.00	0.13	0.05	0.26	0.32	0.00
KHM	6.81	0.00	–	0.01	0.00	0.21	0.00	0.21	1.86	1.45	0.00	2.81	0.06	0.00	0.19	0.00
IDN	0.14	0.00	0.00	–	0.00	0.00	0.00	0.00	0.00	0.00	0.02	0.01	0.00	0.08	0.02	0.00
LAO	1.05	0.00	0.00	0.00	–	0.00	0.00	0.00	0.17	0.03	0.01	0.82	0.01	0.02	0.01	0.00
MYS	1.32	0.00	0.00	0.01	0.00	–	0.00	0.15	0.02	0.01	0.01	0.48	0.00	0.56	0.09	0.00
PHL	0.23	0.00	0.00	0.00	0.00	0.00	–	0.01	0.00	0.00	0.03	0.00	0.02	0.07	0.09	0.00
SGP	0.00	0.00	0.00	0.00	0.00	0.00	0.00	–	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00
THA	0.47	0.00	0.02	0.03	0.00	0.04	0.01	0.00	–	0.03	0.05	0.26	0.00	0.01	0.01	0.01
VNM	0.38	0.00	0.00	0.00	0.00	0.01	0.00	0.02	0.00	–	0.00	0.23	0.03	0.04	0.06	0.00
AUS	0.01	0.00	0.01	0.00	0.00	0.00	0.00	0.00	0.00	0.00	–	n.a.	–	n.a.	n.a.	n.a.
CHN	0.01	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	n.a.	–	–	–	n.a.	n.a.
IND	0.03	0.00	0.00	0.02	0.00	0.00	0.00	0.00	0.00	0.00	–	–	–	n.a.	n.a.	–
JPN	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	n.a.	–	n.a.	–	–	–
KOR	0.07	0.00	0.00	0.00	0.00	0.01	0.00	0.03	0.00	0.01	n.a.	n.a.	n.a.	–	–	n.a.
NZL	0.05	0.00	0.00	0.01	0.00	0.01	0.00	0.00	0.02	0.01	n.a.	n.a.	–	–	n.a.	–

Source: Authors’ simulations.

Table 9

Tariff Concessions in East Asian EPAs: Income Gains

																(%)
Importers	Ave.	Exporters
Importers	Ave.	BRN	KHM	IDN	LAO	MYS	PHL	SGP	THA	VNM	AUS	CHN	IND	JPN	KOR	NZL
BRN	36.9	–	62.6	69.5	0.0	50.3	51.9	14.6	89.3	5.0	12.4	24.7	39.5	80.3	89.0	22.7
KHM	78.7	96.3	–	100.8	100.0	100.1	100.1	100.0	99.9	100.0	43.8	68.6	64.6	2.7	31.1	1.2
IDN	26.2	–	96.9	–	–	70.2	0.0	1.5	0.4	0.0	85.2	17.9	4.4	44.4	52.3	n.s.
LAO	73.4	–	2.4	n.s.	–	23.6	1.3	9.2	32.0	55.1	59.3	96.7	86.1	n.s.	n.s.	94.2
MYS	55.5	99.1	5.1	n.s.	100.0	–	0.5	79.8	31.4	18.8	74.2	68.0	5.6	72.8	20.1	69.7
PHL	26.8	–	–	2.5	–	0.0	–	15.3	0.0	0.0	97.2	0.0	23.3	36.0	44.9	n.s.
SGP	–	–	–	–	–	–	–	–	–	–	–	–	–	–	–	–
THA	8.3	14.0	82.8	8.5	17.5	9.1	3.0	0.8	–	11.3	77.6	13.9	0.0	1.1	2.8	79.5
VNM	10.4	n.s	n.s.	8.9	n.s.	32.8	32.1	16.4	n.s.	–	2.2	9.6	15.8	23.1	7.3	n.s.
AUS	100.0	0.0	100.0	–	–	100.0	100.0	–	100.0	100.0	–	n.a.	–	n.a.	n.a.	n.a.
CHN	20.5	0.0	0.2	n.s.	–3.0	5.9	n.s.	29.7	11.9	63.9	n.a.	–	–	–	n.a.	n.a.
IND	3.2	0.0	0.0	3.6	0.0	1.5	34.1	6.0	5.2	2.5	–	–	–	n.a.	n.a.	–
JPN	n.s.	0.0	68.6	n.s.	0.0	0.9	n.s.	n.s.	0.1	20.8	n.a.	–	n.a.	–	–	–
KOR	11.1	91.7	n.s.	3.4	2.9	87.3	n.s.	97.4	2.8	3.9	n.a.	n.a.	n.a.	–	–	n.a.
NZL	100.0	18.0	100.0	100.0	–	100.0	100.0	–	100.0	100.0	n.a.	n.a.	–	–	n.a.	–

Source: Authors’ simulations.

That said, the ratio of tariff concessions in terms of income gains as well as the trade-weighted average tariff rates would not be as high as those in terms of the number of commodities at the tariff line levels. As discussed above, final tariff rates after implementing the existing EPAs would not be so much lower. Moreover, the differences in those tariff concessions are observed for both average ratios among East Asian countries and to trade partners of individual East Asian countries depending on specific trade structures.

The income gains from tariff reductions according to RCEP are also compared among ASEAN and the other six countries in Table 10. It is suggested that the ASEAN countries have already committed major tariff reductions within ASEAN and in ASEAN+1 EPAs in the past. The income gains of the ASEAN countries from existing East Asian EPAs are estimated to account for 10–70 per cent of full tariff removals. Consequently, the tariff reductions by the existing EPAs would lead to some gains in income, though not to the extent of a situation in which tariffs are fully removed. Therefore, the additional¹¹ income gains from full tariff removals would still be sizable. On the other hand, the other six countries would benefit much more from future RCEP. East Asian countries as a whole would benefit largely from future trade liberalisation in the region. In order to estimate such impacts of future EPAs, accurate baselines for tariff rates will be essential.

Figure 2

Source: Authors’ estimates and simulations.

Table 10

Income Gains from East Asian Tariff Reductions

	From 2011	Past EPAs	Additional	(% of GDP, %) Past ratio
Brunei	5.3	2.2	3.1	41.5
Cambodia	11.0	8.1	3.0	73.5
Indonesia	2.2	0.4	1.8	17.0
Laos	4.2	1.3	2.9	31.1
Malaysia	3.8	1.6	2.2	41.7
Philippines	0.9	0.3	0.5	39.6
Singapore	2.9	0.8	2.0	29.6
Thailand	6.4	0.6	5.8	10.1
Vietnam	6.1	1.3	4.8	21.3
Australia	1.6	0.1	1.5	5.2
China	0.6	0.0	0.6	3.5
India	1.6	0.0	1.6	–0.1
Japan	1.6	0.1	1.5	6.4
Korea	5.3	0.1	5.2	1.9
New Zealand	1.9	0.2	1.8	8.6

Source: Authors’ simulations.

4. Conclusion

Standard data and modelling approaches in global trade analysis do not factor in the tariff concessions that have been implemented in reality apart from the conventional FTAs. This may result in an overestimation of the macroeconomic and sectoral effects of FTAs in future. We address this problem in this article, focusing on East Asia and the Pacific: 115 out of 120 possible combinations of bilateral agreements in East Asia are already covered by EPAs that have been concluded or implemented in the past. In other words, these instances are comprised of a situation wherein tariff liberalisation has already almost completely taken place. Those East Asian EPAs have ‘substantially covered’ various commodities for tariff reductions ranging from around 80 per cent in India to 100 per cent in Singapore, Australia and New Zealand, measured in terms of tariff lines at HS 6-digit levels.

That being said, tariff reductions in East Asia vary significantly in terms of the initial and final levels of tariff rates as well as the degree of tariff cuts. By sector, the least significant declines in tariffs concern agricultural products, especially in sectors in which initial protection was the strongest. Tariff concessions in East Asian EPAs have not substantially been high enough in terms of trade-weighted average tariff rates, which would be much more effective in economics than the number of commodities.

The ratios of income gains through remaining tariff reductions according to existing East Asian EPAs, relative to those by full tariff removals, indicate that they are more or less proportional to the rates of tariff concessions in terms of average tariff rates rather than those at the tariff line levels. East Asian countries would benefit largely from future trade liberalisation in the region. In order to estimate the impacts of future EPAs, accurate baselines for tariff rates will be essential.

One serious outcome of this study is the quantification of gains from tariff reductions when we carefully apportion the effects into past reductions and future commitments. We believe that this is an important outcome and contribution to trade policy analysis and research in future. Not accounting for past tariff concessions may lead to overestimation of gains from RTAs, which is not desirable for trade policymakers.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

Footnotes

Incorporation of Tariff Concessions Data into the Gtap Data

Using the adjusted tariff dataset prepared from the ITC/CEPII MacMAP dataset, we modify the GTAP Database. This is done by using Altertax tool, which is described in Malcolm (1998). It involves the following steps:

First, we compute the shocks in power of tariffs required to modify the tariff rates in the GTAP Database into those implied in the adjusted tariff dataset. The powers of the tariffs are defined as the ratio of the value of imports at market prices (VIMS) to the value of imports at world prices (VIWS); the difference between these two values is the tariff revenue. The alternative and equivalent way of calculating the power of tariffs is (1+tariff rates). We use this method to calculate the adjusted power of tariffs.

Second, we turn to the standard GTAP model and define a closure that changes nothing much in the data other than the matrix involving the VIMS. Shocking the tariffs in the standard GTAP model closure would change a lot of prices and quantities, since this would be a tariff reduction policy exercise. Such a situation should be avoided, since we merely want to change tariff rates and nothing else in the data. This is why we use this alternative closure, which essentially fixes the ratio of change in the trade balance to income and uses unitary elasticities across the board.

Third, we run the simulation of shocks calculated in the first step within the closure defined in the second step, in the standard GTAP model. We employ the final VIMS matrix from the updated data of this simulation, to replace the VIMS in the GTAP Database for our policy simulations.

Notes

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