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BRICS vs. RCEP: A comparative study from India’s Perspective
By
MONIKA BHARDWAJ
Dr Somesh K Mathur(corresponding author)And
Rahul Arora
Department of Humanities and Social SciencesIndian Institute of Technology, Kanpur
12thMay’16
Synopsis
This research work is about working out relative benefits of India, aligning with RCEP
and BRICS, using partial equilibrium tool (SMART-Single Market Partial Equilibrium
Tool) and general equilibrium methodology using GTAP (Global Trade Analysis
Project) model. BRICS (Brazil, Russia, India, China and South Africa) is an association
of five large countries with large populations and diverse societies and abundant
resources, whereas RCEP (Regional Comprehensive Economic Partnership )is the
economic integration of 16 countries, one of largest trading bloc in the world. India
would aim to strengthen its trade relations with both the Free trade Agreements (FTAs),
which have come together in an association in a way that has far exceeded the most
expectations. By far, most of the studies have been conducted focusing on evaluating
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the impact of proposed agreements on various macroeconomic variables such as the
change in country’s GDP, welfare, tariff revenue, changes in imports and export and
change in terms of trade. This study attempts to draw comparative analysis between the
two proposed free trade agreements keeping India in mind. For this purpose, we
calculate the impact of tariff changes on trade flows (trade creation and diversion), tariff
revenues, and consumer welfare using SMART partial equilibrium modeling tools and
then further utilize the GTAP model of world trade to evaluate the impact of agreements
under static general equilibrium framework. Two simulations of different scenarios are
made, involving different stages of the FTA i.e. Reciprocal tariff liberalization and
Specialized Product liberalization. The simulation results confirm that Reciprocal tariff
liberalization would suggest India should align with RCEP as it showed better welfare
effect and increase in export-import volume in the long run, same as we get under
SMART simulation. But Full trade liberalization is an ideal case; at the start of
negotiation member country offers their list of product, for which they want to open
their market for. After categorizing those products, simulation results predicts India
would be better off joining RCEP, having improved its terms of trade and welfare.
The possible reason that we gain more under RCEP could be that the RCEP is group of
16 countries, 10 ASEAN and 6 ASEAN FTA’s partner countries, this agreement might
act as a solution for the Asian Noodle bowl problem. Having a one-mega bloc
agreement instead of multiple RTAs, CEPAs and CECAs, would create a trade between
other member countries and divert the trade from non-member countries. As the
countries are already part of one or the other agreement, it would be easy to have free
trade flow because of similar trade structures which means export can be easily
substituted by other countries import.
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Section 1: Introduction, Literature Review and BackgroundIndia considers regional trading agreements (RTAs) as “building blocks” towards the
overall objective of trade liberalization. Therefore, India aims to participate in
maximum number of RTAs, which include free trade agreements (FTAs), preferential
trade agreements (PTAs), and comprehensive economic cooperation agreements
(CECAs). Till now, India has been a part of 20 such agreements and other 40
agreements are yet to be signed being currently in negotiation phase.
BRICS is an abbreviation for Brazil, Russia, India, China and South Africa. The term
BRIC was firstly coined by Jim O'Neill, then chairman of Goldman Sachs Asset
Management, and latter in Summit held in Sanya, China in April 2011, the group was
renamed due to inclusion of South Africa with a proposal to convert themselves into
economic blocs. It Represents 26% of the planet's land mass, is home to 46% of the
world's population with 20% of the world’s economic output. Statistics says the GDP of
all BRICS states amounted to approximately 14.8 billion U.S. dollars in 2015 and they
export goods worth approximately 3 trillion U.S. dollars and import goods worth
approximately 2.8 trillion U.S. dollars in 2011. Moreover, Participation of BRICS in
global exports is more than doubled between 2001 and 2011, from 8% to 16%. Also,
between 2002 and 2012, intra-BRICS trade increased 922%, from US$ 27 to 276
billion, while between 2010-2012, BRICS international trade rose 29%, from US $ 4.7
to 6.1 trillion dollars. BRICS countries are seeking to form a strong political alliance,
thereby using this as a forum to convert their economic power into geopolitical power.
The suggestions have come up for BRICS to consider proposing a free trade agreement
at the various summits.
Regional Comprehensive Economic Partnership (RCEP) consists of 10 ASEAN
Member States and six states, which already have FTAs with ASEAN viz., Australia,
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China, India, Japan, Korea and New Zealand. The way TPP (Trans-Pacific Partnership)
captures 12 Pacific Rim countries and TTIP (Transatlantic Trade and Investment
Partnership) between EU and US, RCEP covers Asia-Pacific region as the eastern flank,
with the aim of promoting trade and multilateral economic growth between the partner
countries. The participants in the RCEP FTA negotiations have a total population of
over 3 billion people and a trade share at around 27 per cent of global trade (based on
2012 WTO figures), covering GDP of around $US21 trillion (2013 IMF figures).
Among RCEP countries, India accounts for 19-18% share of export to ASEAN + 6 FTA
partners.
RCEP would create the world’s largest trading bloc as contain three of the largest
economies in the world — China, India, and Japan. It represents 49% of the world’s
population and accounts for 30% of world’s GDP. It also makes up 29% of world trade
and 26% of world FDI inflows. RCEP was first introduced in 19 th ASEAN summit held
in Bali, Indonesia from 14th-19th November to reconcile two long stretched proposals
into one agreement: the East Asian Free Trade Agreement and the Comprehensive
Economic Partnership by adopting an open access scheme. Wherein 2011, member
countries realized the benefits associated with this agreement and on 30 August 2012
during 44th ASEAN Economic Ministers (AEMs) meeting, it was decided to start their
negotiations on trade and other economic cooperation among member countries. Since
then, there have been 11 rounds of negotiation on varied subjects, which are expected to
be finalized by 2016.
So now we have two proposed scenario: BRICS and RCEP.India has supported both the
idea from the very beginning and also been an active participant in the negotiations. The
major benefits major of getting involved in both alliances: (i) RCEP provided an
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increased presence in Southeast-East Asian markets, and (ii) BRICS helped in improved
connectivity with politically strong countries like Russia, China etc.
India is likely to join both the alliance. Many recent studies have compared the
existence of these mega blocs with India and found them advantageous for India's
economic growth. Researchers have been focusing on BRICS’s intra and extra trade
analysis in general and/or with a special focus on one of the member countries. De
Castro (2012a, b) found that BRICS countries would show the positive result for the
establishment of PTA when involved in bilateral trade between BRICS-EU using
various trade indicators. Also, Sharma and Kallummal (2012) investigated the higher
level of trade relations among BRICS and the free trade agreement (FTA) using the
GTAP model and found that with the removal of the import tariffs, the scenario would
have an overall more or less positive effect on welfare and macroeconomic indicators
for all BRICS. Further extending the FTA scenario, L. S Sharma (2012) evaluated food
and agricultural trade liberalization for BRICS countries with two growing nations of
South Korea and Mexico to see the economic and welfare impacts and found that Brazil
and China are the main gainers with this liberalization. BRICS economies have already
been strengthening their positions in the current global world for a decade now and have
been justifying their existence. A very recent paper by Songfeng CAI (2015), which
uses GVC (Global Value Chain) based CGE model to asses the impact of TIPP on
BRICS economies and indicated BRICS countries would suffer small negative impacts
due to TIPP with improvement in inter country trade due to substitution effect between
the US –EU trade and the imports from BRICS countries when the TTIP commences.
Similarly, there have been studies of traditional bilateral trade relations and already
existing integration groups such as the analysis of ASEAN and its bilateral trade
intensity with India and ASEAN + 3 (China, Japan, and Korea) discussed by
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Chandran(2010) and Kim (2002), respectively. Literature by Biswajit Nag and
ChandrimaSarkar(2011) have analyzed the impact of India-ASEAN FTA following
the phased liberalization to assess the possible direction chosen by major
macroeconomic variables through their constant interaction under open trade regime.
The study signaled that this agreement would increase the trade diversion and many
countries would loose market share in India and in long run India would gain in
allocative efficiency but remain negative in terms of trade. RanjanSudeshRatna(2014)
investigated regional integration between South Asia and ASEAN and found that
ASEAN would have maximum welfare gain from this liberalization. Rahul
Arora(2015) concluded that under RCEP partnership scenario, India would gain
maximum in terms of trade and would have a positive welfare effect resulting into
increase in India's import from member countries and decline from nonmember
countries using GTAP simulation. Most of the researchers have done a huge amount of
work in analyzing Free trade agreements with ASEAN, which further create a
motivation to find the implication of RCEP’s on Indian Economy.
Although, these past pieces of literature do not address our question of interest i.e.which
alliance would be more beneficial from India's Perspective? So,the main objective of the
present study is to investigate which free trade agreement would bring greater economic
benefit to Indian Economy.This study will involve the use of SMART and GTAP model
to understand trade shifting and trade generation in trade liberalization policy.To pursue
this task, the present study has been divided into six chapters including the present
introductory one. In section 2, India’s Trade relationship with proposed trade
agreements arepresented and discussed. section 3 explains briefly about the SMART
analysis along with basics of GTAP model of trade and the implications of tariff
reforms on various macroeconomic variables. In Section 4, data aggregations and
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simulation scenario have been presented for the purpose of general equilibrium analysis.
section 5 explains the simulation results with interpretation. Section 6 concludes the
whole study. The final chapter discusses the further possibilities of this work.
Section 2 :India’s Traderelation with BRICS and RCEP MembersFor India, BRICS member states provide them great opportunity to share its
development experiences and thereby expand south –south Cooperation. BRICS also act
as a forum to stabilize the regional environment by neutralizing China in soared issues
between India and Pakistan. Through this partnership, India would like to strengthen
their terms with Russia to expand trade; investment and technology flow between the
two countries. And with Brazil, India already share a unique arrangement that has
attracted international attention.
On other hand, India has already been engaged under regional trade agreements with
member countries of RCEP. India has also signed individual agreements with most of
the ASEAN countries like India- Singapore CECA, India – Malaysia CECA, India
Thailand FTA, and India – South Korea-japan CEPA. It has become Asian Noodle bowl
due to large number of FTAs in Asia.
2.1 Tariff Profile of BRICS and RCEP Members
Tariff profile of any region depicts the level of protection of that region over the traded
products. The amount of own tariffs and non-tariffs barriers a country imposes on
imports from partner countries determines a country’s level of protection. It is
calculated by evaluating the year-wise average tariff rate over all the products. Table
shows various indicators of level of protection of all BRICS and RCEP member
countries to all other partner countries of the world. If the level of trade between the
member countries is very high then the gains associated with regional trade agreements
are highly depends upon the level of protection of member countries. Higher level of
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initial protection would lead to larger gains afterwards.
It is observed that India and Brazil have the highest average MFN applied tariff rate
among all BRICS and RCEP member countries. Reduction in this rate would lead to
larger economic benefits for all the partner countries. As we are considering reciprocal
tariff reduction by its partner country from BRICS and RCEP both that would further
improve the chances of benefits related to trade liberalization.
Table: Indicators of level of Protection in RCEP Member Nations
Member Country Year
AVE MFN Applied Tariff (%) (HS-6 digit Duty Averages)
Share of Duty Free HS-6 digit Subheadings
Share of HS-6 digit Subheadings Subject to Non-AV Duties
Share of HS-6 digit Subheadings With AVEs >15
Maximum Duty (%) (Ad Valorem)
Number Of MFN Applied Tariff Lines
Australia 2014 2.7 50.3 0.2 0.1 153 6185
China 2014 9.6 7.9 0.4 14.2 65 13069
India 2014 13.5 3 4.9 18.8 156 11471
Japan 2014 4.2 53 3.3 3.6 783 9610New Zealand 2014 2 63.9 0.4 0 45 7510
South Korea 2014 12.1 15.7 0.4 8.3 887 11938
Brunei 2014 1.2 83.2 0.3 1.1 155 9915
Cambodia 2014 11.2 15.6 0 10.1 35 9557
Indonesia 2014 6.9 12.7 0.5 1.7 150 10011
Laos 2014 10 0 0.2 14.5 40 9557
Myanmar 2014 5.6 3.9 0 5 40 9820
Phillipines 2014 6.3 3.4 0 3.6 65 10276
Singapore 2014 0.2 100 0 0 948 9557
thailand 2014 11.6 20.6 9.3 25.9 258 9564
Vietnam 2014 9.5 35.5 0 24.6 135 9557
Brazil 2014 13.5 5.9 0 36.2 55 10030
Russia 2014 8.4 14.3 9.8 8.8 278 11673South Africa 2014 7.6 61.5 2.6 20.6 642 7308
Source: World tariff profiles, 2014
2.2 Preliminary Analysis through Trade indicators
To benchmark trade policy and performance, we use wide-ranging database and
innovative ranking tool designed based on some statistical ratios known as trade
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indicators to examine country’s performance individually as well as in relation to other
countries or country grouping, (by region, income group, trade agreement or other user-
defined group). The study has calculated four such trade indices to assess the impact of
both the potential trade agreement on India. Those indicators are the Revealed
Comparative Advantage index (RCA), Trade Intensity Index (TII), Indicator of
similarity in merchandise trade structures (Grubel-Lloyd (1975)) and Trade
complementarity index (Michaely’s working paper (1996)). Thestudy employ data of
export and import from the World Integrated trade Solution (WITS) and UNCTAD
Database over HS2007 classification and SITC, Revision 3 level respectively.
Table 2.1 and 2.2 used Revealed Comparative Advantage (RCA) Index and Trade
Intensity Index (TII) to see trade complementarity and Similarity between India- BRICS
and India-RCEP countries. The RCA index of country i for product j is often measured
by the product’s share in the country’s exports in relation to its share in world trade:
RCA ij =
x ij
X ¿
xwj
X wt
Where xij and xwj are the values of country i’s export of product j and world exports of
product j and where Xit and Xwt refer to the country’s total exports and world total
exports. If the index exceeds unity, the country is said to have a revealed comparative
advantage in the product. Similarly, value of less than unity implies that the country has
a revealed comparative disadvantage in the product. As per the Table 2.1, you can see
India and China have the value above 1, means with comparative advantage and rest
who are below 1 will show comparative disadvantage. Countries with comparative
advantage over product will export the product to the countries with comparative
disadvantage, creating continuous trade flow between the member countries.
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Similarly, from Table 2.2, you can see the RCA for Animal is above one for India,
Australia and New Zealand and below one for rest partner countries. This means there is
a scope to trade between India and low RCA countries of RCEP such as Brunei,
Cambodia and Singapore etc. The RCA showed that RCEP countries namely Malaysia,
Indonesia, Brunei, Singapore, India and Australia are having a strong RCA of fuels. But
Thailand, japan, china, Korea got a very low RCA in it and Australia is the only nation
having a comparative advantage in case of minerals. Fuel and Mining are resource-
based products depending on the natural endowments of the country. India has
comparative advantage over Animal, Vegetables, Fuels, Hide skin, Textile clothing,
Foot wear and metals. It shows comparative disadvantage only for categories like Food
production, Plastic- Rubbers, Wood, Machine etc. which increases the chances of trade
with Indonesia, Singapore, Thailand and New Zealand for Food production category,
with Japan, Korea, Malaysia, Indonesia, Singapore and Thailand for Plastic rubbers
product category.
TII index uses similar logic to that of revealed comparative advantage, but for markets
rather than products. It indicates whether a reporter exports more, as a Percentage, to a
partner than the world does on average. It is measured as country i's exports to country j
relative to its total exports divided by the world’s exports to country j relative to the
world’s total exports. A value greater than 100 indicates a relationship more intense
than the world average for the partner.
TII¿100∗
x ijk
X ik
xwkj
Xwk
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Where x is the value of exports of product k from origin country i to destination j, and X
is total exports from i of product k; w indicates the world as origin. However, as for TI
index, Table 2.1 shows Brazil have great trade intensity for the sectors like Animal,
Vegetables, Food Productions, Fuels, Textile Clothing and Woods. India would export
Fuels, textile clothing, Footwear to countries with low trade intensities countries like
South Africa and China. Similarly, Table 2.2 shows Malaysia is main exporter of almost
all products and India is only on Animal, Minerals, Chemicals, Metals and Transport
markets. Similarly, Indonesia will export the products to the countries that have low
trade intensity for those products. It shows how the member countries’ markets are
interdependent and will increase this dependence after the FTA.
The product with comparative advantage and high trade intensity can play significant
role in enhancing the trade between partner countries. So, in Table 2.1 products such as
Animals, Vegetables, Food production and Woods for Brazil, Fuels, textile clothing,
Footwear and Metals for India, wood for Russia, Footwear for china Minerals and
Metals for South Africa have comparative advantage with high Trade intensity whereas
in Table 2.2 such products for Malaysia are: Vegetables, Fuels, Wood, and Plastic-
Rubber, for Indonesia: Vegetables, Food Production, Fuels, Textile clothing, for Brunei:
Fuels, for Singapore: Fuels, Chemicals, Machine etc,
Furthermore, the study evaluate indicator for similarity in merchandise trade structures
and complementarity index (CI) to find trade prospect between the partners for both
proposed FTA. Similarity indicator helps to determine whether the trade structures of
two economies are similar or not and CI measures to what extent the export profile of
country (or country group) j matches the import profile of country (or country group) k,
the trade partner of country j.
Similarity Index:
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Sij = 1- 12∑i
¿hij−h ik∨¿
Complementarity index:
Se j mk=1−∑
i¿ Eij−M ik∨¿
2¿
Where,
Sjk = Indicator of similarity in merchandise trade structures
hij = Share in total merchandise exports or imports of product i of country or country
group j
hik = Share in total merchandise exports or imports of product i in country or country
group k
Sejmk = the index of trade complementarity of exporter j with importer k
i = goods in 3 digit SITC Revision 3
j = exporter (country or country group)
k = importer (country or country group)
Eij = the share of goods i in country j’s total exports to the world
Mik = the share of goods i in country k’s total imports from the world
If the SI value lies closer to 1 reveals the greater similarity of the trade structure
between two countries or two groups of countries and if CI values range from 0 to 1
with 0 indicating that there is no correspondence between country j's export structure
and country k's import structure and 1 indicating a perfect match in their export/import
pattern. Table 2.3 and 2.4 illustrates that the partners can use their comparative
advantage to gain further by exporting more to the world together. The countries with
more than 50% of exports will be similar to the world. Say, in table 2.3 Brunei and
Cambodia exports are coming out to be 50% of both countries, will appear similar to
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world. Table 2.5 and 2.6 illustrate that the countries with higher CI will represent good
prospect of trade. As in case of BRICS, Russia and South Africa comes out to be
around 0.5, implying greater trade exports.
Table 2.1: RCA and TII for BRICS with major commodities Brazil India Russia China S A
Product RCA TII RCA TII RCA TII RCA TII RCA TII
Animal 3.83 180.36 1.71 28.08 0.33 281.69 0.39 38.72 0.6 21.99Vegetable 5.26 283.57 2.15 30.92 0.67 18.71 0.29 36.79 1.65 25.99
FoodProd 3.66 170.9 0.65 54.98 0.33 27.55 0.39 76.44 1.39 45.73
Minerals 9.21 98.16 0.75 93.64 0.67 59.64 0.13 12.71 9.57 113.58
Fuels 0.71 283.54 1.52 126.15 5.39 81.36 0.11 35.27 0.82 232.64
Chemical 0.58 43.72 1.21 89.71 0.49 143.44 0.53 118.92 0.73 59
PlastiRub 0.57 34.62 0.59 69.78 0.26 69.47 0.89 54.7 0.55 57.32
HidesSki 2 178.4 1.82 39.48 0.12 24.02 2.21 89.19 0.72 96.63
Wood 1.83 165.26 0.25 24.15 1.03 239.91 0.73 46.5 1.07 157.89TextCloth 0.27 166.84 2.87 113.54 0.04 36.63 2.9 80.69 0.33 200.91
Footwear 0.66 39.35 1.25 102.03 0.06 4.15 3.59 118.64 0.32 13.35StoneGlas 0.43 41.32 2.82 5.96 0.54 48.81 0.98 20.1 3.29 10.88
Metals 1.03 68.06 1.16 104.81 1.17 17.31 1.13 69.44 1.88 162.32MachElec 0.3 26.74 0.29 48.41 0.11 114.71 1.67 34.92 0.41 21.32
Transport 0.72 37.69 0.82 86.53 0.12 39.61 0.45 57.58 1.07 18.98
Miscellan 0.34 15.29 0.19 56.88 0.29 29.56 1.02 52.4 0.2 12.35Source: WITS
Table 2.2: RCA and TII for RCEP with major commoditiesMal Indo Bru Sin Tha Ind
Product RCA TII RCA TII RCA TII RCA TII RCA TII RCA TII
Animal 0.31 312.85 0.96 217.78 0.04 415.55 0.2 360.99 0.71 267.25 1.71 243.21
Veg 2.27 161.55 4.4 122.27 0.02 465.65 0.32 236.3 1.57 237.51 2.15 77.98
FoodPro 0.9 414.66 1.15 320.58 0.08 609.07 2.11 480.44 2.51 318.24 0.65 96.34
Minerals 0.33 158.8 0.83 105.28 0.01 184.6 0.03 151.95 0.36 143.86 0.75 105.8
Fuels 1.71 391.16 2.24 322.29 7.15 360.61 16.76 391.98 0.41 445.74 1.52 93.8
Chemical 0.58 351.92 0.69 343.89 0.5 199.16 9.28 284.16 0.61 426.93 1.18 108.53
PlastiRub 1.41 271.64 1.26 196.09 0.02 457.17 4.34 354.09 2.79 305.55 0.59 79.11
HidesSki 0.09 308.62 0.38 124.05 0.02 435.91 0.22 232.72 0.71 213.97 1.81 62.19
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Wood 1.05 273.88 2.44 279.49 0.02 392.23 1.93 336.67 0.76 339.77 0.25 51.03
TextClot 0.34 228.69 1.7 123.38 0.02 107.64 0.54 281.93 0.78 218.44 2.86 77.62
Footwear 0.09 591.41 3.01 143.48 0 759.1 0.27 216.59 0.46 211.23 1.24 82.76
StoneGla 0.4 261.53 0.65 240.32 0.01 560.71 2.11 137.96 1.09 146.71 2.82 30.56
Metals 0.7 296.12 0.75 377.44 0.07 494.46 2.76 326.14 0.62 311.61 1.14 109.69
MachElec 1.52 202.16 0.36 231.7 0.04 299.57 43.64 199.38 1.22 172 0.29 74.91
Transpor 0.13 373.61 0.32 396.27 0.03 649.77 2.9 345.21 1.18 383.01 0.77 105.81
Miscellan 0.62 249.24 0.28 197.74 0.06 454.93 12.58 158.84 0.43 244.86 0.21 97.24
Table 2.2: RCA and TII for RCEP with major commoditiesAus Chi Jap Kor New
Product RCA TII RCA TII RCA TII RCA TII RCA TII
Animal 3.14 248.17 0.39 142.91 0.11 250.63 0.15 374.8 22.38 247.3
Vegetable 1.7 199.95 0.29 202.88 0.04 120.42 0.05 284.82 1.71 222.01
FoodProd 0.58 322.75 0.39 243.87 0.13 120.08 0.26 366.43 2.83 379.59
Minerals 21.77 158.67 0.13 52.1 0.09 103.08 0.09 100.36 0.1 50.61
Fuels 2.05 196.4 0.11 201.96 0.18 250.8 0.71 376.83 0.24 481.65
Chemicals 0.5 148.1 0.52 149.59 0.87 229.39 0.77 386.94 0.53 273.77
PlastiRub 0.1 297.69 0.88 97.12 1.24 195.54 1.59 228.99 0.24 315.63
HidesSkin 0.74 362.81 2.2 69.76 0.06 254 0.37 266.6 1.82 191.71
Wood 0.47 256.63 0.72 121.12 0.26 293.06 0.27 223.98 4.29 386.31
TextCloth 0.43 412.77 2.89 124.96 0.29 307.69 0.64 297.41 0.65 370.01
Footwear 0.04 396.77 3.58 129.21 0.03 224.09 0.14 630.54 0.13 631.83
StoneGlas 1.16 422.33 0.98 66.19 0.53 191.39 0.22 257.6 0.35 483.7
Metals 0.76 348.71 1.12 135.99 1.32 251.89 1.24 256.42 0.55 296.29
MachElec 0.14 168.75 1.66 70.41 1.37 160.82 1.41 209.94 0.2 190.72
Transport 0.18 183.36 0.42 151.4 2.2 155.4 1.87 128.66 0.1 376.53
Miscellan 0.5 83.42 1.16 110.16 1.44 214.64 0.83 364.4 0.66 182.32Source: WITs
Table 2.3: Indicator for similarity in merchandise trade structures in RCEPRCE Aus Bru Cam Chi Ind Indo Jap Mal Mya New Phi Sin Sou Tha
Aus 1.00 0.38 0.23 0.13 0.22 0.40 0.22 0.25 0.23 0.30 0.27 0.18 0.42 0.19
Bru 0.38 1.00 0.50 0.02 0.03 0.28 0.25 0.16 0.41 0.06 0.32 0.03 0.12 0.04
Cam 0.23 0.50 1.00 0.19 0.19 0.35 0.08 0.16 0.35 0.25 0.14 0.08 0.13 0.19
Chi 0.13 0.02 0.19 1.00 0.40 0.34 0.45 0.44 0.11 0.18 0.44 0.38 0.24 0.53
Ind 0.22 0.03 0.19 0.40 1.00 0.33 0.35 0.33 0.24 0.23 0.28 0.44 0.33 0.45
Indo 0.40 0.28 0.35 0.34 0.33 1.00 0.28 0.49 0.30 0.26 0.39 0.21 0.28 0.37
Jap 0.22 0.25 0.08 0.45 0.35 0.28 1.00 0.40 0.09 0.21 0.41 0.46 0.35 0.51
Mal 0.25 0.16 0.16 0.44 0.33 0.49 0.40 1.00 0.17 0.22 0.56 0.57 0.23 0.50
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Mya 0.23 0.41 0.35 0.11 0.24 0.30 0.09 0.17 1.00 0.24 0.29 0.08 0.21 0.14
New 0.30 0.06 0.25 0.18 0.23 0.26 0.21 0.22 0.24 1.00 0.24 0.19 0.28 0.25
Phi 0.27 0.32 0.14 0.44 0.28 0.39 0.41 0.56 0.29 0.24 1.00 0.54 0.32 0.44
Sin 0.18 0.03 0.08 0.38 0.44 0.21 0.46 0.57 0.08 0.19 0.54 1.00 0.30 0.47
Sou 0.42 0.12 0.13 0.24 0.33 0.28 0.35 0.23 0.21 0.28 0.32 0.30 1.00 0.41
Tha 0.19 0.04 0.19 0.53 0.45 0.37 0.51 0.50 0.14 0.25 0.44 0.47 0.41 1.00
Source: UNCTAD
Table 2.4: Indicator for similarity in merchandise trade structures in BRICSBRICS Brazil China India Russia South AfricaBrazil 1 0.230767008 0.355415096 0.260704941 0.393789477China 0.230767008 1 0.398460454 0.137202011 0.237402166India 0.355415096 0.398460454 1 0.38143857 0.333854366Russian Federation 0.260704941 0.137202011 0.38143857 1 0.261218822South Africa 0.393789477 0.237402166 0.333854366 0.261218822 1Source: UNCTAD
Table 2.5: Trade complementarity index of RCEPExporters ASEAN Australia China India Japan Korea New Zealand
Australia 0.3 - 0.4 0.3 0.4 0.3 0.2
China 0.5 0.5 - 0.3 0.5 0.4 0.5
India 0.5 0.5 0.3 - 0.4 0.5 0.4
Japan 0.5 0.5 0.5 0.4 - 0.5 0.4Source: UNCTAD
Table 2.6: Trade complementarity index of BRICSExporters Importers Index
India Brazil 0.4
China 0.3
Russia 0.5
South Africa 0.5Source: UNCTAD
Section 3: MethodologyThe main objective of the study will be to compare the impact of India-RCEP and India-
BRICSproposed FTA on India. The study will work out to understand economic and
welfare effects of trade liberalization using the partial (SMART) and general
equilibrium (GTAP) approaches. The study will also evaluate the trade indicators of all
member nations and its specialized products using UN Commodity Trade Statistics data
in WITS.
3.1 SMART Analysis: A Partial Equilibrium Tool
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SMART tool in WITS allows to investigateconsequences of changes in tariff because of
unilateral/preferential/multilateral trade reforms at domestic level or abroad on various
variables such as trade flows (imports and exports volumes, trade creation and trade
diversion), tariff revenue, economic welfare and world prices. It assumes that products
from different countries are imperfect substitutes by automatically set import demand
elasticity equal to 1.5. On the other hand, it assumes infinite export elasticity, that is,
export supplies are perfectly elastic which implies that world prices of each variety of
products are given. Specialized products of India, RCEP and BRICS would be worked
out using trade indices like Revealed Comparative Analysis and further used for
simulations under different tariff reduction scenarios. Trade Creation and Trade
Diversion formulae entails use of import demand elasticities, export supply elasticities
and elasticities of substitution.
3.1.1 The SMART Model
The assumptions of the SMART model are:
Armington assumption: Products imported from different countries are
imperfect substitutes i.e., carrot from Brazil are an imperfect substitute to carrot
from China
No Income Effects: Changes in tariffs will directly affect the changes in prices
and benefits of tariff change will directly pass onto the consumer in terms of
price change.
Export supplies are perfectly elastic as world prices of each variety are given.
Reporter country assumed to be small to affect prices of tradable commodity.
By looking at the demand structure of SMART model and on the basis of above
assumptions, Jammes and Olarreaga (2005) defined an additive utility function (U), also
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quasi linear, which is additive of consumption of aggregate import good (mk) and
composite numeraire good (n). The utility function is given as:
U =∑k
uk (mk )+n…(1)
Maximization of utility function given in (1)subject to budget constraint yields the
demand function for the imported good and composite numeraire good (n) as:
mk , j=f ( pk , jd ; pk ,≠ j
d ) ,∀ k , j… (2)
n= y−∑j∑
kpk , j
d mk , j …(3)
Where, mk , j are the imports of good k from country j; pk , jd and pk , ≠ j
d are the domestic
prices of good k imported from country j and from all other countries other than j
respectively; and y is national income of the country.
Further, the domestic price of the imported good k from country j ( pk , jd ) can be obtained
by adding the effect of tariffs imposed (t k , j) on its imports in the world price of good k
is given as:
pk , jd =pk , j
w (1+t k , j )… (4 )
And the preference tariff imposed on imports of good k imported from country j is
defined as:
t k , j=t kMFN (1−θk , j ) …(5)
Where, t kMFN is the Most Favored Nation (MFN) tariff imposed on good k, and θk, j is the
tariff preference ratio on good k when imported from country j and defined as:
θk, j=1−t k , j
tkMFN
On the basis of above specifications, the model provides the results on four main
effects: Trade; Welfare; Revenue effect to the importer; and revenue effect to the
exporter. Following sub-sections present these four effects in detail.
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3.1.1.1 Trade Effect
Total trade effects in SMART include the quantity and price effects of trade. Quantity
effect further composed of trade creation and trade diversion effect. The sum total of
trade creation, trade diversion and price effect is known as trade effect in SMART.
A) Trade Creation Effect
After the reduction of tariffs on imported product, an increase in domestic
demand for imports in the importing country due to reduction in price of imports
is known as trade creation. In the SMART model, the whole benefit of reduction
in tariffs is fully enjoyed by the consumer in terms of price reduction. This effect
is shown by the direct increase in imports after the reduction of tariffs imposed
on the imports coming from the member exporter. To obtain this effect, SMART
uses the concept of price elasticity of import demand (ε k , j) given as follows:
ε k , j=dmk , j /mk , j
dpk , jd / pk , j
d <0 …(6)
By solving (6) for dmk , j will provide the trade creation effect in terms of change
in imports of product k from country j. In terms of values, trade creation effect
evaluated at world prices can be expressed as:
TC k , j=pk , jw dmk , j= pk , j
w ε k , j mk , jdpk , j
d
pk , jd …(7)
Further, using expression (4), one can also show the impact of change in tariff
on imports given as:
dpk , jd =pk , j
w dtk , j Using (4)
Substitute the above expression into (7.7) provides the final expression of trade
creation given in (8).
TC k , j=pk , jw dmk , j= pk , j
w ε k , j mk , j
dtk , j
1+t k , j=εk , j mk , j
dt k , j
1+t k , j…(8)
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Finally, to obtain the overall level of trade creation, one can simply sum the
expression (8) across goods or countries as per the requirement of the analysis.
Trade creation across countries for a single product k would be:
TC k=∑j
TC k , j
Trade creation across all goods from an exporter j would be:
TC j=∑k
TC k , j
The Overall level of trade creation would be:
TC=∑k∑
jTC k , j
B) Trade Diversion Effect
It occurs when an importer starts importing a product from the member
importing country, which it is previously importing from non-member country.
The reason of this substitution is the decrease in price of imports from member
country due to the preferential treatment, which is not given to the non-member
countries. This effect shows the amount of diverted trade from non-member
country to member country after the adoption of tariff reduction policy in a
preferential trading arrangement. The positive trade diversion shows the
diversion of the trade from non-member to the member country. SMART model
uses the concept of elasticity of substitution of imports between member country
and non-member countries (σ k , j ,≠ j). As per the formula,
σ k , j ,≠ j=
d ( mk , j
mk ,≠ j)/ mk , j
mk , ≠ j
d ( pk , jd
pk ,≠ jd )/ pk , j
d
pk ,≠ jd
<0 …(9)
By using (4), the denominator of above expression (9) can be replaced with the
final expression of (10) as:
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d ( pk , jd
pk ,≠ jd ) / pk , j
d
pk ,≠ jd =
pk , jw dtk , j
pk ,≠ jw (1+t ¿¿k , ≠ j)
pk , jw (1+t¿¿ k , j)
pk ,≠ jw (1+t ¿¿k ,≠ j)
=pk , j
w dtk , j
pk , jw (1+t ¿¿k , j)=
dt k , j
(1+t¿¿k , j)…(10)¿¿¿¿
¿
And the simplification of numerator of (9) will provide the following:
d ( mk , j
mk ,≠ j)=mk , ≠ jd mk , j−mk , j d mk ,≠ j
mk , ≠ j2 =
d mk , j
mk ,≠ j−
mk , jd mk ,≠ j
mk ,≠ j2
Further, by following the theory of trade diversion, the increment in imports
must be equal to the decrease (diverted) in imports from non-member countries
to which preferential access is not granted and are given as:
dmk , j=−dmk , ≠ j
And the numerator of equation (9) becomes:
d ( mk , j
mk ,≠ j)=d mk , j ( mk , j+mk , ≠ j )
mk ,≠ j2 …(11)
By substituting (10) and (11) into (9), we get the expression for trade diversion
in terms of change in imports (d mk , j) as:
TDk , j=d mk , j=mk , ≠ jmk , j
mk ,≠ j+mk , j
dt k , j
1+t k , jσ k , j ,≠ j… (12)
There is an upper limit on the value of trade diversion because as per the
definition of trade diversion, the diverted trade cannot be greater than the actual
trade previously existed between member and non-member countries. In this
model, SMART uses the following expression for trade diversion by adding one
more term in the denominator of the actual formula for calculating trade
diversion in (12).
TDk , j=d mk , j=−dmk ,≠ j=mk, ≠ jmk , j
dt k , j
1+t k , jσ k, j , ≠ j
mk , ≠ j+mk , j+[mk , jdt k , j
1+t k , jσ k , j , ≠ j]
…(13)
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When the added term in (13) tends to infinity then the value of trade diversion
would be same as total imports from countries other than j. The above logic is
not free from the criticisms as it clearly shows an underestimation of the trade
diversion effect for small changes in tariffs1. Also in case when all the tariffs
would be eliminated then the term in the numerator of the bracketed term
(change in tariffs) would be t k , j which is not separately mentioned in the
SMART formulation. Because of these criticisms, Jammes and Olarreaga (2005)
suggested to use the simple way of introducing the constraint on the value of
trade diversion given in (7.14).
TDk , j=d mk , j=−dmk ,≠ j={ mk ,≠ jmk , j
mk ,≠ j+mk , j
dt k , j
1+t k , jσ k , j ,≠ jif −dmk ,≠ j ≤ mk , ≠ j
mk ,≠ j if −d mk ,≠ j>mk ,≠ j
… (14)
C) Price Effect
With the assumption of infinite export supply elasticity, price effect would be
zero because the exporter is ready to supply as much as the importer demands at
the world price existing in the economy for that particular product. In other
words, the exporter can easily meet increased demand for exports in the
importing country and there will be no effect on prices. However, in case when
export supply elasticity is inelastic then it will have a positive impact on prices
received by the exporter to compensate the increased demand from the
importer(s), which arises due to decrease in importing price because of tariff
reduction. In this case, price effect arises and adds to the total trade effect.
Mathematically, price effect can be obtained by calculating the change in world
1 For a small change in tariffs, the bracketed term will not tend to infinity, which results in larger
denominator than actual and led to underestimation of trade diversion.
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prices (pk , jw ) of import of good k coming from country j through the expression
of export supply elasticity given as:
μk , j=
dxk , j
xk , j
dpk , jw
pk , jw
>0 … (15)
Solving the above expression of export supply elasticity for change in world
prices of commodity k coming from country j will provide the price effect for
the SMART model.
dpk , jw =
dxk , j
xk , j
μk , j
pk , jw
With the assumption of normalization of initial world prices at one, the above
expression can be written as:
dpk , jw =
dxk , j
xk , j
μk , j…(16)
By using (4), domestic prices become:
d pk , jd = pk , j
w dt k , j+dpk , jw (1+ tk , j ) …(17)
And the price effect can be written as:
d pk , jd
pk , jd =
dtk , j
(1+t k , j)+dpk , j
w
Using (16), the price effect becomes:
d pk , jd
pk , jd =
dtk , j
(1+t k , j)+
dmk , j
mk , j
1μk , j
…(18)
Where, dmk , j is the value of trade creation arrived under the assumption of
inelastic export supply elasticity which is derived using the results given in (16)
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and (17).Hence, the formulas for trade creation and trade diversion, given in (8)
and (13) will alter and derived in following sub-sections.
Trade Creation with inelastic export supply elasticity: As per the definition of
trade creation given in (7):
dmk , j=εk , jmk , jdpk , j
d
pk , jd
dmk , j=εk , jmk , j
pk , jw dt k , j+dpk , j
w (1+ tk , j )pk , j
w (1+t k , j )
dmk , j=εk , jmk , j( dtk , j
(1+t k , j)+
dpk , jw
pk , jw )
From (17)
dmk , j=εk , jmk , j( dtk , j
(1+t k , j)+
dxk , j
xk , j
μk , j)
As per the partial equilibrium condition, mk , j=xk , j anddmk , j=dxk , j
dmk , j
mk , j=εk , j
dt k , j
(1+t k , j )+
εk , j
μk , j
dmk , j
mk , j
dmk , j
mk , j(1−
ε k , j
μk , j)=ε k, j
dt k , j
( 1+ tk , j )
TC k , j=dmk , j=ε k , j mk , jdtk , j
1+t k , j ( 1
1−εk , j
μk , j)… (19)
The expression in (19) above shows that if export supply elasticity is perfectly
elastic (i.e., infinite), then it becomes equal to the old expression of trade
creation given in (8). On the other hand, with finite export supply elasticity, the
bracketed term of (19) becomes less than one, which reduces the change in
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quantity of imports due to increased world price of good k coming from country
j.
Trade Diversion with inelastic export supply elasticity: Recalling the definition
of trade diversion from (9):
σ k , j ,≠ j=
d ( mk , j
mk ,≠ j)/ mk , j
mk , ≠ j
d ( pk , jd
pk ,≠ jd )/ pk , j
d
pk ,≠ jd
<0
Using (11) for the numerator:
d ( mk , j
mk ,≠ j)=d mk , j ( mk , j+mk , ≠ j )
mk ,≠ j2 …(11)
And alter the (10) for denominator using (17) as:
d ( pk , jd
pk ,≠ jd ) / pk , j
d
pk ,≠ jd =
pk ,≠ jd dpk, j
d −pk , jd dpk ,≠ j
d
( pk ,≠ jd )2
pk , jw (1+t¿¿ k , j)
pk ,≠ jw (1+t ¿¿k , ≠ j)
¿¿
Assuming initial world prices are equal to 1, we get
d ( pk , jd
pk ,≠ jd ) / pk , j
d
pk ,≠ jd =
dpk , jd
pk ,≠ jd −
pk , jd dpk ,≠ j
d
( pk , ≠ jd )2
(1+t ¿¿k , j)(1+t¿¿k ,≠ j)
¿¿
Before trade policy change, it is assumed that all countries face same level of
tariffs which implies t k , j = t k ,≠ j due to which denominator becomes 1.
d ( pk , jd
pk ,≠ jd ) / pk , j
d
pk ,≠ jd =
dpk , jd
pk ,≠ jd −
pk , jd dpk ,≠ j
d
( pk ,≠ jd )2
Using 17), we get
d ( pk , jd
pk ,≠ jd ) / pk , j
d
pk ,≠ jd =
pk , jw dtk , j+dpk , j
w (1+t k , j )pk ,≠ j
w (1+t k ,≠ j )−pk , j
w ( 1+ tk , j )pk ,≠ j
w dtk , ≠ j+dpk , ≠ jw (1+t k ,≠ j )
( pk ,≠ jw (1+t k ,≠ j ))
2
24
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With dt k ,≠ j=0∧pk , ≠ jw =pk , j
w =1
d ( pk , jd
pk ,≠ jd ) / pk , j
d
pk ,≠ jd =
dt k , j+dpk , jw (1+t k , j )
(1+t k ,≠ j )−dpk , ≠ j
w …(20)
d ( pk , jd
pk ,≠ jd ) / pk , j
d
pk ,≠ jd =
dt k , j
(1+t k ,≠ j )+dpk , j
w −dpk ,≠ jw
Using (16)
d ( pk , jd
pk ,≠ jd ) / pk , j
d
pk ,≠ jd =
dt k , j
(1+t k ,≠ j )+
dxk , j
xk , j
μk , j−
dxk ,≠ j
xk ,≠ j
μk , ≠ j
Since dxk , j=−dxk ,≠ jand dmk , j=−dmk , ≠ j , therefore
d ( pk , jd
pk ,≠ jd ) / pk , j
d
pk ,≠ jd =
dt k , j
(1+t k ,≠ j )+dxk , j( 1
xk , j μk , j+
1xk ,≠ j μk ,≠ j )…(21)
By substituting (7.21) and (7.11) and solving for change in imports (dmk , j) will
provide us the trade diversion effect as follows:
TDk , j=d mk , j=mk , ≠ jmk , j
mk ,≠ j+mk , j
dt k , j
1+t k , jσ k , j ,≠ j [ ( mk , j+mk , ≠ j ) μk , j μk ,≠ j
(mk , j+mk ,≠ j ) μk , j μk ,≠ j−mk , j μk , j−mk ,≠ j μk ,≠ j ]…(22)
The above new expression for trade diversion shows that in case export supply
elasticities are infinitely elastic then (22) becomes (12).
One interesting case becomes in which export supply elasticity of rest of the
world is infinitely elastic but the same of partner country is not then (22)
becomes (23) as follows.
TDk , j=dmk , j=mk , ≠ jmk , j
mk ,≠ j+mk , j
dt k , j
1+t k , jσ k , j ,≠ j [ (mk , j+mk ,≠ j ) μk , j
(mk , j+mk ,≠ j ) μk , j−mk , ≠ j ]…(23)
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3.1.1.2 Tariff Revenue Effect
In the SMART model, change in tariff revenue can be easily calculated using the
following formula:
dTRi=TRiPost−TRiPre …(24 )
TRi0=∑
kt k , j
0 ( pk , jw mk , j
0 ) …(24 A)
TRi1=∑
ktk , j
1 ( pk , jw mk , j
1 ) …(24 B )
Where, TRi0 and TRi
1 are the total tariff revenues incurred by the importing country (i)
before and after the change in trade policy; t k , j0 and t k , j
1 are the tariff rates before and
after trade policy shock; and ( pk , jw mk , j
0 ) and ( pk , jw mk , j
1 ) are the value of imports before and
after the trade policy change at world prices.
3.1.1.3Welfare Effect
The net welfare effect is estimated by multiplying the change in imports with the
average between the incidence of tariff barriers before and after their change (Laird and
Yeats, 1986).
w k ,i=0.5 ( dt k , j × dmk , j ) …(25)
Generally, welfare effect is defined as the sum of producer and consumer surplus in the
economy due to the adoption of tariff reduction policy. With the infinite export supply
elasticity, the whole welfare effect is composed of consumer surplus only which arises
because of decrease in price of imported product with the reduction of tariffs on that
product. However, with less than infinite export supply elasticity, one can calculate the
producer welfare existed in the exporting country due to increment in the world price of
imports because of increase in demand for imported product.
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3.1.1.4Revenue Effect to the Exporter
In this partial equilibrium setup, change in revenue to the exporter in a post simulation
environment, can also be calculated. The result on this effect is not directly reported by
SMART model but one can get the answer by using the following mathematical relation
given in Laird and Yeats (1986). The revenue to the exporter (ER) can be written as:
By assuming: xk , j=mk , j
ERk , j=pk , jw mk , j… (26)
It can be changed either by change in world prices or change in imports of product k
from country exporter j or both. In case of infinite export supply elasticity, there is no
price effect and exporter’s revenue increases with the increase in imports only.
However, in case of finite export supply elasticity, the change in exporter’s revenue
depends upon both of the variables: changes in world prices and changes in imports
from country j. Following expression (27) shows the change in revenue in case when
export supply elasticity is finite.
dER k , j=pk , jw d mk , j+mk , j dpk , j
w … (27)
By dividing (27) with (26); we get
dERk , j
ERk , j=
d mk , j
mk , j+
d pk , jw
pk , jw
Using (16) and (19), we get the final expression for revenue effect to the exporter as:
dERk , j
ERk , j=
d mk , j
mk , j+
d mk , j
mk , j
1μk , j
dERk , j
ERk , j=
d mk , j
mk , j [1+ 1μk , j ]
dERk , j
ERk , j=ε k, j
dt k , j
1+t k , j ( 1
1−ε k , j
μk, j)[1+
1μk , j ]
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dERk , j
ERk , j=ε k, j
dt k , j
1+t k , j( μk , j
μk , j−εk , j) [ μk , j+1
μk, j]
dERk , j
ERk , j=ε k, j
dt k , j
1+t k , j( μk, j+1
μk , j−εk , j)…(28)
3.1.2) Implementation of the Model
SMART model is easily implemented in WITS database available online and uses the
inbuilt data on applied tariff rates and imports. One can chose between the two tariff
rates available: MFN applied and Bound rates, while making the simulation scenario.
The model has also assumed the given values of elasticity parameters. As explained in
the above section, there are three main elasticity parameters: Import demand elasticity2 (
ε); Substitution elasticity3 (σ ); and Export supply elasticity4 (μ). The value of these
parameters varies over the products but remains same for the partner country. While
doing simulations using SMART, one can update/change the value of substitution and
2Import demand elasticity varies from importer to importer and proportionally affects the change in
imports. Doubling this elasticity will double the change in imports.3The substitution elasticity also varies by product and remains same for all the varieties of the considered
product. It also implies that elasticity remains same irrespective of exporting partner. It also affects
proportionally to the value of trade diversion but with a ceiling as explained in the previous section. The
total diverted trade cannot be greater than the actual trade existed before the change in trade policy. One
can use the original value of this elasticity parameter which is relevant to the concerned simulation.4The value of export supply elasticity varies by product but remains same for all varieties of that product.
It implies that elasticity remains same irrespective of exporting partner. WITS assumed infinite export
supply elasticity by default with its representing value 99 with zero price effect. As per this model
structure, maximum trade creation can be achieved with infinite export supply elasticity and total trade
effect (creation effect + price effect) becomes lower with any other value of this elasticity parameter. It is
recommended that one should take finitely elastic export supply function in case when the importing
country is sufficiently large to influence the world prices by importing very large quantity after the
reduction in tariff rates from the preference receiving country.
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export supply elasticity instead of using the default values: 1.5 and 99 respectively but
the value of Import demand elasticity is system defined and cannot be changed.
3.2 GTAP Analysis: A General Equilibrium Tool
For General Equilibrium analysis, the study will utilize the GTAP model of
world trade to estimate the effect of FTA between EU and India on economy wide
variables. To get the general equilibrium assessment, the study has used GTAP model
of global trade5. It is a multi-region static computable general equilibrium model which
includes the treatment of private household behavior using non-homothetic Constant
Difference of Elasticities (CDE) functional form, international trade and transport
activity and global savings/investment relationships. In this model, bilateral trade is
handled via the Armington assumption6. The GTAP model7is easily implemented by
using General Equilibrium Modelling Package (GEMPACK), a suite of economic
modeling software, developed and provided by Centre of policy studies, Monash
University8.Using CGE analysis, the study will present the disaggregated results on
economy-wide variables for the given GTAP sectors in GTAP-9 database with data of
2011 reference year. In GTAP, the whole economy is divided into 57 aggregated sectors
including the services sectors as well. Given below is a detailed explanation.
3.2.1 General Equilibrium Tool to Assess the Proposed Trade Policy
The main disadvantage of the partial equilibrium analysis is that it ignores the
interaction effect between sectors. It also misses the existing constraints that apply to
5 See Burfisher (2011) for practical exercises. 6 As per this assumption, products of the same industry, produced in different countries are distinct but substitute to each other. In GTAP model, elasticity of substitution between domestic and imported goods and elasticity of substitution among imports of different destinations are defined in the Armington aggregation structure for all agents in all the regions. 7 For detailed reading on GTAP Model, See Brockmeier (1996) and Hertel (1997). 8 See http://www.copsmodels.com/gempack.htm and Pearson and Horridge (2005), Harrison et al. (2013) for more details.
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the various factors of production and their movement across sectors and very sensitive
to some behavioral parameters such as elasticities. However, General Equilibrium
modeling captures all these feedback effect of an economy and captures all indirect
impacts on other market of any change in policy variable.For a trade policy change,
such as tariff reduction/elimination, has dual impact on the importer and exporter
country. It has direct effects through the reduction in price of the imported product in
the importer country and increase in exports from an exporter country. In addition to
these, due to presence of linkage and feedback effects in an economy, it also affects the
demand for its substitutes available in the home market and in foreign market with other
supplier. Due to change in demand for substitute good, price will also be affected and
hence affect the overall income of an economy through number of other linkage effects.
Due to ignorance of these linkage and feedback effects in partial equilibrium analysis
makes it simpler to understand because it focuses only on one market at a time. But in
reality these linkages and feedback effects cannot be ignored and played a very
important role in an economy. Hence, there arises a need to take all these effects
together and study the effect of change in trade policy variable on all sectors of the
economy rather than concentrating on one market at a time.
A general equilibrium model is a complete picture of an economy describing the
behavior of consumers and producers and their relationships with the help of
mathematical equations.Any general equilibrium model which is computable by using
the appropriate data is known as Computable General Equilibrium (CGE) model. In
CGE model, an economy is assumed to be in equilibrium at the initial prices and all
agents are satisfied with the reward they are getting and with their economic activities.
Change in trade policy, such as changes in tariff rate, acts as a shock and create
disequilibrium in the model which further causes reactions into the whole economic
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system. All of the mathematical equations will be resolved to get new equilibrium
solution which again satisfy market clearing conditions. There exists very large number
of country specific general equilibrium models which differs in their economic
structure, as different countries have different economic structure. They also differfrom
one another due to different assumptions.For detailed reading on applied general
equilibrium see: Shoven and Whalley (1992); Bouet (2008); Burfisher (2011); and other
handbook and user guides of trade policy analysis already mentioned above. In this
chapter, the structure of one of the famous model of world trade, i.e. GTAP model of
trade, has been discussed in detail.
The GTAP model (see Brockmeier, 1996, 2001; Hertel, 1997) is a static multi-
region general equilibrium model, which divides the whole economy into various
agents’ dependent upon each other. It is static in nature in the sense that it provides a
comparison of the state of the economy before and after changing the value of shock
variable and its impact on economy-wide variables. The framework of this model is
provided under the Global Trade Analysis Project (GTAP) which was started in 1992 to
facilitate the researchers working in the area of quantitative analysis of international
trade. Under this project, a fully documented database, GTAP database, is also provided
which gives economy-wide data of all 140 defined regions of the world. The analysis of
trade liberalization and its impact on economy-wide variables among countries are the
main research application of this project. It also provides the software, a tool to
implement the GTAP model using data from GTAP database. Under the GTAP model
framework, each separate region assumes common domestic structure and linked
through trade and investment flows between them. The domestic structure consists of
one regional household specified over private consumption, government consumption
and saving activities; production behavior of the region; and two global sectors through
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which all the regions of the world are linked with each other. Following sub-sections
briefly explain the domestic structure of a GTAP region and its inter-linkages with the
rest of the world as defined in GTAP model.
3.2.2 GTAP ModelFramework
To explain the GTAP model framework, two different types of equations have to be
explained: Accounting and behavioral equations. Following two sub-sections elaborate
the structure of GTAP model by specifying behavioral and accounting equations.
3.2.2.1Behavioral Equations
These equations are defined to specify the behavior of optimizing agents in the
economy such as demand functions in consumer behavior, production function in
producer behavior among others. Under the GTAP model framework, each separate
region assumes common domestic structure and linked through trade and investment
flows between them. The domestic structure consists of one regional household
specified over private consumption, government consumption and saving activities;
production behavior of the region; and two global sectors through which all the regions
of the world are linked with each other and are given as follows.
A) Household Behavior:
The behavior of a regional household is governed by an aggregated utility function that
allocates the expenditure across private, government and savings activities (McDougall,
2001). In GTAP model, in each region, household allocates regional income so as to
maximize per capita aggregate utility according to Cobb-Douglas utility function. The
utility maximization problem with budget constraint is as follows:
. . ( , ) ( , ) ... (7.29)
G SP B BBP G S
P P P G G G P S
Maximise U CU U Us t E P U E P U P U X
……………………………… (29)
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Where U is the per capita aggregate utility of a regional household; UP, UG, and US are
the per capita utility obtained from private, government and real savings activities and
at lower level these utilities are specified using some expenditure function9; EP and EG
are per capita expenditure functions; PP, PG, and PS are the price vectors for private
consumption, government consumption, and savings; Bi is the distribution parameter
which is assumed as variable; and X is the per capita income. Regional household
receives income by selling his endowments to the producer and spend over private
household expenditure, government expenditure and savings.
B) Producer Behavior
In GTAP model, producer tries to minimize the cost of production and his
behavior is specified by the nested Constant Elasticity of Substitution (CES) function
(Gohin and Hertel, 2003). In case of more than two inputs, Sato (1967) proposed a
nested CES function with less restrictive conditions on elasticity of substitution which is
a good approximation for empirical applications. In GTAP model, the same nested
structure has been used to specify the substitution possibilities between various inputs.
At the upper level, CES function is defined to indicate the substitution possibility
between intermediate inputs and value added and at the lower level CES function is
defined to show substitution between primary factors in the value added nest. The basic
idea behind nested CES structure is to accommodate the substitution possibilities within
the aggregated input category which is composed from other individual inputs. The
mathematical structure of nested CES production function with four inputs is given as
follows. Suppose x1 and x2 are aggregated into one single input and x3 and x4 are
9 The government consumption expenditure (EG) system is governed by Cobb-Douglas utility function with constant expenditure shares over all goods; the private consumption expenditure (EP) system is modeled by using CDE implicit expenditure function and is non-homothetic given by Hanoch (1975); and the third component of final demand system, i.e savings (ES) is a single commodity and fully exhausted by the investment demand.
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aggregated into another single input then the upper level CES function composed of two
lower level CES functions with two inputs each shown as follows:
1
1 2( (1 ) ) ... (7.30)Q CES CES
(30)
Where
1
2 1 2( (1 ) ) , 1, 2i i ii i i i i iCES x x i
are the two lower level CES functions.
The final specification of the four input nested CES function becomes:
1 1 1 2 2 2
1
1 1 1 2 2 3 2 4( (1 ) ) (1 )( (1 ) ) ... (7.31)Q x x x x
(31)
If 1 2 , then the above nested CES function becomes a plain four input CES
function.
The producer receives incomes from regional household by selling consumption goods
to private and government households; investment goods to savings sector and
intermediate goods to other producer. These incomes are exhausted on the purchase of
intermediate goods and primary inputs. Further, in this model, primary factors have
been divided in to two categories: perfectly mobile and sluggish ones. In case of mobile
factors, the reward is same regardless of the employed sector but in case of sluggish
factor, reward changes with the position of its employment.
C) Policy Interventions: Taxes and Subsidies
The policy interventions in the economy refer to the imposition of taxes by the
government on demand and supply activities. Due to the introduction of these transfer
payments, there will be changes in the accounting relationships which are captured by
difference between market prices and agent’s prices. In other words, in this model taxes
and subsidies drive a wedge between the market and agent’s price.
D) Global Sectors
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In a multi-region GE model, there also exist two global sectors through which regions
are linked together. In GTAP model, one global sector is the external sector, which
accounts the International trade and transport activities between the regions. Under this
sector, a composite good consist of exports of commodity, transport, and insurance
services are produced and used to move in between regions. The value of these services
exhausts the difference between global fob exports and global imports at cif prices.
Demand for domestic product coming from the external sector (other regions of the
world) generates additional revenue to the domestic producer and also it provides the
additional source of intermediate goods from the outside by paying the import taxes
which is already explained in the policy interventions. As the current GTAP-9 database
divides the whole world into 140 regions so to differentiate the goods from different
regions, the model employs the Armington assumption10 in the trading sector. The
model also includes the separate conditional demand equations for private and
government consumption for imported commodity. The other global sector is Global
Bank which intermediates between global savings and investments of all regions at
same prices. This sector satisfies the regional household’s demand for savings by selling
shares from regional investment good assembled for this purpose. In the GTAP model,
the implication of this sector is that if all sectors in a multi-region model are in
equilibrium then the global investments must be equal to global savings to satisfy
Walras’ law.
3.2.2.2 Accounting Relations
To ensure the balance in the economy, accounting equations are defined which show
that the economy is balanced.In GTAP model, each separate region assumes common
10 As per this assumption, products of the same industry, produced in different countries are distinct but
substitute to each other. In GTAP model, elasticity of substitution between domestic and imported goods
and elasticity of substitution among imports of different destinations are defined in the Armington
aggregation structure for all agents in all the regions.
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domestic structure which is shown in Figure 3.1 given in Hertel (2004) to showthe
structural11 representation of this model. Following points briefly explains theoretically
the accounting relationships existed in this model.
Producer pays to the regional household for using his endowments which is
equal to the value of output at agent’s prices (VOA) and regional household
allocates this regional income across private expenditures (VDPA), government
expenditure (VDGA) and savings activities in such a way that all regional
income earned is exhausted between three forms of final demand;
The producer also purchases intermediate goods as inputs use in the production
process;
After the production, the producer sells the consumption and investment good to
the regional household and intermediate good to the other producers and
receives payments;
NETINV is the payment received by the producer for selling investment good to
the regional household for the saving activity;
VDFA is the payment received by the domestic producer for selling intermediate
goods to other producer in the economy;
Under the zero profit assumption, all income earned is exhausted between the
purchases of value added services and intermediate goods;
Further under the closed economy, due to government interventions, taxes has
been introduced;
Due to taxes private household and government have to pay taxes in addition to
their expenditure on consumption good;
Producer also have to pay taxes on the purchase of intermediate goods used in
the process of production;
11 See Brockmeier (2001) for details.
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Tax revenues are computed by comparing the value of transaction at agent’s and
market prices separately;
To show the relationship with outside word, one region, say rest of the world,
has been introduced;
In this setup, the firms will get extra revenue (VXMD) by selling their products
to the outside world and also spend (VIFA)on the purchases of intermediate
inputs from the rest of the world;
Private households and government also spend on imported commodities and
flows are represented by VIPA and VIGA respectively;
To accommodate the third source of final demand such as savings, the GTAP
model computes global savings and investment which creates the equilibrium
system;
Further, at the end, the rest of the world region also earns revenue from the
exports to single domestic region and spent on exports of domestic household to
rest of the world (VXMD) and on import (MTAX) and export (XTAX) taxes to
the regional household. It completes the circular flow in the open economy.
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Figure 7.1: Graphical Explanation of GTAP ModelSource: Hertel, 2004
3.2.3 Implications for Tariff Reform in GTAP Model
Effect on Prices
In GTAP model, the effect of a trade policy shock such as reduction of tariff on
imports of commodity i from region r to s can be represented by changing the values of
quantity demanded and supplied with their prices. From the importer side (i.e. region s),
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with the reduction in tariffs on imports of good i from region r to s, there will be a
reduction in domestic price of region r exports in the importing country. This price
reduction has two immediate impacts:
a) Firstly, it lowers the price of composite imports. This effect can also be seen in
changing terms of trade effect by change in price index of imports and exports;
and
b) Secondly, it encourages agents’ in the importing country to alter their sourcing
of imports in favor of region r. One can termed this effect as a trade diversion
effect i.e. diversion of imports from expensive region to the cheaper one due to
reduction of import tariffs. The total increase in imports may be greater than the
diverted imports from other regions. If the total increase in imports is greater
than the diverted imports from non-member countries to member country then
the surplus imports is categorized into trade creation effect. Hence, the trade
effect of any preferential trade agreement is composed of trade diversion and
trade creation effect. The responsiveness of this shift in the model is dictated by
the value of elasticity of substitution among imports from different destinations.
One can measure the trade effect by looking at the figures of change in quantity
of imports from different sources.
However, from the exporters’ side, due to decrease in prices in importing region, after
the tariff reform, market prices of the exportable rises in the exporting country due to
increase in demand. Since, there is no change in border tax, Pfob12rises by same amount.
The Pcif13 further depends upon the changes in price index of international transport
12Pfob is exporter price which includes the actual cost of the product, transportation cost, insurance, freight up to the port of loading. The extra cost is borne by the exporter. 13Pcif is faced by importer while receiving the goods at his port. It includes insurance cost and freight charges from exporters’ port to importers port and has to bear by the importer.
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services. If price of transport services declines then Pcif will rise but not as the same
amount as Pfob.
Other Macroeconomic Effects
The policy of tariff liberalization also has an impact on other aggregated variables of the
economy’s concerned.
Terms of Trade
Terms of trade (TOT) of a region are defined as the ratio of price index received for
tradable produced in region r (PSW) to the price index paid for tradable used in the
same region (PDW). This measure in GTAP model includes the sales of net investment
to the global bank and purchases of savings from the global bank. Following equation
(1) shows the percentage change in terms of trade (tot) is the difference between
percentage change in PSW and PDW.
( ) ( ) ( ) ...(1)tot r psw r pdw r
Regional GDP
As the study has assumed fixed endowments in pre and post simulation environment
therefore, the quantity index of GDP represents only the shift in the economy’s
production possibilities frontier owing to the improved allocation of a fixed resource
base.
( ) ( ) ( ) ...(9)qgdp r vgdp r pgdp r
Where vgdp is the percentage change in value of GDP in region r and pgdp is the
percentage change in price index for GDP in region r.
Welfare Effect14
The estimation of GTAP model also provides the regional equivalent variation (EV)
measure in monetary terms, which represents the welfare effect in this model. From the
household point of view, it measures the cost to the household of the same bundle of 14 See Huff and Hertel (2000) for more details.
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goods, before and after a given policy shock. In other words, it is the difference between
the expenditure required to obtain the new level of utility at initial prices and the initial
expenditure. In GTAP model, the regional household utility level is depends upon per
capita household consumption, per capita government expenditure and per capita
savings. Any change in this aggregate utility level provides the welfare effect in this
model.
In a multi-region general equilibrium model, there exist several sources which
contribute in the total change in expenditure and also to welfare. In the GTAP model,
these sources are clubbed into the following main six sources:
Allocative Efficiency Effect: It occurs due to reallocation of resources from one use to
another in a post-simulation environment in a particular region. In this model, allocative
efficiency effect for a region is explained with the percentage change in the values of
various types of taxes due to changes in the quantity demanded with which these are
linked. It is calculated by multiplying changes in per capita quantity with initial taxes.
The different types of taxes are the taxes on use of domestic and imported intermediate
goods, private consumption of domestic and imported good, government consumption
of domestic and imported good, use of endowment good and tax on exports and imports
of goods. One can report the contribution of every type of quantity change in total
change in welfare effect of a given region.
Terms of Trade Effect: In a multi-region general equilibrium model, terms of trade
effect also plays an important role in changing economic welfare of a particular region.
This effect arises due to changes in the fob and cif prices of exports and imports. In the
GTAP model, change in prices of commodities and services provided to international
transport sector are also included in the calculation of terms of trade effect. To calculate
it, change in the value of imports from region s and services paid to international
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transport sector is subtracted from change in value of exports of region r at fob prices
and changes in value of sales to international transport sector by region r. Positive
difference shows the positive contribution of this effect.
Investment–Saving Effect: Under this effect, change in price of saving and investment
is compared. Percentage change in prices of capital goods when multiplied with the net
initial investment of the region gives the value of change in net investment and the
percentage change in price of savings in region r when multiplied with regional savings
gives the value of change in savings and the difference between the two provides the
contribution of this effect in total welfare. As the utility level is also depends upon the
net national savings so the regions with net suppliers of savings (Savings > Investment)
to the global bank benefit from rise in price of savings relative to investment goods.
Endowment Effect: Under this effect, percentage change in quantity of endowment is
calculated and then multiplied with the value of output at agent’s prices to evaluate the
contribution of changes in quantity of endowments. Value of capital depreciation is also
subtracted while giving the final figure to this effect. In case of fixed endowment
assumption, this effect is zero.
Effect of Change in Technology: In this model, the contribution of this effect comes
from various technological changes viz, output augmenting technology change, primary
factor augmenting technology change, value added augmenting technology change,
composite intermediate input augmenting technical change, technical change in
transportation sector and contribution of bilateral import-augmenting technical change.
Change in any technology would lead to change in associated demand which further
affect level of utility. In a comparative static model setup in which technology is
assumed fixed, the contribution of this effect is zero.
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Effect of change in population: The effect of change in population on change in
expenditure level is known as population effect. Contribution of this effect is zero in
comparative static model with fixed population.
The above specified GTAP model is easily implemented by using General Equilibrium
Modelling Package (GEMPACK), a suite of economic modeling software, developed
and provided by Centre of policy studies, Monash University (Pearson &Horridge,
2005; Harrison, et al., 2013). The global trade analysis project also provides the
simulation software, RunGTAP, which helps in running simulations in a windows
environment using GTAP model. Except these simulation packages, it can also be
implemented in GAMS (General Algebraic Modeling System) which is a high level
modeling system for mathematical programming and optimization. GAMS is tailored
for complex, large scale modeling applications, and allows you to build large
maintainable models that can be adapted quickly to new situations. Read Burfisher
(2011) for details on implementation of GTAP model.
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Section 4: Data Aggregations and Simulation Scenarios
4.1 Data Aggregations
The present study used the GTAP database version 9 provided by Purdue University
under Global Trade Analysis Project (GTAP). It is the most suited available database
used for the purpose of general equilibrium analysis which provides data for three
reference years: 2004, 2007 and 2011. The whole database is the reflection of World
economy andconsists of data on all-important macroeconomic variables such as output,
employment, wages, prices and welfare. For the analysis purpose, all 140 GTAP regions
of the world have been aggregated into 18 regions. Among 18 aggregated regions, 17
regionscover the member countries of RCEP and BRICS and rest all the countries are
under Rest of world. Similarly, the 57 sectors of the GTAP model have been aggregated
into 15 sectors. The trade flows across these commodities are distinguished by their
origin and are based on agents such as intermediate demand, final demand by private
households, government and investment.
Table 4.1: Region AggregationS.No Aggregated Region S.No Aggregated Region S.No Aggregated Region
1. India 7 Brazil 13 China
2. Russia 8 South Africa 14 Thailand
3. Australia 9 Vietnam 15 New Zealand
4 Japan 10 Singapore 16 Philippines
5 Malaysia 11 Laos 17 Indonesia
6 Cambodia 12 Korea 18 Rest of World
Table 4.2 Sector AggregationS. No Sector S. No Sector S. No Sector
1. Vegetables 6. Chemicalplas 11. Stoneglass
2. Animals 7. Hideskin 12. Metals
3. FoodProduction 8. Wood 13. Machelec
4. Fuels 9. TextWapp 14. Transport
5. Minerals 10. Footwear 15. OthServices
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4.2. Simulation Scenario
We use SMART tool to study the relevant preparations required at policy level to
ensure the implementation of BRICS and RCEP will produce maximum benefits for
Indian economy as it may bring about unprecedented opportunities and challenges to
the business and investment activities.
We have also utilized GTAP 8 database for general equilibrium analysis of various
trade policy shocks given to study possible impacts of liberalization initiative between
India- RCEP and India BRICS. We have used General Equilibrium standard closure
where prices, quantities of all the non-endowment commodities, and regional incomes
are endogenous variables whereas policy variables, technical change variables and
population are exogenous to the model.Additionally, global savings is equated to
investment by the virtue of Walrus’s law. This GE standard closure is met when all
markets are in equilibrium. To fulfill the objective of the study, simulations are
conducted considering following two scenarios:
Full Liberalization: In this case, all the tradable commoditiesare open for both
the proposed free trade agreement. This means that there will be zero tariffs for
all the tradable commodities between India- RCEP and India – BRICS.
Scenario with Specialized Products: This scenario takes into the account that
some traded products have comparative advantage over others with better trade
intensity between partner countries. Say, India will have comparative advantage
by exporting animal products, Fuels, Vegetables etc. If these products are fully
opened between both the blocs then would determine the impact of liberalization
on the market where they have greater growth.
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Section 5: Simulation Results5.1 SMART Simulations for India- BRICS and India- RCEP Scenario
SMART reports the results of any trade policy shock on effects on trade flows and trade
effects in terms of trade creation and trade diversion, Revenue effect and Consumer
Surplus effect. We summarize the simulation results in Table 5.1.1 to 5.1.4. Table 5.1.1
gives the exporters view on BRICS. By the export figures, we can note that export
change is coming out to be positive for the BRICS members while negative for rest of
the countries. Table 5.1.2 below shows the import change of 12043401.18 and tariff
change in revenue of -13694251.09, 1000 US $ while the consumer surplus of
1,138,366.94, 1000 US $ due to reduction in tariffs on India coming from BRICS
countries. Table 5.1.3 shows the welfare effect of India-BRICS FTA and works out to
be 897,951.08, $1000 USD.
Table 5.1.1 Exporter View-BRICSExportsBefore (in 1000 USD)
ExportsAfter (in 1000 USD)
ExportChangeInRevenue (in 1000 USD)
Brazil 3,247,241.77 3,568,970.78 321,728.99
China 48,340,694.87 60,524,937.80 12,184,242.94
Russia 3,758,842.42 4,952,614.92 1,193,772.46
SouthAfrica 7,336,018.66 8,713,049.31 1,377,030.75
Thailand 4,993,294.77 4,897,272.64 -96,022.15
Australia 10,750,158.36 10,667,867.08 -82,291.36
Vietnam 2,498,065.52 2,452,096.00 -45,969.53
NewZealand 633,726.89 626,969.38 -6,757.50
Japan 10,235,934.46 10,048,314.83 -187,619.61
Singapore 6,703,127.53 6,634,130.76 -68,996.77
Philippines 400,459.15 395,099.85 -5,359.30
Malaysia 9,214,074.60 9,147,899.05 -66,175.57
Indonesia 14,573,931.15 14,490,955.85 -82,975.03
Cambodia 4,341.77 4,083.50 -258.271
Korea 32,446.41 31,904.66 -541.747Source: WITS
Table 5.1.4 gives the total trade effect, sum of price terms of trade effect, and quantity
effects i.e. trade creation and trade diversion. We have taken price effects to be zero
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because we have assumed India to be the small country. China gains the most in terms
of total trade effects followed by Russia, South Africa and Brazil. Total trade effect is
negative for all the other countries, except BRICS, would be negative as there will be
trade diversion from these countries to BRICS countries. Total trade effect for world
comes out to be positive and 12,043,401.18 1000 US$.
Table 5.1.2Market View- BRICS
ImportsBefore in 1000 USD Import Change TariffRevenue
in 1000 USD
Tariff New Revenue in 1000 USD
ConsumerSurplus in 1000 USD
India 449,376,397.28 12043401.18 49,794,220.91 36,099,969.82 1,138,366.94Source: WITS
Table 5.1.3Revenue effect- BRICSRevenue Effect in 1000 USD
Trade Total Effect in 1000 USD
Trade Value in 1000 USD Welfare in 1000 USD
India -4,250,160.04 12,043,401.18 449,376,397.28 897,951.08
Source: WITS
Table 5.1.4Trade Creation Effect - BRICSTradeTotalEffect in 1000
USDTradeCreationEffect in
1000 USDTradeDiversionEffect in
1000 USDBrazil 321,728.99 240,154.06 81,574.93
China 12,184,242.94 10,163,851.41 2,020,391.52
Russia 1,193,772.46 871,905.16 321,867.33
SouthAfrica 1,377,030.75 767,490.51 609,540.27
Thailand -96,022.15 0 -96,022.15
Australia -82,291.36 0 -82,291.36
Vietnam -45,969.53 0 -45,969.53
NewZealand -6,757.50 0 -6,757.50
Japan -187,619.61 0 -187,619.61
Singapore -68,996.77 0 -68,996.77
Philippines -5,359.30 0 -5,359.30
Malaysia -66,175.57 0 -66,175.57
Indonesia -82,975.03 0 -82,975.03
Cambodia -258.271 0 -258.271
Korea -541.747 0 -541.747
World 12,043,401.18 12,043,401.16 0.107Source: WITS
Table 5.1.5 to 5.1.8 describes the same figures for the RCEP FTA case. Table 5.1.5
gives you an overview of export change in revenue for RCEP countries. Here, again,
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member countries have shown gradual increase in the exports similar to that shown by
BRICS members.
Table 5.1.6 shows the positive import change of 22370873.28 1000 US $ and tariff
change in revenue of – 22821331.97 1000 US $. Also, RCEP will have greater
consumer surplus effect and welfare effect than BRICS, as can be seen from Table 5.1.6
and 5.1.7. As observed from Table 5.1.8, Total trade effect (World) is larger in case of
RCEP than BRICS suggesting RCEP would be a better agreement for Indian Economy.
Although, RCEP shows similar trend for trade creation and trade diversion as BRICS,
positive for member countries and negative for all other countries with maximum trade
creation for Japan followed by Indonesia and Thailand.
Table 5.1.5 Exporter View- RCEP
ExportsBefore (in 1000 USD)
ExportsAfter (in 1000 USD)
ExportChangeInRevenue (in 1000 USD)
Brazil 3,247,241.77 3,219,095.82 -28,145.97
China 48,340,694.87 60,083,084.54 11,742,389.64
Russia 3,758,842.42 3,699,491.32 -59,351.14
South Africa 7,336,018.66 7,239,975.10 -96,043.52
Thailand 4,993,294.77 7,172,466.15 2,179,171.40
Australia 10,750,158.36 11,958,398.86 1,208,240.65
Vietnam 2,498,065.52 3,787,704.04 1,289,638.51
New Zealand 633,726.89 711,077.09 77,350.20
Japan 10,235,934.46 13,637,668.92 3,401,734.43
Singapore 6,703,127.53 7,829,027.35 1,125,899.83
Philippines 400,459.15 494,170.71 93,711.57
Malaysia 9,214,074.60 11,293,831.33 2,079,756.74
Indonesia 14,573,931.15 17,158,961.21 2,585,030.32
Cambodia 4,341.77 5,765.17 1,423.40
Korea 32,446.41 40,326.64 7,880.24Source: WITS
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Table 5.1.6 Market View RCEP
ImportsBefore in 1000 USD Import Change TariffRevenue
in 1000 USD
TariffNewRevenue in 1000 USD
ConsumerSurplus in 1000 USD
India 449,376,397.28 22370873.28 49,794,220.91 26,972,888.94 1,878,973.78Source: WITS
Table 5.1.7 Revenue effect RCEPRevenue Effect in 1000 USD
Trade Total Effect in 1000 USD
Trade Value in 1000 USD
Welfare in 1000 USD
India -12,072,824.39 22,370,873.28 449,376,397.28 2,990,293.02Source: WITS
Table 5.1.8 Trade Creation Effect RCEPTrade Total Effect in 1000 USD
Trade Creation Effect in 1000 USD
Trade Diversion Effect in 1000 USD
Brazil -28,145.97 0 -28,145.97
China 11,742,389.64 10,163,851.41 1,578,538.24
Russia -59,351.14 0 -59,351.14
SouthAfrica -96,043.52 0 -96,043.52
Thailand 2,179,171.40 1,906,718.01 272,453.40
Australia 1,208,240.65 826,624.35 381,616.29
Vietnam 1,289,638.51 1,219,373.50 70,265.03
NewZealand 77,350.20 51,147.10 26,203.10
Japan 3,401,734.43 2,820,344.74 581,389.70
Singapore 1,125,899.83 807,882.15 318,017.68
Philippines 93,711.57 77,834.10 15,877.47
Malaysia 2,079,756.74 1,927,078.21 152,678.53
Indonesia 2,585,030.32 2,393,061.91 191,968.42
Cambodia 1,423.40 1,256.57 166.829
Korea 7,880.24 5,190.26 2,689.98
World 22,370,873.28 22,370,873.31 0.071Source: WITS
5.2 Impact on Macroeconomic variables and Welfare of India- BRICS and India-
RCEP Full Liberalization
Under this scenario, we reduced the tariffs on imports from all the BRICS members to
India to zero and vice versa. However, we also considered the case where we have
brought down the tariffs on imports from all the RCEP members to India and on imports
from India to all the RCEP countries to Zero, to draw comparative analysis on
macroeconomic variables on partner countries and India.
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Table 5.2.1 represents the implication of full liberalization on macroeconomics
variables for BRICS and RCEP respectively. In BRICS full liberalization Scenario,
India would experience 0.89% fall in GDP and 1.08% in GDP Price index*. Among
BRICS comprising Brazil, Russia, China and South Africa, South Africa and Russia
would experience highest increase in GDP of 0.78% and 0.40% respectively. Whereas
all the RCEP (All countries excluding BRICS members, India and ROW) members
would show fall in GDP and GDP Price Index.
Table 5.2.1 Macro Economics VariablesBRICS RCEP
Change in Value GDP
Change in GDP Price Index
Change in Value GDP
Change in GDP Price Index
India -0.89 -1.08 -1.62 -2.18
Brazil 0.12 0.12 -0.13 -0.13
China 0.28 0.25 0.181 0.159
Russia 0.40 0.43 -0.18 -0.161
SouthAfrica 0.78 0.77 -0.234 -0.224
Thailand -0.05 -0.05 0.225 0.224
Australia -0.11 -0.11 0.924 0.874
Vietnam -0.05 -0.04 0.054 0.073
Newzealand -0.04 -0.04 0.055 0.056
Japan -0.01 -0.01 0.192 0.19
Singapore -0.07 -0.07 0.514 0.502
Philippines 0.01 -0.00 -0.045 -0.048
Malaysia -0.07 -0.07 0.39 0.359
Laos -0.02 -0.02 -0.031 -0.026
Indonesia -0.11 -0.11 2.28 2.25
Cambodia -0.07 -0.06 -0.146 -0.125
Korea -0.02 -0.02 0.271 -0.276
ROW -0.03 -0.03 -0.082 -0.081Source: GTAP Simulations
The results of simulations for RCEP full liberalization scenario shows greater fall in
GDP and GDP Price index of 1.62 % and 2.18% respectively. Philippines and Laos are
only RCEP member countries where the decrease in GDP and GDP Price Index are
recorded whereas all members are better off in terms of macroeconomic indicators. This
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bilateral trade Agreement would be most beneficial for Indonesia (2.28%), Australia
(0.924%) and Singapore (0.514%).
Table 5.2.2 corresponds to changes in trade variables for the countries under the two
different liberalization scenarios. Under the BRICS full liberalization Scenario, Volume
of exports and imports for the member countries has increased and decreased for rest of
the regions. Export and Import volume of India is consistently better than other BRICS
members. However, India would show negative trade balance that would only mean that
India would have sharp increase in import overexport. China and Russia would export
more and import less because of positive trade balance. Terms of trade would decrease
for India but would improve for rest of the BRICS countries significantly; 0.131% for
Brazil, 0.212% for china, 0.231% for Russia and 0.784% for South Africa.
Table 5.2.2 Trade indicators BRICS RCEP
Export Volume
Import volume
Trade Balance TOT Export
VolumeImport
volumeTrade
Balance TOT
India 6.34 5.36 -2335.18 -0.696 13.7 10.6 -3379 -1.59
Brazil 0.26 0.65 -296.27 0.131 0.078 -0.157 240 -0.065
China 0.38 0.69 628.85 0.212 0.235 0.406 367 0.111
Russia 0.61 0.95 594.18 0.231 -0.034 -0.221 -295 -0.192
SouthAfrica 0.83 2.36 -711.3 0.784 -0.052 -0.36 165 -0.132
Thailand -0.01 -0.05 7.74 -0.025 0.183 0.452 -80.6 0.147
Australia -0.1 -0.23 94.77 -0.087 0.423 1.94 -371 1.35
Vietnam 0.01 -0.01 3.76 -0.013 0.482 0.516 -48.8 0.047
NewZealand -0.01 -0.03 1.77 -0.014 0.235 0.078 39 -0.046
Japan -0.02 -0.07 222.14 -0.022 0.074 0.246 4.27 0.146
Singapore -0.04 -0.08 -6.68 -0.026 0.349 0.676 125 0.232
Philippines 0.01 0.03 -4.29 0.017 0.125 0.191 -43.4 -0.015
Malaysia -0.02 -0.07 -16.46 -0.034 0.223 0.469 166 0.182
Laos 0 0.01 -0.09 -0.002 0.047 -0.078 0.232 -0.109
Indonesia -0.06 -0.12 -31.47 -0.059 1.49 3.12 716 1.64
Cambodia -0.01 -0.04 0.81 -0.019 0.062 -0.072 1.37 -0.112
Korea -0.04 -0.07 42.6 -0.02 -0.279 0.412 -2248 0.172
Row -0.02 -0.05 1839.34 -0.019 -0.013 -0.085 4567 -0.04Source: GTAP Simulations
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Comparing trade figures with BRICS Scenario, under RCEP liberalization India would
again show increase in volume of trade and negative trade balance. Similarly, most of
the RCEP countries record slight increase in their Export- Import Volume and trade
balance. Terms of Trade would also improve for most of them except New Zealand,
Philippines, Laos and Cambodia as in the case under RCEP full liberalization. Terms of
trade gain for RCEP is due to rise in price of their export items than over their import by
proposed FTA. To sum up, for both the Full liberalization scenario India shows increase
in trade but at the cost of declination in terms of trade. The trade gain in RCEP is much
higher in comparison to BRICS but its terms of trade get worsen.
Figure 5.2 clearly depicts the simulation results of integration of India- BRICS and
India- RCEP. India and China both being part of proposed FTA show opposite effect
i.e. negative trade balance for India and positive trade balance for China. China would
experience sharp increase in export than imports whereas India would be affected
adversely.
Table 5.2.3 gives us results on sector wise trade balance for India under the discussed
two FTAs. Under India-BRICS liberalization, India would have positive trade balance
for 8 sectors out of 15 sectors. India would have maximum positive trade balance for
Textile and wearing apparels, Footwear and Transport services. It would have
maximum negative trade balance for sectors like Vegetables and Metals.In case of
RCEP liberalization, trade balance would improve particularly for Vegetables, Fuels
and Textile while deteriorate forsectors like Food production, Minerals, metals and
Heavy Machine electronics. As observed from table 2.1 and 2.2, we can say India’s
comparative advantage is focused in the sectors like Animals, Vegetables, Fuels, and
Chemicals, Hide skin, Text clothing, Footwear, Stone glass andmetals. These are the
sectors where India would like to export more and any free trade agreement would be
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beneficial for India, which would improve trade in these sectors. Table shows RCEP
would have better prospects of improving trade in these sectors, hence improving
overall trade for India.
Table5.2.3 Sector Wise Trade BalanceFull Liberalization
DTBALi India-Brics India-RCEP
Veg -2273.96 3906.246
Animals 114.35 144.441
FoodPro -45.39 -8102.912
Fuels 191.59 1970.124
Minerals -493.54 -2719.183
Chemplas 248.91 635.104
Hideskin 3.39 -1.562
Wood -211.50 -196.741
TextWapp 1712.94 1382.492
Footwear 401 426.758
Stoneglas -163.13 -109.275
Metals -1683.19 -1017.578
Machelec -465.42 -1482.475
Transport 257.87 773.763
OtherServices 135.75 893.545Source: GTAP Simulations
It is necessary to measure change in economic welfare to determine whether the
proposed FTA is better or worse off as a result of movement of natural persons. In the
GTAP model, regional welfare is reported as percentage change in regional utility or as
Equivalent variation in Income. The regional household’s EV is equal to the difference
between the expenditure required to obtain the new (post simulation) level of utility at
initial prices and that available initially.Welfare gain can be bifurcated into the various
components: Allocative efficiency effects, terms of trade effects and saving- investment
effects. In comparative static model we keep population, technology and endowments
fixed, so the only way to increase welfare is to reduce excess burden arising from
existing distortions.Changes in Allocative efficiency are directly related to tax or tax
changes interacting with equilibrium quantities changes. Thus, policy simulations
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results in changes in real income due to change in endowments net of depreciation
(usually comes zero in a comparative static model), tax on output of any good, tax on
use of endowment and intermediate input of any industry, tax on private household
consumption and government consumption, export-import taxes, changes in regional
terms of trade and change in relative price of savings and Investment (Huff and Hertel,
2000). This would improve welfare gain, as it would increase the level of taxed activity
by relocating commodity and endowment from the low value use to high value use.
Good that yields trade tax to economy would be beneficial for economy. If the export
prices post liberalization rises more than import prices would contribute positively to
the society. Even though, investment doesn’t contribute in regional utility as saving
does but does generate current income.
Analyzing figures of Table 5.2.4, we can deduce that all the member countries are
gaining over their respective FTA scenario. Although under RCEP, welfare effect does
vary among member countries. Welfare gain for countries like India, Thailand,
Australia, Vietnam, Japan, Singapore, Malaysia, Indonesia and Korea are positive.
Looking from the table below by we can easily say, Indiawould registers higher positive
figure by aligning with RCEP.
Table5.2.4 Impacts on change in WelfareEV India-BRICS India-RCEP
India 231.15 1542.46
Brazil 278.93 -88.16
China 3196.23 -650.98
Russia 410.72 -758.05
SouthAfrica 736.51 -100.25
Thailand -38.03 311.34
Australia -173.08 2956.43
Vietnam -10.7 39.21
Newzealand -3.98 -1.73
Japan -89.3 1470.56
Singapore 46.89 594.9
Philippines 16.22 -7.64
Malaysia -60.58 484.91
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Laos 0.13 -1.86
Indonesia -59.55 2093.95
Cambodia -1.36 -8.24
Korea -49.87 6284.61
ROW -2114.99 -2442.44
Table 5.2.5 shows the decomposition of welfare effects. The decomposition of welfare
effect suggests that India gain’s from region integration is primarily driven by
Allocation under both the scenarios. Changes in Allocative efficiency rise when
allocation of resources changes with regards to pre existing distortions. Allocation gain
for India is higher in case of RCEP liberalization than BRICS. However, we have
greater negative terms of trade and investment and savings in RCEP but overall welfare
effect is significantly bigger for RCEP.
Table5.2.5 Decomposition of Welfare effectIndia-BRICS India-RCEP
Allocation 2376 6584
TOT -1706 -4085
Investment-savings -438 -1022
Welfare 231 1476Source: GTAP Simulations
5.3 Impact on Macroeconomic variables and Welfare of India- BRICS and India- RCEP scenario on specialized productsWhen two countries come forward to negotiate the terms of their free trade agreement,
both the countries don’t open their market instantly. While negotiating any trade,
members suggest their list of products to start the trade liberalization considering
various scenarios. As eliminating tariffs in all the sectors at the beginning of
negotiations is not feasible and can be achievable in the long run, one can categorize the
products into different categories on the basis of bilateral tariff rates on each other’s
exports. The present study utilizes the list of RCA products of the each country
calculated using WITS Database (Table 2.1 and table 2.2) to assess trade scenario where
we eliminate tariffs only on those products, which will show comparative advantage on
the export of that product.
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Table5.3.1 below depicts the scenario where we have only liberalized the specialized
products of each country to find impact of proposed FTA on India.ColumnIII and I
provides the simulation results on full liberalization and Column II and IV considers
scenario with tariff reduction on comparative advantage products. Under specialized
product scenario, change in value of GDP is declining more in case of RCEP whereas it
becomes positive in case of BRICS. Although change in GDP price index would like to
differ from Change in value of GDP as it increase by 0.4263% for RCEP and by 0.01%
for BRICS. Average Priceshave improved when scenario shifted from full trade
liberalization to specialized product liberalization. Change in export and import volume
will be better in full trade liberalization for both the agreement. Trade balance has
substantially improved in specialized product scenario. Even though, Both FTA would
have negative trade balance but the fall in trade balance has diminished, more in case of
BRICS. Tariff reduction in specialized products has resulted in improved terms of trade.
In every discussed scenario, India continues to have negative terms of trade; in other
words, it fails to drive home the price advantage. The terms of trade is more negative in
case of ASEAN because of larger fall in prices of import items than exports. While
RCEP shows marginal positive change in terms of trade, BRICS has shown a marked
improvement. The selected macroeconomic variables, under specialized products
scenario, agreement with BRICS will have positive impact over India with net positive
trade gain and improved terms of trade. Additionally, total welfare also supports India’s
alignment with RCEP, as India’s welfare gain is notably higher in RCEP than BRICS.
Table: 5.3.1 Macroeconomic and Trade variables
Variables BRICS I BRICS II RCEP I RCEP II
Change in Value GDP -0.89 0.02 -1.62 -1.909
Change in GDP Price Index .19 0.01 -2.18 0.4263
Export Volume 6.34 0.98 13.7 9.50
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Import volume 5.36 0.95 10.6 7.146
Trade Balance -2335.18 -486.20 -3379 -3042.92
TOT -0.70 -0.01 -1.59 -1.57
Change in welfare effect 231.15 141.83 1545.55 966.4299
Source: GTAP Simulations
Table 5.3.2 below shows sector wise trade balance on India under different scenario.
Column I and II provide simulation results on full trade liberalization while column
show results on specialized product liberalization. Under specialized Product scenario,
India with BRICS would have positive trade balance for Fuels, Textile and wearing
Apparels, and footwear. In same scenario, India with RCEP would have negative trade
balance for Food Production, Minerals and machine electronics sector. Under BRICS,
India would like to export more products of Fuels, Textile, footwear and metals whereas
Under RCEP, India would export Animal, chemical, metals. We would want other
countries to reduce tariff over these products so that we can export more in reduced
tariffs. As the results suggest, India under RCEP has shown positive trade balance for
specialized products and increased trade balance than full liberalization scenario.
Table 5.3.2 Sector wise Trade balance DTBALi India-Brics I India-Brics II India-RCEP I India-RCEP II
Veg -2273.96 -159.54 3906.246 279.47
Animals 114.35 -5.35 144.441 348.76
FoodPro -45.39 -484.79 -8102.912 -8083.96
Fuels 191.59 213.29 1970.124 1269.63
Minerals -493.54 -347.52 -2719.183 -1994.73
Chemplas 248.91 -39.05 635.104 1649.63
Hideskin 3.39 -0.31 -1.562 10.26
Wood -211.5 -83.63 -196.741 181.47
TextWapp 1712.94 1278.91 1382.492 830.54
Footwear 401 152.92 426.758 280.82
Stoneglas -163.13 -5 -109.275 122.74
Metals -1683.19 -561.12 -1017.578 287.03
Machelec -465.42 -94.58 -1482.475 -338.75
Transport 257.87 -59.66 773.763 872.85
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OtherServices 135.75 -280.67 893.545 1285.31Source: GTAP Simulations
Table 5.3.3 below gives decomposition of welfare effect under various scenarios. Gain
in allocative efficiency has the major contribution in welfare gain under specialized
product scenario with negative contribution from terms of trade and investment savings
factors. RCEP under both the liberalization outperforms BRICS in terms of welfare
effect. India with BRICS specialized product scenario show fall in allocative efficiency
thus leading to decline in welfare effect whereas as RCEP’s allocation is better off when
we eliminate tariff from specialized products.
Table 5.3.3 Decomposition of welfare effectIndia-BRICS I India-BRICS II India-RCEP I India-RCEP II
Allocation 2376 161 6584 5250
TOT -1706 -10.2 -4085 -4004
Investment-savings -438 -9.02 -1022 -831
Welfare effect 231 142 1476 415Source: GTAP Simulations
Section 6: ConclusionsIn this study, we have studied impact of BRICS and RCEP over India under three
different scenarios. Under partial equilibrium model, we investigated the liberalization
scenario based on 4 variables such as Total trade effect, revenue effect, Consumer
Surplus effect and welfare effect for total trade and result confirms that their will be
trade creation among the countries and trade diversion from the non member countries.
As we studied this for two FTA, we found that India will have greater total trade effect,
revenue effect, and welfare and consumer surplus effect in case of RCEP.Further we
analyzed the impact of proposed trade policy under general equilibrium model using
GTAP software considering reciprocal tariff reduction followed by specialized product
liberalization to asses the flow of agreement in the long run. Under the full trade
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liberalization, we can conclude that RCEP shows huge increase in export- import
volume with respect to BRICS. Also, India would be importing more from the RCEP
than BRICS as it has greater negative trade balance withgreater negative terms of trade.
RCEP has the greater welfare gain than BRICS and better welfare effect because of
positive contribution of allocative efficiency. These results can be aimed to achieve in
long run as no country open their full market with zero tariff within the instant it sign
the agreement. Free trade agreement involves long process of negotiations from both
sides of member countries. Practically, countries offer the list of products in which they
want to reduce their tariffs and we capture this scenario by categorizing them the basis
of comparative advantage. Even after reducing tariffs on specialized products, our result
was concurrent with the full trade liberalization. Second scenario shows positive
welfare gain and improvement in terms of trade and trade balance. RCEP also shows a
marked improvement in trade balance for the products it had comparative advantage.
With our analysis we can say affirmatively that India would be better off aligning with
RCEP instead of BRICS.
The possible reason could be as RCEP is group of 16 countries, 10 ASEAN and 6
ASEAN FTA’s partner countries, this agreement might act as a solution for the Asian
Noodle bowl problem. Having a one-mega bloc agreement instead of multiple RTAs,
CEPAs and CECAs, would create a trade between other member countries and divert
the trade from non-member countries. As the countries are already part of one or the
other agreement, it would be easy to have free trade flow because of similar trade
structures which means export can be easily substituted by other countries import.
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Section 7: Future WorkThe main limitation of this study is the application of static general equilibrium model
where dynamics aspects such as savings and investments are excluded from the
assumptions and capital stock is taken constant, mainly focusing on intersectoral
allocation of resources, for the assessment of India’s position in proposed trade
agreement with data of 2011 reference year. The results can be further improved by
using dynamic GTAP model as apart from obtaining results on variables that you are
already familiar with for the GTAP model, it also includes changes in foreign and
domestic wealth and growth rates in capital. It can answer important policy questions
such as: long run impact of change in policy variables on member countries and the
time required to achieve that stage wherein each member country will eliminate all the
tariffs in other member country’s export, among others. We can further incorporate
features of imperfect competition and scale economies.
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