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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

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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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