indian tea industry

Impact on Import of Tea in India after Summer 2010 ASEAN INDIA FTA Agreement: A Simulation analysis

1. Introduction

The last two decades have witnessed a virtual explosion in the number of free trade agreements (FTAs), some of them involving several countries, many of them bilateral. The proliferation of FTAs has led to fierce debate about the merits of these agreements. While some herald the FTAs as stepping-stones towards worldwide free trade, others such as Bhagwati (1994), fear that preferential trading arrangements may lead to trade diversion and welfare loss. Recently, with the signing of the FTA with the 10 member states of the Association of South East Asian Nations (ASEAN), India too has belatedly joined the bandwagon. According to this agreement, about 80 percent of the traded goods will be subjected to tariff reduction or tariff elimination. The countries under ASEAN are: Brunei Darussalam, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand, & VietNam.

2. Objective of this term paper:

This paper will focus on the impact of the agreement in the selected plantation commodity, Tea, which is part of what is called the “special products” in India’s tariff reduction negotiations. India’s present tariff rate in this commodity is quite high by international standards. The ASEAN-India FTA (henceforth AIFTA) envisages that the tariff rates in these commodities will be brought down in a phased manner during 2010-19. “ASEAN and India signed the ASEAN-India Trade in Goods (TIG) Agreement in Bangkok on 13 August 2009, after six years of negotiations. The signing of the ASEAN-India Trade in Goods Agreement paves the way for the creation of one of the world’s largest free trade areas (FTA) – a market of almost 1.8 billion people with a combined GDP of US$ 2.75 trillion. The ASEAN-India FTA will see tariff liberalisation of over 90% of products traded between the two including the so-called “special products,” such as palm oil (crude and refined), coffee, black tea and pepper. Tariffs on over 4,000 product lines will be eliminated by 2016, at the earliest. The ASEAN-India TIG Agreement entered into force on 1 January 2010.” (ASEAN)

Since this commodity has been overly protected in India, tariff reduction may lead to a significant increase of India’s imports of Tea from the ASEAN countries. The possible surge in imports may have adverse impact on the domestic prices in India with significant implications for the livelihood of the Indian farmers engaged in the production of these commodities.

Against this background, the present study attempts to quantify the extent of import increase in Tea import as result of India’s tariff reduction commitments. Trade creation and trade diversion effects of the proposed tariff reduction schedules is simulated using partial equilibrium model, called the SMART model, developed jointly by UNCTAD and World Bank. “The SMART model also allows us to analyze the welfare and revenue effects associated with tariff reduction. The results of the SMART model, however, are sensitive to the underlying assumptions about the various elasticity parameters. Therefore, the SMART model simulations are complemented with simulations based on gravity model analysis. The advantage with the gravity model simulation is that it does not depend on any elasticity parameters. Tariff rates in the importing countries are used as one of the explanatory variables in the gravity model. The coefficient of the tariff variable in the estimated gravity model measures the responsiveness of imports to tariff changes. The estimated model is then used for analyzing the impact of different tariff reduction scenarios.” (Lang)

3. Presentation of Topics:

The paper is prepared according to following section: Section I discusses the main features of the

EM 556: Managing International Trade & Investment of 20


AIFTA as applicable to Tea. Section II analyses the trends and patterns of India and ASEAN bilateral trade in Tea. Section III deals with the SMART model simulations, where we quantify the extent of total import increase and decompose this into trade creation and trade diversion under different tariff reduction scenarios. This section also analyzes the revenue and welfare effects associated with tariff reduction. Section IV estimates the gravity model and then, using the estimated model, quantifies the extent of the increase in India’s imports under different tariff reduction scenarios.

4. Methodology used and Data presentation:

Basically the whole project is based on descriptive analysis and statistical analysis using SMART Model and Gravity Model discussed in the analysis part.

The graphical presentation of the proposed framework depicted the pattern of the structure of the relationship among the sets of measured variable. The purpose of the study is to measure correlation among the variables.

5. Source of Data:

All the information sources are taken from World Wide Web and National Tea Board of India.

6. Limitations of Data

1. Lack of time and budget2. Limited source of information

7. Indian Tea Industry

“The tea industry in India is about 172 years old. It occupies an important place and plays a very useful part in the national economy. Robert Bruce in 1823 discovered tea plants growing wild in upper Brahmaputra Valley. In 1838 the first Indian tea from Assam was sent to United Kingdom for public sale. Thereafter, it was extended to other parts of the country between 50's and 60's of the last century. However, owing to certain specific soil and climatic requirements its cultivation was confined to only certain parts of the country.

Tea plantations in India are mainly located in rural hills and backward areas of North-eastern and Southern States. Major tea growing areas of the country are concentrated in Assam, West Bengal, Tamil Nadu and Kerala. The other areas where tea is grown to a small extent are Karnataka, Tripura, Himachal Pradesh, Uttaranchal, Arunachal Pradesh, Manipur, Sikkim, Nagaland, Meghalaya, Mizoram, and Bihar.

Unlike most other tea producing and exporting countries, India has dual manufacturing base. India produces both CTC and Orthodox teas in addition to green tea. The weightage lies with the former due to domestic consumers’ preference. Orthodox tea production is balanced basically with the export demand. Production of green tea in India is small. The competitors to India in tea export are Sri Lanka, Kenya, China, Indonesia and Vietnam.

Tea is an agro-based commodity and is subjected to vagaries of nature. Despite adverse agro climatic condition experienced in tea growing areas in many years, Indian Tea Plantation Industry is



able to maintain substantial growth in relation to volume of Indian tea production during the last one decade.

There has been a dramatic tilt in tea disposal in favour of domestic market since fifties. While at the time of Independence only 79 M.Kgs or about 31% of total production of 255 M.Kgs of tea was retained for internal consumption, in 2008 as much as 802 M.Kgs or about 82% of total production of 981 M.Kgs of tea went for domestic consumption. Such a massive increase in domestic consumption has been due to increase in population, greater urbanisation, increase in income and standard of living etc.

“Indian tea export has been an important foreign exchange earner for the country. There was an inherent growth in export earnings from tea over the years. Till 70s’, UK was the major buyer of Indian tea Since 80s’ USSR became the largest buyer of Indian tea due to existence of the trade agreement between India and erstwhile USSR. USSR happened to be the major buyer of Indian tea accounting for more than 50% of the total Indian export till 1991. However, with the disintegration of USSR and abolition of Central Buying Mechanism, Indian tea exports suffered a set back from 1992 -93. However, Indian Tea exports to Russia/CIS countries recovered from the setback since 1993 under Rupee Debt Repayment Route facilities as also due to long term agreement on tea entered into between Russia and India. Depressed scenario again started since 2001 due to change in consumption pattern, i.e. switch over from CTC to Orthodox as per consumer preference and thus India has lost the Russian market. Another reason for decline in export of Indian tea to Russia is offering of teas at lower prices by China, South Asian countries like Indonesia and Vietnam.” (Chatergee)

The major competitive countries for India in tea in the world are Sri Lanka, Kenya, China and Indonesia. China is the major producer of green tea while Sri Lanka and Indonesia are producing mainly orthodox varieties of tea. Kenya is basically a CTC tea producing country. While India is facing competition from Sri Lanka and Indonesia with regard to export of orthodox teas and from China with regard to green tea export, it is facing competition from Kenya and from other African countries in exporting CTC teas.”( Chatergee)

“The tea industry occupies a place of considerable importance in the Indian economy, producing a fourth of the world’s annual tea output—among them some gardens producing high quality teas - and employing around 1.26 million people at tea plantations and 2 million people indirectly. With domestic demand at an estimated 825 million kg (MKg) as of 2008, India is one of the largest consumers of tea globally. However, as domestic demand accounts for over 85% of the country’s tea output and since tea imports are permitted only for re-export, India’s share of the global tea trade is on the lower side. Nevertheless, exports have a critical role to play in maintaining the demand-supply balance in the domestic market. Although tea is produced in 14 States in India, five of them—Assam and West Bengal in North India, and Tamil Nadu, Kerala and Karnataka in South India account for over 98% of India’s tea production. Within that, North India alone accounts for around 75% of India’s total tea production, of which 85-90% is consumed in the domestic market. The balance, much of it of high quality, is exported. Tea is among the most labour-intensive of all plantation crops. On an average, around 65% of the cost of production is incurred on labour.” (Roy & Das, 2009)

Because of absence of large domestic base and due to comparatively small range of exportable items, Sri Lanka and Kenya have an edge over India to off-load their teas in any international markets. This is one of the reasons of higher volume of export by Sri Lanka and Kenya compared to India. Another important point is that, U.K has substantial interest in tea cultivation in Kenya. Most of the sterling companies, after Indianisation due to implementation of FERA Act started tea cultivation in



Kenya. So, it makes business sense for U.K. to buy tea from Kenya and Kenya became the largest supplier of tea to U.K.

Tea is an essential item of domestic consumption and is the major beverage in India. Tea is also considered as the cheapest beverage amongst the beverages available in India. Tea Industry provides gainful direct employment to more than a million workers mainly drawn from the backward and socially weaker section of the society. It is also a substantial foreign exchange earner and provides sizeable amount of revenue to the State and Central Exchequer. The total turnover of the Indian tea industry is in the vicinity of Rs.9000 Crs. Presently, Indian tea industry is having (as on 18.12.2009 )

• 1692 registered Tea Manufacturers,

• 2200 registered Tea Exporters,

• 5848 number of registered tea buyers, • Nine tea Auction centres.

8. Import of Tea into India

India's tea imports are low, but had increased significantly until FY2005. Quantitative restrictions on tea imports were removed from March 2001. However, customs duty was raised from 35% to 70%, and subsequently to 100%. The bulk of the tea imported by India is orthodox tea from Indonesia, Vietnam and Sri Lanka. The industry is encouraging orthodox tea production as an import substitution strategy to reduce imports. India's tea imports are estimated to have declined significantly from 31.8 mkgs in FY2005 to around 18.7 mkgs in FY2006. India also imports Tea to various countries like Argentina, Bangladesh, China, Indonesia, Keya, Nepal, South Africa, Vietnam etc. with a high import duty of 70%. But from 2003-2008 the tariff rate significantly higher comparative to other SAARC countries. As a result the domestic deadweight loss is very high in that period.” (Tea Board of India)

Import of Tea in to India

YearQuantity(M.Kg)

Values (Rs. Crs.)

Unit C.I.F.price (Rs./kg)

1992-93 1.37 5.14 37.521993-94 0.87 3.99 45.861994-95 0.2 1.1 551995-96 0.45 2.41 53.561996-97 1.25 6.21 49.681997-98 2.61 17.79 68.161998-99 8.93 64.73 72.491999-2000 10.36 61.97 59.82000-2001 15.35 96.67 632001-2002 16.79 86.59 51.562002-2003 22.49 105.32 49.82


Import of Tea in India

0

20

40

60

80

100

120

140

160

180

200

1992

-93

1993

-94

1994

-95

1995

-96

1996

-97

1997

-98

1998

-99

1999

-200

0

2000

-200

1

2001

-200

2

2002

-200

3

2003

-200

4

2004

-200

5

2005

-200

6

2006

-200

7

2007

-200

8

2008

-200

9

Year

Quanti

ty &

Valu

e

Quantity(M.Kg)Values(Rs. Crs.)


2003-2004 11.36 66.23 58.412004-2005 32.53 145.15 44.612005-2006 17.41 102.77 59.032006-2007 20.8 111.02 53.372007-2008 16.75 108.07 64.512008-2009 22.3 181.45 82.36

Source: Archives from Tea Statistics in Tea Board of India

Source: Archives from Tea Statistics in Tea Board of India

Tariff:

Tax levied upon goods as they cross national boundaries, usually by the government of the importing country. The words tariff, duty, and customs are generally used interchangeably. Usually assessed on imports, tariffs may apply to all foreign goods or only to goods produced outside the borders of a customs union. A tariff may be assessed directly, at the border, or indirectly, by requiring the prior purchase of a license or permit to import specified quantities of the good. Examples of tariffs include transit duties and import or export taxes, which may be levied on goods passing through a customs area en route to another destination. In addition to providing a source of revenue, tariffs can effectively protect local industry by driving up the price of an imported item that competes with domestic products. This practice allows domestic producers either to charge higher prices for their goods or to capitalize on their own lighter taxes by charging lower prices and attracting more customers. Tariffs are often used to protect “infant industries” or to safeguard older industries that are in decline. They are sometimes criticized for imposing hidden costs on domestic consumers and encouraging inefficiency in domestic industries



9. AIFTA’s Tariff Reduction Schedules

“The ASEAN-India Free Trade Agreement (AIFTA), which has been concluded after protracted discussions, is a strategic event that holds promise for both parties. The FTA signals India’s readiness to contribute to the development of the region, and seek benefits from the process. There is no doubt that ASEAN welcomes India’s involvement in the region. India’s trade with ASEAN has not been spectacular. India has been running a deficit with ASEAN in the last decade, and the deficit has been growing. India’s trade deficit with ASEAN has increased from about US$2 billion in 1998 to around US$15 billion in 2007. The widening trade deficit is a reflection of India’s trade trends with ASEAN. In 2004-05, India’s total imports from ASEAN were worth roughly $9 billion, with exports amounting



to $8 billion. In 2007-08, total imports ($22 billion) continued to exceed exports ($16 billion), with a trade deficit around $6 billion. But total trade between the two has been increasing rapidly.”(Nambiar, 2010)

“India has been willing to extend tariff reduction commitments on 89 per cent of its tariff lines through the AIFTA. India has also signaled its intention to lower tariffs on highly sensitive items like palm oil, tea, coffee and pepper. The import duties on these commodities will be lowered to around 40-45 per cent by 2019. The stance that India has taken on these agricultural commodities, in the face of domestic resistance, indicates the store the government puts on the agreement. It is also an indication of India’s long-term economic interest in ASEAN and the synergy that it envisages it could develop with the region over time.”( Nambiar, 2010)

As per the agreement, the tariff lines (HS 8-digit items) subject to tariff reduction and/or elimination are categorized into four groups. First, about 74% of India’s tariff lines are under the ‘normal track’ category, where tariff rates will be reduced first and subsequently eliminated. Second, about 15% of the tariff lines are under the ‘sensitive track’, where tariff rates are to be reduced to 5% or less by a certain date. Third, a few tariff lines (about 40) are refereed to as India’s ‘special products’, where India has decided to reduce tariff rates at a much more gradual pace than either the normal track or the sensitive track. The ‘special products’ include plantation commodities such as coffee, tea, pepper and palm oil. Finally, there is an ‘exclusion list’, where no tariff reduction commitments have been made. The agreement provides for safeguard measures in the event of imports causing substantial injury to the domestic producers. The agreement also has quite strict provisions for rules of origin.

Chart 2 shows the changes in India’s import tariff rates in the three plantation commodities during the period 1990-2008. It can be seen that the tariff rates of Tea were as high as 100% in 1990. As part of the trade liberalization process initiated in India since 1991, the tariff rates had been brought down considerably during the 1990s. However, in a significant reversal of this trend, the tariff rates have been raised significantly during the early 2000s and remained high till 2008.



Table 2 shows the AIFTA’s proposed tariff reduction schedule for the Tea. The applied tariff rates for tea will be reduced in accordance with the tariff reduction schedule shown in the Table. It can be seen that, during the period from 2010 to December 2019, the tariff rates for Tea will be brought down from the base rate at an average annual rate of 6.9%. It may be noted that the extent of tariff reduction is rather modest and even by 2019 tariff rates would remain quite high. However, since this product has been overly protected in India, even a modest tariff reduction can lead to significant increase of imports.

Table 2: Tariff Reduction Schedule for Tea

CommoditiesBaseRate

Proposed Tariff RatesDec

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2019Tea 100 95 90 85 80 75 70 65 60 55 50 45

Source: India-ASEAN Trade in Goods Agreement

India-ASEAN Trade in Tea: General Trends

and Patterns



From Chart A2 it is clearly visualized that India’s imports are generally are higher than exports in Tea. The period starting from 1993 is considered since the full convertibility on current account was adopted in India in the year 1993. India’s tea imports show significant fluctuation throughout the period 1995-2008 while exports showed some increase in 2006 and then declined in 2008.

In order to gauge, from the past data, the effect of tariff rates on import growth rate, we identify two distinct phases based on the tariff data shown in Table 2: low tariff phase (1993-1999) and high tariff phase (2004-2008). The tariff rates started showing an increasing trend in the year 2001. However, tariff data are not available for 2002 and 2003. Therefore, based on the available information, we consider the sub period 2004 -2008 as the high tariff phase. During this period, tariff rates remained high for all the commodities – that is, 100% for Tea. Table 3 reports the average annual growth rates of India’s exports and imports (in quantity terms) in the three commodities during the two phases.

Table 2: Average Annual Growth Rates of Exports and Imports, Quantities (KG)

As expected, the import of tea showed a very high growth rate during the low tariff phase while the growth rates have been negative during the high tariff phase. In the meanwhile, the growth rate of export was negative during the low tariff phase and positive in High Tariff phase. Therefore, the analysis indicates that the reduction in tariff may cause significant increase in imports while its impact on exports is not clear.


Commodities

Export Import

Low tariffphase:

High tariffphase:

Low tariffphase:

High tariffphase:

Tea -12.6 25.4 136.6* -26.4Note: (i) * Import growth rate for Tea is calculated for the period 1995-99 due tonon-availability of data for 1993 and 1994.Source: COMTRADE-WITS


10. Simulation Analysis

C. Veeramani and Gordhan K. Saini (2010) from Indira Gandhi Institute of Development Research (IGIDR) conducted a simulation analysis on the features of the partial equilibrium models used to simulate the trade impact of the AIFTA in subsection IV.1. Subsections IV.2 and IV.3 discuss the simulation results based on the SMART and gravity models respectively as discussed earlier. I will be discussing some of the outcomes from that experiment to get an idea about how AIFTA will impact on the tariff reduction and thereby economic welfare.

10.1 Partial Equilibrium Analytical Tools for Trade Policy Simulations

According to the theory of customs unions, whether or not the increase in trade caused by the FTA would be welfare improving depends on the source of the increased trade; that is the extent of trade creation relative to trade diversion (Viner, 1950). Trade creation occurs when the lowering of tariffs allows partner country imports to replace high-cost domestic production; this improves welfare. Trade diversion, on the other hand, occurs when the removal of tariffs causes trade to be diverted from a third country to the partner country despite the fact that, were the countries treated equally, the third country would be the low cost source of imports.

SMART Model

In order to simulate the trade creation and trade diversion effects of the proposed tariff reduction in the selected commodities, we use an ex ante partial equilibrium model (called the SMART model), measuring the first-round effects of the simulated tariff changes. “Unlike the general equilibrium models, the partial equilibrium models do not take into account the second-round effects of trade policy changes. A major advantage of the partial equilibrium approach is that it is relatively simple to compute and can be applied at a very fine level of detail. The SMART model, developed by UNCTAD and World Bank, is available in the World Bank’s World Integrated Trade Solution (WITS). The WITS brings together the various databases on trade flows and trade policy instruments. It also integrates analytical tools that support simulation analysis. The SMART model is one of the analytical tools in the WITS used for simulation purposes.”( WITS official website)

The SMART contains in-built analytical modules that support trade policy analysis, covering the effects of multilateral tariff cuts and preferential trade liberalization. It focuses on one importing market (in our case India) and its exporting partners (in our case ASEAN countries) and assesses the impact of a tariff change scenarios by estimating new values for a set of variables. “In addition to decomposing the total trade effect in to trade creation and trade diversion, the SMART model can be used to analyze welfare and revenue effects. The net welfare gain/loss estimated in the SMART model, depends on (i) the additional tariff revenue entailed by the increase in imports and (ii) the additional consumer surplus entailed by the increase in imports.” (WITS official website)

Veeramani & Saini mentioned that the SMART model relies on Armington assumption – that is, similar products from different countries are imperfect substitutes. The representative agent maximizes her welfare through a two-stage optimization process: First, given a general price index, she chooses the level of total spending/consumption on a ‘composite good’. The relationship between changes in the price index and the impact on total spending is determined by given import demand elasticities. Second, within this composite good, she allocates the chosen level of spending among the different ‘varieties’ of the good, depending on the relative price of each variety. The extent of the between-variety allocative response to change in the relative price is determined by the Armington substitution



elasticity (1.5 in the SMART model). However, SMART Model is very sensitive to the choice of the different elasticity values

That why Veeramani & Saini used second model named Gravity model which does not rely on any elasticity parameters and can be used to simulate ex ante the potential increase in imports under different tariff reduction scenarios. These models have been widely used to analyze the bilateral trade flows between country pairs and have been successful to a high degree in explaining trade flows. (Harrigon, 2001 and Anderson and van Wincoop, 2004). In addition to the standard gravity variables, they included the tariff rate in the importing countries as a separate independent variable. The coefficient of the tariff variable in the estimated gravity model measures the responsiveness of imports to tariff changes. The estimated model is then used for analyzing the impact of different tariff reduction scenarios.

10.2 Simulation Analysis using the SMART Model

Veeramani & Saini quantified trade impact of the proposed tariff reduction scenarios of Tea. It is evident from the tariff reduction schedule shown in Table 2 that the tariff rate in Tea will be reduced from the base rate of 100% to 70% by 2015 and further to 45% by December 2019. Accordingly, two tariff reduction scenarios have been considered as follows:

Scenario 1: base tariff rate to be reduced to the scheduled rate for the year 2015; tariff rates for Tea will be brought down from 100% to 70%.

Scenario 2: base tariff rate to be reduced to the scheduled rate for December 2019; tariff rates for Tea will be brought down from 100% to 45%.

The simulation results at the under the above two scenarios are shown in Table 3 and 4. The simulation results in Table 3 are based on the assumption of infinite export supply elasticity (suppose say for Indonesia the infinite export supply elasticity for Green Tea, HS Code: 090210, is -37.23579) while the results in Table 4 are obtained based on the assumption of finite export supply elasticity values. The table reports the increase in total imports of tea and its decomposition in to trade creation and trade diversion. It also reports the loss in tariff revenue and the overall welfare effects.

Table 3: Aggregate Impacts in each Commodity under Different Tariff Reduction Scenarios, Simulation Results Based on the SMART Model (values in 000 US$)



Table 4 Aggregate Impacts in each Commodity under Different Tariff Reduction Scenarios, Simulation Results Based on the SMART Model (values in 000 US$)

Commodity

Base YearImpor

2007

Total Increasein Imports

TradeCreat

on

TradeDiversion

P

Eff

Loss

nTar

Revenue

Tota

We

fare

Scenario 1Value%%%%

Value

Value

Tea

10312

3603

34.9

20.0

11.7

3.2

-1903

2096

Scenario 2Value%%%%

Value

Value

Tea

1031

6683

64.8

36.7

22.2

5.9

-518

3492


Commodity Base Year

Import(2007)

Total Increasein Imports

TradeCreation

TradeDiversion

Loss inTariff

Revenue

TotalWelfare

Scenario 1Value % % % Value Value

Tea 10312 3801 36.9 23.2 13.7 -1841 2207

Scenario 2Tea 10312 7065 68.5 42.5 26.0 -5170 3671


2 3

The results in both the tables reveal that trade creation dominate over trade diversion and under both the scenarios. The results suggest that the total increase in imports is mostly driven by trade creation. It is evident that, at least in the context of tea, the AIFTA does not lead to significant trade diversion. As discussed earlier, trade creation improves welfare as the new imports replace high-cost domestic production.

The analysis shows that the proposed tariff reduction may lead to significant tariff revenue loss to the government under both the scenarios. However, the gain in consumer surplus (due to the fall in domestic price) outweighs the loss in tariff revenue leading to net welfare gain.

The assumption of infinite export supply elasticity implies that trade does not affect domestic prices and hence the results in Table 3 do not include price effects (which is zero). The assumption of finite export supply elasticity, however, implies that tariff change will generate price effects (positive or negative). Therefore, the results in Table 4, which assume finite export supply elasticity, show the price effect. It can be seen that the price effects in Table 4 are positive, which implies a terms of trade gain for India. The mechanisms that lead to India’s terms of trade gain can be explained as follows.

There will be a downward pressure on prices in India due to her higher imports (or excess supply) and there will be an upwards pressure in the ASEAN due to higher exports (or excess demand). If the downward pressure on price (in India) is higher than the upward pressure (in ASEAN), there will be a net fall in the prevailing price in ASEAN post tariff reduction (The Indian price (pi) is related to the ASEAN price (pa) as follows: pi = (1+t) pa, where t is the tariff rate. Therefore, pa = pi / (1+ t)). India, being an importing country, derives a terms of trade gain (loss) if the ASEAN price falls (increases) in the post tariff reduction equilibrium. It may be noted that India derives a terms of trade gain in tea. There will be a positive optimal tariff that will maximize national welfare of India.

We now turn to examine how the total trade creation tea is distributed across the ASEAN trading partners (Table 6). Vietnam accounts for the largest share of trade creation while Indonesia accounts for the largest share in coffee. The contributions of Malaysia, Singapore and Thailand are not significant.

Table 6: Trade Creation in each Commodity with each ASEAN Partner (values in 000 US$)

CommodityBase Year Import

(2007)

Scenario 1 Scenario 2

Trade Creation Trade Creation

Value Value ValueTea 10312 2063 3782

Indonesia 3014 (29.2) 607 (29.4) 1113 (29.4)Malaysia 97 (0.9) 19 (0.9) 36 (0.9)Singapore 0 (0.0) 0 (0.0) 0 (0.0)Thailand 0 (0.0) 0 (0.0) 0 (0.0)Vietnam 7201 (69.8) 1436 (69.6) 2633 (69.6)

Note: (i) figures in parentheses are percentage shares of each commodity total; (ii) finite export supply elasticity values are assumed.



While we have noted that trade creation generally dominates over trade diversion, it is of interest to identify the countries from which trade is being diverted to the ASEAN. In the present context, trade diversion is said to occur when the removal of tariffs causes trade to be diverted from a non-ASEAN country to one or more of the ASEAN country. Table 7 provides a list of the top 10 non-ASEAN countries whose trade is being diverted to the ASEAN due to the AIFTA. It can be seen that, as expected, the list contains a large number of least developed or developing countries. The most affected country in tea is Kenya.

Table 7: List of Top 10 Non-ASEAN Countries whose trade is being diverted to the ASEAN Countries (values in 000US$), Scenario 2

sl.No.

Tea

Country Value1

Kenya -1021.12

Nepal -593.63

China -235.74

Argentina -230.55

Papua New Guinea -109.36

Sri Lanka -91.27

United Kingdom -69.48

Malawi -68.29

Iran, Islamic Rep. -49.210

Brazil -16.9

Note: (i) finite export supply elasticity values are assumed.

Gravity Model Analysis

As mentioned earlier, SMART simulation results are very sensitive to the choice of the elasticity parameters. An alternative approach, Veeramani & Saini used the gravity model. Tariff rates in the importing countries are used as one of the explanatory variables. The coefficient of the tariff variable in the estimated gravity model measures the responsiveness of imports to tariff changes. The estimated model is then used to simulate the likely increase in imports under the different tariff reduction scenarios.



The main idea of the gravity model is borrowed from the Newtonian model of gravitational forces – that is, the force of attraction between two bodies is proportional to the product of their masses and inversely proportional to the square of the distance between them. The simplest gravity model predicts that the trade between two countries will be proportional to the product of their gross domestic products and inversely proportional to the physical distance between them. This basic model can be augmented using other variables that can facilitate or hinder bilateral trade flows. The reduced form of the augmented gravity model is specified as follows:

Veeramani & Saini used the Tobit model, which addresses the estimation problems arising from the truncation of the dependent variable. The Tobit regression results are shown in Table 8. They estimated two regression equations; one using simple average tariff rate and another using weighted average. It is evident that the coefficients of all the independent explanatory variables show correct signs and are statistically significant at 1 percent level. As expected, both the tariff variables yield negative signs with statistical significance for tea. The point estimates suggest that the elasticity of import of tea with respect to tariff is in the range of –0.24 to –0.26. Taking the midpoint of the elasticity range for tea, the results imply that a 10% reduction in import tariff (TARj) increases import by about 4.2 percentage points, which is quite large.



Size of the exporting and importing countries are measured by their GDP. More specifically, GDPi

will capture the effect of the level of supply in the exporting country while GDPj will capture the effect of the level of demand in the importing country. As expected both GDPi and GDPj show a statistically significant positive coefficient, which implies that higher output levels (GDP) in both the exporting and importing countries stimulate higher volume of trade. The results show that higher population size of the exporting country (POPi) causes higher volume of exports due to their higher supply. In contrast, higher population size of the importing country (POPj) causes lower volume of imports.

That the volume of bilateral trade falls with geographical distance is a well documented fact (e.g., Leamer and Levinsohn, 1995). The volumes of bilateral trade between geographically closer countries tend to be higher due to the lower transport and search costs and other advantages arising from greater geographical proximity. Indeed, the variable DISTij yield a large statistically significant negative coefficient, indicating that the countries that are geographically closer trade more.

Table 8: Tobit Estimation Results of the Gravity Model, 2007

ExplanatoryVariables

Tea(1) (2)

GDPi 1.090 1.091(0.057) (0.057)

GDPj 1.462 1.463(0.069) (0.071)

POPi 0.766 0.765(0.063) (0.063)

POPj -0.423 -0.424(0.075) (0.078)

DISTij -2.001 -1.996(0.082) (0.082)

BORDij 1.550 1.562(0.330) (0.330)

LANGij 2.575 2.594(0.177) (0.177)

COLij 2.204 2.191(0.343) (0.343)

SMCTYij 1.878 1.878(0.460) (0.460)

TARj (Simple -0.258Average) (0.059)TARj

(Weighted-0.235

Average) (0.059)-59.085 -59.205

Constant (1.629) (1.630)Number ofobservation 18792 18792

- -Log likelihood 10189.620 10191.275



LR chi2(10) 5204.620 5201.310Prob > chi2 0.0000 0.0000

Note: (i) values in parenthesis represent standard error; (ii) all coefficients are significant at 1 percent level

Countries that share a common border are likely to trade more again due to lower transport and search costs and other advantages arising from greater geographical proximity. As expected the border dummy (BORDij) show a significant positive coefficient. Similarily, common cultural and political history can stimulate bilateral trade. Thus we include the dummies to capture common language (LANGij ), colonial history (COLij) and political history (SMCTYij). As expected, the coefficients of all these variables are positive and statistically significant.

Using the estimated regression equations in Table 8, we now proceed to simulate the extent of import increase due to tariff reduction under the two scenarios considered earlier. While the SMART and gravity models provide some differences on the relative magnitude of import increase of tea. The gravity model suggests that under both the scenarios the percentage increase for tea in import is 10% and 22% respectively under scenario 1 and 2 while the SMART model indicates the percentage increase for tea in import is 20% and 36% respectively under scenario 1 and 2 (Table 9).

Table 9: Import Increase in each Commodity under Scenario 1 & 2, Simulation Results based on the Gravity Model (values in 000 US$)


(2007)

Import Increase under Import Increase under


Value % Value %

Tea 10312 981 10 2318 22

Finally, Table 10 shows the partner-wise distribution of import value increase in tea under the two scenarios. Overall, the pattern remains the same as discussed earlier with reference to the SMART simulation results.

Table 10: Partner-wise Import Increase in each Commodity under Scenario 1 & 2, Simulation Results based on the Gravity Model (values in 000 US$)


(2007)


Import Increase Import Increase

Value Value Value

Tea 10312 981 2318Indonesia 3014 287 678Malaysia 97 9 22Singapore 0 0 0Thailand 0 0 0Vietnam 7201 685 1619



11. Conclusion

Overall, the results suggest that the AIFTA will cause significant impact in increase in imports mostly driven by trade creation rather than trade diversion. From the point of view of economic efficiency, trade creation improves welfare as the new imports replace the high-cost domestic production. The analysis shows that the proposed tariff reduction may lead to significant tariff revenue loss to the government. However, the gain in consumer surplus (due to the fall in domestic price and the consequent reduction in dead-weight loss) outweighs the loss in tariff revenue leading to net welfare gain.

Even though, the AIFTA envisages rather modest reduction of India’s import tariff in tea, my analysis shows that even such a small reduction in tariff will lead to significant import increases into India. While the AIFTA is welfare improving for the consumers of tea in India, the surge of new imports may have adverse impact for the livelihood of the farmers engaged in the production of these commodities. Farmers will have to realign the structure of production according to the changing price signals and hence it is critical to provide adjustment assistance to the affected farmers.



References:

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http://www.hubrural.org/pdf/uneca_partial_equilibrium_analysis_of_impact_of_ecowas_eu_epa.pdf

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