Impact of SAFTA on Pakistan’s Trade
Info: 40485 words (162 pages) Dissertation
Published: 13th Dec 2019
Tagged: EconomicsInternational Studies
Abstract
This paper assesses the potential economic impacts of South Asian Free Trade Area that was signed in 2004, on Pakistan’s trade using the GTAP Model which is a Computable General Equilibrium Model. The proliferation of regionalism and opening up of economies towards free trade has led to creation of SAFTA. The need for economic development for South Asian countries has also led to the need for such an agreement. The problem statement of the paper is “How will South Asian Free Trade Area benefit Pakistan’s trade and what factors are required to make SAFTA successful? The desirability of this paper lies in the fact that it investigates why there is need for SAFTA with focus on Pakistan. It also uses a comparatively newer version of GTAP database with respect to previous literatures.
GTAP database 7 has been used in the paper to assess the possible effects of complete trade liberalization. Actual trade data after the implementation of SAFTA from 2006-2014 was used to support and analyze the simulation results.
Several conclusions were drawn. Firstly, SAFTA is beneficial to Pakistan’s trade as it will increase Pakistan’s exports at a higher rate than imports; there will be decreased trade balance deficit and a trade surplus through trade with SAFTA members however at the cost of negative welfare effects. Total intraregional trade will increase in the region which is the main purpose of forming SAFTA therefore the trade arrangement is recommended to be implemented at an accelerated pace. There are issues with implementation of SAFTA that need to be corrected which include hostile political climate, lack of political will, supply-side issues and weak SAFTA framework.
Governments need to collaborate and reduce tariff rates at a more accelerated pace. They are already behind schedule. Pakistan’s policy makers are advised to take steps to make sure SAFTA is operational fully to maximize benefits. A separate government division should be created that monitors and controls the effectiveness of SAFTA on a regular basis and is to be strengthened with more autonomy. Exporting companies should be fostered with special attention to investment in research and development, technological advancements and financial aids and help in facilitating exports of products for export businesses. Pakistan is advised to take the first step in reducing hostilities by eliminating items from the sensitive lists as quick as possibly.
[Keywords]: SAFTA, Regional Trade Agreements, Pakistan trade, GTAP.
Contents
Chapter Two Pakistan and South Asian Free Trade Area
2.1 Background of Regional Trade Agreements
2.2 Pakistan and Free Trade Arrangements
2.3 Background of South Asian Free Trade Area Members
2.4 History of South Asian Free Trade Area
3.1 Computable General Equilibrium Model
3.3 Design Scenarios of Trade Liberalization
3.4 Comparison with Actual Trade Data
Chapter Four Results and Analysis
4.2 Effects on Intraregional-trade
4.6 Comparison of Results using Actual Trends
Chapter One Introduction
1.1 Background of Research
Pakistan is a nation that came into existence in August 1947. It is currently a developing country and thriving to become a prosperous nation in terms of economy, peace and prosperity. It opened up its economy to the world in the early 1990s after realizing that the economy can only grow rapidly if it increases trade with the rest of the world.
With the rapid proliferation of Regional Trade Agreements in the early 90s and in the past twenty to thirty years; most notable success story comes from European Union that is now a customs union. Countries that join Regional Trade Agreements have the advantage of increased access to markets firstly in terms of international trade. They benefit from similar characteristics in culture and geography that allows producers of goods to reach out to a larger and wider market. Secondly, resource market increases immensely since inputs for production become much cheaper and more easily available. Relaxed border laws allow mobility of labor that increases labor resource in terms of quantity and quality. Capital flow and investment increases with the access to large markets and the huge potential for business. The EU is an example of peace in the region since countries are members of one union with common goal of economic prosperity; there is low proportion of expenditure on military which allows for countries to allocate more towards the economy and the social welfare of its citizens.
For Pakistan, trade is an essential part of economic growth. Pakistan moved from its import substitution and protectionist schemes in the early nineties and opened doors to the outside world by welcoming foreign investment and export oriented policies. Pakistan however has always been in a state of trade deficit which means that there has always been flow of income out of the economy. In recent years, the Ministry of Commerce realized the importance of trade and stated that the country’s basket of goods for imports is more price-inelastic therefore in order to improve Pakistan’s trade balance there is not much that can be done through the manipulation of imports. Therefore, the exports of Pakistan which consists of a narrow basket of similar goods, including textile and agricultural products of primary industry nature which are highly price elastic are the target of latest policy-making. With collective measures of trade facilitation, export subsidies and financing, export promotion and several other measures, the government aimed to increased exports to spark the rise of number of export oriented policies with government support. Very prominent ties with different countries have also been made for example with Sri-Lanka, Malaysia and other ASEAN countries, and China through bilateral free trade agreements. The South Asian Free Trade Area is one of the products of free trade area that the government has shown keen interest in.
Various trade theories are available that explain the benefits of trade to enhance economic growth. The earliest trade theories known as mercantilism promoted exports as it increased country’s wealth. “To increase wealth; sell more to strangers yearly than we consume of theirs value[1]” (Mun, 1664). This means that increase one’s wealth, one must sell or in other words, engage in trading with another entity or country and profit from them.
Secondly, the theories of Absolute[2] (Smith, 1776) and Comparative Advantage[3] (Ricardo, 1817) can help in explaining the benefits trade. These theories both emphasize on the importance of specialization which results in increased production and availability of two goods when each country focuses on one product instead of two.
Finally, “New Trade theory” introduced in 1979 by Krugman that countries can gain from trade since the market base is larger and producing countries can benefit from increasing returns to scale or economies of scale[4].
Keeping such benefits in mind, Pakistan and countries the South Asian countries realized this potential and formed the South Asian Association for Regional Cooperation initially for the purpose of peace and cultural sharing. Later the South Asian Preferential Trade Agreement was signed for a more economic motive. Seven member countries of SAARC signed the South Asian Free Trade Area in 2004 and Afghanistan later joined to become the eighth member. This agreement had a clearer economic view and a more focused framework for trade liberalization among the SAARC members. Modeling the European Union, SAFTA’s ultimate goal is to become a customs union.
Therefore, this research was carried out to identify the potential economic effects of SAFTA particularly aiming at Pakistan and its trade potential after complete trade liberalization. There have been several researches conducted on potential effects of Regional Trade Agreements that have definitely been in favor of RTAs. Similarly there are many researches specifically aimed at the potential effects of SAFTA that have deemed them beneficial. Only a handful of researches have been conducted with specific focus on Pakistan but though the model and methodology carried out is similar, it has been used with an updated database, therefore validating the motive for carrying out this research.
The potential effects on trade of Pakistan were conducted with the help of a popular methodology used in policy analysis worldwide by a large network of researchers called the GTAP Database. It is a Computable General Equilibrium Model that simulates the effects of policy shock, in case of this research, elimination of import tariff, from a state of economy which is the base year before the policy implementation to a state of economy after the policy is implemented. The results yielded from running the simulation showed interesting and significant results that proved that SAFTA is overall beneficial to Pakistan’s trade. In short, it was found that after all tariff rates were removed among all the member countries of SAFTA, the intra-regional trade increased and both imports and exports rose for Pakistan. Exports rose at a rate faster than imports, which is a good sign for the trade balance of Pakistan, even though the trade balance for Pakistan remained at a deficit. Positive effects were also shown on the industrial output of the country. Overall welfare for Pakistan however found to be at loss while for India it was found to be the opposite. Similarly GDPs major components of consumption and investment expenditure decreased at the cost of increased trade for Pakistan.
The research paper is divided into five main sections. The first section introduces the research paper, gives background information about Pakistan’s economy, background information of SAFTA members, the history of SAFTA, its core elements, and its current status. The second section provides a literature review of previous works done on the topic of regional trade agreements and South Asian Free Trade Area. The third section provides detailed information on the methodology used in this paper and a review of all the methods and options available to conduct the research, the fourth section discusses the results from running the GTAP simulation and the fifth and final section concludes the paper with recommendations to policy makers.
1.2 Research Objectives
Owing to the rapid proliferation of Regional Trade Agreements and its benefits as well as the need for Pakistan and South Asian nations to improve their economy and standard of living through increased trade-particularly through increased regional cooperation and increased intraregional trade, this paper aimed to find out how beneficial the completion of South Asian Free Trade Area would be to these countries especially for Pakistan in terms of international trade. Therefore the problem statement is “How will South Asian Free trade Area benefit Pakistan’s trade and what factors are required to make SAFTA successful.”
This paper assesses the impact of SAFTA on Pakistan’s trade at a time when Pakistan is looking for ways to increase its economic growth through trade. At a time when Pakistan is considering bilateral trade agreement options with other countries and where SAFTA’s complete implementation is going at a slow pace. This paper tends to be a reminder and update of previous literatures to show the policy makers that SAFTA is a beneficial option that needs attention.
The paper uses GTAP simulation model with an updated version 7. Previous works on SAFTA focus on Pakistan’s economy in general terms, and versions no later than GTAP version 5. The paper focuses more on trade and intraregional trade of Pakistan using a later database version, even though due to shortage of resources, the latest version of GTAP 8 or 9 could not be used. It also makes use of the latest, actual trade data after the signing of SAFTA in its analysis.
1.3 Literature Review
1.3.1 Reasons for Regional Trade Agreements
In recent years, Regional Trade Agreements have witnessed to be proliferating. In 2013, there were 546 RTAs notified by the World Trade Organization of which 345 were active (Kahouli & Maktouf, 2014). The reasons for the proliferation cannot be explained in simple terms as according to Fernandez & Portes (1998) there is no “One-size-fits-all” explanation of the proliferation and Regional Trade Agreements are all different in scope, motivation and coverage.
The benefits and reasons for having Regional Trade Agreements have been discussed in various literatures mostly pertaining to trade creation, trade diversion and welfare. Many literatures have praised three popularly known Regional Trade Agreements; NAFTA, EU, and ASEAN including Akhtar & Ghani (2010) and Whalley (1998). Akhtar & Ghani (2010) state the welfare benefits in the form of improved standard of living for NAFTA, EU, and ASEAN members resulting from Regional Integration and also discuss the concept of trade creation and trade diversion benefits from signing RTAs along with Koo, Kennedy, & Skripnitchenko (2006), and Jayasinghe & Sarker (2008). According to Koo, Kennedy & Skripnitchenko (2006),
Trade creation is the increase in trade volume through the replacement of domestic products with low-priced imports from trading partners and Trade diversion is the increase in trade volume through replacement of imports from third countries with low-priced imports from trading partners in free-trade areas for example U.S shifting textile imports to Mexico from China through NAFTA. ASEAN and CER members’ foster greater trade worldwide hence having welfare enhancing effects (Jugurnath, Stewart, & Brooks, 2007).
Whalley (1998) is of the opinion that RTAs are formed for six reasons which include traditional trade gains, strengthening domestic policy reform, increased multilateral bargaining power, strategic linkages, and guarantees of market access, multilateral and regional interplay. Bilateral trade rises by 50% and in 10 years it can rise by more than 100% (Baier & Bergstrand, 2007). Ahmed & Bhatnagar (2008) state that RTAs, specifically South Asian Association for Regional Cooperation are formed for geopolitical advantages, to promote regional identity and to improve intra-regional trade and social and political development. Fernandez & Portes (1998) state that RTAs increase private sector capital flow.
Forty percent of the global trade is done among regional partners (Pal, 2008). The average effect according to Grant & Lambert’s (2008) findings was that 72% increase in members’ agricultural trade not occurring immediately but after ten years and increase in members’ agricultural trade by 149% after 12 years. It was also found that 137% increase in trade was experienced by NAFTA/CUSTA but one-third of the effect was faced after twelve years. Similarly Koo, Kennedy, & Skripnitchenko (2006) found that PTAs on agricultural trade had significant positive effects on overall trade and increased trade volumes among member nations through inter as well as intra industry trade. Along with this it was found that RPTAs are not harmful to non-member countries and can help in improvement of global welfare.
In South Asian perspective, closer economic integration leads to increase in intra-regional trade particularly in the manufacturing sector. (Mehta & Bhattacharya, 2000).If Pakistan, Sri Lanka and India cooperate and integrate economic efforts; trade can increase by thirty times (Akhtar & Ghani, 2010).
1.3.2 Measuring and Modeling
The Gravity Model has been used by prevalent researches and was first introduced by Tinbergen (1962). The model is argued to have lack of theoretical backing but Feenstra, Markusen, & Rose, (1998) and Estevadeordal, Frantz, & Taylor (2003) were able to provide enough theoretical backing of the model. From the review of literature, it was found that while some used standard and basic gravity model like Vincent (2011), Koo, Kennedy, & Skripnitchenko (2006) and Jugurnath, Stewart, & Brooks (2007),others used more complex and modified models of the gravity model including two-step regression model (Shariat Ullah & Inaba, 2012),Extended Gravity Model (Jayasinghe & Sarker, 2008), the Calibrated General Equilibrium Model (Whalley, 1998), Generalized Gravity Model (Rahman, 2004), and Static and Dynamic Gravity Models (Kahouli & Maktouf, 2014).
All the gravity models show negative effect of distance on international trade according to (Krugman & Obstfeld, 2009). Similarly, according to gravity model, trade is proportional to the national income and inversely related to the distance which is a proxy for transportation and information costs (Akhtar & Ghani, 2010)
According to MacPhee & Sattayanuwat (2014), there are two categories of analyzing FTA policy effects; ex-poste and ex ante. Ex-poste utilizes data on both before and after RTA has been formed and studies the effect of RTAs on trade shares of members and non-members. Ex ante on the other hand predicts before RTAs are formed using estimated parameters and data corresponding to the period preceding the formation of RTA. Ex ante usually include Computable General Equilibrium Models.
Johnson (1960) explained trade diversion and trade creation effects with the help of a partial equilibrium diagram that he developed. This followed from the works done by Viner (1950) where welfare effects of customs unions were explained by difference in trade diversion and trade creation. This is a classical theory which argues that customs unions or regional trade agreements do not always have positive effects. A more related comprehensive and complex model is the Computable General Equilibrium Model that has been introduced by GTAP- Global Trade Analysis Project, and is widely known in literatures as the GTAP model. Introduced by Hertel (1997), the model is multi-regional, multi-sectoral (Global Trade Analysis Project, 2015) Computable General Equilibrium Model that is widely used for its better understanding of the effects of PTA (Bandara & Yu, 2001). Several literatures (Bandara & Yu, 2001), (Siriwardana, 2004) (Kumar & Saini, 2009) (Heng & Gayathri, 2004) (Hertel, Walmsley, & Itakura, 2001) have used the GTAP model and scholars have agreed that it is more useful that econometric models and partial equilibrium models in analyzing PTAS. They have agreed that the model incorporate necessary links between different agents in each country or region, are based on input-output structures of each country which links industries together, and that the global CGE model reflects the fact that all parts of the world economy hinge together in a network of linkages-direct or indirect and changes in any part of the system will result in different effects throughout the world.
1.3.3 Failures of Regional Trade Agreements
Some studies found that RTAs failed to yield positive effects on International Trade. Krugman & Obstfeld (2009) is of the opinion that even if goods and services face few legal restrictions or do not have to pay tariffs, there is a lot more trade between regions of the same country instead of between different countries in equivalently situated regions. Ahmed & Bhatnagar (2008) found that SAARC member countries failed to yield positive results due to ineffective administration of several initiatives, lack of trust among member nations, territorial disputes, cross-border terrorism, water sharing disputes and problems of member countries’ refugees and migration at their borders. MacPhee & Sattayanuwat (2014) similarly found that South Asian Preferential Trade Agreement; the agreement prior to SAFTA, did not foster trade flows among members to great extent and one of the reasons was the political problems between Pakistan and India. Finally, Shariat Ullah & Inaba (2012) also found failure in RTA to yield positive effect on the exports of Bangladesh due to many non-tariff barriers that were not taken care of in the RTAs which included administrative delays, excessive quality control measures, ban on imports using false claim of dumping and the fact that member countries were members of different trade blocs that created impediments to trade.
1.3.4 Studies on SAFTA
The Law of gravity model states that countries trade with different regions within a 3000 Km radius and tend to trade with nearby regions, starting from neighbors such as European Union, North Asian Free Trade Area and Association of South East Asian Nations, formed Regional Trade Areas not only for trade but for common culture and exchange of resources. However, for South Asian nations, the gravity model does not apply since intra-regional trade in South Asia was only 5.67% in 2006 and trade in South Asia has been very low with 1.35% of world trade consisting of South Asian countries (Bhuyan, 2010). This shows that intra-regional trade is low within South Asian countries and they do not trade with each other, instead the major trading partners for South Asian countries are the richest regions in the world including USA, European Union and Japan. Reasons for this includes South Asian products being similar and competitive to each other although researchers disagree with this and claim them to be complementary rather than competitive.
The foremost reason for this also lies in the hostility between Pakistan and India, the two largest economies in the region. It was back in the nineteenth century when the whole region was one under the British rule, known as the sub-continent and one of the highest trading was done in this region. The partition of the subcontinent led to two countries having hostile relations with each other, including three major wars being fought since independence. Since then, political and trade ties have been extremely poor although relations in the past have improved; the signing of SAFTA shows interest between the countries for peaceful cooperation as an example, while post 2000s, important figureheads have visited each other including visits in 2015.
The most discussed topics about regarding the pending success of SAFTA was the political issues that India and Pakistan have had over the past. Though SAFTA’s benefits are known, they have to be “Successfully launched” according to Burki & Akbar (2005) ; this term has a significant meaning that although SAFTA has been signed and eventually time will pass while the countries fulfill the terms of agreement on a regular basis, the intention to build a free trade area is not present in the members. It is stated that the political will is not present in the countries policy makers and implementation of SAFTA was not done with full intention (USAID, 2005).
The latest Committee of Experts meetings has been reported in news media that the members representatives made formal speeches, spent vacations in resorts then flew back to their countries. Similarly, countries like Sri Lanka and Nepal did not even send out notifications for tariff reductions on time; member nations made several commitments but no notifications were issued in sooner time for example Bangladesh was allowed 8 million piece duty free access textile products into India but no notifications were made afterwards. Such instances display the importance of the term “Successful Launch” which is not just the visual or exterior part that can be seen, but also what is going on in the minds of the politicians and policy makers.
Numerous literatures agreed on few common problems and obstacles to success of SAFTA. USAID (2005) made a detail report of such studies. The first and foremost issue is politics (Bhuyan, 2010). The water distribution issue that led to Indus Water Treaty in 1959, territory issues for example Kashmir issue and currency valuation issue after independence raised the tensions between the two nations and to date, these issues have not yielded solutions.
Second is the political will that is not being existent. After SAFTA was signed, Pakistan introduced a long sensitive list to India, which is against the spirit of RTAs.
Thirdly, high protectionism measures are present in the nations and are not addressed in SAFTA agreement. Though import substitution policies were no longer in use since 1990s, high level of non-tariff and para-tariff measures were setup. These non-tariffs and para-tariffs are not well addressed by SAFTA and instead are to be “negotiated” in upcoming meetings which in reality do not even come in the goal of the policy makers. Another problem is of trade facilitation measures such as harmonization and standardization. Trade facilitation measures are not addressed in SAFTA as well. The problem of sensitive lists also adds to the list of negatives for SAFTAs success. High number of goods is on negative list by countries such as Pakistan and India which like the issue of non-tariffs and para-tariffs are to be negotiated in up-coming meetings. The list is ridiculously long and is against the principles of free trade. ASEAN is an example where sensitive lists and non-tariffs were carefully taken care of in a short period of time after formation. Other things lacking in the SAFTA agreement as criticized by researchers include lack of agreements on transit rights and infrastructure development.
There have also been studies that found that availability of sensitive lists allows countries to abuse these powers while separate treatments for LDCs and Non-LDCs lead to unfair, abusive actions that can be seen as loopholes to the agreement. India has been known to abuse the power to use harassment cases against other nations. Rules of origin are also confusing for the member states and businessmen due to “Double criterion” It has been made so confusing that it is hard for producers to understand. ASEAN on the other hand has simplified Rules of Origin. Adding to the confusion is what has resulted from the frustration of the SAFTA member countries, signing multiple trade agreements outside of SAFTA with member and non-member countries which has resulted in what is known as the “Spaghetti Bowl Effect” (Krueger, 1995; Cadot et al. , 2002 and Batra, 2007), which is when signing of multi-trade agreements such as BIMSTEC, Bangkok Agreement and different bilateral free trade agreements signed among memebrs such as Sri-Lanka- Inda Free Trade Agreement and Sri-Lanka- Pakistan Free Trade Agreement has led to so many levels of tariff rates and tariff rates reduction that businessmen and even customs offices are confused about the tariff rate calculation.
Another criticism for SAFTA in USAID’s report is that it ignores the services sector completely. The services sector stands at 50% of the regions exports but has no place in the SAFTA agreement. Tourism, financial and transport services all have potential to grow under RTAs and can help with the situation; however they have been ignored.
Supply-side problems exist massively in South Asia. Even if SAFTA takes off and tariff rates are liberated, the nations are still developing nations and they lack the capability to supply the needs of the new markets. They lack the technology and are inefficient in production, they lack production base and have narrow export-base and a small basket of goods for export. Their export portfolios consist of agricultural, low-value labor intensive goods and lack standardization in the production process which makes their products inferior in the global market.
Bhuyan (2010) labels India as the role model and should be the “growth pole” for South Asia like Brazil was for South America. It needs to set an example for other countries, settle its differences and be a source of growth for the entire region.
1.3.5 Effects of SAFTA
Various studies have been conducted analyzing the potential effects of SAFTA using gravity model, Computable general Equilibrium Model and Partial Equilibrium Model and they are on the favorable sides agreeing with the statement that SAFTA will bring positive change to the region.
Almost all of the researches carried out agree that intra-regional trade is low and after the implementation of SAFTA, trade will increase including Moktan (2005). Bhuyan (2005) found that intra-regional trade could go up to 50%, while Burki & Akbar’s (2005) study found that within five years of launch, trade will boost by 2.5 times and will follow a five times increase in the following five years. In addition to trade, GDP will increase, economic structure will change for the better through increased quality and basket of goods, long term growth prospects will be available, the incidence of poverty will decline and quality of legal system will improve. Adding to the advances in intraregional trade, India will replace Saudi Arabia as the single largest source of imports for Pakistan while Pakistan was also suggested to be the future energy hub for the entire region in Burki & Akbar’s (2005) study.
Also relating to economic effects, Bhuyan mentions the benefits of boosted Foreign Direct Investment in the region, intraregional. Foreign investors are attracted to areas with large market size or large market potential and South Asia, being a region with a population of around 1.5 billion fulfills this requirement. Once SAFTA opens or softens its borders, foreign investors could invest in least-cost locations and cater to large markets due to low barriers. The author suggests Indian investment in Pakistan could be huge in a number of sectors as identified by FCCI, the Federation of Indian Chamber of Commerce and Industry which include ICT, fish processing, drugs and pharmaceuticals, agro-chemicals, automobile ancillaries, where Pakistan and India can collaborate as partners or form Joint Ventures.
Though business communities will get hurt, and the study by USAID shows that large businesses communities are not receptive of SAFTA since exports in South Asian region will be reduced as Indian products are of high quality and will be the major chunk of their imports hence replacing local production. Therefore some sort of safeguard measures is required by the government to receive full support from the business community for example subsidies to infant industries.
Burki & Akbar (2005) in addition to the economic effects also mentioned a few non-economic long term effects and said that SAFTA should be seen for dynamic effects and not just static effects. With mobility of labor, a huge movement of labor may be seen and efficiency and skill of labor will be improved through the relocation from inefficient regions to efficient regions for example skilled labor form India can move to Pakistan to work in industries while agricultural land that is vast in India could be supplied with unskilled-labor from Pakistan. All this can happen when borders are softened and restrictions are reduced.
Going beyond the economic effects, SAFTA may promote cultural ties, peaceful cooperation and learning and tourism. Since many families were split up due to the partition of India, they could reunite under less stricter rules. Hindus in India can visit holy places in Pakistan and Sikhs in India can also pay visit to Pakistan to visit their holy places, similarly, Muslims in Pakistan can visit holy places in India.
A very interesting proposal comes from some studies including Burki & Akbar (2005) and Kumar & Saini (2009) regarding SAFTA reaping “peace dividends.” This term evokes two concepts; SAFTA will allow peace in the region which would eliminate changes or reduce the changes of ‘open conflict’ since countries will be living in harmony and so most of the problems and issue might even be solved once they coordinate and cooperate with each other, following this peace, since there will be no conflicts, military expenditures will be significantly reduced since they will feel more secure with their neighbors and the need for military expenditure will decrease.
Although benefits are immense and supported by many analysts, there are some that criticize the operation of SAFTA including Bandara & Yu (2001). In this study, three classifications have been made; optimistic view, moderate view and pessimistic view. The study fell under the pessimistic view terming SAFTA a very difficult RTA to implement due to hostile political climate. In the author’s view, SAFTA would not benefit and instead, it would be more beneficial to all member countries if they unilaterally reduce their tariffs with the rest of the world instead of among themselves. The research also blames the Indo-Pak conflict and after 1999, it has been made very difficult to achieve meaningful regional cooperation in economic and social matters and that countries have become frustrated and entered bilateral trade agreements with member countries instead.
Chapter Two Pakistan and South Asian Free Trade Area
2.1 Background of Regional Trade Agreements
Regional Trade agreements have become increasingly prevalent especially since early 1990s. Some over 619 notifications of RTAs including services, goods and accessions separately, as of December 1, 2015 were received by the GATT/WTO.[5] 413 are already under implementation process. 452 physical RTAs including goods, accessions and services inclusively were notified of which the numbers currently in force is 265.
The World Trade Organization was formed for the purpose of promoting trade liberalization across the globe through worldwide agreements. Its aim was to have one nation to have trade liberalization extended to every World trade Organization member in a nondiscriminatory manner. However Regional Trade agreements go against this principle and tend to reduce barriers of trade targeted to a small group of partners which discriminates against the rest of the world. They do so since they are not motivated to or not interested in liberalization worldwide since it involves so many countries and requires a lot of time and energy to form linkages and agreements. They feel that such agreements do not allow them to realize economies of scale, so they focus on strengthening ties within their region. Negotiating processes comparatively are simpler and countries within a region have greater common interests than the whole world collectively. In such regional blocks, labor resource can be adjusted more efficiently through labor force moving to countries where they have competitive advantage in producing certain items or in certain production processes, therefore increasing quality and standard of production.
In theory, there are six types of Regional Trade Arrangements. The first type is simple Economic integration where two of more nations form a trading arrangement which includes eliminating restrictions on trade, factor mobility and payments. The second level of regional trade arrangement includes members agreeing to remove all tariff and non-tariff barriers among member countries. However, in this setup, each member is allowed to maintain its own trade barriers or policies against outside members. An example of this arrangement is North American Free Trade Area (NAFTA) – the association of United States, Canada and Mexico. Such an arrangement is also known as Free Trade Area
The third type of arrangement is a Customs union. Like a Free Trade Area, tariffs and non-tariff barriers are agreed to be removed among member nations but the difference is that each member also agrees to maintain a common or identical set of trade restrictions against the non-members of the association. An example of this is the Benelux- an association of Belgium, Luxembourg and the Netherlands.
The fourth type of arrangement is called a Common market which involves free movement of goods, services and resources among member nations. Common external trade restrictions are imposed against the nonmember countries. An example of this is the European Union that was formed in 1992.
The fifth type of regional trade arrangement is an economic union. Here, the member countries agree to have common national, social, fiscal and taxation policies to be harmonized and be under the administration of one single supranational institution and this institution has economic sovereignty.
The sixth type is known as Monetary Union. This is a modification of the economic union which attains its highest level by unifying all the national monetary policies among the nations and the members accept a common currency which administered by a supranational monetary authority. The United States can be called a monetary union since its fifty states use US dollar as the common currency which is administered by the Federal Reserve. Labor and Capital can move freely across the States and there is free trade among these fifty states.
Many countries feel that global trade liberalization is impossible or exhausting. They have negative views about the success of the Doha Round of multilateral talks and feel that regional and bilateral agreements are of more benefits to themselves. They also tend to use regional agreements to show power and strength so that they can have influence over their demands in a global setting such as WTO.
A few examples of Regional Trade Agreements involving countries include South Korea- European Union Agreement which was signed in 2009. It includes agreement on annual trade worth $96 billion. Virtually, it involves elimination of all tariffs among the two parties while Korea agreed to decrease its barriers on automobile imports from EU.
Canada-Colombia Free Trade Agreement signed in 2008 is more focused on gradual elimination of Colombian tariffs on agriculture and food-safety standards that Colombia has on trade. It therefore enhances trade by involving trade deals worth US$1.2 billion annually.
The Japan Trade Agreement with Association of Southeast Asian Nations that was signed in 2008 involved trade deals worth US$211.4 billion annually and features the elimination of Japanese tariffs 93% of the total import value and the elimination of six member nations’ tariffs on Japanese imports of around 90%.
Regionalism is a huge motivation for countries to enhance economic growth through benefits of economies of scale since markets and trade potential expands resulting in increased production scale. Foreign investment results from the large market potential and specialization of skills and products results through gaining of gradual experience and expertise. Other than the non-economic benefits, regional security is promoted since nations are on friendlier terms, instead of having tensions among each other; they share power against external threats. Immigration flows are also better managed through regional cooperation. The availability of large number of policy makers and the monetary power of a collection of many governments allows enhancement of domestic and social reforms.
A more academic view on the benefits of Regional Trade Agreements shows that such arrangements allow two sorts of effects- static effects that comprise effects on consumer welfare and productive efficiency and dynamic effects that focus on long-term benefits and growth rates. Viner (1950) talked about the trade-creation and trade- diversion effect resulting from Regional Trade Agreements.[6] Trade creation effects includes welfare gain in countries when a member of a nation reduces its local production and replaces it with imports from another member country which produces it at lower cost therefore creating trade within the region. Welfare loss may however be experienced from joining regional trade agreements when a country of a union reduces its imports from a non-member which produces a product at a lower-cost and replaces it with imports from a member of the trade agreement which produces it at a higher cost but is cheaper due to lower or eliminated taxes. Though cost is low, society may suffer from lower quality products.
2.2 Pakistan and Free Trade Arrangements
Pakistan is a developing country located in South Asia. It gained independence on 14th August 1947. It shares a common border with China in the North-east, India on the East, Afghanistan and Iran in the West. According to World Bank, its GDP stood at US$236.5 billion as at 2013, GDP with Purchasing power parity at US$571.4 billion. The per capita GDP PPP was US$3100 in 2013, giving it the status as a developing country and low income country. This section introduces a few economic statistics of Pakistan based on World Bank Data.[7]
The country has historically been known as an agricultural economy due to its importance of the agriculture sector. Almost 75% labor force used to be engaged in agriculture but has declined to 45.1% in 2010. Also because majority of Pakistan’s land is arable land and used in agriculture. The GDP contribution in this sector was 25.3% in 2013. Agricultural products are mostly in the rawest form, without added value which includes cash crops, livestock, and forestry. Important production includes cotton, wheat, rice, sugarcane, fruits, vegetables, milk, beef, mutton and eggs.
Manufacturing is becoming a very important sector. It contributes to 21.6% of the GDP and 20.7% of the labor force is engaged in industrial production. Textiles and apparel is an important industry which is a major portion of Pakistan’s exports basket- almost 30%. Food processing, construction materials- particularly cement, pharmaceuticals, fertilizer paper products and shrimp are other important industries.
Services sector is 53.1% of the GDP whereas only 34.2% of the labor force is engaged in this sector. Major industries include financial services, and transport and trade management. Policies are being implemented to make the country develop the service sector particularly Information and Communications Technology, incubation centers, venture capitalists and entrepreneurship support.
The population below poverty line is 22.3% which shows high poverty level in the country and Pakistan faces a problem of wide gap in income distribution. The population was 199 million in 2014 with a labor force of 59.21 million in 2012. The labor force is mostly young and this is a positive outlook for the economy of Pakistan where the population is consumption oriented and willing to take risks and try new technology. The unemployment rate is high at 6.6% in 2013 with shadow unemployment being a high problem. Overemployment in different sectors is also a problem. For example, labor force is engaged in agriculture where two or three people are engaged in farming when only one person is required. Similarly in government institutions for example Pakistan International Airlines, a state owned airline company, the number of staff per aircraft is one of the highest in the world. Inflation remains to be a huge problem in the country with official statistics stating 9.7% in 2012 and 7.7% in 2013.
Balance of Payments of Pakistan has always been in a deficit with imports exceeding exports. Pakistan’s exports stood at US$25.05 billion in 2013 and imports stood at US$39.27 billion. The Current Account Balance stood at a deficit of US$2.36 billion. Recent government policy- especially the Strategic Trade Policy Framework under the Ministry of Commerce has emphasized the importance of increasing Exports through development of local industry and export companies, product and market development, and financing availability for exporting businesses along with several other policy initiatives.
Finally, Foreign Direct Investment is also one of the key agendas of the government for economic development. In 2013, the stock of FDI was US$24.33 billion. One of the major developments in investment into Pakistan is the China-Pakistan Economic Corridor which was officially signed in April 2015 when the Chinese president visited Pakistan in a high profile meeting.
2.2.1 Dependence of International Trade for Pakistan 2000-2013
Fig 2.1 Trade Dependence of Pakistan
Source: World Development Indicators, World Bank
The average trade dependence figure was 32% for the period of 2000-2013. The highest was 38% in 2006 and the lowest was 28% in 2001.
Table 2.1 Trade Dependence of
| Year | Imports of goods and services (constant 2005 US$) | Exports of goods and services (constant 2005 US$) | GDP (constant 2005 US$) | Trade Dependence (Imports exports/GDP)*100 |
| 2000 | 14,245,359,962.53 | 10,052,951,384.88 | 85,822,303,909.76 | 28% |
| 2001 | 14,553,085,491.36 | 11,277,727,230.66 | 87,523,717,381.30 | 30% |
| 2002 | 14,995,966,911.43 | 12,400,992,271.94 | 90,345,858,357.60 | 30% |
| 2003 | 16,678,596,922.05 | 15,920,072,590.08 | 94,724,308,605.85 | 34% |
| 2004 | 15,248,357,610.81 | 15,676,841,521.24 | 101,704,136,879.05 | 30% |
| 2005 | 21,422,766,419.13 | 17,180,327,371.73 | 109,502,102,510.88 | 35% |
| 2006 | 25,425,428,924.24 | 18,880,325,471.44 | 116,266,640,923.99 | 38% |
| 2007 | 24,390,545,596.65 | 19,165,366,978.76 | 121,885,595,234.15 | 36% |
| 2008 | 25,820,295,939.12 | 18,292,943,565.41 | 123,959,363,413.06 | 36% |
| 2009 | 21,713,391,756.16 | 17,678,085,036.78 | 127,469,469,287.50 | 31% |
| 2010 | 22,657,266,817.76 | 20,454,898,529.82 | 129,517,496,850.37 | 33% |
| 2011 | 22,630,238,640.93 | 20,940,129,181.54 | 133,077,173,575.81 | 33% |
| 2012 | 21,929,703,339.29 | 17,798,933,401.14 | 137,744,248,678.60 | 29% |
| 2013 | 22,285,851,988.20 | 20,222,143,897.21 | 143,816,996,323.01 | 30% |
Pakistan Source: Author’s own calculations from World Development Indicators
Table 1.1 shows that Pakistan’s economy is moderately dependent on trade although higher proportion of this comes from high imports since the country faces trade deficits. Therefore there is need for such trade agreements to boost trade of Pakistan in order to have positive effects on the GDP and economy of Pakistan.
2.2.2 Trading Partners of Pakistan
| Country | Percentage of Pakistan’s Exports |
| United States | 14% |
| China | 12% |
| Afghanistan | 9% |
| Germany | 5.1% |
| United Kingdom | 5% |
| United Arab Emirates | 4.4% |
| South Korea | 3% |
| France | 2.5% |
| Italy | 2.3% |
| Turkey | 2.3% |
Source: The Observatory of Economic Complexity
The table 1.2 shows that Pakistan’s top trading partner for its exports is the United States followed by China and Afghanistan. Pakistan has had strong political ties with the United States, with high dependence on the country’s foreign aid, followed by strong relations with China. China rose to second position after signing with Pakistan in 2008, the China-Pakistan Free Trade Agreement in 2008. Afghanistan takes third place and is the only SAARC or SAFTA member that is in the top ten list of trading partners with Pakistan which is a huge area of concern.
| Country | Percentage of Pakistan’s Imports |
| China | 17% |
| United Arab Emirates | 15% |
| Kuwait | 8.8% |
| Saudi Arabia | 8.5% |
| Malaysia | 4.8% |
| Japan | 4.1% |
| India | 3.9% |
| Indonesia | 3.3% |
| United States | 3.2% |
| Germany | 2.4% |
Source: The Observatory of Economic Complexity
Pakistan’s imports are similarly too less when it comes to trading with South Asian countries. The highest imports come from United Arab Emirates, Kuwait, and Saudi Arabia which are all the Middle Eastern countries. SAFTA is proposed to be the solution and in literatures it has been stated that India can replace Saudi Arabia as the top import source for Pakistan.
2.2.3 Composition of Trade
Table 2.4 Exports by Product Category
| Category | Percentage |
| Textiles | 52.55% |
| Vegetable Products | 13.59% |
| Mineral Products | 6.95% |
| Metals | 4.37% |
| Animal Hides | 4.15% |
; Source: The Observatory of Economic Complexity
Pakistan’s exports are dominated by a narrow basket of goods that include textile products such as house linens and cotton yarn. 52.55% of its exports are all textile products which show the huge comparative advantage it has over this product category. Literatures have stated that Pakistan’s product complement with South Asian countries like Bangladesh and can supply raw cotton yarn to Bangladesh who in turn can export Wearing apparel made from Pakistani yarn. Following this, mining products and vegetable or food processing industry
| Product | Percentage |
| House Linens | 10% |
| Non-Retail Pure Cotton Yarn | 9.2% |
| Rice | 7.9% |
| Non-Knit Men’s Suits | 4.3% |
| Refined Petroleum | 3.2% |
Source: The Observatory of Economic Complexity
The top export product of Pakistan is House-Linen, closely followed by cotton yarn at 10% and 9.2% respectively. These fall under Textile category. Rice, which falls under agriculture category shares 7.9% of exports.
| Product | Percentage |
| Refined Petroleum | 21% |
| Crude Petroleum | 11% |
| Palm Oil | 4.8% |
| Cars | 1.9% |
| Coal Briquettes | 1.6% |
Source: The Observatory of Economic Complexity
Table 2.7 Imports by Product Category
| Category | Percentage |
| Mineral Products | 34.66% |
| Machines | 13.69% |
| Chemical Products | 11.39% |
| Metals | 7.4% |
| Textiles | 7.31% |
Source: The Observatory of Economic Complexity
The tables 1.6 and 1.7 show Pakistan’s import products. Pakistan highly depends on imports of mineral products particularly petroleum products- refined and crude. With the help of foreign investment from South Asian countries, the need for energy can be reduced through investment in its own oil reserves.
2.2.4 Pakistan’s prominent membership in International Organizations
Since creation of Pakistan in August 1947, the country has quickly involved itself into many international organizations in order to gain several advantages in the international market, to promote its trade and also for political reasons such as territory, border and water disputes with its neighbor, India. Some of the prominent WTO summits include; WTO, Asian Developing Members, Cairns group, G-20, G-33, Friends of Fish, W52 Sponsors, MFN status to India.
2.2.5 Regional Trade Agreements
The government of Pakistan is keen in pursuing bilateral trade and investment agreements. Since creation it has been proactive in seeking trade agreements with various countries in order to improve its economy. Negotiations on a US-Pakistan bilateral investment treaty, as a step towards a US-Pakistan FTA, have been quite controversial and remain unresolved. Asia Regional Integration Center lists seventeen Free Trade Agreements undertaken by Pakistan as of 2015 as illustrated in table 1.8.
Table 2.8 Regional Trade Agreements signed by Pakistan
| Trade Agreement | Status |
| Pakistan-Bangladesh FTA | Negotiations Launched |
| Pakistan-Gulf Cooperation Council FTA | Negotiations Launched |
| Pakistan-Morocco PTA | Negotiations Launched |
| Pakistan-Singapore FTA | Negotiations Launched |
| Pakistan-Turkey PTA | Negotiations Launched |
| Economic Cooperation Organization Trade Agreement | Signed, Not in effect |
| Trade Preferential System of the Organization of the Islamic Conference | Signed, Not in effect |
| Malaysia-Pakistan Closer Economic Partnership Agreement | Signed, in effect |
| Pakistan-Indonesia FTA | Signed, in effect |
| Pakistan-Iran PTA | Signed, in effect |
| Pakistan-Mauritius PTA | Signed, in effect |
| Pakistan-MERCOSUR PTA | Signed, in effect |
| Pakistan-Sri Lanka FTA | Signed, in effect |
| Pakistan-US Trade and Investment Framework Agreement | Signed, in effect |
| People’s Republic of China-Pakistan FTA | Signed, in effect |
| Preferential Tariff Arrangement-Group of Eight Developing Countries | Signed, in effect |
| South Asian Free Trade Area | Signed, in effect |
Source: Asia Regional Integration Center
2.3 Background of South Asian Free Trade Area Members
SAFTA is an association of eight South Asian countries which started off with seven countries. Afghanistan was given membership status later on. South Asian countries are classified as middle to low-income developing economies and face the world’s worst problems of poverty, unemployment and high illiteracy rates amid all the huge potential that the region has through its large resource endowments. It has a potential to be a frontrunner in prosperity and growth but is not utilizing these resources effectively and efficiently.
The economies of the member nations are open economies. Like Pakistan, they had high protectionist policies post-independence, with high import tariffs and high non-tariff barriers. In late 1970s, this changed and countries became more open to the outside world. Sri-Lanka was the first to do so and other countries followed. In the early ninety’s, countries starting becoming more and more liberalized in trade and even started relaxing foreign investment rules.
Table 2.9 Economic profiles of SAFTA members
| Country Name | Population | GDP (Current) | GDP, PPP | Current Account Balance | Trade (% of GDP) |
| Afghanistan | 31,627,506.00 | 1,150,816,738,640.29 | 61,132,547,122.96 | (9,239,000,000.00) | 52.87 |
| Bangladesh | 159,077,513.00 | 13,436,744,000,000.00 | 496,758,428,046.52 | (1,677,258,362.00) | 44.51 |
| India | 1,295,291,543.00 | 125,412,081,273,533.00 | 7,384,098,903,973.73 | (31,288,847,935.00) | 48.70 |
| Bhutan | 765,008.00 | 119,545,800,000.00 | 5,979,045,312.09 | (470,619,295.90) | 93.62 |
| Maldives | 401,000.00 | 47,124,000,000.00 | 5,024,399,096.51 | (191,134,962.80) | 197.58 |
| Pakistan | 185,044,286.00 | 25,068,059,000,000.00 | 890,315,208,211.22 | (3,544,000,000.00) | 31.00 |
| Nepal | 28,174,724.00 | 1,941,624,000,000.00 | 66,892,835,546.74 | 1,160,000,000.00 | 52.87 |
| Sri Lanka | 20,639,000.00 | 10,291,581,000,000.00 | 230,769,818,273.76 | (2,018,156,357.00) | 55.60 |
Source: World Development Indicators
South Asia is home to the largest population. It is blessed with the world’s 23% population or 1.72 billion people living on 3.8% of the total land area in the world. It can be a burden for poverty; with the world’s poorest 40% living there, but it can be seen as a potential for huge labor market as well as a market for huge consumption.
The region’s intra-regional trade is quite disappointing and is reported to be 1.4% of total world imports and 1.2% of world exports which is the lowest in the world.[8] According to World Development Indicators trade was only US$8-9 billion in 2000s and the figure was US$23 billion in 2013. World Bank predicts that by 2020 this trade figure can be raised to US$100billion with an annual growth rate of 30%. Currently the growth rate is only 5%.
A research conducted by Bandara & Yu (2001) found areas of cooperation in products that the SAFTA members could work together on in order to gain certain economies of scale. Table 1.10 illustrates them.[9]
Table 2.10 Areas of cooperation for SAFTA members
| Country | Product |
| India | Textiles and Apparel |
| Pakistan | Cane sugar and Chemical products, ICT, Fishing processing, drugs and pharmaceuticals, automobile ancillaries |
| Sri-Lanka | Printing, writing paper, plastic goods, soap cutting and molding machines |
| Bangladesh | Shirts, tanned or crust hides, grains, footwear, chemical fertilizer, food processing, light engineering, gas exploration, power generation |
| Maldives | Articles for conveyance of packaging of plastics, Air conditioners, water pumps |
| Nepal | Fruit Juices, Carpets, garments, copper wire, zinc oxide, acrylic yarn, steel pipes |
Source: Bandara & Yu (2001)
2.3.1 Division under SAFTA
South Asian Free Trade Area is meant to create free trade among members of South Asia. There is however, differential treatment given to some countries and therefore two groups are formed based on economic development status of the countries. These are LDCs and Non LDCs.
LDCs or Least Developing Countries are those lesser developed countries in SAFTA and they enjoy more relaxed policy requirements. These countries need support and help from the more developed countries in SAFTA in order to develop their own economies. The biggest difference is in the Trade Liberalization Program. These nations are allowed a longer time span to reduce their tariff rates to South Asia and at lower annual reduction rates. SAFTA members also keep two separate sensitive lists for LDC and Non-LDCs. The countries classified as LDCs are Afghanistan, Bangladesh, Bhutan, Maldives, and Nepal.
Non-LDCs or Non Least Developing Countries are the nations that are more developed in the region which include India, Pakistan and Sri-Lanka. India is the largest economy in the region and Pakistan ranks second. Sri-Lanka however is also allowed one year longer time span in the reduction of its tariffs charged to the members. These countries have higher GDP and infrastructure development and are to be role models for growth in the region especially India. They are expected to facilitate the Non-LDCs in developing their economies through foreign investment and government-to-government support in all areas of development.
SAFTA however, faces hindrance in smooth operationalization due to hostile relations between the two largest economies in SAFTA. These political tensions have led to breaking down of agreements and negotiations, slowing down of the tariff liberalization process and slower reduction in the number of items in the sensitive list. Therefore, when the two Non-LDCs who are supposed to be growth drivers and good role models, have not been cooperating with each other, growth in SAFTA has been hindered.
2.4 History of South Asian Free Trade Area
On 2nd May, 1980, the president of Bangladesh insisted on the need for cooperation on regional, political and economic issues in the South Asian region. The idea of such cooperation was mentioned and talked about in a minimum of three conferences before it was formed; the Asian Relations Conference in 1947, The Baguio Conference, Philippines in 1950, and Colombo Powers Conference in 1954, Columbia.
During the final years of 1970, the seven original members of SAARC; Pakistan, Bangladesh, Bhutan, Maldives, India, Nepal and Sri-Lanka agreed on the need for creating a trade bloc which would provide a platform for people in South Asia to collaborate and work in the a spirit of friendship, trust and understanding together. Finally, this collaboration came true with the formation of SAARC with its first summit being hosted by the president of Bangladesh in Dhaka in December, 1985. The declaration was signed by the countries respective heads of state and therefore SAARC was created with the ideology of promoting people-to-people contact, peace and stability and sharing of culture among the region. In 2005, Afghanistan applied for membership in the organization despite its regional identity of a Central Asian Nation. In 2007, despite all the reluctance and debates, Afghanistan was accepted as the eight member of SAARC.
Earlier on, this organization was formed with regional cooperation with larger focus on social stability and prosperity with not much focus on economy. This point of view only started coming into existence ten years after the formation of SAARC to open up trade within the region. Once this ideology of economic cooperation came into light, it was quickly accepted by the members and was one of the new agendas in the region. The South Asian Preferential Trade Agreement (SAPTA) was proposed immediately and was accepted in December 1995. And the passion for greater economic cooperation was seen when the members immediately proposed the South Asian Free Trade Area in 1996. The members agreed to implement the agreement by 2000 and no longer than 2005.
This speed of economic cooperation however came to a halt when relations between Pakistan and India deteriorated immensely therefore postponing the next SAARC Summits for the next three years. Negotiations on SAFTA’s framework resumed in 2002 and in January 2004, it was finally formulated. By January 2006, the key areas of the treaty were finalized which included tariff liberalization, sensitive lists and rules of origin. It was planned under the SAFTA, that the tariff liberalization program would be fully implemented for Non LDC members by 2013 and 2016 for LDC members. SAFTA officially came into force in January 2006 after it was signed on the 12th SAARC Summit in 2004 without actual agreements on Rules of origin, Sensitive Lists or technical assistance or even a mechanism for the compensation of losses on revenue for LDCs.
SAPTA was considered a weaker framework for economic cooperation but it was a first formal step towards regional economic co-operation. Its effectiveness was known to be poor, with only small list concessions of only 3857 tariff lines. The trade coverage for preferential access was very low; an estimated average of 8.4% tariff lines on imports from non-LDCs and 6.2% on imports from LDC’s (World Bank, 2005).[10] Between SAARC members, only 15% of imports were given SAPTA concessions therefore in reality, this had very little impact on the intraregional trade for the South Asian Nations.
SAFTA provided a more comprehensive framework of agreement that covered larger base of products with more focus on a lot of key areas of economic cooperation for instance; sensitive lists, rules of origin and rules that made it form a regional trade agreement.
2.5 Salient Features of SAFTA
The SAFTA Agreement was signed with the intention to maximize trade and development in the South Asian region through economic cooperation for benefitting the people through a spirit of mutual accommodation. The SAPTA agreement signed in 1993 provided a basic structure to be built on for the trade liberalization program in the area. This agreement was agreed to act as a stimulus to strengthen national and economic resilience of the organization members by developing and expanding production and investment opportunities, trade and earnings from foreign exchange along with development of technological and economic cooperation. Another motive for members entering this agreement was to enhance trade in the region through the free movement of goods and further moves will be taken in future to eliminate trade barriers. Finally, Least Developed Countries of Bangladesh, Nepal, Bhutan, Afghanistan and Maldives were to be given special and different treatment in accordance to their needs.
The objective of SAFTA is to promote and enhance intraregional trade through economic cooperation through elimination of barriers to trade, promotion of fair competition, creating steps and systems to implement the SAFTA for combined administration and dispute resolution, and to further establish a framework to expand regional cooperation and mutual benefits for members.
The salient features of SAFTA are based on seven core elements which include; a) trade liberalization program b) Rules of Origin c) Institutional Arrangements d) Revenue Compensation Mechanism e) Technical Assistance for LDCs f) Safeguard Measures g) Consultations and Dispute Settlement Procedures.
2.5.1 Trade Liberalization Program
This program is the main part of the SAFTA framework. After moving out from the positive list approach adopted by SAPTA, a negative list approach had been adopted to reduce tariffs. LDCs and Non-LDCs are important segregations in the treaty and have different obligations and rights. Non-Least Developed Countries are Pakistan, Sri-Lanka and India. The end goal of the Trade Liberalization Program was to have target rates of tariffs at 0-5% for goods other than those on the negative list. Non-tariff barriers were to be reviewed on regular basis through meetings with the ultimate aim of elimination or turning them non-restrictive in nature.
The trade liberalization program provides a time schedule for tariff reductions for Least Developing Countries and Non-Least Developing Countries. Non-LDCs are to lower tariffs within a shorter time period for LDCs and they must reduce tariffs to 0-5% for LDCs within a period of seven years.
India, Pakistan and Sri-Lanka, within two years of coming to force of SAFTA, must reduce tariffs to 20% and within 5 years to 0-5% i.e. till 2013. Sri-Lanka can extend this to 2014 or an extension by one year.
LDC members of Bangladesh, Nepal, Maldives, Bhutan and Afghanistan were to reduce tariffs to 30% within the first two years and later reduce tariffs to 0-5% in a time frame of eight years lasting till 2016.
Regarding Non-tariff barriers and para-tariff barriers, Quantitative Restrictions were to be removed once the tariff lines reach the 0-5% level although there is no actual commitment to eliminate these QRs. It is only stated in the agreement that the Committee of Experts will meet regularly to review the status and fate of the non-tariff barriers.
2.5.2 Sensitive Lists
SAFTA uses a negative list approach for maintaining sensitive lists. Products in this list are exempted from the Trade Liberalization Program. These are treated differently for LDCs and Non LDC members. LDCs maintain a longer sensitive list than Non-LDCs.
Table 2.11 Sensitive lists of SAFTA
| Country | Total Number of Sensitive List | Coverage of Sensitive List as % of Total HS Lines | ||
| For > | Non-LDCs | LDCs | Non-LDCs | LDcs |
| Bangladesh | 1,254 | 1,249 | 24 | 23.9 |
| Bhutan | 157 | 157 | 3 | 3 |
| India | 865 | 744 | 16.6 | 14.2 |
| Maldives | 671 | 671 | 12.8 | 12.8 |
| Nepal | 1335 | 1299 | 25.6 | 24.9 |
| Pakistan | 1191 | 1079 | 20.7 | 20.7 |
Source: Raihan & Razzaque (2007)
2.5.3 Rules of Origin
The Rules of Origin are an important section of Free Trade Areas. Under SAFTA, the Rules of Origin are very general in nature or one criterion applies for all products although 1991 products are barred for product specific application of rules. In short, SAFTA Rules of Origin requires in order for enjoying preference in SAFTA, the product has to undergo sufficient change in processing so that the tariff heading changes from non-originating inputs and to have at least 40% value addition measures of the F.O.B value. For Sri Lanka and LDCs this requirement for value addition is lower at 35% and 30% respectively. Detailed operational certification procedures have also been adopted to avoid fraudulent practices.
2.5.4 Institutional Arrangement
For the implementation of SAFTA Agreement to be monitored, two bodies were established; the SAFTA Ministerial Council (SMC) and Committee of Experts (COE). The SMC, which includes members from Commerce or Trade Ministers of member countries, is the highest decision making authority in SAFTA and is required to meet at least once a year. Committee of Experts supports this body and its members are chosen from senior trade officials of the member countries who are required to meet at least once in six months.
2.5.5 Mechanism for Compensation of Revenue Loss
The SAFTA has designed a mechanism to compensate the LDCs in case revenue loss is faced as a result of tariff reduction. Cash and partial compensation is made. 5% of custom duty is the maximum compensation, collected from imports of SAARC in 2005. The compensation extended to four years only while Maldives was allowed compensation for six years.
2.5.6 Technical Assistance for LDCs
Provisions for providing LDCs with technical assistance at their request include the following;
- Trade related capacity building
- Development of tax policy and instruments and their improvement
- Measures related to customs procedures
- Measures related to legislations and policy, help in improving national capacity
- Research and studies on banking sector improvement, export finance development and development of physical infrastructure related to trade
2.5.7 Safeguard Measures
For the safety and protection of domestic industry from probable injury from increased imports after reduction of tariffs, the agreement provided possibility and option for members to partially or fully withdraw from preference for a maximum period of three years. However these safeguard measures cannot be used against LDC products if its share of import out of total import of the importing country is less than 5%.
2.5.8 Consultations and Dispute Settlement Procedures
Dispute settlement mechanisms are provided for in the agreement with specific time schedule. Consultation at bilateral level will take place within 30 days on the request made by a member. If through bilateral consultation, the dispute cannot be settled, the COE will be referred to for the matter and a period of 60 days is given to come up with a recommendation. Panel of experts may be consulted. If the decision of COE is not acceptable, members can appeal to the SMC for a decision with a time limit of 60 days. This decision made by SMC will be the final decision.
SAFTA is not going being implemented according to the time schedule for tariff liberalization, while nations have mixed opinions about the implementation of SAFTA. Though countries have been reducing tariff rates and the number of products on the sensitive lists for example India reduced the sensitive list to Sri Lanka, Nepal Bangladesh and Bhutan down to 25 products. Pakistan for example also took out 233 tariff lines from the sensitive list and immediately reduced the tariff on these products by 20% in 2011. However, four members have decided not to follow the tariff liberalization schedule and have undertaken to eliminate the tariff lines completely by 2020.
The meetings for SAFTA Ministerial Council and for Committee of Experts have regularly been taking place. Although the members have not implemented or strictly followed the time schedule under the trade liberalization program or have focused attention on bilateral trade agreements or trade agreements with other regions, the importance of SAFTA has not been ignored since country leaders often mention it in their visit to member countries.
Chapter Three Methodology
Measuring the impact of Free Trade Agreements is quite complicated since the effects of policy changes effect a wide range of parties and agents involved not only in a single economy but the whole world. Additionally, the impacts are argued to not only have direct impacts but complicated indirect effects that will have long-term implications that are very hard to measure from simple models. The model used in this paper addresses some of these key issues and has been widely accepted by many researchers as the most suitable models for measuring the impacts of policy changes in Free Trade Areas. This model is commonly known as the “GTAP Model” which stands for Global Trade Analysis Project Model- a project of Purdue University that consists of the GTAP Database which is a publicly available database to researchers in the field of measuring trade policy changes impacts.[11] The database is incorporated into the CGE model, or the Computable General Equilibrium Model which is a multi-country, multi-sectoral model accounting for wide range of inputs and outputs and factors in the economy. A general equilibrium approach does not only reveal direct effects of trade policies changes such as tariff reduction, but also indirect effects in related markets. The model is multi-market, with markets for final goods, intermediate goods, traded goods and factors of production. It is additionally multiregional with a region representing a country or a group of countries. Factor endowments- land, skilled labor, unskilled labor, natural resources and initial capital are the fixed exogenously within the GTAP model.
Plummer, Cheong, & Hamanaka (2010) published a report for Agricultural Development Bank comprising the different methods for assessing impacts of Free Trade Agreement. Two main categories are classified in the report based on data usage and events- ex-ante and ex-post.[12]
Ex-ante classifies the methodologies that predict or simulate data before policy changes take place. Ex-ante refers to “before the events” and therefore, before trade liberalization and trade policy changes, it tends to utilize past and present data, manipulate it and predict the future conditions. Ex-post refers to “after the events” or after when the FTA is in place, it uses the data collected before and after the formation and launch of FTA in order to calculate the actual effects that took place as a result of policy change.
These methods have their own advantages and disadvantages and own focal points. Some shed light at macroeconomic level while some only focus on industry-level effects. A few are just indicators collected from trade data or information from national customs offices while some are econometric models that are very sophisticated in nature.
Ex-ante methods cover indicators of comparative advantage and trade interdependence, SMART model, and CGE estimation. Ex-post evaluation methods include Free Trade Area preference indicators comprising utilization rate, gravity model and extrapolation methods.
One of the earliest and most quoted literatures includes Viner’s (1950) research, in which he argued with common economist belief at that time that regional trade agreements improved welfare due to trade liberalization and increased trade.[13] However, Viner introduced a model to debunk this theory by showing that regional trade agreements do have a possibility of having negative impacts on welfare. The key points in his model included trade creation and trade diversion and based on these two points that effect welfare; many researches have been and are being conducted based on studying these two important principles.
3.1 Computable General Equilibrium Model
The complicated nature of assessing widespread impacts of economy and policy changes involved in a regional trade agreement requires rigorous, innovative quantitative methods and the Computable General Equilibrium model fulfills these needs. Due to its nature, it is popularly used in designing policies.
Fig 3.1 General Equilibrium; Source: Inter-American Development Bank (2015)
This model fundamentally recreates the structure of a complete economy in the most realistically possible way, including the nature of its economic transactions within the diverse agents which include households, productive sectors, government and others. This analysis is able to capture wider set of economic impacts derived from policy changes compared to the many techniques available. Therefore, CGE modelling is an essential tool in estimating effects of policy changes if they are complex, and go through several transmission channels. The table provides a simple structure of a CGE model.
Essentially, partial equilibrium models capture tariff reduction effects inside an individual import market. RTA negotiations practically cover removal of trade barriers and tariffs throughout several sectors and regions at the same time. To capture the entire effects of such widespread changes, a general equilibrium approach is used. This will show not only the direct effects, but also the indirect effects and changes in the different markets.
Fig 3.2 Steps of conducting CGE Modelling; Source: Shoven & Whalley (1992)
The diagram in fig 3.2 illustrates the process of conducting Computable General Equilibrium method. The first step is to organize a set of data related to the economy or economies under study from a year of benchmark. The required data is found from national I-O (Input-Output) tables that are well arranged into Social Accounting Matrix (SAM). SAM uses this information to include components of aggregate demand which include consumption, investment, government expenditure and also the external sectors- imports and exports. This data should be consistent throughout, which means that the numbers should form equilibrium- the set of values for variables which equate demand and supply in the entire markets.
The Next step is to assign values for parameters which include price, income and substitution elasticities. These are measures of consumers and producing agents’ responsiveness to relative income and price changes. Therefore these values have significant influence on the CGE simulation outcomes. These values can be derived from statistical studies carried out in previous literatures while some unknown variables may have to have calibrated data which involves computing the data through what is available so that SAM values can be reproduced from the benchmark year. Following this, a replication check is necessary to verify that SAM data from benchmark year can be reproduced from the equilibrium solution.
Finally, values of exogenous variables or any variable that is needed to simulate the changes in policy is altered to form a simulated environment to form a new equilibrium and this equilibrium is called the “counterfactual equilibrium.” A comparison of the counterfactual equilibrium is made with the equilibrium in the benchmark year to identify and analyses changes as a result of such policy changes. Typically, changes in exports, imports, outputs, and welfare and factor prices are studied in this step.
3.2 GTAP Model
This section gives a breakdown of what the GTAP model consists of and how it works. Hertel (1997) was the original formulator of the GTAP (Global Trade Analysis Project).[14] This model is multi-market and multi-regional which accounts for final goods, intermediate, traded goods and factors of production with regions representing a nation or a group of nations. Endowment quality of land labor, natural resources and capital are fixed exogenously for all regions.
Producers, consumers and the government are main agents in the model who are styled based on standard neoclassical theory. The model assumes perfect competition in the market and prices are adjusted clear markets.
Like in the real world, regions trade with each other and international trade is defined as shipment of commodities from a source to a region of destination through international transport sector. This sector buys inputs from different regions. Importers purchase transport services and transport costs create space between FOB prices and their freight, insurance and basic cost price. Due to perfect competition, importers and transport sector satisfy zero profit conditions when in equilibrium.
A system of linear equations viewed in the form of percentage change of variables is a feature of this comparative static multi-regional CGE model. ORANI model (Dixon, Parmenter, Sutton, & Vincent, 1982) forms the basis for each regions modeling in GTAP.[15]
GTAP is a fully documented global database that is publicly available; a modeling framework of standard general equilibrium approach; consists of software to manipulate data and to implement the model; a global network of over six thousand seven hundred researchers in over one fifty countries that have a common aim to analyze the economy, trade, environment and resources; a consortium of agencies-international and national who provide leadership and fundamental level support to the project; and also a website that is a source of information, data, and softwares.
Version seven of GTAP database divides the world into 113 countries, and has divided the commodities into 57 sectors. Based on the study in this paper, the regions have been aggregated via GTAPagg into 12 regions and 12 sectors as shown in table 3.1 and table 3.2. Since this paper studies the effect of Regional Trade Agreements, particularly the South Asian Free Trade Area with focus on Pakistan, the regional aggregation supports importance of each member nation and the top trading partners of Pakistan and SAFTA members.
After regional and sector aggregation, shocks were added to simulate effects similar to SAFTA’s change in policies. The effects of trade liberalization which is shown as the reduction and elimination of tariffs were used as shocks to simulate the effects of SAFTA. This was done with the help of software called RunGtap. Following this step, results were generated to show different effects on welfare, economic indicators like GDP, GDP components, trade balance, breakdown volume and percentage changes in imports and exports and the output volumes in each region and each sector.
3.3 Design Scenarios of Trade Liberalization
Version seven of GTAP database divides the world into 113 regions, and has divided the commodities into 57 sectors. Focusing on the study in this paper, the regions have been aggregated with the help of the software, “GTAPagg” into 12 regions and 12 sectors as shown in tables 3.1 and 3.2.
Table 3.1 Regional aggregation used in the model
| Code | Description | Comprising |
| Rest of Asia | Rest of Asia | China; Hong Kong; Korea; Taiwan; Rest of East Asia. |
| ASEAN | ASEAN | Cambodia; Indonesia; Lao People’s Democratic Republic; Myanmar; Malaysia; Philippines; Singapore; Thailand; Viet Nam; Rest of Southeast Asia. |
| BGD | Bangladesh | Bangladesh. |
| IND | India | India. |
| PAK | Pakistan | Pakistan. |
| LKA | Sri Lanka | Sri Lanka. |
| South Asia | Rest of South Asia | Rest of South Asia(Afghanistan, Nepal, Maldives, Bhutan) |
| NAFTA | North America | Canada; United States of America; Mexico; Rest of North America. |
| EU_25 | European Union 25 | Austria; Belgium; Cyprus; Czech Republic; Denmark; Estonia; Finland; France; Germany; Greece; Hungary; Ireland; Italy; Latvia; Lithuania; Luxembourg; Malta; Netherlands; Poland; Portugal; Slovakia; Slovenia; Spain; Sweden; United Kingdom. |
| MENA | Middle East and North Africa | Rest of Western Asia; Egypt; Morocco; Tunisia; Rest of North Africa. |
| Rest of World | Rest of World | Australia; New Zealand; Rest of Oceania; Argentina; Bolivia; Brazil; Chile; Colombia; Ecuador; Paraguay; Peru; Uruguay; Venezuela; Rest of South America; Costa Rica; Guatemala; Nicaragua; Panama; Rest of Central America; Caribbean; Switzerland; Norway; Rest of EFTA; Albania; Bulgaria; Belarus; Croatia; Romania; Russian Federation; Ukraine; Rest of Eastern Europe; Rest of Europe; Kazakhstan; Kyrgyzstan; Rest of Former Soviet Union; Armenia; Azerbaijan; Georgia; Iran Islamic Republic of; Turkey; Nigeria; Senegal; Rest of Western Africa; Central Africa; South Central Africa; Ethiopia; Madagascar; Malawi; Mauritius; Mozambique; Tanzania; Uganda; Zambia; Zimbabwe; Rest of Eastern Africa; Botswana; South Africa; Rest of South African Customs . |
| Japan | Japan. |
Source: Regional Aggregation through GTAPagg 7
Table 3.2 Sectoral aggregation used in the model
| Code | Description | Comprising |
| Agriculture | Agriculture | Paddy rice; Wheat; Cereal grains nec; Vegetables, fruit, nuts; Oil seeds; Sugar cane, sugar beet; Plant-based fibers; Crops nec; Cattle, sheep, goats, horses; Animal products nec; Raw milk; Wool, silk-worm cocoons; Meat: cattle, sheep, goats, horse; Meat products nec; Processed rice. |
| ForestFish | Forestry | Forestry; Fishing. |
| Mining | Mining and Quarrying | Coal; Oil; Gas; Minerals nec. |
| ProcFood | Processed Food | Vegetable oils and fats; Dairy products; Sugar; Food products nec; Beverages and tobacco products. |
| Tex | Textiles | Textiles. |
| TextWapp | Wearing Apparel | Wearing apparel. |
| LightMnfc | Light Manufacturing | Leather products; Wood products; Paper products, publishing; Metal products; Motor vehicles and parts; Transport equipment nec; Manufactures nec. |
| PetroCoal | Petroleum, coal products | Petroleum, coal products. |
| HeavyMnfc | Heavy Manufacturing | Chemical, rubber, plastic prods; Mineral products nec; Ferrous metals; Metals nec; Electronic equipment; Machinery and equipment nec. |
| Util_Cons | Utilities and Construction | Electricity; Gas manufacture, distribution; Water; Construction. |
| TransComm | Transport and Communication | Trade; Transport nec; Sea transport; Air transport; Communication. |
| OthServices | Other Services | Financial services nec; Insurance; Business services nec; Recreation and other services; Public Administration/Defense/Health/Education; Dwellings. |
Source: Sectoral Aggregation through GTAPagg 7
The regions have been aggregated as so that each of the major South Asian Free Trade Area members are illustrated which include Bangladesh, India, Pakistan and Sri-Lanka. The remaining four countries- Afghanistan, Bhutan, Maldives and Nepal are part of Rest of South Asia and have been grouped together since they are not separate regions in the GTAP database version seven. Aggregation of the mainstream regional trade areas follows which include European Union, North American Free Trade Area (NAFTA), and Association of South-east Asian Nations (ASEAN), followed by Middle East and North Africa (MENA) Japan and Rest of Asia which largely consists of China. These are top trading partners for South Asian countries. Finally, the rest of the countries have been aggregated together into a group called Rest of the World.
The commodities in the GTAP database have been aggregated into 12 sectors for the purpose of this research. These include Agriculture, Forestry and Fishing, Mining, Textiles, Wearing Apparel, Light Manufacturing, Petroleum & coal, Heavy Manufacturing, Utilities & Construction, Transport and Communication and Other Services. Important sectors of South Asian Free Trade Area members have been taken into consideration for the purpose of research for example textile and wearing apparels have been separated since some countries have a comparative advantage in specific segment of wearing apparels such as Bangladesh.
Table 3.3 Pre-simulation Ad valorem Tax rates
| Bangladesh | BGD | IND | PAK | LKA | ROSA | |
| Agriculture | 0 | 16.265 | 3.317 | 18.216 | 25.58 | |
| ForestFish | 0 | 22.89 | 7.796 | 22.468 | 0 | |
| Mining | 0 | 14.218 | 22.936 | 8.425 | 0 | |
| ProcFood | 0 | 13.625 | 25.003 | 24.671 | 3.67 | |
| Tex | 0 | 21.104 | 25.983 | 27.089 | 15.252 | |
| TextWapp | 0 | 32.185 | 32.238 | 32.454 | 30.138 | |
| LightMnfc | 0 | 22.692 | 14.851 | 21.573 | 25.905 | |
| PetroCoal | 0 | 29.033 | 20.002 | 0 | 0 | |
| HeavyMnfc | 0 | 13.345 | 16.177 | 16.215 | 19.835 | |
| Util_Cons | 0 | 0 | 0 | 0 | 0 | |
| TransComm | 0 | 0 | 0 | 0 | 0 | |
| OthServices | 0 | 0 | 0 | 0 | 0 | |
| Total | 0 | 185.358 | 168.303 | 171.112 | 120.38 | |
| India | BGD | IND | PAK | LKA | ROSA | |
| Agriculture | 19.372 | 0 | 31.838 | 44.386 | 25.057 | |
| ForestFish | 0.445 | 0 | 6.27 | 12.455 | 26.025 | |
| Mining | 14.039 | 0 | 14.238 | 9.438 | 1.588 | |
| ProcFood | 26.17 | 0 | 16.099 | 40.264 | 32.777 | |
| Tex | 14.49 | 0 | 15.765 | 15 | 1.08 | |
| TextWapp | 15 | 0 | 15 | 15 | 0 | |
| LightMnfc | 14.096 | 0 | 13.909 | 14.944 | 3.331 | |
| PetroCoal | 15 | 0 | 15 | 15 | 0 | |
| HeavyMnfc | 10.096 | 0 | 14.887 | 15.039 | 4.665 | |
| Util_Cons | 0 | 0 | 0 | 0 | 0 | |
| TransComm | 0 | 0 | 0 | 0 | 0 | |
| OthServices | 0 | 0 | 0 | 0 | 0 | |
| Total | 128.708 | 0 | 143.006 | 181.526 | 94.523 | |
| Pakistan | BGD | IND | PAK | LKA | ROSA | |
| Agriculture | 8.153 | 8.211 | 0 | 13.478 | 14 | |
| ForestFish | 49.135 | 94.111 | 0 | 124.3 | 10.025 | |
| Mining | 0 | 4.67 | 0 | 4 | 8.54 | |
| ProcFood | 19.201 | 11.086 | 0 | 28.117 | 20.255 | |
| Tex | 18.558 | 11.773 | 0 | 13.507 | 19.918 | |
| TextWapp | 24.423 | 25 | 0 | 24.794 | 25 | |
| LightMnfc | 20.212 | 18.005 | 0 | 25.821 | 23.44 | |
| PetroCoal | 20.946 | 22.314 | 0 | 0 | 7.973 | |
| HeavyMnfc | 17.023 | 11.319 | 0 | 8.458 | 9.172 | |
| Util_Cons | 0 | 0 | 0 | 0 | 0 | |
| TransComm | 0 | 0 | 0 | 0 | 0 | |
| OthServices | 0 | 0 | 0 | 0 | 0 | |
| Total | 177.651 | 206.489 | 0 | 242.476 | 138.322 | |
| Sri-Lanka | BGD | IND | PAK | LKA | ROSA | |
| Agriculture | 8.961 | 22.556 | 32.389 | 0 | 10.32 | |
| ForestFish | 0 | 13.673 | 5.517 | 0 | 7.762 | |
| Mining | 0 | 4.062 | 8.332 | 0 | 0 | |
| ProcFood | 11.941 | 17.133 | 9.389 | 0 | 8.104 | |
| Tex | 1.347 | 0.878 | 0.294 | 0 | 7.703 | |
| TextWapp | 8.502 | 8.134 | 9.582 | 0 | 9.978 | |
| LightMnfc | 9.416 | 8.923 | 12.535 | 0 | 6.006 | |
| PetroCoal | 15.769 | 6.306 | 0 | 0 | 0 | |
| HeavyMnfc | 10.943 | 4.498 | 7.018 | 0 | 10.607 | |
| Util_Cons | 0 | 0 | 0 | 0 | 0 | |
| TransComm | 0 | 0 | 0 | 0 | 0 | |
| OthServices | 0 | 0 | 0 | 0 | 0 | |
| Total | 66.88 | 86.162 | 85.055 | 0 | 60.48 | |
| Rest of South Asia | BGD | IND | PAK | LKA | ROSA | |
| Agriculture | 9.982 | 10.082 | 5.964 | 15.138 | 0 | |
| ForestFish | 0 | 9.158 | 0 | 19.568 | 0 | |
| Mining | 0 | 9.958 | 22.801 | 22.738 | 0 | |
| ProcFood | 30.62 | 24.358 | 7.704 | 14.904 | 30.243 | |
| Tex | 5.913 | 9.903 | 9.854 | 20.022 | 29.443 | |
| TextWapp | 28.319 | 19.091 | 24.077 | 24.943 | 29.983 | |
| LightMnfc | 11.335 | 27.522 | 4.818 | 27.495 | 28.909 | |
| PetroCoal | 10 | 16.433 | 0 | 24.316 | 0 | |
| HeavyMnfc | 16.884 | 18.219 | 10.645 | 20.885 | 28.427 | |
| Util_Cons | 0 | 0 | 0 | 0 | 0 | |
| TransComm | 0 | 0 | 0 | 0 | 0 | |
| OthServices | 0 | 0 | 0 | 0 | 0 | |
| Total | 113.053 | 144.723 | 85.863 | 190.008 | 147.005 |
Source: GTAP Database 7
The table 3.3 shows the average import tariff charged by each SAFTA member to other SAFTA members. Average tariff rates vary from country to country and range from 0 to about 125%. The GTAP model used in this paper was simulated so that these tariff rates were reduced to zero percent. One of the main features of South Asian Free Trade Area is Trade Liberalization over a period of eight years. At the end of the eight year period, the import tariff rates are to be ranging from zero to five percent for all member countries. This is why, using “RunGtap”, the intraregional tariff rates were reduced to exactly zero percent. The table 3.4 shows the shock commands used in RunGtap to reduce the tariff rates to zero percent.
Another measure taken in this research is the complete elimination of import tariffs, therefore ignoring the sensitive lists of the nations. This is in hope that the negotiations will lead to elimination of the sensitive list which is not in the spirit of free trade. Also, it is difficult to implement each and every item due to complications in allowing this to happen in the GTAP model. The main reason being there are not enough product classifications in the GTAP that can be as close to that of the real world.
Table 3.4 Shocks used in RunGTAP
| Shock tms(TRAD_COMM,”BGD”,”IND”) = target% 0 from file tms.shk;
Shock tms(TRAD_COMM,”BGD”,”PAK”) = target% 0 from file tms.shk; Shock tms(TRAD_COMM,”BGD”,”LKA”) = target% 0 from file tms.shk; Shock tms(TRAD_COMM,”BGD”,”SouthAsia”) = target% 0 from file tms.shk; Shock tms(TRAD_COMM,”IND”,”BGD”) = target% 0 from file tms.shk; Shock tms(TRAD_COMM,”IND”,”PAK”) = target% 0 from file tms.shk; Shock tms(TRAD_COMM,”IND”,”LKA”) = target% 0 from file tms.shk; Shock tms(TRAD_COMM,”IND”,”SouthAsia”) = target% 0 from file tms.shk; Shock tms(TRAD_COMM,”PAK”,”BGD”) = target% 0 from file tms.shk; Shock tms(TRAD_COMM,”PAK”,”IND”) = target% 0 from file tms.shk; Shock tms(TRAD_COMM,”PAK”,”LKA”) = target% 0 from file tms.shk; Shock tms(TRAD_COMM,”PAK”,”SouthAsia”) = target% 0 from file tms.shk; Shock tms(TRAD_COMM,”LKA”,”BGD”) = target% 0 from file tms.shk; Shock tms(TRAD_COMM,”LKA”,”IND”) = target% 0 from file tms.shk; Shock tms(TRAD_COMM,”LKA”,”PAK”) = target% 0 from file tms.shk; Shock tms(TRAD_COMM,”LKA”,”SouthAsia”) = target% 0 from file tms.shk; Shock tms(TRAD_COMM,”SouthAsia”,”BGD”) = target% 0 from file tms.shk; Shock tms(TRAD_COMM,”SouthAsia”,”IND”) = target% 0 from file tms.shk; Shock tms(TRAD_COMM,”SouthAsia”,”PAK”) = target% 0 from file tms.shk; Shock tms(TRAD_COMM,”SouthAsia”,”LKA”) = target% 0 from file tms.shk; Shock tms(TRAD_COMM,”SouthAsia”,”SouthAsia”) = target% 0 from file tms.shk; |
After inputting the shocks, the solution was run using Gragg 2-4-6 steps extrapolation method to solve and run the simulation. The Gragg method is a multi-step solution method that reduces linearization errors and is more accurate than single-step methods such as the Johansen solution method. Errors are super-proportional to shock size, so each step increase increases the solution accuracy and reduces errors.
After running the simulation, selective aspects of the results were presented and analyzed. These include, the welfare decomposition including the allocative efficiency and terms of trade effect. Following this, important indicators like GDP and its components were studied. The main part of the research followed, which is to study the effects on trade, particularly exports. Volume changes and percentage changes in exports, imports were analyzed, particularly impact on regions and sectors. Also, changes in sectors were also studied, regarding industrial output as well as value.
3.4 Comparison with Actual Trade Data
Since, the GTAP model used is not of the latest version, in order to make up this discrepancy or to make analysis more accurate, the actual trade data after the signing of SAFTA has been included in the analysis section. The growth rates of trade, export, imports in terms of Pakistan’s total trade as well as trade with the SAFTA region and general intraregional figures have been compared with the simulation results to support the research.
3.5 Limitations
The GTAP model is the most commonly used model for assessing impacts on economies due to policy changes and regional trade agreements. It possesses features that make it superior over other methods such as the also popular gravity model and the partial equilibrium model-SMART. However, GTAP itself has its own drawbacks that can decrease the accuracy of the results and limit the capabilities of the research. The model is built and run on certain assumptions that may be hard to find true in the real world, though it has to use assumptions in order to avoid complications. Some of the assumptions are discussed in the following sections.
Firstly, the behavior of consumers, producers and governments are based on assumptions. They are expected to achieve their objects by behaving optimally. Producers aim to maximize their profits while consumers tend to maximize utility. The government has a specific pool of tax collection through direct taxes, import and indirect taxes. Government spending is assumed to allocate expenditure on different sectors based on pre-fixed sectoral shares, but these are questionable.
Secondly, the model assumes perfect competition in the market for products, services, and factors of production although in the real world it is impossible. The model assumes increasing returns to scale in production instead of constant returns to scale. Therefore, this fact can change the reality of results by overestimating economic impacts through policy shocks such as tariff reductions.
In the GTAP model, assumptions made about factors of production of labor and capital is that they are mobile among sectors within a country and not across borders. There is no flexibility in such mobility so it is unrealistic in this world of globalization and in certain regional agreements. Similarly, foreign workers and foreign direct investments are yet to be handled in a satisfactory manner in CGE models including GTAP. GTAP model is static in nature so it means that dimension of time is not considered explicitly. The long-run impacts or potential impacts cannot be studied in detail and so results in some cases may be misleading.
The GTAP database on its own uses base data from older periods of time due to lack of availability of updated data on certain countries. This may result instable or inaccurate results which may be misleading. Researchers are advised to modify the database to give it a more suitable, real world scenario but in this research paper, the standard GTAP version seven databases was used due to lack of source to updated data.
Additionally, the GTAP database version seven is comparatively an older database since currently version ten is available, however due to lack of resources, version seven has been used. For purpose of SAFTA, it may be appropriate since most of the countries databases have not been updated in these versions. In relation to this, the databases used for South Asian countries may also be labelled as not up-to date for example the database uses 2004 as the base year while Pakistan’s I-O tables consist of data collected from 1992. To make up for this, comparison of actual trade data has been used to support the results, even though the actual trade figures include several real world factors and is not limited to keeping SAFTA as the only changing variable.
Another point to note is the parameter values in use. A few GTAP model’s parameter values come from recent econometric work however, there are some that go back to the SALTER model in 1991.
The design scenario used in this research may also be labelled as “too simple” due to the fact that the GTAP model cannot handle a lot of policy shocks in Free Trade Agreements such as trade facilitation measures, non-tariff and para-tariff changes. The design scenario only involves elimination of trade tariffs among South-Asian Nations bilaterally. Time schedule for tariff liberalization of SAFTA has also not been taken into consideration since it would be too complicated to incorporate it into the study.
Chapter Four Results and Analysis
This section discusses the simulation results yielded from running the GTAP database after SAFTA scenario was implemented as shocks into the new economy. A comparison has been made on the pre-simulation or the data that was stood before SAFTA’s implementation and after the implementation or the post-simulation data. It is to be noted that the implementation of SAFTA here means that the tariffs on imports were all reduced to exactly 0% among all the SAFTA members as shown in the Tables 4.1, 4.2, 4.3, 4.4 and 4.5. Comparisons were made on welfare, GDP and GDP components, Imports and Exports and the industrial output in the economies.
Table 4.1 Post Simulation Ad valorem rates of Bangladesh
| RoAsia | ASEAN | BGD | IND | PAK | LKA | ROSA | NAFTA | EU_25 | MENA | ROW | Japan | Total | |
| Agriculture | 7.868 | 4.676 | 0 | 0 | 0 | 0 | 0 | 25.97 | 3.623 | 2.071 | 15.752 | 66.328 | 126.289 |
| ForestFish | 8.581 | 15.25 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2.963 | 0.203 | 2.558 | 29.556 |
| Mining | 1.911 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3.616 | 5.244 | 10.77 |
| ProcFood | 3.47 | 30.568 | 0 | 0 | 0 | 0 | 0 | 0.048 | 3.196 | 46.208 | 8.432 | 0.284 | 92.207 |
| Tex | 7.475 | 10.404 | 0 | 0 | 0 | 0 | 0 | 8.881 | 0 | 18.188 | 7.412 | 0.318 | 52.678 |
| TextWapp | 9.921 | 1.878 | 0 | 0 | 0 | 0 | 0 | 10.535 | 0 | 8.313 | 10.212 | 0.001 | 40.861 |
| Light Mnfc | 3.671 | 4.952 | 0 | 0 | 0 | 0 | 0 | 3.161 | 0 | 8.119 | 9.24 | 0.043 | 29.185 |
| PetroCoal | 0 | 0.308 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3.213 | 0 | 3.521 |
| HeavyMnfc | 3.809 | 4.104 | 0 | 0 | 0 | 0 | 0 | 0.462 | 0 | 6.089 | 8.539 | 0 | 23.003 |
| Util_Cons | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| TransComm | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| OthServices | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Total | 46.705 | 72.14 | 0 | 0 | 0 | 0 | 0 | 49.057 | 6.819 | 91.952 | 66.62 | 74.777 | 408.07 |
Source: author’s own calculations in GTAP Database 7
Table 4.2 Post Simulation Ad valorem rates of India
| RoAsia | ASEAN | BGD | IND | PAK | LKA | ROSA | NAFTA | EU_25 | MENA | ROW | Japan | Total | |
| Agriculture | 32.454 | 3.259 | 0 | 0 | 0 | 0 | 0 | 2.986 | 17.061 | 3.252 | 21.939 | 15.322 | 96.273 |
| ForestFish | 5.183 | 9.44 | 0 | 0 | 0 | 0 | 0 | 4.082 | 1.51 | 5.813 | 4.729 | 2.476 | 33.233 |
| Mining | 0.297 | 1.645 | 0 | 0 | 0 | 0 | 0 | 1.428 | 0.005 | 2.741 | 0.898 | 0.115 | 7.129 |
| ProcFood | 7.583 | 6.317 | 0 | 0 | 0 | 0 | 0 | 2.599 | 6.981 | 14.74 | 13.695 | 3.642 | 55.556 |
| Tex | 6.174 | 9.984 | 0 | 0 | 0 | 0 | 0 | 7.514 | 7.391 | 9.061 | 13.643 | 3.455 | 57.222 |
| TextWapp | 7.764 | 9.909 | 0 | 0 | 0 | 0 | 0 | 12.431 | 8.572 | 6.05 | 19.811 | 9.061 | 73.598 |
| Light Mnfc | 3.363 | 2.673 | 0 | 0 | 0 | 0 | 0 | 1.052 | 1.507 | 3.395 | 11.63 | 0.563 | 24.182 |
| PetroCoal | 5.05 | 2.519 | 0 | 0 | 0 | 0 | 0 | 1.296 | 0 | 7.855 | 4.857 | 2.786 | 24.363 |
| HeavyMnfc | 6.054 | 3.454 | 0 | 0 | 0 | 0 | 0 | 1.36 | 0.442 | 5.553 | 9.077 | 0.365 | 26.305 |
| Util_Cons | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| TransComm | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| OthServices | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Total | 73.921 | 49.2 | 0 | 0 | 0 | 0 | 0 | 34.748 | 43.469 | 58.46 | 100.28 | 37.784 | 397.861 |
Source: author’s own calculations in GTAP Database 7
Table 4.3 Post Simulation Ad valorem rates of Pakistan
| RoAsia | ASEAN | BGD | IND | PAK | LKA | ROSA | NAFTA | EU_25 | MENA | ROW | Japan | Total | |
| Agriculture | 160.928 | 4.49 | 0 | 0 | 0 | 0 | 0 | 3.413 | 37.948 | 1.762 | 19.929 | 19.343 | 247.814 |
| ForestFish | 3.821 | 28.063 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1.021 | 2.803 | 0.664 | 36.373 |
| Mining | 0.622 | 2.954 | 0 | 0 | 0 | 0 | 0 | 0.155 | 0.701 | 4.318 | 1.111 | 0.301 | 10.162 |
| ProcFood | 19.32 | 15.297 | 0 | 0 | 0 | 0 | 0 | 3.728 | 3.966 | 6.185 | 32.186 | 5.051 | 85.734 |
| Tex | 5.386 | 12.741 | 0 | 0 | 0 | 0 | 0 | 9.171 | 3.646 | 7.944 | 16.992 | 3.083 | 58.963 |
| TextWapp | 9.645 | 12.711 | 0 | 0 | 0 | 0 | 0 | 12.426 | 1.058 | 5.207 | 23.159 | 11.421 | 75.627 |
| Light Mnfc | 6.373 | 5.562 | 0 | 0 | 0 | 0 | 0 | 3.912 | 1.278 | 7.012 | 10.579 | 8.197 | 42.913 |
| PetroCoal | 5.347 | 10.296 | 0 | 0 | 0 | 0 | 0 | 1.202 | 0 | 4.027 | 3.095 | 2.965 | 26.932 |
| HeavyMnfc | 3.997 | 3.43 | 0 | 0 | 0 | 0 | 0 | 2.065 | 0.02 | 5.441 | 8.994 | 0.023 | 23.971 |
| Util_Cons | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| TransComm | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| OthServices | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Total | 215.44 | 95.544 | 0 | 0 | 0 | 0 | 0 | 36.073 | 48.619 | 42.918 | 118.846 | 51.048 | 608.489 |
Source: author’s own calculations in GTAP Database 7
Table 4.4 Post Simulation Ad valorem rates of Sri-Lanka
| RoAsia | ASEAN | BGD | IND | PAK | LKA | ROSA | NAFTA | EU_25 | MENA | ROW | Japan | Total | |
| Agriculture | 10.204 | 6.713 | 0 | 0 | 0 | 0 | 0 | 2.124 | 6.698 | 5.358 | 36.392 | 9.855 | 77.344 |
| ForestFish | 9.874 | 8.539 | 0 | 0 | 0 | 0 | 0 | 0.316 | 2.929 | 11.54 | 0.912 | 3.342 | 37.452 |
| Mining | 0.537 | 0.679 | 0 | 0 | 0 | 0 | 0 | 0.075 | 0 | 2.617 | 3.257 | 0.061 | 7.227 |
| ProcFood | 9.241 | 6.059 | 0 | 0 | 0 | 0 | 0 | 1.841 | 9.926 | 6.816 | 32.082 | 7.05 | 73.016 |
| Tex | 7.198 | 15.975 | 0 | 0 | 0 | 0 | 0 | 11.189 | 10.835 | 8.253 | 10.37 | 4.668 | 68.488 |
| TextWapp | 9.14 | 6.879 | 0 | 0 | 0 | 0 | 0 | 12.438 | 11.013 | 32.843 | 17.135 | 8.541 | 97.989 |
| Light Mnfc | 2.414 | 2.43 | 0 | 0 | 0 | 0 | 0 | 1.6 | 0.995 | 2.761 | 6.187 | 1.663 | 18.049 |
| PetroCoal | 0 | 0.161 | 0 | 0 | 0 | 0 | 0 | 1.33 | 0 | 8.229 | 0 | 0 | 9.72 |
| HeavyMnfc | 6.032 | 2.676 | 0 | 0 | 0 | 0 | 0 | 1.613 | 0.8 | 8.025 | 6.237 | 0.001 | 25.384 |
| Util_Cons | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| TransComm | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| OthServices | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Total | 54.639 | 50.111 | 0 | 0 | 0 | 0 | 0 | 32.526 | 43.197 | 86.441 | 112.572 | 35.182 | 414.669 |
Source: author’s own calculations in GTAP Database 7
Table 4.5 Post Simulation Ad valorem rates of Rest of South Asia
| RoAsia | ASEAN | BGD | IND | PAK | LKA | ROSA | NAFTA | EU_25 | MENA | ROW | Japan | Total | |
| Agriculture | 6.089 | 4.455 | 0 | 0 | 0 | 0 | 0 | 0.025 | 0 | 7.897 | 7.313 | 0.508 | 26.288 |
| ForestFish | 1.057 | 26.269 | 0 | 0 | 0 | 0 | 0 | 0.003 | 0 | 3.27 | 0 | 3.333 | 33.932 |
| Mining | 0.075 | 0 | 0 | 0 | 0 | 0 | 0 | 0.036 | 0 | 0.055 | 0.175 | 0.017 | 0.359 |
| ProcFood | 19.575 | 48.924 | 0 | 0 | 0 | 0 | 0 | 6.899 | 27.728 | 8.765 | 3.21 | 4.067 | 119.167 |
| Tex | 9.221 | 5.435 | 0 | 0 | 0 | 0 | 0 | 6.142 | 0 | 13.567 | 7.925 | 0 | 42.29 |
| TextWapp | 12.935 | 15.733 | 0 | 0 | 0 | 0 | 0 | 9.634 | 0 | 10.576 | 5.686 | 0.355 | 54.92 |
| Light Mnfc | 7.868 | 2.127 | 0 | 0 | 0 | 0 | 0 | 1.249 | 0.001 | 11.154 | 3.34 | 0.018 | 25.758 |
| PetroCoal | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3.999 | 0.573 | 0 | 4.571 |
| HeavyMnfc | 7.249 | 7.021 | 0 | 0 | 0 | 0 | 0 | 1.914 | 0.001 | 8.826 | 8.38 | 0 | 33.39 |
| Util_Cons | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| TransComm | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| OthServices | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Total | 64.071 | 109.964 | 0 | 0 | 0 | 0 | 0 | 25.901 | 27.729 | 68.109 | 36.602 | 8.299 | 340.676 |
Source: author’s own calculations in GTAP Database 7
The tables 4.1~4.5 show each countries average tariff rates after full implementation of SAFTAs trade liberalization program. It can be seen that while the tariff rates have been maintained across non-member regions, the tariff rates for each SAFTA member with Rest of SAFTA members have been changed to exactly a target rate of 0%. Therefore, the remaining part of this paper will discuss the effects after the implementation of such tariff liberalization.
4.1 Effect on Trade Balance
Table 4.6 Pre and post simulation Trade Balance (US$ million)
| Export | % | Imp | % | Total | % | ||||
| Base | Post-sim | Base | Post-sim | Base | Post-sim | ||||
| RoAsia | 1371393.88 | 1371355.75 | 0.00 | -1150570.63 | -1150539.75 | 0.00 | 220823.25 | 220816.00 | 0.00 |
| ASEAN | 627145.81 | 627083.44 | -0.01 | -541346.94 | -541294.44 | -0.01 | 85798.88 | 85789.00 | -0.01 |
| BGD | 10764.21 | 10762.45 | -0.02 | -13187.45 | -13077.12 | -0.84 | -2423.24 | -2314.67 | 4.48 |
| IND | 104154.88 | 104603.72 | 0.43 | -127255.79 | -127754.88 | 0.39 | -23100.91 | -23151.16 | -0.22 |
| PAK | 16648.30 | 16718.57 | 0.42 | -27229.16 | -27274.69 | 0.17 | -10580.86 | -10556.12 | 0.23 |
| LKA | 7598.65 | 7691.40 | 1.22 | -9891.13 | -9941.39 | 0.51 | -2292.48 | -2249.99 | 1.85 |
| South Asia | 2850.74 | 2900.57 | 1.75 | -5558.68 | -5347.68 | -3.80 | -2707.94 | -2447.11 | 9.63 |
| NAFTA | 1608986.00 | 1608978.38 | 0.00 | -2162837.00 | -2162826.00 | 0.00 | -553851.00 | -553847.63 | 0.00 |
| EU_25 | 4144038.75 | 4143941.75 | 0.00 | -4190592.50 | -4190495.00 | 0.00 | -46553.75 | -46553.25 | 0.00 |
| MENA | 465455.41 | 465447.00 | 0.00 | -385061.16 | -385053.34 | 0.00 | 80394.25 | 80393.66 | 0.00 |
| R.O.W | 1474830.50 | 1474775.00 | 0.00 | -1336593.00 | -1336542.25 | 0.00 | 138237.50 | 138232.75 | 0.00 |
| Japan | 655701.50 | 655664.38 | -0.01 | -539445.44 | -539776.88 | 0.06 | 116256.06 | 115887.50 | -0.32 |
| Total | 10489568.62 | 10489922.40 | 0.00 | -10489568.86 | -10489923.42 | 0.00 | -0.25 | -1.02 |
Source: Authors own calculations from GTAP Database 7
Table 4.7 Change in Trade Balance (US $million)
| Region | Change in Trade Balance |
| R.O.Asia | -7.15 |
| ASEAN | -9.73 |
| BGD | 108.57 |
| IND | -50.24 |
| PAK | 24.74 |
| LKA | 42.49 |
| R.O.SA | 260.83 |
| NAFTA | 3.58 |
| EU_25 | 1.03 |
| MENA | -0.62 |
| R.O.W | -4.95 |
| Japan | -368.56 |
Source: author’s own calculations from GTAP Database 7
This section is the main part of this research paper which is the analysis of trade for Pakistan after implementation of SAFTA. Firstly, when it comes to trade, SAFTA will help improve the situation in South Asia since it can be seen that the overall changes in volumes of trade balance is positive for all members except for India which has a US$50million decrease in trade balance. The net increase in trade balance is US$386.38million and the total percentage change in trade balance for SAFTA members adds up to 15.98% which is a large number. Bangladesh will have the highest improvement in trade balance of US$108.57 million or a 4.48% improvement. Sri-Lanka follows with a 1.85% increase in trade balance or a US$42.48 million increase. Rest of South Asia also has a huge increase of US$260.83 million or a 9.63% improvement in trade balance. Pakistan has the lowest gain in trade balance but it is a positive outlook for Pakistan. Pakistan experiences increased exports by 0.42% and a 0.23% or a US$24.74 million improvement in the trade balance. Therefore, it can be said that the overall trade balance of SAFTA members will improve and will boost trade within the region.
Table 4.8 Change in Trade balance by Region and Sector
| R.O.Asia | ASEAN | BGD | IND | PAK | LKA | R.O.SA | NAFTA | EU_25 | MENA | R.O.W | Japan | |
| Agriculture | 1.10 | -0.28 | -38.01 | 49.42 | -1.42 | -32.94 | 35.41 | -2.09 | -0.10 | -2.98 | -26.51 | -14.84 |
| ForestFish | 0.74 | -0.54 | 2.48 | -0.79 | -10.34 | 2.85 | 3.13 | 0.44 | 0.17 | -0.01 | 0.87 | -2.46 |
| Mining | 3.39 | 12.34 | 9.29 | -105.37 | 4.53 | 9.92 | -1.67 | 3.11 | 19.52 | 49.41 | 34.06 | -49.59 |
| ProcFood | 2.89 | -16.42 | 26.59 | -11.53 | -0.22 | 8.16 | 35.78 | -0.09 | -8.56 | -7.67 | -17.34 | -17.07 |
| Tex | -30.34 | -4.69 | -53.69 | 27.96 | 39.61 | 10.46 | 10.17 | -0.55 | -1.65 | -1.41 | -2.90 | -8.58 |
| TextWapp | 3.05 | -1.04 | -11.69 | 6.90 | 0.82 | -0.72 | 2.97 | 0.26 | 0.62 | -0.43 | -1.87 | -10.35 |
| LightMnfc | -9.15 | -4.88 | 20.15 | 42.55 | 2.22 | -3.37 | 50.06 | -1.13 | -16.94 | -15.37 | -5.49 | -61.10 |
| PetroCoal | 1.38 | -5.87 | 15.92 | 45.60 | -11.45 | -15.49 | 8.07 | -0.14 | -0.80 | -21.29 | -9.71 | -7.74 |
| HeavyMnfc | 5.49 | 0.76 | 101.77 | -63.00 | -10.98 | 42.11 | 57.56 | 3.47 | -16.71 | -2.15 | 13.02 | -135.62 |
| Util_Cons | 0.38 | 0.43 | 0.16 | -1.78 | 0.04 | 0.14 | 2.12 | 0.78 | 2.22 | 0.16 | 0.66 | -5.30 |
| TransComm | 11.68 | 7.08 | 19.70 | -12.19 | 7.06 | 11.07 | 26.06 | 2.12 | 27.34 | 1.25 | 9.41 | -21.97 |
| OthServices | 2.25 | 3.39 | 15.91 | -28.00 | 4.87 | 10.29 | 31.17 | -2.59 | -4.08 | -0.13 | 0.85 | -33.94 |
Source: Author’s own calculations from GTAP database 7
A general breakdown is given for each regions change in trade balance with respect to the aggregated sectors in the table 4.8. Discussing Pakistan’s scenario, the largest change in trade balance comes from the textile sector with an increase of US$39.61million which is the largest change in the sector in SAFTA. Transport and Communication services follow with a US$7.06million increase. The third sector to benefit is mining with a US$4.53 million increase in the trade balance.
Pakistan faces a US$11.45 million negative effect on the trade balance under the petroleum and coal sector and a US$10.98 million worsening of trade balance in Heavy manufacturing sector. Following this is a US$10.34 million decrease in trade balance in the forest and fishing sector. A further look will be given into the individual exports and imports in the later sections.
4.2 Effects on Intraregional-trade
The table 4.9 shows the intraregional trade within SAFTA members before and after trade liberalization. It can be seen that the total trade before implementation of trade liberalization amounted to US$6.808 billion and after trade liberalization it increases by US$682 million, to US$7.490 billion, a large increase of 10.02% which shows that SAFTA will be able to increase the intra-regional trade and stimulate trade within the region.
For Pakistan, base value for exports before trade liberalization stood at US$1.023 billion and after trade liberalization it will increase to US$1.095 billion, an increase of 72.455 million. This means that the trade liberalization will increase exports to SAFTA members by 7.08%.
Imports for Pakistan stood at US$664 million and after trade liberalization; it also increases to US$743.43 million which is an increase of US$79.35 million or an 11.99% increase in imports from SAFTA members.
After trade liberalization, Pakistan remains to have a trade surplus of US$352.36 million from the SAFTA region which means that Pakistan has more inflow of income compared to leakage of income despite the higher increase in imports from the region compared to exports to the region.
Table 4.9 Intra-regional Trade in South Asia (US$ million)
| Base Values | Post Simulation Values | ||||||||||||||
| Importing Countries | Importing Countries | ||||||||||||||
| Exporting Countries | BGD | IND | PAK | LKA | ROSA | Total Exports | BGD | IND | PAK | LKA | ROSA | Total Exports | Vol | % | |
| Bangladesh | 0 | 104.831 | 49.953 | 13.04 | 12.226 | 180.05 | 0 | 116.571 | 55.161 | 13.784 | 13.292 | 198.808 | 18.758 | 10.41822 | |
| India | 1477.71 | 0 | 516.306 | 1386.145 | 1012.416 | 4392.577 | 1673.391 | 0 | 576.132 | 1485.804 | 1098.607 | 4833.934 | 441.357 | 10.04779 | |
| Pakistan | 231.142 | 149.932 | 0 | 176.348 | 465.905 | 1023.327 | 275.492 | 176.529 | 0 | 187.704 | 456.057 | 1095.782 | 72.455 | 7.080337 | |
| Sri-Lanka | 15.745 | 459.441 | 46.465 | 0 | 83.925 | 605.576 | 18.504 | 535.742 | 55.184 | 0 | 92.668 | 702.098 | 96.522 | 15.93887 | |
| ROSA | 14.755 | 518.543 | 51.351 | 20.266 | 1.685 | 606.6 | 17.232 | 562.262 | 56.949 | 21.514 | 1.907 | 659.864 | 53.264 | 8.780745 | |
| Total Imports | 1739.352 | 1232.747 | 664.075 | 1595.799 | 1576.157 | 6808.13 | 1984.619 | 1391.104 | 743.426 | 1708.806 | 1662.531 | 7490.486 | 682.356 | 10.02266 | |
Source: author’s own calculations from GTAP database 7
Table 4.10 Regional exports (US$ million)
| VALEXPORTS | R.O.Asia | ASEAN | BGD | IND | PAK | LKA | R.O.SA | NAFTA | EU_25 | MENA | R.O.W | Japan | Total |
| Agriculture | 10404.87 | 12538.55 | 155.41 | 5502.45 | 1059.73 | 741.53 | 179.10 | 64611.09 | 95754.56 | 6821.25 | 91547.73 | 407.16 | 289723.41 |
| ForestFish | 2136.06 | 2868.86 | 36.67 | 213.14 | 33.19 | 74.18 | 56.01 | 4060.59 | 7769.19 | 555.64 | 9203.90 | 278.53 | 27285.95 |
| Mining | 7789.47 | 34414.38 | 0.34 | 4623.90 | 47.43 | 77.15 | 335.96 | 63337.85 | 44993.85 | 220761.64 | 348223.19 | 329.80 | 724934.96 |
| ProcFood | 19445.74 | 32163.86 | 444.85 | 3971.08 | 539.65 | 536.92 | 165.68 | 41764.22 | 185862.02 | 7661.43 | 83753.73 | 2602.60 | 378911.75 |
| Tex | 79013.78 | 15828.15 | 3538.99 | 9558.08 | 7191.85 | 695.77 | 262.69 | 21931.39 | 84497.87 | 6686.15 | 30985.49 | 7670.88 | 267861.10 |
| TextWapp | 70473.72 | 17978.86 | 4607.50 | 6471.90 | 2435.69 | 2411.87 | 261.22 | 10954.90 | 50536.38 | 10048.85 | 27574.48 | 620.53 | 204375.90 |
| LightMnfc | 218802.59 | 67365.16 | 467.53 | 23212.36 | 1361.22 | 624.25 | 94.51 | 383201.25 | 937905.06 | 28590.54 | 147566.84 | 158216.39 | 1967407.71 |
| PetroCoal | 17128.86 | 13661.10 | 4.97 | 3629.40 | 161.29 | 9.99 | 0.36 | 22960.06 | 57515.18 | 35421.71 | 52028.13 | 1905.31 | 204426.35 |
| HeavyMnfc | 717896.31 | 334603.84 | 303.18 | 25250.41 | 908.87 | 1094.32 | 274.90 | 652768.81 | 1673725.50 | 71677.06 | 405632.28 | 389284.75 | 4273420.26 |
| Util_cons | 3153.25 | 2001.36 | 3.96 | 317.05 | 25.04 | 27.96 | 91.57 | 7758.10 | 41789.38 | 2062.72 | 16773.52 | 6243.52 | 80247.42 |
| Transcomm | 113552.74 | 36421.33 | 198.99 | 4593.07 | 1254.74 | 917.76 | 642.63 | 88799.93 | 290550.69 | 30985.25 | 111922.59 | 27164.33 | 707004.05 |
| OthServices | 58780.80 | 35051.01 | 977.13 | 13420.41 | 1541.42 | 389.41 | 453.27 | 216485.81 | 513080.97 | 33018.33 | 104171.10 | 24152.23 | 1001521.89 |
| Total | 1318578.19 | 604896.46 | 10739.52 | 100763.25 | 16560.12 | 7601.11 | 2817.88 | 1578633.99 | 3983980.63 | 454290.57 | 1429382.97 | 618876.04 | 10127120.74 |
Source: author’s own calculations from GTAP database 7
Table 4.11 Volume change in exports (US$ million)
| R.O.Asia | ASEAN | BGD | IND | PAK | LKA | R.O.SA | NAFTA | EU_25 | MENA | R.O.W | Japan | Total | |
| Agriculture | -0.53 | -1.42 | 10.50 | 91.43 | 18.84 | 27.45 | 33.57 | -1.92 | -0.78 | -4.06 | -25.37 | -0.30 | 147.42 |
| ForestFish | 0.62 | -0.51 | 2.81 | 3.84 | 0.11 | 4.19 | 7.12 | 0.44 | 0.00 | -0.04 | 1.01 | -0.13 | 19.47 |
| Mining | 1.48 | 8.12 | 0.05 | -2.99 | 0.64 | 0.89 | 23.46 | 2.13 | 14.52 | 44.34 | 36.07 | -0.18 | 128.51 |
| ProcFood | 2.58 | -17.18 | 16.66 | 23.39 | 4.38 | 19.50 | 27.26 | -0.15 | -7.96 | -8.35 | -17.21 | -1.43 | 41.47 |
| Tex | -33.09 | -6.28 | 127.82 | 29.47 | 57.00 | 12.31 | 19.03 | 0.03 | 10.16 | -1.86 | -3.51 | -4.83 | 206.25 |
| TextWapp | 3.16 | -0.19 | 161.75 | -1.76 | 5.40 | 13.31 | 17.15 | 1.05 | 5.69 | -0.09 | -0.82 | -0.39 | 204.27 |
| LightMnfc | -14.36 | -9.59 | 15.92 | 44.86 | 3.03 | 17.01 | 6.94 | -4.09 | -15.24 | -17.17 | -11.02 | -103.16 | -86.89 |
| PetroCoal | 0.50 | -7.14 | 0.42 | 54.18 | -1.84 | 0.08 | 0.02 | -0.28 | 1.45 | -21.91 | -10.15 | -0.24 | 15.10 |
| HeavyMnfc | -32.73 | -23.46 | 14.92 | 90.02 | 10.00 | 54.48 | 28.95 | -0.25 | -18.52 | -5.41 | 4.57 | -214.12 | -91.54 |
| Util_cons | 0.26 | 0.29 | 0.14 | -0.53 | 0.05 | 0.28 | 6.72 | 0.78 | 2.29 | 0.14 | 0.55 | -3.39 | 7.58 |
| Transcomm | -2.04 | 1.13 | 7.28 | -8.91 | 2.01 | 9.18 | 48.64 | -5.38 | -10.76 | -0.82 | -1.02 | -18.46 | 20.86 |
| OthServices | 1.38 | 1.72 | 36.52 | -28.24 | 2.38 | 4.42 | 34.60 | -2.15 | -2.82 | -0.21 | 0.43 | -16.50 | 31.54 |
| Total | -72.77 | -54.51 | 394.78 | 294.74 | 101.99 | 163.10 | 253.46 | -9.79 | -21.97 | -15.41 | -26.46 | -363.13 | 644.03 |
Source: author’s own calculations from GTAP database 7
Table 4.12 % Change in exports for different sectors in each region
| RoAsia | ASEAN | BGD | IND | PAK | LKA | ROSA | NAFTA | EU_25 | MENA | ROW | Japan | Total | |
| Agriculture | -0.01 | -0.01 | 6.97 | 1.69 | 1.81 | 3.80 | 21.08 | 0.00 | 0.00 | -0.06 | -0.03 | -0.07 | 0.05 |
| ForestFish | 0.03 | -0.02 | 7.98 | 1.84 | 0.32 | 5.93 | 13.43 | 0.01 | 0.00 | -0.01 | 0.01 | -0.05 | 0.07 |
| Mining | 0.02 | 0.02 | 16.39 | -0.06 | 1.38 | 1.15 | 6.97 | 0.00 | 0.03 | 0.02 | 0.01 | -0.06 | 0.02 |
| ProcFood | 0.01 | -0.05 | 3.75 | 0.59 | 0.82 | 3.70 | 18.15 | 0.00 | 0.00 | -0.11 | -0.02 | -0.06 | 0.01 |
| Tex | -0.04 | -0.04 | 3.61 | 0.31 | 0.80 | 1.79 | 7.26 | 0.00 | 0.01 | -0.03 | -0.01 | -0.06 | 0.08 |
| TextWapp | 0.00 | 0.00 | 3.50 | -0.03 | 0.22 | 0.55 | 6.56 | 0.01 | 0.01 | 0.00 | 0.00 | -0.06 | 0.10 |
| Light Mnfc | -0.01 | -0.01 | 3.41 | 0.19 | 0.22 | 2.77 | 7.42 | 0.00 | 0.00 | -0.06 | -0.01 | -0.07 | 0.00 |
| PetroCoal | 0.00 | -0.05 | 8.98 | 1.52 | -1.12 | 0.82 | 6.46 | 0.00 | 0.00 | -0.06 | -0.02 | -0.01 | 0.01 |
| HeavyMnfc | 0.00 | -0.01 | 5.01 | 0.36 | 1.11 | 5.19 | 10.97 | 0.00 | 0.00 | -0.01 | 0.00 | -0.06 | 0.00 |
| Util_Cons | 0.01 | 0.01 | 3.54 | -0.17 | 0.19 | 1.00 | 7.34 | 0.01 | 0.01 | 0.01 | 0.00 | -0.05 | 0.01 |
| TransComm | 0.00 | 0.00 | 3.66 | -0.19 | 0.16 | 1.00 | 7.57 | -0.01 | 0.00 | 0.00 | 0.00 | -0.07 | 0.00 |
| OthServices | 0.00 | 0.00 | 3.74 | -0.21 | 0.15 | 1.14 | 7.63 | 0.00 | 0.00 | 0.00 | 0.00 | -0.07 | 0.00 |
| Total | -0.01 | -0.01 | 3.68 | 0.29 | 0.62 | 2.17 | 9.16 | 0.00 | 0.00 | 0.00 | 0.00 | -0.06 | 0.01 |
Source: author’s own calculations from GTAP database 7
Table 4.13 Volume change in exports region to region (US$ million)
| Importing Countries | |||||||||||||
| DTOT | R.O.Asia | ASEAN | BGD | IND | PAK | LKA | R.O.SA | NAFTA | EU_25 | MENA | R.O.W | Japan | Total |
| R.O.Asia | -13.99 | -12.08 | -93.09 | 30.37 | -4.77 | -10.38 | -30.17 | -7.56 | -10.65 | -1.18 | -5.94 | 86.66 | -72.77 |
| ASEAN | -1.68 | -9.33 | -61.51 | 24.04 | -3.82 | -13.06 | -32.81 | 1.50 | 0.49 | 0.10 | -0.50 | 42.06 | -54.51 |
| BGD | 6.62 | 6.18 | 0.00 | 15.82 | 7.23 | 1.22 | 1.53 | 117.66 | 204.43 | 8.72 | 18.24 | 7.15 | 394.78 |
| IND | -15.33 | -10.47 | 192.95 | 0.00 | 59.02 | 97.74 | 84.83 | -28.18 | -48.54 | -16.41 | -17.33 | -3.55 | 294.74 |
| PAK | 2.37 | 0.77 | 44.12 | 26.60 | 0.00 | 11.66 | -9.33 | 8.28 | 9.91 | 2.94 | 3.87 | 0.81 | 101.99 |
| LKA | 2.25 | 2.02 | 2.94 | 81.42 | 9.33 | 0.00 | 9.62 | 15.60 | 23.31 | 4.75 | 8.57 | 3.29 | 163.10 |
| R.O.SA | 7.82 | 6.60 | 3.77 | 82.38 | 9.78 | 2.73 | 0.35 | 39.94 | 70.95 | 3.86 | 16.36 | 8.91 | 253.46 |
| NAFTA | -3.78 | -5.41 | -24.15 | 24.78 | -5.27 | -5.69 | -34.31 | -1.85 | -6.91 | -0.69 | -5.65 | 59.14 | -9.79 |
| EU_25 | -0.20 | -5.90 | -54.77 | 71.38 | -11.13 | -21.61 | -69.00 | 8.57 | 11.36 | 1.37 | -4.60 | 52.55 | -21.97 |
| MENA | -2.19 | -5.03 | -34.05 | 65.81 | -9.40 | -4.74 | -48.54 | -1.26 | -3.45 | -0.85 | -2.24 | 30.52 | -15.41 |
| R.O.W | -0.45 | -3.66 | -64.55 | 78.13 | -4.23 | -15.80 | -61.10 | 4.66 | 1.09 | 0.10 | -5.04 | 44.38 | -26.46 |
| Japan | -102.54 | -40.57 | -28.95 | 7.00 | -3.47 | -3.71 | -13.50 | -79.15 | -60.73 | -10.17 | -27.35 | 0.00 | -363.13 |
| Total | -121.10 | -76.88 | -117.30 | 507.74 | 43.28 | 38.34 | -202.41 | 78.22 | 191.27 | -7.46 | -21.60 | 331.92 | 644.03 |
Source: author’s own calculations from GTAP database 7
4.3 Effects on Exports
This section discusses in detail the results from running the simulation of trade liberalization regarding the exports of Pakistan and SAFTA. The table 4.10 shows the post-simulation results of each aggregated regions exports and the contribution of each sector to the exports. It is to be noted that the values are noted at world price in US$ million. The total value of exports for Pakistan will be US$16.560 billion at world prices. The largest portion of exports will come from textiles at US$7.191 billion followed by wearing apparels at US$2.435 billion. Other services, light manufacturing, transport and communication and agriculture all contribute at least US$1 billion to the exports of Pakistan. After trade liberalization, the change in exports will amount to US$101.99 million; largest volume changes in Pakistan’s exports comes from textiles with a US$57 million increase, followed by agriculture with a change of US$18.84 million. Heavy manufacturing comes third with an increase of US$10 million. Wearing Apparels increase by US$5.40 million and processed food industry increases output by US$4.38 million. The Petroleum and coal industry is the only sector that decreases in volume of exports and by US$1.84 million.
The Table 4.12 shows changes in each sector exports of different regions in terms of percentage increase or decrease based on world prices. For Pakistan, there will be an overall increase in the exports by 0.62% in terms of world prices. The largest percentage increases can be seen in agriculture sector where there will be increased exports of 1.81% followed by mining at 1.38%. Heavy manufacturing follows with an increase of 1.11%. Textile industry exports will increase by 0.80%. Petroleum and coal will be the only sector to suffer decrease in exports, and it does so by 1.12%.
Increase in exports in these sectors is very moderate and not as high as expected, however there is positive change nonetheless. The Table 4.13 shows volume changes in exports from region to region. It illustrates the shift in regions’ exports to other regions as a result of the implementation of SAFTA. While exports of Pakistan will increase by US$101.99 million, imports will increase but at a lower figure of US$43.28 million. The largest change in volume of exports would go to Bangladesh with about US$44.12 million followed by India at US$26.60 million and thirdly trade to Sri-Lanka will increase by US$11.66 million. There will also be increases in exports to non-SAFTA members such as US$9.91 million increase in exports to European Union and US$8.28 million to North American Free Trade Area members. Exports to the aggregated region-Rest of South Asia however would decrease by US$9.33 million.
Pakistan will export a total of US$275.492 million to Bangladesh, an increase of US$44.118 million. This large change is owing to the US$38.718 million increase in exports to Bangladesh in the Textile sector, followed by US$2.915 million in the Heavy Manufacturing sector. These two sectors can be seen as the largest export products to Bangladesh from Pakistan.
A total of US$176.529 million worth of goods will be exported to India which is an increase of US$26.598 million. After trade liberalization, 10.487 million increases in agricultural exports to India will occur, a US$5.039 million increase in processed food exports, and a US$3.902 million increase in exports to India for textile products will follow. Agriculture is the highest export product of Pakistan to India with US$42.845 followed by processed food which totals US$35.422, petroleum and coal exports to India amount US$32.451 million and textile exports are worth US$28.271 million.
For Sri-Lanka, Pakistan will face an increase in exports to US$187 million which is an increase by US$11.657 million. The greatest increase will be coming from exports of Agriculture sector at US$9.085 billion; Heavy manufacturing will contribute to a US$1.256 million increase in exports. Pakistan’s largest export products include Textile products at US$112.07 million to Sri-Lanka, and Agriculture at US$38.701 million. Heavy Manufacturing industry also remains a high export sector to Sri-Lanka at US$21.788 million.
Table 4.14 Pakistan’s sectoral exports to regions (US$ million)
| RoAsia | ASEAN | BGD | IND | PAK | LKA | ROSA | NAFTA | EU_25 | MENA | ROW | Japan | Total | |
| Agriculture | 31.361 | 78.961 | 20.75 | 42.845 | 0 | 38.701 | 56.182 | 30.53 | 119.919 | 429.322 | 206.271 | 4.889 | 1059.73 |
| ForestFish | 6.683 | 3.795 | 0.027 | 1.166 | 0 | 0.039 | 0.22 | 0.643 | 5.287 | 9.75 | 1.277 | 4.299 | 33.186 |
| Mining | 20.003 | 3.036 | 1.941 | 1.637 | 0 | 0.02 | 2.949 | 2.949 | 7.701 | 2.731 | 2.209 | 2.256 | 47.433 |
| ProcFood | 27.981 | 34.296 | 2.939 | 35.422 | 0 | 9.391 | 140.696 | 28.105 | 181.415 | 33.827 | 28.066 | 17.509 | 539.646 |
| Tex | 824.865 | 158.997 | 204.132 | 28.271 | 0 | 112.07 | 14.177 | 2164.229 | 2135.706 | 523.944 | 911.643 | 113.816 | 7191.851 |
| TextWapp | 4.235 | 7.654 | 2.943 | 1.429 | 0 | 3.364 | 0.262 | 937.022 | 1193.491 | 153.238 | 124.687 | 7.368 | 2435.692 |
| Light Mnfc | 89.387 | 44.849 | 11.084 | 3.461 | 0 | 1.465 | 45.052 | 167.795 | 460.008 | 154.689 | 354.213 | 29.217 | 1361.22 |
| PetroCoal | 32.533 | 4.062 | 1.122 | 32.451 | 0 | 0.003 | 72.008 | 0.312 | 1.757 | 4.102 | 0.431 | 12.51 | 161.29 |
| HeavyMnfc | 82.19 | 38.588 | 27.911 | 15.903 | 0 | 21.788 | 123.319 | 81.769 | 251.559 | 133.591 | 110.894 | 21.362 | 908.874 |
| Util_Cons | 1.88 | 1.12 | 0.002 | 0.405 | 0 | 0.004 | 0.017 | 1.165 | 11.581 | 1.208 | 4.551 | 3.104 | 25.037 |
| TransComm | 92.772 | 41.756 | 1.587 | 5.655 | 0 | 0.315 | 0.68 | 251.589 | 566.12 | 46.652 | 162.138 | 85.477 | 1254.741 |
| OthServices | 49.243 | 32.809 | 1.053 | 7.884 | 0 | 0.544 | 0.493 | 715.981 | 339.55 | 208.735 | 153.47 | 31.655 | 1541.418 |
| Total | 1263.133 | 449.922 | 275.492 | 176.529 | 0 | 187.704 | 456.057 | 4382.089 | 5274.094 | 1701.788 | 2059.849 | 333.461 | 16560.12 |
Source: author’s own calculations from GTAP database 7
Table 4.15 Pakistan’s Volume changes in sectoral exports to regions (US$ million)
| RoAsia | ASEAN | BGD | IND | PAK | LKA | ROSA | NAFTA | EU_25 | MENA | ROW | Japan | Total | |
| Agriculture | 0.046 | 0.096 | 0.05 | 10.487 | 0 | 9.085 | -1.968 | 0.044 | 0.175 | 0.552 | 0.262 | 0.011 | 18.84 |
| ForestFish | 0.009 | 0.005 | 0.001 | 0.073 | 0 | 0.002 | -0.016 | 0.001 | 0.008 | 0.013 | 0.002 | 0.009 | 0.106 |
| Mining | 0.02 | 0.004 | 0.2 | 0.141 | 0 | 0.001 | 0.257 | 0.003 | 0.008 | 0.003 | 0.003 | 0.003 | 0.641 |
| ProcFood | 0.053 | 0.06 | 0.489 | 5.039 | 0 | 0.689 | -2.469 | 0.051 | 0.312 | 0.063 | 0.05 | 0.045 | 4.381 |
| Tex | 1.603 | 0.299 | 38.718 | 3.902 | 0 | 0.235 | 0.32 | 4.432 | 4.335 | 1.039 | 1.821 | 0.293 | 56.997 |
| TextWapp | 0.007 | 0.013 | 0.623 | 0.191 | 0 | 0.254 | 0.029 | 1.665 | 2.109 | 0.271 | 0.218 | 0.018 | 5.398 |
| Light Mnfc | 0.21 | 0.1 | 1.081 | 0.435 | 0 | 0.15 | -1.499 | 0.359 | 0.988 | 0.336 | 0.783 | 0.084 | 3.026 |
| PetroCoal | 0.031 | 0.003 | 0.148 | 4.333 | 0 | 0 | -6.374 | 0 | 0.002 | 0.004 | 0 | 0.018 | -1.835 |
| HeavyMnfc | 0.159 | 0.068 | 2.915 | 1.946 | 0 | 1.256 | 2.498 | 0.162 | 0.481 | 0.251 | 0.215 | 0.052 | 10.002 |
| Util_Cons | 0.003 | 0.002 | 0 | 0.002 | 0 | 0 | -0.001 | 0.002 | 0.021 | 0.002 | 0.008 | 0.009 | 0.047 |
| TransComm | 0.153 | 0.066 | -0.065 | 0.022 | 0 | -0.005 | -0.059 | 0.42 | 0.937 | 0.079 | 0.266 | 0.195 | 2.009 |
| OthServices | 0.078 | 0.05 | -0.043 | 0.03 | 0 | -0.009 | -0.047 | 1.142 | 0.536 | 0.332 | 0.241 | 0.07 | 2.379 |
| Total | 2.371 | 0.766 | 44.118 | 26.598 | 0 | 11.657 | -9.329 | 8.282 | 9.91 | 2.943 | 3.87 | 0.806 | 101.992 |
Source: author’s own calculations from GTAP database 7
The rest of South Asia consists of a US$456.057 export market; however there will be a huge 9.329% decline in the exports to these countries. The top export products to Rest of South Asia include processed foods, heavy manufacturing sector, petroleum and coal, and agricultural products. There will be decline in volume of exports from all sectors except for mining, textiles, wearing apparel, light manufacturing and heavy manufacturing which shows that SAFTA members will be facing increased efficiencies and will improve sectors where they have competitive advantage.
4.4 Effects on Imports
Pakistan’s shifts in import pattern can also be seen in Table 4.13. At first glance, it is apparent that Pakistan will reduce its imports from non-SAFTA members and replace them with SAFTA members. It will have increased imports from all the SAFTA regions particularly India where it will increase imports by US$59.02 million, US$9 million worth of imports will be increased from Sri-Lanka and Rest of South Asia while imports from Bangladesh will increase by US$7.23 million. The total imports volume for Pakistan will increase by US$43.28 million.
The Table 4.16 illustrates the breakdown of imports by sector and region at world prices. For Pakistan, the imports at world prices will amount US$25.928 billion which will be an increase of 0.15%. The largest portion of imports will come from heavy manufacturing at US$9.468 billion, followed by US$3.387 billion imports from transport and communication. Other services will also be important components of imports at US$2.455 billion worth of imports followed by the mining sector which will bring in US$2.295 billion worth of imports. In terms of percentage changes, largest change will come from Forest and fishing sector at 28.18% but looking at the figure of US$38million it is quite small compared to the industries worth billions. There will be very small increases in Agriculture sector, processed food sector, textile sector, petroleum and coal sector and heavy manufacturing while the remaining sectors will face decreases.
Table 4.16 Imports by sector and region (US$ million)
| RoAsia | ASEAN | BGD | IND | PAK | LKA | SouthAsia | NAFTA | EU_25 | MENA | RestofWorld | Japan | Total | |
| Agriculture | 27926.779 | 11753.53 | 1526.547 | 1810.896 | 1533.386 | 510.916 | 270.806 | 38392.844 | 123563.63 | 18572.1 | 42199.668 | 21662.31 | 289723.415 |
| ForestFish | 4786.486 | 919.446 | 38.401 | 668.679 | 38.091 | 14.184 | 3.849 | 3017.643 | 11967.605 | 447.307 | 1463.456 | 3920.808 | 27285.954 |
| Mining | 101363.65 | 33646.79 | 374.913 | 33164.19 | 2295.037 | 770.075 | 35.463 | 158801.97 | 227567.7 | 10690.2 | 78134.031 | 78090.88 | 724934.895 |
| ProcFood | 21841.633 | 16782.7 | 867.975 | 2955.826 | 957.035 | 583.919 | 489.076 | 58042.395 | 174427.28 | 19750.34 | 56695.563 | 25518.03 | 378911.771 |
| Tex | 30467.398 | 14273.13 | 2265.034 | 2371.606 | 727.422 | 1618.381 | 346.453 | 49108.023 | 98027.477 | 14437.72 | 42122.164 | 12096.31 | 267861.114 |
| TextWapp | 13346.997 | 3313.04 | 73.059 | 158.965 | 86.151 | 110.742 | 88.518 | 60412.594 | 81876.141 | 6557.576 | 22637.768 | 15714.33 | 204375.879 |
| Light Mnfc | 91247.625 | 58880.36 | 1418.739 | 10607.92 | 3431.56 | 1213.533 | 1045.66 | 545176.56 | 866439.25 | 74186.84 | 253375.344 | 60384.48 | 1967407.88 |
| PetroCoal | 21149.977 | 16480.1 | 694.416 | 2316.42 | 1522.368 | 553.816 | 522.668 | 41876.07 | 63337.324 | 7373.586 | 34544.805 | 14054.79 | 204426.345 |
| HeavyMnfc | 646027.88 | 283393.8 | 4011.582 | 48428.79 | 9468.775 | 2764.432 | 1522.202 | 844735.75 | 1592846 | 141689.5 | 517459.969 | 181071.6 | 4273420.28 |
| Util_Cons | 3590.698 | 3202.346 | 3.959 | 934.809 | 25.63 | 9.806 | 26.353 | 5479.661 | 41318.047 | 1460.919 | 18487.584 | 5707.603 | 80247.415 |
| TransComm | 77864.227 | 31698.84 | 464.926 | 5703.315 | 3387.894 | 578.818 | 292.244 | 112265.38 | 318210.97 | 21070.63 | 90084.117 | 45382.68 | 707004.041 |
| OthServices | 60602.883 | 44272.36 | 373.034 | 12557.25 | 2455.633 | 557.163 | 323.555 | 176610.8 | 485714.59 | 49094.85 | 117382.781 | 51577.09 | 1001521.98 |
| Total | 1100216.2 | 518616.5 | 12112.59 | 121678.7 | 25928.98 | 9285.786 | 4966.847 | 2093919.7 | 4085296 | 365331.5 | 1274587.249 | 515180.9 | 10127121 |
Source: author’s own calculations from GTAP database 7
Table 4.17 Change in imports (US$ million)
| RoAsia | ASEAN | BGD | IND | PAK | LKA | ROSA | NAFTA | EU_25 | MENA | ROW | Japan | Total | |
| Agriculture | -0.01 | -0.02 | 2.08 | 2.71 | 1.00 | 8.86 | -4.86 | 0.00 | 0.00 | -0.01 | -0.01 | 0.06 | 0.04 |
| ForestFish | 0.00 | -0.02 | -2.35 | 0.68 | 28.18 | 3.25 | -3.80 | 0.00 | 0.00 | -0.01 | -0.01 | 0.05 | 0.05 |
| Mining | 0.00 | -0.02 | -2.45 | 0.31 | -0.15 | -1.21 | 2.29 | 0.00 | 0.00 | 0.00 | -0.01 | 0.06 | 0.02 |
| ProcFood | 0.00 | -0.02 | -2.62 | 1.27 | 0.35 | 0.23 | -3.65 | 0.00 | 0.00 | -0.01 | -0.01 | 0.06 | 0.00 |
| Tex | -0.01 | -0.02 | 2.00 | 0.56 | 0.29 | -0.19 | -2.56 | 0.00 | -0.01 | -0.01 | -0.01 | 0.05 | 0.01 |
| TextWapp | 0.00 | -0.01 | 4.12 | 0.59 | -0.01 | 0.61 | -3.42 | -0.01 | -0.01 | 0.00 | -0.01 | 0.06 | 0.00 |
| Light Mnfc | 0.00 | -0.01 | -1.31 | 0.30 | -0.08 | 1.01 | -4.29 | 0.00 | 0.00 | 0.00 | 0.00 | 0.06 | 0.00 |
| PetroCoal | 0.00 | -0.01 | -2.10 | 0.43 | 0.59 | 2.71 | -1.41 | 0.00 | 0.00 | 0.00 | 0.00 | 0.05 | 0.01 |
| HeavyMnfc | 0.00 | -0.01 | -2.22 | 0.35 | 0.19 | 0.05 | -2.94 | 0.00 | 0.00 | 0.00 | 0.00 | 0.06 | 0.00 |
| Util_Cons | 0.00 | -0.01 | -3.84 | 0.19 | -0.16 | -1.42 | -7.44 | 0.00 | 0.00 | 0.00 | 0.00 | 0.09 | 0.00 |
| TransComm | 0.00 | -0.01 | -4.07 | 0.22 | -0.21 | -1.85 | -8.18 | 0.00 | 0.00 | 0.00 | 0.00 | 0.06 | -0.01 |
| OthServices | 0.00 | -0.01 | -4.10 | 0.22 | -0.20 | -1.81 | -8.79 | 0.00 | 0.00 | 0.00 | 0.00 | 0.06 | 0.00 |
| Total | 0.00 | -0.01 | -0.95 | 0.38 | 0.15 | 0.41 | -3.94 | 0.00 | 0.00 | 0.00 | 0.00 | 0.06 | 0.00 |
Source: author’s own calculations from GTAP database 7
Therefore, there is a larger impact on exports compared to imports for Pakistan after trade liberalization. Overall trade will increase and exports will grow faster than imports which is a positive point for Pakistan’s economy.
4.5 Other Effects
4.5.1 Effects on Industrial output
After trade liberalization, the impact will also be made on industrial level of output. The total industrial output will increase by US$127.43 million or by 0.88%. The largest increase in Industrial output will come from textile industry which will increase by US$91.09 million followed by Agriculture sector which will benefit by a US$18.21 million increase. Heavy manufacturing will also benefit by US$14.34 million increase in industrial output. Looking at the percentages, it can be seen that growth rates are quite low and textile has the highest growth rate at 0.47%. Forest and fishing sector and Petroleum and coal will face a small percentage decrease in industrial output of 0.03% and 0.11% respectively.
Table 4.18 Sectoral change in output by region (US$ million)
| R.O.Asia | ASEAN | BGD | IND | PAK | LKA | R.O.SA | NAFTA | EU_25 | MENA | R.O.W | Japan | Total | |
| Agriculture | -8.34 | -6.27 | -108.56 | 108.44 | 18.21 | 13.12 | -57.82 | -2.11 | 0.01 | -6.38 | -34.44 | 10.01 | -74.12 |
| ForestFish | -0.34 | -2.45 | -34.57 | 2.82 | -0.21 | -0.93 | -18.28 | 0.44 | -0.24 | -0.28 | -0.19 | 1.91 | -52.32 |
| Mining | -0.87 | 5.59 | -4.39 | 9.69 | 0.66 | 1.07 | 22.87 | 1.08 | 13.75 | 24.09 | 28.13 | 0.78 | 102.45 |
| ProcFood | -0.21 | -22.59 | -10.45 | 34.83 | 3.33 | 20.30 | 2.97 | 1.12 | -2.57 | -8.89 | -21.22 | 33.63 | 30.26 |
| Tex | -46.80 | -9.19 | 252.12 | 56.59 | 91.09 | 11.36 | 14.75 | 4.72 | 31.60 | -1.96 | -3.71 | -1.72 | 398.86 |
| TextWapp | 1.88 | -0.62 | 159.33 | -0.90 | 5.94 | 6.03 | 14.05 | 10.58 | 29.30 | 0.18 | 0.84 | 6.23 | 232.83 |
| LightMnfc | -35.63 | -17.90 | -6.99 | 106.43 | 6.18 | 15.10 | -10.99 | -12.78 | -14.17 | -20.14 | -17.64 | -50.98 | -59.52 |
| PetroCoal | -9.14 | -10.88 | -11.64 | 136.89 | -4.05 | -10.50 | -0.07 | -0.88 | 11.53 | -25.32 | -14.92 | 40.53 | 101.55 |
| HeavyMnfc | -108.03 | -34.74 | -14.96 | 261.19 | 14.34 | 52.56 | 14.63 | -9.55 | -21.86 | -7.73 | -2.84 | -106.87 | 36.15 |
| Util_cons | -19.93 | -2.65 | -86.74 | 50.42 | -0.58 | -9.30 | -35.72 | 0.38 | 5.74 | -1.98 | -1.72 | 234.11 | 132.05 |
| Transcomm | -5.80 | -0.46 | -78.55 | 76.41 | 7.73 | -31.33 | -12.99 | 5.98 | 48.26 | 1.23 | 6.23 | 81.14 | 97.87 |
| OthServices | -19.94 | -7.80 | -79.35 | -4.88 | -15.22 | -19.36 | -78.85 | 2.80 | 9.36 | -0.23 | -2.52 | 110.68 | -105.32 |
| Total | -253.14 | -109.94 | -24.74 | 837.93 | 127.43 | 48.11 | -145.46 | 1.77 | 110.71 | -47.39 | -63.99 | 359.45 | 840.74 |
Source: author’s own calculations from GTAP database 7
Table 4.19 %Change in Industrial output
| RoAsia | ASEAN | BGD | IND | PAK | LKA | South Asia | NAFTA | EU_25 | MENA | RestofWorld | Japan | |
| Agriculture | 0.00 | -0.01 | -0.50 | 0.06 | 0.05 | 0.27 | -1.10 | 0.00 | 0.00 | -0.01 | -0.01 | 0.01 |
| ForestFish | 0.00 | -0.01 | -0.62 | 0.02 | -0.03 | -0.12 | -1.48 | 0.00 | 0.00 | -0.01 | 0.00 | 0.01 |
| Mining | 0.00 | 0.01 | -0.27 | 0.04 | 0.05 | 0.39 | 4.76 | 0.00 | 0.01 | 0.01 | 0.01 | 0.01 |
| ProcFood | 0.00 | -0.02 | -0.25 | 0.05 | 0.03 | 0.69 | 0.27 | 0.00 | 0.00 | -0.02 | 0.00 | 0.01 |
| Tex | -0.02 | -0.02 | 2.38 | 0.13 | 0.47 | 1.27 | 1.20 | 0.00 | 0.01 | -0.01 | 0.00 | -0.01 |
| TextWapp | 0.00 | 0.00 | 3.18 | -0.01 | 0.16 | 0.21 | 3.93 | 0.01 | 0.01 | 0.00 | 0.00 | 0.02 |
| LightMnfc | -0.01 | -0.01 | -0.15 | 0.11 | 0.11 | 1.01 | -1.16 | 0.00 | 0.00 | -0.02 | 0.00 | -0.01 |
| PetroCoal | 0.00 | -0.02 | -1.75 | 0.29 | -0.11 | -0.79 | -1.15 | 0.00 | 0.00 | -0.03 | -0.01 | 0.05 |
| HeavyMnfc | -0.01 | -0.01 | -0.29 | 0.16 | 0.16 | 2.04 | 1.12 | 0.00 | 0.00 | -0.01 | 0.00 | -0.01 |
| Util_Cons | 0.00 | 0.00 | -0.57 | 0.04 | 0.00 | -0.26 | -1.14 | 0.00 | 0.00 | 0.00 | 0.00 | 0.03 |
| TransComm | 0.00 | 0.00 | -0.35 | 0.04 | 0.03 | -0.33 | -0.22 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 |
| OthServices | 0.00 | 0.00 | -0.50 | 0.00 | -0.04 | -0.41 | -1.52 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Total | -0.04 | -0.10 | 0.31 | 0.90 | 0.88 | 3.98 | 3.51 | 0.01 | 0.04 | -0.08 | -0.02 | 0.11 |
Source: author’s own calculations from GTAP database 7
Sri-Lanka is the country that will gain the most in terms of increase in Industrial output with a growth of 3.98% while remaining members will also benefit from increase in the industrial output after trade liberalization.
4.5.2 Effects on Welfare
Table 4.20 Post simulation welfare effects (US$ million)
| WELFARE | Allocative Efficiency | Terms of Trade | IS1 | Total |
| R.O.Asia | -17.779 | -67.532 | 54.008 | -31.302 |
| ASEAN | -7.142 | -39.911 | 7.068 | -39.984 |
| BGD | -66.007 | -398.295 | -78.325 | -542.627 |
| IND | 135.579 | 204.439 | 34.414 | 374.432 |
| PAK | 8.242 | -29.393 | -21.639 | -42.789 |
| LKA | -0.909 | -72.057 | -23.46 | -96.425 |
| R.O.SA | -47.824 | -207.331 | -161.036 | -416.19 |
| NAFTA | 22.382 | 66.153 | 76.722 | 165.257 |
| EU_25 | 34.183 | 173.134 | 74.507 | 281.824 |
| MENA | -3.457 | 6.94 | 7.749 | 11.232 |
| R.O.W | -4.602 | -8.545 | 45.927 | 32.779 |
| Japan | 71.622 | 357.725 | -22.815 | 406.533 |
| Total | 124.288 | -14.672 | -6.879 | 102.737 |
Source: Author’s own calculations from GTAP Database 7
The table 4.20 shows the results that do not appear to be very favorable for Pakistan at first sight. It can be seen that complete trade liberalization will lead to increase in total welfare to only India as it yields a US$374.432 million increase in welfare while the remaining SAFTA members including Pakistan, will have negative effect on welfare. Bangladesh has a US$66million welfare loss, Sri-Lanka has a –US$96.425 million effect, Rest of South Asia has a total of US$-416million effect on welfare while Pakistan has a negative US$42.789 million effect on its total welfare. This shows that Pakistan and South Asia except for India will have more trade diversion effects compared to trade creation effects. In other words, although trade within member countries will increase and countries will benefit from lower prices from within SAFTA, they will be importing inefficiently produced goods of lower quality, resulting in net welfare loss.
For Pakistan, the net welfare loss can be explained by the negative impact on Terms of Trade and the on the investment and savings. Allocative efficiency is positive for Pakistan and results show a US$8.242 million increase after the implementation of SAFTA.
The table 4.21 breaks down the allocative efficiency effects in the countries into different sectors of the economy. Allocative efficiency measures the production with consumer preference. Here social surplus is maximized with no deadweight loss, or that the society is content with the level of output and resources being used. It can be seen that there is an increase in the level of allocative efficiency after reduction of tariff rates within SAFTA. A study of the breakdown of allocative efficiency shows that for Pakistan, majority of the sectors will result in increase in allocative efficiency, highest being for the forest and fishing sector, or the highest welfare will be on this sector, with an increase in US$3.763million. The petroleum and coal sector follows with a similar increase of US$3.015 million. The textile is third with an increase in allocative efficiency of US$1.145 million. The agriculture sector is fourth with an increase in allocative efficiency of US$1.114 million. The Light manufacturing sector suffers the highest fall in allocative efficiency of US$1.343 million.
The table 4.22 illustrates the effects on Terms of Trade of the economies with respect to their individual sectors. Terms of trade measures the relative prices of exports in terms of the prices of imports or is the ratio of export prices to import prices. A negative sign means there is negative impact on terms of trade, or the gap between the export prices and import prices increased due to either fall in export prices, rise in import prices or both. A positive sign means that there is positive impact on terms of trade, or the gap between export and import prices increased but with an increase in export price or fall in import prices or both.
For Pakistan, the overall terms of trade effect is negative after trade liberalization. Almost all sectors except Agriculture and Forest and Fishing experience a negative impact on terms of trade. Agriculture faces a US$0.561million increase in terms of trade and Forest and Fishing sector experiences a US$0.27 million increase in terms of trade. One of the most important sectors- textiles faces the largest fall in terms of trade with a US$14.974 million loss and a similar sector of wearing apparels also decreases by US$4.332 million. These are important sectors of Pakistan and the fall in terms of trade means that textiles and wearing apparel export prices compared to import prices increased.
Table 4.21 Decomposition of Allocative Efficiency (US$ million)
| Agriculture | ForestFish | Mining | ProcFood | Tex | TextWapp | LighMnfc | PetroCoal | HeavyMnfc | Util_Cons | TransComm | OthServices | Total | |
| R.O.Asia | -0.157 | 0.003 | -0.254 | -0.089 | -1.967 | 0.038 | -3.182 | -1.906 | -8.678 | -0.589 | -0.338 | -0.72 | -17.779 |
| ASEAN | -0.264 | 0.099 | 0.1 | -0.117 | -0.295 | 0.024 | -2.433 | -1.199 | -2.457 | -0.067 | -0.23 | -0.301 | -7.142 |
| BGD | 3.756 | 0.02 | -4.748 | -13.56 | -20.321 | 2.885 | -9.022 | -6.607 | -18.665 | -1.072 | -0.306 | 1.634 | -66.007 |
| IND | 4.997 | 0.608 | 13.738 | 12.515 | 2.669 | -0.436 | 7.67 | 62.481 | 27.998 | 1.312 | 2.063 | -0.035 | 135.579 |
| PAK | 1.114 | 3.763 | 0.093 | -0.556 | 1.145 | 0.016 | -1.343 | 3.015 | 0.76 | 0.235 | -0.006 | 0.007 | 8.242 |
| LKA | 5.607 | 0.038 | -0.027 | -0.861 | -0.026 | 0.419 | 0.23 | 0.292 | -0.787 | -0.496 | -2.502 | -2.794 | -0.909 |
| R.O.SA | -1.662 | -0.047 | -0.564 | -2.952 | -2.648 | -0.489 | -22.511 | -3.542 | -9.57 | -0.541 | -4.213 | 0.914 | -47.824 |
| NAFTA | 0.088 | 0.015 | 0.114 | 0.567 | 4.061 | 22.719 | -3.273 | -0.112 | -2.399 | -0.005 | 0.23 | 0.284 | 22.382 |
| EU_25 | 0.167 | 0.024 | 0.976 | 4.266 | 8.185 | 12.714 | -2.824 | 13.513 | -4.956 | 0.307 | 1.237 | 0.501 | 34.183 |
| MENA | -0.145 | -0.022 | 0.431 | 0.182 | 0.304 | 0.092 | -1.924 | -1.505 | -0.9 | -0.13 | 0.127 | -0.003 | -3.457 |
| R.O.W | 0.941 | -0.005 | -0.256 | 0.7 | 0.98 | 0.861 | -3.824 | -2.171 | -2.371 | -0.159 | 0.103 | -0.063 | -4.602 |
| Japan | 5.677 | 0.2 | 0.983 | 8.374 | 0.527 | 1.848 | 1.514 | 34.295 | 0.969 | 11.424 | 3.56 | 2.283 | 71.622 |
| Total | 20.117 | 4.695 | 10.586 | 8.468 | -7.386 | 40.691 | -40.923 | 96.554 | -21.056 | 10.217 | -0.275 | 1.705 | 124.288 |
Source: Author’s own calculation from GTAP Database 7
Table 4.22 Terms of Trade effect on sectors (US$ million);
| R.O.Asia | ASEAN | BGD | IND | PAK | LKA | R.O.SA | NAFTA | EU_25 | MENA | R.O.W | Japan | Total | |
| Agriculture | 0.16 | -1.576 | -5.924 | 17.863 | 0.561 | -8.662 | -13.272 | 1.426 | 3.201 | 1.458 | 2.257 | 0.317 | -2.189 |
| ForestFish | 0.261 | 0.534 | -1.36 | 1.566 | 0.27 | -0.731 | -4.188 | 0.352 | 0.591 | 0.21 | 0.191 | 1.837 | -0.467 |
| Mining | -7.545 | -1.749 | -0.091 | 10.093 | -0.139 | -0.83 | -24.734 | -0.86 | 13.864 | 19.44 | 3.217 | -3.326 | 7.34 |
| ProcFood | 0.227 | 0.599 | -16.485 | 12.321 | -1.082 | -9.382 | -11.257 | 4.68 | 10.914 | 3.963 | 2.052 | 2.578 | -0.872 |
| Tex | 1.333 | 0.852 | -134.162 | 21.862 | -14.974 | -4.848 | -19.011 | 20.917 | 101.554 | 3.395 | 8.555 | 4.243 | -10.283 |
| TextWapp | 1.651 | 0.665 | -171.562 | 12.134 | -4.332 | -13.781 | -18.056 | 75.526 | 87.716 | 0.181 | 2.798 | 1.685 | -25.375 |
| LightMnfc | -2.15 | -7.575 | -16.23 | 35.661 | -3.251 | -8.081 | -6.197 | -29.845 | -15.034 | -20.726 | -14.13 | 89.52 | 1.963 |
| PetroCoal | -0.129 | -0.871 | -0.168 | 2.351 | -0.215 | -0.199 | -0.075 | 0.194 | -1.593 | 2.678 | -0.298 | -0.585 | 1.089 |
| HeavyMnfc | -60.294 | -27.154 | -10.535 | 43.761 | -1.83 | -11.618 | -18.72 | -32.31 | -44.613 | -14.828 | -16.892 | 201.587 | 6.552 |
| Util_cons | 0.113 | -0.111 | -0.142 | 0.572 | -0.043 | -0.28 | -6.944 | 0.509 | 0.842 | 0.094 | 1.044 | 3.766 | -0.579 |
| Transcomm | -1.006 | -2.218 | -8.285 | 16.817 | -2.261 | -10.106 | -56.259 | 5.335 | 13.17 | 0.791 | 0.859 | 40.17 | -2.994 |
| OthServices | -0.159 | -1.316 | -36.965 | 29.627 | -2.281 | -4.474 | -35.565 | 20.232 | 2.525 | 10.282 | 1.803 | 15.987 | -0.303 |
| Total | -67.538 | -39.918 | -401.909 | 204.628 | -29.578 | -72.993 | -214.277 | 66.156 | 173.138 | 6.94 | -8.546 | 357.78 | -26.118 |
Source: Author’s own calculations from GTAP Database 7
A negative Terms of Trade normally occurs in a regional trade area due to the changes in tariff rates. Once tariff rates are eliminated, imports become more attractive and in order to reduce this effect, exporters tend to reduce their prices to be more competitive. Therefore this can explain why the most important sectors of Pakistan will result in negative impact on terms of trade since textiles are one of the highest export products of Pakistan, so the effect is highest on this sector.
4.5.3 Effect on GDP
The table 4.23 shows the net effect on GDP of SAFTA members. A comparison is made on the pre-simulation and post-simulation GDP figure and its components of Private consumption, Investment, Government Expenditures and Net Exports. The results show that after trade liberalization, India is the only gainer in GDP with a minute 0.21% increase. Rest of the SAFTA members will suffer decreases in GDP. Bangladesh will suffer a huge 4.36% decrease while Pakistan will have the lowest decrease of only 0.23%. Sri-Lanka will have a 1.76% decrease while rest of South-Asia will have a total of 9.36% decrease in GDP. The overall effect on the total GDP for SAFTA’s region will be a fall of 0.36% which is a small decrease however; it is contrary to various literatures findings that state that economy will improve after the implementation of SAFTA.
A breakdown of the components of GDP shows that overall Consumption, Investment, and Government Expenditure all decrease in Pakistan’s case which is the reason for the small decline in GDP. Consumption expenditure declines by 0.23%, Investment by 0.22% and Government Expenditure by 0.22%. Imports also increase by 0.17% which has a negative impact on the total GDP of Pakistan. The only increase seen in the components of GDP is exports and it is the largest single component change by about 0.42%. This decrease in GDP and other components can be explained by the fact that trade liberalization will lead to overall increase in trade and so, the patterns of aggregate expenditure of Pakistan will shift towards trade. It is evident that total trade will increase since both exports and imports figure will be increased. The problem is that imports will become cheaper therefore the economic agents will spend their money or buy products from SAFTA members and shift their domestic expenditure
Table 4.23 Pre and Post simulation GDP composition (US$ million)
| Consumption | Investment | Government Expenditure | Exports | Imports | Total | |||||||||||||||||
| Base | Post-Sim | % | Base | Post-Sim | % | Base | Post-Sim | % | Base | Post-Sim | % | Base | Post-Sim | % | Base | Post-Sim | % | |||||
| BGD | 41680.13 | 39812.77 | -4.48 | 13581.35 | 13037.61 | -4.00 | 3072.03 | 2934.39 | -4.48 | 10764.21 | 10762.45 | -0.02 | -13187.45 | -13077.12 | -0.84 | 55910.28 | 53470.10 | -4.36 | ||||
| IND | 433997.44 | 434941.22 | 0.22 | 156389.78 | 156676.92 | 0.18 | 73971.57 | 74132.42 | 0.22 | 104154.88 | 104603.71 | 0.43 | -127255.79 | -127754.87 | 0.39 | 641257.88 | 642599.41 | 0.21 | ||||
| PAK | 79456.42 | 79270.63 | -0.23 | 16946.90 | 16909.39 | -0.22 | 8911.48 | 8890.63 | -0.23 | 16648.30 | 16718.57 | 0.42 | -27229.16 | -27274.69 | 0.17 | 94733.93 | 94514.54 | -0.23 | ||||
| LKA | 15587.24 | 15298.37 | -1.85 | 5123.85 | 5047.37 | -1.49 | 1664.91 | 1634.06 | -1.85 | 7598.65 | 7691.40 | 1.22 | -9891.13 | -9941.39 | 0.51 | 20083.52 | 19729.80 | -1.76 | ||||
| South Asia | 11444.73 | 10342.37 | -9.63 | 3366.56 | 3086.09 | -8.33 | 1798.47 | 1625.24 | -9.63 | 2850.74 | 2900.57 | 1.75 | -5558.68 | -5347.68 | -3.80 | 13901.81 | 12606.59 | -9.32 | ||||
| Total | 582165.96 | 579665.36 | -0.43 | 195408.44 | 194757.39 | -0.33 | 89418.45 | 89216.74 | -0.23 | 142016.77 | 142676.70 | 0.46 | -183122.21 | -183395.75 | 0.15 | 825887.41 | 822920.43 | -0.36 | ||||
Source: Author’s own calculations from GTAP Database 7
towards imported goods. The effect is also seen on private investment where due to decrease in local demand, investors will not invest as they have a negative outlook on local market.
The positive point is that exports of Pakistan as well as total trade will increase, which is one of the reasons for signing free trade agreements, but at the cost of the decreased consumption, investment and government expenditure. The GDP decline is also minute at 0.23% or US$219.4 million however a decline is also a point of concern.
4.6 Comparison of Results using Actual Trends
This section takes a look at the actual trade performance indicators of Pakistan in the past 9 years after the signing of SAFTA, in support of the simulation results gained in the previous sections in this chapter. Table 4.24 shows the total trade performance of Pakistan. The table 4.25 illustrates intraregional trade indicators of Pakistan with South Asia after the year of signing and table 4.26 shows the overall intraregional trade performance of SAFTA members.[16]
The tables all have a similar trend during the year surrounding of signing the SAFTA agreement. Large increase in growth rates occurred for exports, imports, and trade- almost peak growth rates right after the signing of SAFTA which shows that there was a huge impact after SAFTA was signed. Healthy growth rates were also present. The larger peak was faced in 2010 after the recovery from global recession of 2008 that had negative impacts in 2009.
Table 4.24 Trade growth of Pakistan
| Indicator | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | Average |
| Export Growth % | 2.88 | 14.16 | 15.21 | -19.31 | 21.43 | 20.5 | -0.63 | 3.94 | 2.14 | 6.70 |
| Import Growth % | 34.57 | 16.68 | 16.35 | -31.83 | 37.67 | 17.06 | 2.44 | 4.46 | 8 | 11.71 |
| Total Trade Growth % | 22.3 | 15.86 | 15.99 | -27.84 | 31.89 | 18.19 | 1.41 | 4.29 | 6.09 | 9.80 |
| Total Trade (US$million) | 50708.03 | 58751 | 68143.68 | 49170.78 | 64849.58 | 76645 | 77728.6 | 81064.37 | 85997.27 | 68117.59 |
Source: Asian Development Bank
Pakistan’s export growth rate jumped after the first year to 14.16%. The average growth rate in the following 8 years was 6.70%. This is high compared to the simulation results that predicted a 0.42% increase in Pakistan’s exports. It is even higher in the immediate year of implementation in 2006. Similarly, import growth rate grew at an average of 11.71% which is high compared to the simulation result of an increase in imports by 0.15%. Trade performance also increased in Pakistan over the past years at an average rate of 9.8%. Trade grew by 22.3% immediately in 2006 when SAFTA was signed and steadily. These figures are much higher than the simulation since the GTAP model only considered results from effect of SAFTA. The actual trade performance was influenced possibly by SAFTA by a small or large amount but also by other factors such as domestic and international economic growth and favorable trade with other countries such as China.
Table 4.25 South Asia’s Intraregional growth statistics
| Intraregional Trade | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | Average |
| Intraregional Export Growth (%) | 12.26 | 33.58 | 2.62 | -15.87 | 40.72 | 22.23 | 6.3 | 7.59 | 19.59 | 14.34 |
| Intraregional Import Growth (%) | 21.58 | 29.13 | 17.69 | -28.34 | 41.94 | 26.24 | -2.53 | 5.26 | 19.46 | 14.49 |
| Intra-regional Trade Share (%) | 5.16 | 5.34 | 5 | 4.31 | 4.55 | 4.25 | 4.29 | 4.52 | 5.31 | 4.75 |
| Total Trade Growth (%) | 16.99 | 31.24 | 10.44 | -22.77 | 41.34 | 24.29 | 1.68 | 6.42 | 19.53 | 14.35 |
| Total Trade, in million US$ | 20701.03 | 27167.17 | 30004.56 | 23173.24 | 32753.95 | 40711.03 | 41394.69 | 44052.2 | 52654.46 | 34734.70 |
Source: Asian Development Bank
The intraregional trade figures also had healthy gains after the signing of SAFTA. Imports and exports grew at an average of 14.35%. The simulation results predicted a lower 10.02% increase in intraregional exports. After the initial implementation of SAFTA, SAARC members’ trade continued to grow although with huge year-by-year fluctuations.
Table 4.26 Trade indicators of Pakistan’s trade with SAFTA
| Indicator | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | Average |
| Export with SAFTA Growth (%) | 4.15 | 20.34 | 18.09 | -18.36 | 22.44 | 20.62 | 2.96 | -0.23 | 4.95 | 8.33 |
| Import with SAFA Growth (%) | 97.14 | 46.68 | 0.47 | -40.1 | 108.24 | -21.27 | 3.54 | 24.45 | -2.75 | 24.04 |
| Total Trade with SAFTA Growth (%) | 31.93 | 32.09 | 9.36 | -28.26 | 55.05 | -0.77 | 3.19 | 9.8 | 1.4 | 12.64 |
| Total Trade with SAFTA in million US$ | 3380.94 | 4466.02 | 4883.88 | 3503.91 | 5432.91 | 5391.15 | 5563.31 | 6108.71 | 6194.32 | 4991.68 |
Source: Asian Development Bank
Focusing on Pakistan’s trade performance in SAFTA, there have been positive results. Comparing the simulation results, exports would increase by static 7.08% whereas in actual results in the first year after implementation of SAFTA it grew by 4.15%, jumped to 20.34% in the following year and grew at an average rate of 8.33%. Imports however do not yield similar results as predicted. Pakistan, after initial implementation of the agreement increased imports from SAFTA members by 97.14%, much higher than the predicted 11.99%. Nonetheless, this shows that Pakistan’s trade within the South Asian region increased after signing of SAFTA at an average growth rate of 12.64%. This may show weaker policy by the Pakistani government on either controlling imports or more so, failure to facilitate export industry while other members were able to support their exporting businesses. Also, the discrepancy as well as the high level of import growth may be explained by the long sensitive list kept by the Pakistani side which keeps exports of Pakistan away from tariff reductions while imports became cheaper. The GTAP simulations ignored the sensitive list.
A point to note is that growth rates declined in recent years such as 2014, possibly due to achievement of the maximum level of trade or the saturation point that may be explained by weak supply side factors such as capacity or infrastructure issues. It is too early for the maximum potential of SAFTA to be achieved since countries are yet to completely reduce their tariff rates and eliminate the items from their sensitive lists.
Chapter Five Conclusion and Recommendations
This paper aimed to identify and analyze the potential effects of South Asian Free Trade Area signed in 2004 and implemented in 2006 of January. A study of various research articles along with the use of Computable General Equilibrium model- GTAP version database seven, several conclusions were made regarding the positive and negative effects of South Asian Free Trade Area for Pakistan.
This section discusses three main findings. The first is the potential effects of SAFTA- positive and negative, the second is the feasibility problems of SAFTA and the third part is a series of recommendations given to policy makers regarding the problems identified in this research.
5.1 Potential of SAFTA
There are mixed reviews in literatures about the potential effects of SAFTA. Bandara and Wu (2001) established three classes of viewpoints in the domain of SAFTAs research- Optimistic, Moderate and Pessimistic.[17] The research conducted by them concluded with a pessimistic view of SAFTA by claiming that firstly, SAFTA members would benefit more if they reduced their tariff rates to 15% unilaterally to the whole world and not bilaterally among the members through a Regional Trade Agreement. Secondly, even if SAFTA was to yield economic benefits, they are pessimistic about the conditions necessary for the existence of SAFTA with huge blame going towards the politically hostile environment owing to Pakistan and India’s relations.
The results in this paper on the other hand yielded an optimistic view about the effects and progress of SAFTA. After eliminating import tariff rates from all SAFTA member countries, to simulate a state of final implementation stage of SAFTA, certain conclusions were drawn. From the data and simulation run under GTAP it was found that Pakistan has a net loss of US$42.789 million on total welfare after SAFTA, but with positive results on allocative efficiency. There are negative impacts on terms of trade but it is due to the import prices being lower than export prices. These can be improved with time after the implementation of SAFTA and the improvement in quality of production resulting from increased scale of production after increased export market. These are longer term dynamic effects that the GTAP model fails to capture where quality of labor improves through education and skill through every increase in volume of production. Similarly higher demand for exports would lead to investment in production technologies that lead to lower cost of production, higher profitability, higher quality and standardization of products.
Pakistan will have slight decrease in GDP of 0.23% through decrease in domestic private and government expenditure, but shift in GDP growth will come from increased trade and improve balance of payments through increased exports for Pakistan. Therefore a sacrifice can be seen from the trade liberalization policy of SAFTA that intraregional trade, which is the main goal of the South Asian Free Trade Area, will be increased but at the cost of decreased domestic expenditure. Economy of Pakistan will shift to higher dependence of trade. Again, the longer term effects of increased trade within the region are not captured by the GTAP model. Through increased trade, potential for profitability grows and businessmen will tend to increase investments and therefore create jobs, and increase disposable income for people thereby enhancing quality and standard of life, through reduction of poverty levels in Pakistan. Eventually these will result in increased GDP in the longer run.
The positive results on SAFTA’s trade can be seen as intraregional trade will increase by 10.02%. For Pakistan, trade will increase by 11.99% in terms of imports and 7.08% in terms of exports to SAFTA members after trade liberalization. It is argued that Pakistan has not been benefitting from recent joining of bilateral trade agreements since after joining them, the imports rise faster than exports, resulting in higher strain on the trade balance of Pakistan. SAFTA however results in an improvement in trade balance of Pakistan by 0.23% even though it will still be in a trade deficit but the positive result can follow up in the years following that and eventually lead to trade surplus of US$352.36 million. Similarly, for Pakistan, simulation shows that Pakistan will result in a trade surplus from trading within SAFTA members. Exports rise at 0.42%- 0.62% at world prices while agriculture, mining, heavy manufacturing and textile industry will have the greatest growth rate in exports. At the same time, imports will only rise by 0.15-0.17% at world prices which is lower than the export growth rate. Pakistan will rely on large increase of imports of heavy manufacturing and transport and communication sector, therefore increased demand of capital goods and the need for transportation services will be the result followed from increased international trade for example freight forwarding services and telecommunication services to coordinate with other countries.
Actual trade performance however, was not the same due to assumptions used in the simulation including removal of sensitive lists and complete trade liberalization- something that has not been implemented yet. Despite this, conclusion can be drawn that Pakistan’s government did not handle the situation well yet again, after signing of trade agreement, imports growth rate rose much faster than export rate.
Positive results are also yielded from the implementation of SAFTA on industrial output. The industrial output will increase by 0.88% with large benefits to the textile industry where output will increase by 0.47% and agricultural sector will follow with the second highest increase in industrial output. Sri-Lanka benefits the most with an increase of 3.98% in industrial output.
For Pakistan, sectors that benefit from SAFTA include textile, agriculture, food processing, mining and forest and fishing and these are the sectors that are recommended to be key areas of investment by private investors, foreign investors from SAFTA members and for the government to provide certain policies to support these industries to enhance production and exports.
5.2 Feasibility of SAFTA
Benefits of SAFTA can be comprehended for Pakistan in terms of increased trade and industrial output which are two main drivers of economic growth. However, the area of concern for many researchers is the feasibility or whether SAFTA can actually be operational or implemented due to hostile political climate, lack of will to commit to regional cooperation, lack of trade facilitation measures and the supply side issues.
It is up to Pakistan and India to resolve their conflicts for the benefit of not only themselves but also the rest of the region. India is seen as the bigger economy and expected to be a role model to lead the growth in the region and settle the differences with Pakistan as soon as possible. It can be seen that in recent times, political tensions have cooled down with simultaneous change in the rule of government for both countries that believe in promoting friendship between the countries. Therefore, benefit for SAFTA members can be seen in the near future.
Researchers blame lack of will for the SAFTA Ministerial Council and SAFTA governments to implement SAFTA. Again, with the change in political leadership and cooling down of tensions, the will to increase regional cooperation is being restored and the relative governments recently put SAFTA on top of their agendas. They have been reducing the number of items on the sensitive lists and Pakistan has put Free Trade Agreements like SAFTA on the priority list and on the latest trade policy framework to increase exports. India has also expressed strong interest in SAFTA when meeting with Pakistan’s leadership. Sri-Lanka has also turned towards faster implementation of SAFTA to increase its international trade.
There is criticism on the framework of SAFTA not shedding light on trade facilitation measures and have left it on the mercy of SMC meetings that are not being taken seriously in recent years Also, if SAFTA yields the economic and social benefits as shown in this paper and in many other researches, supply side issues exist where increased demand for trade cannot be fulfilled by the lack of capacity to produce, the lack of infrastructure to coordinate and transfer goods and mobilize resource and the lack of information for producers just makes it under-perform. There are still many producers in the South Asian region who do not even know about their products having the advantage of zero tariff rates in other countries as a result of Free Trade Agreements.
5.3 Recommendations
The benefits of SAFTA have been revealed in this paper and it is recommended to the Pakistan’s government to realize these benefits and implement policies that will foster regional cooperation and eliminate barriers to such cooperation. A few recommendations are given in these sections that are divided into general recommendations to the member nations and specifically to Pakistan.
5.3.1 General Recommendations
India and Pakistan should look beyond its history and hostile relations and look towards the future of the region to grow together in harmony and take advantage of the ‘peace dividend.’ It is recommended to the governments to focus their policies towards faster implementation of SAFTA.
- One of the means is to increase the pace at which annual tariff rates are being reduced.
- The governments should increase people-to-people contact to remove the idea of resentment towards the other nation.
- The SAFTA Ministerial Council should be strengthened by giving more autonomy and power that will allow the members to decide for the betterment of the regional cooperation, following economic agenda rather than fall on the path of the countries’ own political agendas. Steps should be taken to eliminate the bureaucracies involved that slows down most of the decision making and notification process.
- Strengthening the SMC will allow the top officials running the SMC to focus on SAFTA and therefore they can focus on issues such as reduction of non-tariff and para-tariff barriers as well as the reduction of product lines in the Sensitive list at an accelerated pace. Other issues that can make the SAFTA framework more effective in promoting regional cooperation will also be the top priority and agenda of the SMC.
- It is also recommended for the SAFTA members to focus on measures to promote services and investment through various policies that have been ignored in the SAFTA framework. Services are a huge part, almost 50% of the regions GDP and also an indicator for economic development in an economy, therefore services such as tourism promotion should be an area of focus in coming times. The liberalization and relaxation of investment and improvement of financial sector and services should also be a topic of interest for the policy makers since these are what facilitate and drive trade.
- Trade facilitation measures and the joint cooperation of member countries is required in eliminate the supply side problem of capacity, information share and facilitation of businesses to startup and be involved in importing and exporting goods. Trade Facilitation involves the improvement of the administrative measures when exporting and importing goods so that goods can be transferred from border to border at lowest possible time and cost especially through the customs office; it is recommended to strengthen them and introduce ways in which these processing points will become more efficient. The biggest challenge to SAFTA members is to jointly invest in intra-regional infrastructure such as road and other transport networks that will allow the free movement of goods, services and factors of production within the regions to take advantage of removed borders.
5.3.2 Recommendations to Pakistan
- It is advised to private investors and the government to focus investment on areas of agriculture, textile such as cotton yarn and linen, processed food, mining, forest and fishing. These areas have been identified as core areas that will benefit from the regional trade since Pakistan will be having an advantage in these areas. The government should foster domestic as well as foreign investment in these sectors through subsidies, and technological as well as infrastructure support. Research should be carried out on improving technology and production methods and to remove inefficiencies in the production process. These are key areas through which Pakistan can gain highest export earnings. They can be integrated into a South Asian Wearing-apparel hub, with Pakistan becoming a key supplier in the supply chain.
- Keeping the fostering of the identified sectors in mind, the government should introduce more policies to foster export of Pakistan. This can be done through a assortment of measures ranging from direct investment in exporting businesses, fostering growth of existing and new export businesses through export financing, compensation mechanisms, infrastructure and technology development, and setting up research and training facilities. Also, it should make export process must simpler and smoother, providing businesses with administrative support.
- Reduce the number of items on the sensitive lists as quickly as possible.
- Create and strengthen a separate wing that deals with SAFTA only. The division should have SAFTA as a top priority and shall include areas such as research, statistics collection, analysis as well as monitoring department.
- The Pakistani government should take the initiative to reduce hostility with India. Realizing the benefit not only the two nations, but the whole region will receive from mutual cooperation, it has to step up and do so. Pakistan also desperately needs to do so since India is already a strong and growing economy with support from the rest of the SAFTA members. It naturally blocks access of Pakistan with the rest of SAFTA members geographically, so it risks being alienated. It can do so by rapidly reducing the items on the sensitive lists. People-to-people contact can be improved to offering of exchange programs as well as scholarships to India and Rest of South Asia to create positive sentiments for Pakistan among South Asian students.
South Asian Free Trade Area is a regional trade agreement that was signed for the purpose of economic cooperation within South Asian countries. It has had criticism for unfavorable results and has faced several barriers to full implementation in the past. This paper proved the positive benefits of the arrangement and suggests few points that will strengthen the framework of the agreement.
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List of Figures and Tables
Fig 2.1 Trade Dependence of Pakistan
Table 2.4 Exports by Product Category
Table 2.7 Imports by Product Category
Table 2.8 Regional Trade Agreements signed by Pakistan
Table 2.9 Economic profiles of SAFTA members
Table 2.10 Areas of cooperation for SAFTA members
Table 2.11 Sensitive lists of SAFTA
Fig 3.1 General Equilibrium; Source: Inter-American Development Bank (2015)
Table 3.1 Regional aggregation used in the model
Table 3.2 Sectoral aggregation used in the model
Table 3.3 Pre-simulation Ad valorem Tax rates
Table 3.4 Shocks used in RunGTAP
Table 4.1 Post Simulation Ad valorem rates of Bangladesh
Table 4.2 Post Simulation Ad valorem rates of India
Table 4.3 Post Simulation Ad valorem rates of Pakistan
Table 4.4 Post Simulation Ad valorem rates of Sri-Lanka
Table 4.5 Post Simulation Ad valorem rates of Rest of South Asia
Table 4.6 Pre and post simulation Trade Balance (US$ million)
Table 4.7 Change in Trade Balance (US $million)
Table 4.8 Change in Trade balance by Region and Sector
Table 4.9 Intra-regional Trade in South Asia (US$ million)
Table 4.10 Regional exports (US$ million)
Table 4.11 Volume change in exports (US$ million)
Table 4.12 % Change in exports for different sectors in each region
Table 4.13 Volume change in exports region to region (US$ million)
Table 4.14 Pakistan’s sectoral exports to regions (US$ million)
Table 4.15 Pakistan’s Volume changes in sectoral exports to regions (US$ million)
Table 4.16 Imports by sector and region (US$ million)
Table 4.17 Change in imports (US$ million)
Table 4.18 Sectoral change in output by region (US$ million)
Table 4.19 %Change in Industrial output
Table 4.20 Post simulation welfare effects (US$ million)
Table 4.21 Decomposition of Allocative Efficiency (US$ million)
Table 4.22 Terms of Trade effect on sectors (US$ million);
Table 4.23 Pre and Post simulation GDP composition (US$ million)
Table 4.24 Trade growth of Pakistan
Table 4.25 South Asia’s Intraregional growth statistics
Table 4.26 Trade indicators of Pakistan’s trade with SAFTA
Glossary of Terms
| ASEAN | Association of South East Asian Nations |
| Benelux | Belgium, Luxembourg and Netherlands |
| BGD | Bangladesh |
| BIMSTEC | Bay of Bengal Initiative for multi-Sectoral Technical and Economic Cooperation |
| BOP | Balance of Payments |
| CD | Constant Difference of Elasticities |
| CES | Constant Elasticities of Substitution |
| CGE | Computable General Equilibrium Model |
| COE | Committee of Experts |
| CPEC | China Pakistan Economic Corridor |
| EU | European Union |
| FCCI | Federation of Indian Chamber of Commerce and Industry |
| FDI | Foreign Direct Investment |
| FOB | Free on Board |
| FTA | Free Trade Area/ Agreement |
| G-20 | Group of twenty |
| GATT | General Agreement on Tariffs and Trade |
| GDP | Gross Domestic Product |
| GTAP | Global Trade Analysis Project |
| GTAPagg | GTAP Aggregation |
| HeavyMnfc | Heavy Manufacturing |
| ICT | Information Communication Technology |
| IND | India |
| I-O | Input-Output |
| LDC | Least Developed Country |
| LightMnfc | Light Manufacturing |
| LKA | Sri Lanka |
| MENA | Middle East and North Africa |
| MFN | Most Favored Nation |
| NAFTA | North American Free Trade Area |
| Non-LDC | Non-Least Developed Country |
| OthServices | Other Services |
| Pak | Pakistan |
| PetroCoal | Petroleum and coal products |
| PTA | Preferential Trade Agreement |
| QR | Quantitative Restriction |
| ROW | Rest of the World |
| RTA | Regional Trade Agreement |
| SAARC | South Asian Association for Regional Cooperation |
| SAFTA | South Asian Free Trade Area |
| SAM | Social Accounting Matrix |
| SAPTA | South Asian Preferential Trade Agreement |
| SMART | Software for Market Analysis and restrictions on Trade |
| SMC | SAFTA Ministerial Council |
| STPF | Strategic Trade Policy Framework |
| Tex | Textiles |
| TextWapp | Wearing Apparel |
| TLP | Tariff Liberalization Program |
| TransComm | Transport and Communication |
| USAID | United States Agency for International Development |
| Util_Cons | Utilities and Construction |
| WTO | World Trade Organization |
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