The growth of vertical specialization in BRIIC countries

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The growth of vertical specialization

in BRIIC countries

Master Thesis

Pratami Mutya

S2503832

Supervisor: Dr. Abdul Erumban

Co-assessor: Dr. Dirk Bezemer

Faculty of Economics and Business

University of Groningen

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This thesis analyzes trends in vertical specialization in Brazil, Russia, India, Indonesia and China (BRIIC). We employ methodology introduced by Hummels et al. (2001) in our analysis and use data from National Input-Output Table provided by World Input-Output Database. Overall, there is an increase in VS share of export. This could suggest that the amount of imported input embodied in exported goods from the BRIICs to global trade increased during the last two decades (1995-2011). However, not all countries share the same pattern of vertical specialization. China has become more dependent on vertical linkage of production while in the other countries, horizontal specialization is a key driver of export growth. Our decomposition analysis shows that changes in vertical specialization intensity within sector contributes the most to the growth of vertical specialization and that manufacturing sectors account for most of the increase in the VS share of export.

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I. Introduction ... 1

II. Literature Review ... 6

III. Methods and Data ... 11

IV. Data Analysis ... 16

V. _{Conclusion ... 25}

References ... 26

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The growth of vertical specialization in BRIIC countries

I. Introduction

The falling costs of communication and co-ordination have lead the world towards a new wave of globalization which is characterized by increasing fragmentation of production (Baldwin, 2006). This means that stages in a manufacturing process need not to be done in one location only. Instead, one or more tasks can be outsourced to other firms or even offshored to different companies overseas. This phenomenon has attracted researchers to study the global value chain (GVC) and analyze many aspects related to it. For instance, Schmitz (2006), Sturgeon (2008), Wad (2009) and Ivarsson and Alvstam (2010) studied the governance or structure of the global value chain in different industries which lead to a conclusion that in any industry, GVC allows large companies, or head firms, to choose suppliers that can provide goods which meet their standards. Linden et al. (2009) and Sturgeon et al. (2012) study value added in GVC and Timmer et al. (2013) proposed the new measure of competitiveness of a country which is not based on gross export anymore. Instead, it is based on value added and jobs involved in global production chains.

In relation to production fragmentation, the GVC allows countries to specialize in certain jobs or be involved in value addition in one or more stages of production. In the latter case, a country exports intermediate or final goods to another country that will use the goods in further manufacturing process or add more value to the goods. The participation of more than one country in production of a good enhances trade in intermediate goods as these goods are being traded between different countries several times during the manufacturing process (Feenstra, 1998).

Outsourcing of activities to foreign countries and trade in intermediate goods are clear indications of countries engage in vertical production networks in which each of them specialize in one or more production stage(s) of a good. Since a country can specialize in certain stage or stages of production along the chain, trade in intermediate goods must take place between one country and another in which a country imports intermediate goods and add value in the manufacturing process within the country and exports some or all of the products which embody the imported intermediates to other countries. This phenomenon is called ‘vertical specialization’ by some researchers (Sanyal (1983), Hummels et al. (1998), Hummels et al. (2001) and Pitigala (2009, 2010).

These vertical production networks have also caught the attention of researchers, for example, in analyzing patterns of specialization that occured within a country (Sanyal, 1983), the trends toward foreign outsourcing (Feenstra, 1998) and specialization of a country in particular segments of the value chain (Hummels et al., 1998). Hummels et al. (2001) examine the concept of this vertical linkage and their measure of vertical specialization (VS) involves the use of imported intermediate inputs to produce goods that a country exports.

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the globalization since the fragmentation of production bring about their comparative advantages in a specific task (or tasks) and hence enhancing their integration to world trade (Pitigala, 2009). China and India are clear examples of how they engaged in this vertical linkage as they opened up their economy in the 1990s and hence provided an enormous amount of low-wage labours. Indonesia, another emerging economy in Southeast Asia, has also significantly engaged in GVC with intermediate goods accounted for more than 75% of its exports as well as its imports (Tijaja, 2012).

China, India and Indonesia are among the emerging nations that experienced growth in the dispersion of global economic activity. Adding Brazil and Russia, the Organisation for Economic Co-operation and Development (OECD) grouped the countries (BRIIC) based on their increasing importance in world trade (Safadi and Lattimore, 2009). Although those countries come from different income groups – Brazil is upper middle income, Russia is high income-non OECD, India and Indonesia are lower middle income, and China is upper middle income1– all of them experienced positive GDP growth even after the global economic crisis in 2008.

Figure 1 presents the total Gross Domestic Products (GDP) of the BRIIC countries. The total GDP of every country are increasing between 1995 and 2013, especially that of China which had more than four times increase in 2013 compared to that in 1995. Since the GDPs are based on the valuation of purchasing power parity2 _{of countries’ GDP, then the increase should be interpreted as} the augmentation of the spending power of the people in those countries. Overall share of the BRIIC countries in terms of world GDP increased from 17% in 1995 to 30% in 2013 (see Figure 2). In addition to the increase in GDP, there were also an increase in trade performances of the BRIICs, as shown in Figure 3 and Figure 4. Both exports and imports of these countries rose from about 4% in 1990 to more than 14% in 2012. Most of the increase was due to increase in China’s share in export and import.

This categorization is based on World Bank’s World Integrated Trade Solution (WITS).

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Figure 1. Total Gross Domestic Products (GDP) of BRIIC countries in millions USD

Source: The Conference Board Total Economy Database3 Note:

The total GDP is expressed in constant price of 2013 US dollars and is converted to 2013 price level with updated 2005 EKS PPPs.

Figure 2. Share of BRIIC countries in world’s GDP

Source: Author’s calculation based on The Conference Board Total Economy Database4

The Conference Board Total Economy Database is developed by the Groningen Growth and Development Centre and provides annual data from 123 countries covering GDP, population, employment, labor quality, capital services and productivity. Data are accessible from http://www.conference-board.org/data/economydatabase/.

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There are 34 member countries of the Organisation for Economic Co-operation and Development (OECD) which span from North and South of America to Europe and the Asia-Pacific region. The OECD members include many advanced countries and emerging countries such as Mexico, Chile and Turkey. More detailed explanation is available at http://www.oecd.org/about/membersandpartners/

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Figure 3. Share of BRIIC countries in terms of world’s exports (%)

Source: Author’s calculation based on UN Statistics Division5

Figure 4. Share of BRIIC countries in terms of world’s imports (%)

Source: Author’s calculation based on UN Statistics Division

World trade integration through disintegration of production is indeed enhanced as previously mentioned that there are many researchers studied this extension of study in GVC and that developing countries are also benefiting from the proliferation of GVC. Thus, looking at the increasing export share of BRIIC countries, which is more than tripled for over two decades, one might wonder if the participation in production network globally can be accounted for the growth. The same thing also happened on the import side and the increase of import share is even higher than that of the export share. China experienced the highest increase in export and import shares among those countries, followed by India, Russia, Brazil and Indonesia.

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The fact that the BRIICs have increased both their export shares as well as import shares implicitly suggest a strong correlation between share of export and share of import. The simple correlation between exports and imports in BRIIC countries during 1990-2012 is 0.99 which means that a country that heavily exports also imports heavily. This result is similar to that of Bernard et al. (2007) who find that industries in which firms are exporting correlate highly to those in which firms are importing. This might suggest the existence of international fragmentation of production, where some stages of production are performed at home while others performed abroad (Bernard et al., 2007). In the case of the BRIIC, this strong correlation may indicate that countries are increasingly engaged in a vertical production network resulting in a rise in both their exports and imports since intermediate and final goods are shipped across national boundaries.

Despite the increasing importance of the BRIICs in world trade, there is little evidence regarding the role of GVC that focuses in these countries. Most study about GVC and its impact on countries are performed in the context of developed countries (see, for example, Feenstra, 1998; Feenstra and Hanson, 1999; Hummels et al., 1998; Timmer et al., 2013). This thesis attempts to enrich the literature by analyzing vertical specialization in BRIIC countries. Given the increasing share of exports and imports of BRIIC countries, this thesis aims to study the sources of growth by focusing on each country’s involvement in vertical production chain. The main research question proposed in this thesis is, does vertical specialization contribute significantly to the growth of exports in the BRIICs and what causes changes in vertical specialization over time?

As mentioned earlier, vertical specialization refers to a mode of production in which countries specialize in particular stages of manufacturing process of a good (Hummels et al., 1998). This mode of production involves trade in intermediate goods between countries. A country that imports intermediate goods uses those goods as input in goods production domestically and exports some of the goods produced to another country. This process ends when the final goods reach end consumers. Therefore, following Hummels et al. (2001), we measure vertical specialization as the import content of export. An Input-Output (IO) framework is employed as it allows direct and indirect relationships between sectors and countries which capture the flows of goods from one country to another, then to third country and so on. Moreover, IO tables (IOT) distinguish goods according to end-use – whether the goods are intermediate goods (used as input for production process) or final goods (used for consumption). Time-series National Input-Output Tables (NIOT) from 1995 to 2011 available from World Input-Output Database (www.wiod.org) are used for our analysis.

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This section discusses an overview of the relevant literatures that link the development of global value chain studies in international trade to the concept of vertical specialization. First of all, this part will start with descriptions about global value chains and followed by studies regarding vertical specialization, and then provide an overview of studies performed in developing countries.

Globalization has lead international trade towards different patterns as the world’s economies become more integrated. Marked by two great unbundlings – declining transportation costs and declining communication and coordination costs –, globalization had caused the separation of production and consumption. As a result the location of factories needs not to be close to that of consumers (first unbundling) and manufacturing stages need not to be performed near each other anymore (second unbundling) (Baldwin, 2006). In the first unbundling, a country fully specialize in producing certain varieties of final good. That is, the entire manufacturing process of a good – starting from the provision of raw material until the finishing process of the good – is done in the country that specializes in that good. Other researchers called the first unbundling as specialization in final goods (Sanyal, 1983) or horizontal specialization (Balassa (1967) in Sen and Morgan, 1968; Hummels et al., 1998).

In the second unbundling, with the breakdown of the vertically-integrated mode of production, a country can perform particular stages of production process of a good and export the good to other country which will use that good as input to produce another good. So, there will be more than one country involve in a vertical processing of a good. This pattern of production provides opportunity for countries to offshore some tasks or stages of production. Baldwin (2006) illustrates the possibility by pointing out vast wage differences between industrialized and developing countries which outpace distance and productivity gap that makes it more profitable for developed countries to offshore several jobs to developing countries which have low-wage labour. Other than offshoring, there are also studies about the second unbundling under various terms, such as vertical specialization (Balassa (1967) in Sen and Morgan, 1968; Sanyal, 1983; Hummels et al., 1998; Pitigala, 2009), foreign outsourcing or disintegration of production (Feenstra, 1998).

Offshoring jobs means that there are more than one country that add value to a product before the product is distributed to consumers. In other words, those countries involve in a global value chain (GVC) in manufacturing a product. The concept of GVC which links companies, workers and consumers worldwide accounts for a rising share of international trade, global GDP and employment (Gereffi and Fernandez-Stark, 2011). GVC also provides opportunity for developing countries to integrate into global economy by taking part and performing activities within the chain and, thus, obtaining the gains for economic development, capacity building and job provision to alleviate unemployment and poverty.

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particular activity along the production chain. Dedrick et al. (2008) studies a dispersed innovation network in electronics industry and taking example of Apple’s iPod and notebook PC from Lenovo and Hewlett-Packard (HP) to analyze financial value created along the production chain of those products. By using a value chain analysis, breaking down the production process and components of value added and gross profit, they find that the profit gained by the lead firms depend on the product whether it is highly differentiated or not. The more sophisticated or integrated systematically a product, the more value and profit captured by the leading company. Linden et al. (2009) confirmed this result by taking the case of Apple’s iPod to further evaluate the distribution of the value generated by the product innovation to several countries that are involved in the production of iPod. After breaking down the retail price of iPod in thier study, they find that eventhough there are many firms in different countries take part in the production chain, the lead firm, Apple, keeps high value activities in home country, which is the United States. This is due to very specialized knowledge and ways of performing tasks that are tacit within the company and are difficult to transfer to other companies.

Going beyond specific case studies, researchers have also examined GVC from a more aggregate perspective. For example, Timmer et al. (2013) analyzed the measure of competitiveness of a country based on value added and activities or jobs performed in globally integrated production network to suit the increasing fragmentation of production across national borders. Focusing on European region, they employ the World Input-Output Tables (WIOT) from WIOD to calculate manufactures GVC income of a country that measures the income originated from production activities of final manufacturig goods that are carried out within the country. Comparing the GVC income across countries, they find a decline in shares of world’s GVC income for the EU region, NAFTA (comprising Canada, Mexico and US) and East Asia (comprising Japan, South Korea and Taiwan), but an increase in the shares for China and other emerging markets (Brazil, Russia, India, Indonesia, Australia and Turkey). They also examine the loss of jobs in manufacturing sectors related to GVC and find that in most of EU27 countries, job increase in services exceeds job loss in manufacturing and there is a shift from low-skilled towards high-skilled employment. Their results are clearly indicative of the fact that with production fragmentation that takes place internationally, countries actually specialize in certain activities along the chain.

Dedrick et al. (2008), Linden et al. (2009) and Timmer et al. (2013) have shown that when the activities that constitute a value chain are broken down so that they can be carried out in different countries linked by a global production network, a country can choose to specialize in certain stages of a good production. This type of specialization has been subject to analysis in the past as well. For instance, Sanyal (1983) studies vertical specialization to examine which stage of a vertical production process a country can specialize at. In a model of two countries,6 _{Sanyal shows that both}

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countries can benefit under vertical specialization when they choose to specialize in stages of production that match their comparative advantages. Sanyal also takes note that the nature of exports between developed and developing countries are different. Less developed economies export more raw materials and semi-finished goods while developed economies export goods that are relatively more finished the most. This implies that less developed economies have comparative advantage concerning raw materials and semi-finished goods and hence they specialize in stages of production where they produce those goods.

There has also been a number of studies at empirical level examining the concept of vertical linkages as a result of production fragmentation. Feenstra (1998) argues that the world has become more integrated through trade and the integration bring a disintegration of production with it, in which there is combination between production activities carried out within a country and those carried out overseas. He reports increasing foreign outsourcing in several OECD countries by pointing out several measures such as share of exports and imports by end-use categories, ratio of imported to domestic intermediate inputs and share of of imported to total intermediate inputs. Overall, the imported intermediate inputs increased over several decades of observation across countries. The observation leads to a conclusion that the world has become more integrated through trade and that the trade has moved towards vertical linkage of production.

The impact of foreign outsourcing is further investigated by Feenstra and Hanson (1999) by focusing on the offshoring of intermediate goods in the United States, that is, the transfer of tasks or stages of production to the United States from abroad that could have been done by any company within the United States. Imported intermediate inputs is measured as the product of the share of imports of a particular good in the consumption of that good and the amount of input purchased for that good in a particular industry. The results show an increase in foreign outsourcing in the United States.

The increasing of international production as pointed out by previous studies will be associated with the increasing trade when countries are vertically linked in a good’s production (Hummels et al., 1998). That is, when fragmentation of production gives opportunity for countries to take part and perform certain activities along the vertical linkage of production. Hummels et al. (1998) distinguish two modes of production, which are horizontal and vertical specialization. In a horizontal specialization chain of production, countries produce their own goods from the start until the end of the production process and trade the goods in the form of finished goods to consumers elsewhere. In a vertical specialization set, there is a sequential mode of production in which different country specialize in particular stages of good production. This mode of production involves trade in intermediate goods between countries. In the sequence, a country imports a good from another country, uses that good in its production process, and produce its own good some of which will be exported to another country. The sequence ends when the final good reaches its final destination.

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Vertical specialization is considered as an important mechanism to explain trade growth because it can amplify the impact of tariff reductions and results in a large increase in trade (Yi, 2003; Pitigala, 2010). Standard trade models focus on declining tariff barriers to explain growth in world trade but they cannot explain the dramatic trade growth despite of small tariff reduction and the non-linear effect of the tariff reduction overtime. Yi (2003) proposes a model which focuses on vertical specialization as a key component because in a vertical production chain many countries are connected through production processes in a sequential manner, with each country specializing in particular stages of production. Goods that are produced in a vertical specialization chain cross national borders several times during the production process. Since a tariff is incurred every time these goods in process cross a border, the back and forth flow of the goods will create multiplier effect of the tariff reduction and lead to cost reduction in producing these goods. This cost reduction can magnify increase in trade. Furthermore, tariff reductions allow more efficient production of goods under vertical specialization setting which, in turns, lead to more increase in trade. Thus, we can observe growth of trade in vertically specialized goods which exceeds growth of trade in regular goods. Overall trade growth will therefore be higher than the prediction of standard trade models.

Hummels et al. (2001) use a measure of vertical specialization (VS) for the vertical linkage of production for goods that are exported. Their measure is different from Feenstra and Hanson (1999) who measure imports in intermediate inputs for overall production of goods. A country can take part in a VS chain by importing goods that are used as inputs for producing exported goods or by exporting goods that are used as inputs into another country’s production of export goods. In their study, Hummels et al. (2001) used input-output framework which facilitates the classification of goods based on their purposes (intermediates or final goods) and their origins (domestic or foreign). Besides country-level analysis, they also focus on manufacturing sectors to explain the contribution of those sectors to the growth in vertical specialization. Their study indicates a rise in vertical specialization for all sample OECD countries, and the growth of VS contributes to growth in export share of gross output in those countries. They also find that manufacturing sectors have main contribution to the increase in vertical specialization through increases in their vertical intensity, i.e. increases in vertical specialization within sector. Their findings suggest that the increase of vertical specialization is due to the increase of exports in sectors that use imported inputs intensively and to the increase in share of total imported intermediates in sectors with high exports.

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result to the measure of VS by Hummels et al. (2001), they find the correlations across the European Union countries (EU 27) of these two measures are high during the this period, indicating that there are clear trends towards increased fragmentation.

The development of measures accounting for value added flows due to international fragmentation is also studied by Stehrer (2013) who compares two concepts of measuring value added flows between countries. One concept is calculating a country’s domestic and foreign value added content of its exports, i.e. vertical specialization as developed by Hummels et al. (2001), and the other is calculating value added created in a country due to consumption in other countries, i.e. the value added exports as developed by Johnson and Noguera (2012). After generalising both approaches by considering value added imports from other countries which leads to a consideration of net trade positions in value added terms, he finds that both concepts have the same result of the level of net exports for a country’s total trade in value added terms. The result justifies to calculate a country’s domestic value added content of its exports using total exports, i.e. including intermediate exports, rather than final goods exports only as in national accounts exports. Stehrer (2013) also provides empirical evidence that the shares of the foreign value added in a country’s exports mirrors the value added exports shares, or, to be more precise, both foreign and domestic value added embodied in exports make up for 100% of gross exports.

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Another study conducted by Reyes et al. (2009) regarding trade pattern of Brazil, Russian Federation, India, Indonesia, China and South Africa (BRIICS) shows that the countries have more trade partners in raw materials, intermediate goods, consumer goods and capital goods yet not all of them experience an increase in the number and value of trade (exports and imports). This finding suggests that the wave of globalisation has resulted in an increase in the number of connections but has different effect in trade intensity across the network between BRIICS and their trade partners. They also discuss that each country has different specialization in serving world market and that all BRIICS countries import large amount of intermediate goods to produce capital goods and exported consumer goods. However, they did not provide analysis about vertical specialization in the BRIICS and to what extent does the vertical specialization account for the trade relationship between the BRIICS and their trading partners.

While the previous studies highlight the importance of GVC for the world economy and its increasing role in developing countries, there is still hardly any evidence on the specialization of those countries along the vertical production chain. This thesis makes important contribution to the literature by providing empirical evidence on the contribution of vertical specialization to export growth in emerging economies, i.e. Brazil, Russia, India, Indonesia and China (BRIIC) and the sources of change in vertical specialization over time. Given the importance of vertical specialization for economic growth and the growing importance of BRIIC, we hypothesize that vertical specialization contributes significantly to the growth of export in BRIIC countries.

III. Methods and Data

This thesis aims to provide empirical evidence on vertical specialization that took place in BRIIC countries, i.e. how the vertical specialization contributes to export growth and what causes the change in vertical specialization over time. This section will present methodology used and the data needed to answer those questions. Prior to it, we will review the theory of vertical specialization which leads to the methodology development.

III. 1. Methodology

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An illustration of a vertical specialization chain is shown in Figure 5. Assume there are three countries involved in the chain. Country 1 produces intermediate good which it exports to Country 2. Country 2 makes some value added by processing the imported intermediate input it gets from Country 1 using its capital, labour and domestic input to make another good (final good). Some of the final good is then exported to Country 3.

Figure 5. Vertical specialization chain

Source: Hummels et al. (2001)

The condition when a country uses imported inputs to produce its good and then export some of the goods, as illustrated, is one way a country can participate in a vertical specialization chain. This is the focus of this thesis, which is to examine the measure of vertical specialization (VS) defined as the import content of a country’s export, or in other words, foreign value-added embodied in exports. For this purpose, we follow heavily on the method developed by Hummels et al. (2001).

The method developed by Hummels et al. (2001) to measure the value of imported inputs embodied in goods that are exported, VS, is widely used as reference measure in conforming the increase fragmentation or value added flows. While there exists other approaches to measure fragmentation, a comparison of these approaches suggest a convergence rather than a contradiction in results (Stehrer, 2013; Timmer et al., 2013). Therefore, the results are invariant to the method we use, and taking this into account we opt to use the vertical specialization measure of Hummels et al. (2001) in analysing a country’s import content of export.

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However, due to the difficulties in measuring the second approach of vertical specialization, Hummels et al. (2001) focused on calculating the former concept of vertical specialization.

The measure of vertical specialization (VS) in country k and a particular good or sector i provides the value of imported input content of export. It is defined as the share of imported inputs into gross production multiplied by the amount of goods exported (Hummels et al., 2001), as presented in equation (1). Thus, VSki can be interpreted as the amount of imported input needed to

fulfill every unit of export of good or sector i in country k.

= . (1)

Equation (1) implies that for good or sector i, the VS share of exports is equivalent to the imported input share of gross output. The sum of VS across all sectors in the country, i.e. VSk = ∑i

VSki, yields a country’s VS, and the VS share of total exports is:

= ∑" "

∑ " " =

∑ #" _"/ "%∗ "

∑ " " (2)

Xki is denoting exports of country k for sector i. To calculate the VS measure for many countries which

includes many industries, it will be more convenient to employ matrix operation. In matrix term, the VS share of total exports is written as:

VSk/Xk = uAMX/Xk (3)

u is a vector of ones in 1xn dimension, AM _{is a coefficient matrix of imported goods in nxn dimension,} X is a vector of exports with an nx1 dimension, n is the number of sectors and Xk is total exports across all sectors in a country.

Since it is possible for the intermediate goods to be used indirectly in the production of exported final goods, that is, imported inputs is used in a sector whose output is used as inputs in another production process before they eventually become a content in exported goods, we need to embody this indirect inputs into the matrix equation. This can be done by applying a term which captures those inputs used in stages of production process before they become embodied in goods that are exported. The matrix equation is now:

VSk/Xk = uAM[I-AD]-1X/Xk (4)

with I as the identity matrix, AD _{as n x n domestic coefficient matrix and [I-A}D_]-1 _{as the term that} captures all intermediate inputs, direct and indirect, embodied in final goods that are exported.

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Koopman et al. (2014) point out a problem of double counting in VS measure in terms of value added that is re-imported by a country. This happens when, for example, Country 1 produce intermediate goods and export them to Country 2. Country 2 then use the goods as input in its production process to make more-finished goods. Some of these goods are further exported to Country 1 who will incorporate them in a manufacturing process to produce a final good. In this case, Country 1 imports intermediate good which already contains value added from previous production stage takes place within the country, or in other words, value added exports that are returning back home (Stehrer, 2013). Koopman et al. (2014) performed accounting for vertical specialization and find that the double counting accounts for 5.1% of gross exports in 2004. However, as Stehrer (2013) examines the accounting of value added flows in world trade, the double counted terms cancel out when aggregating bilateral trade over partner countries. In addition, Koopman et al. (2014) also explain that some parts of their accounting equation to generate measures of vertical specialization are consistent with the idea of Hummels et al. (2001) that a country’s gross exports consist of domestic and foreign content and that the measure of vertical specialization developed by Hummels et al. (2001) can be used to quantify the extent to which intermediate goods cross international borders more than once. Thus, the measure of VS is still considered reliable to analyze the extent of a country’s participation in a vertical production chain.

Further analysis regarding vertical specialization is to observe whether a country’s participation in vertical specialization chain contributes to the country’s exports. In relation to vertical specialization, exports can be divided into exports due to vertical specialization and other exports, i.e. decomposing exports into foreign value-added embodied in exports and domestic value-added embodied in exports (Hummels et al., 2001). Calculating the exports as a share of gross output (GO), the decomposition of change in exports takes the following form:

∆ ,) *+ ,)= ∆ ,) *+ ,)+ ∆ - ,). ,)/ *+ ,) (5)

Equation (5) allows us to examine the growth of overall exports in terms of gross output and the contribution of vertical specialization to that growth.

Since VS measure is changing over time, we will also perform analysis to identify the sources of those changes. We employ structural decomposition analysis that decompose the changes in VS share of exports into the changes in sectoral VS intensity and sectoral share of overall export. In doing so, we re-arrange equation (2) into:

= ∑ #" "/ "%∗ "

∑ _{" "} = ∑ 0 "# /1 %2 (6)

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VSk,i,t, Xk,i,t and ωk,i,t are, respectively, VS, exports and share of total exports for country k, sector i, in time t.

Equation (7) decomposes the changes in VS share of a country due to the changes in sectoral VS share (changes within sectors) and changes in the composition of every sector’s share of total exports (changes between sectors). Both changes are captured in the first and second term, respectively.

III. 2. _Data

The calculation of the amount of intermediate input comes from abroad that is used in the manufacturing of exported goods requires very detailed data on the production process of a good since we need to know at which stage each good is being traded across national boundaries. Since those data are impossible to obtain, we will use input-output tables which contain sector-level data on inputs, value added, final demand and gross output. There are several advantages of using input-output tables. The input-input-output tables show distribution of goods from one industry (or sector) to other industries (intermediate goods) as well as to other use such as consumption or export (final goods). Furthermore, they distinguish the source of inputs, either from abroad or from within the country. Hence, the classification of goods by end use and origin in the tables is an advantage for the purpose of measurement because the measure is only considering intermediate goods from abroad that are used for producing goods that are exported.

For the purpose of this thesis, we rely on the World Input Output Database (WIOD) which was developed with regard to the fragmentation of production as the world enters a new phase of globalization. Using the database, one can investigate the trade patterns, environmental degradation and changes in socio-economic accounts due to globalization across countries (Timmer, 2012). The database is constructed using national supply and use tables (SUTs) which include domestically produced and imported goods. Imported goods are categorized by end-use. Different from most databases which apply assumption of import proportionality, i.e. there is the same, fixed percentage of total use of a product assumed to be imported, in the national SUTs the allocation of imported goods to each of the end-use category has different allocation of imported goods (Dietzenbacher et al., 2013). We will employ the National Input-Output Tables (NIOT) for Brazil, Russia, India, Indonesia and China from 1995 to 2011 which are publicly accessible in www.wiod.org.7 _{We will} include all sectors in the analysis and use the data on inputs (domestic and foreign), exports and total output.

7 _{WIOD consists of World Input-Output Tables (WIOT), NIOT, Socio-Economic Accounts (SEA) and Environmental Accounts.}

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We measure vertical specialization as a share of total exports (from here on, the term used will be VS share of export) in each country using equation (4), and the results are depicted in Figure 1. The VS share of export show notable variation between 1995 and 2011 across BRIIC countries. It is worth noting that India’s VS share of export in 1995 was below China’s VS share of export but in 2011 both countries reached about the same level of VS share of export in 2011, which reflects the growing importance of both countries in international production.

The import content of Brazilian exports as share of total exports also increased from 0.079 in 1995 to 0.1195 in 2011. VS share of export for Indonesia fluctuated and experienced a slight decrease as well as Russia between the time period. In 2011, VS share of export were 0.1472 and 0.0633 for Indonesia and Russia respectively. Of all countries, India has the largest increase in VS share of export which is more than 100% during the last two decades. This means that India has intensively used imported intermediate goods in its exports more than other countries in the BRIIC group. Brazil and China have more than 40% increase, while Indonesia and Russia are having around 5% and 15% decrease, respectively, in VS share of export.

Figure 6. VS share of exports of BRIIC countries (1995-2011)

Source: Author’s calculation based on equation (4) using data from WIOD

After calculating VS share of exports for each of BRIIC countries, we calculate the VS share of exports for the entire countries. The results are presented in Table 1, which also includes more detailed results for each country. Share of the BRIICs in world exports increased more than twice from 1995 to 2011. Aggregating across all countries the VS share of export in the initial and final years are 0.125 and 0.188 respectively. This means that overall, exports from BRIIC countries to their trading partners embodied 50% more of imported inputs in 2011 compared to that in 1995. The

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increase in share of world exports and in VS share of exports confirm the role of BRIIC countries in world trade which has become more significant in the last two decades.

Table 1. BRIIC’s share in world exports

Country Share in export VS share of exports Change in export share Change in VS share of exports 1995 2011 1995 2011 BRIIC 0.073 0.186 0.125 0.188 0.113 154.7% 0.063 50.4% Brazil 0.010 0.016 0.079 0.120 0.006 57.7% 0.041 51.3% Russia 0.015 0.026 0.075 0.063 0.011 76.9% -0.012 -15.4% India 0.008 0.018 0.105 0.218 0.011 139.9% 0.113 107.1% Indonesia 0.010 0.012 0.155 0.147 0.002 21.0% -0.008 -4.9% China 0.030 0.113 0.160 0.226 0.083 271.9% 0.066 41.2%

Source: Author’s calculation using data from WIOD

Note: Value of export of every sector per year in each country is a substraction of domestic input and final demand from total output. Adding all exports from every sector yields total export of a country for a particular year. World’s export is calculated as the total exports of all countries in the World Input-Output Tables (WIOT).

18

Contribution of VS exports to growth in export share of gross output from 1995 to 2011

Country Change in export share Change in share of VS export Change in share of non-VS export Contribution of VS share (%) Contribution of non-VS share (%) Brazil 0.029 0.005 0.024 _{18.08 81.92} Russia 0.014 -0.001 0.015 _{-4.46 104.46} India 0.036 0.014 0.021 _{40.09 59.91} Indonesia 0.015 0.001 0.013 _{8.70 91.30} China 0.005 0.007 -0.002 _{146.16 -46.16}

Source: Author’s calculation based on equation (5) using data from WIOD Note: All columns are expressed as a share of gross output

It is interesting to observe that while the other countries having no more than 50% of VS share contribution to the export growth, VS share of China has extraordinary positive contribution on the increase of the country’s exports. When we look at the split of changes in export share of gross output, non-VS exports contributed negatively to the increase in export share, suggesting that China incorporated more imported intermediate input and less domestic input to produce exported goods in the last twodecades. This is in line with studies concerning China’s participation in global value chain in which China imports high value added goods to be used as inputs in its production processes (Linden et al., 2009; Ivarsson et al., 2010), specializes in assembling and exporting final goods (Reyes et al., 2009), and that China’s export values contain expensive imported inputs (Sturgeon et al., 2012). This finding also suggests that vertical specialization has been a dominant source of export development in China.

On the contrary to China, VS share of Russia has negative influence on the increase of the country’s export share of gross output. Russia is the only country who has a decrease in its VS export share of gross output and an increase in its non-VS export share. This implies that Russia incorporated more domestic value added and less foreign value added in the goods it exports, and that non-VS share of output, i.e. export of horizontal specialization goods, is the dominant source of export growth in Russia. This phenomenon might be explained by Russia having abundant raw materials (e.g. natural gas) and comparative advantage in mining (Kiyota et al., 2009), and by the development of gas and oil pipelines (Reyes et al., 2009) so that Russia’s exports in raw materials, which is not part of vertical specialization chain, play major role in increasing the country’s export share of gross output.

19

percentage of the domestic value added than the foreign value added compared to India. Brazil and Indonesia have comparative advantages in raw materials and both of them have good connectivity in terms of number of trading partners and trade value of raw materials (Reyes et al., 2009). In addition, especially in Indonesia, there are measures from government to embed more value addition domestically in total exports (Tijaja, 2012) so that Indonesia produces and exports more finished-goods. These conditions could explain the high contribution of horizontal-specialization products to the growth of export as share of gross output in those countries.

In India, the difference between contribution of VS export and non-VS export to the growth of export is not as wide as the difference in Brazil and Indonesia. This might be because India has more balanced foreign and domestic value added embodied in its exports. India provides an enormous amount of labour so that labour-intensive stages of goods production are offshored to India (see Schmitz (2006), for example). Hence, India imports high value added goods from industrialized countries and those goods enter labour-intensive stages of production in India. In this case, the value of foreign input is bigger than domestic value added. On the other hand, India has developed its service industries which shows higher growth after 1993 (Bosworth and Collins, 2008) and the value added in service sectors exceeds that in manufacturing sectors (Shepherd and Pasadilla, 2012). India has also joined the global hardware and software industries (Linden et al., 2009) and developed information technology (IT) industry with increasing value of exports of software (Bhatnagar, 2006). The results obtained from decomposing changes in export into changes in VS export and non-VS export suggest that for BRIIC countries (except China), vertical specialization is not the dominant source of growth in export share of gross output.

20

Sources of growth in VS share of total exports (1995-2011)

Country

Change in VS share of exports

Level Contribution of: (%)

Change in sector VS intensity Change in sector share of overall exports Change in sector VS intensity Change in sector share of overall exports Brazil 0.041 0.042 -0.002 103.80 -3.80 China 0.066 0.044 0.022 66.67 33.33 Indonesia -0.008 0.001 -0.008 -7.26 107.26 India 0.113 0.089 0.024 78.65 21.35 Russia -0.012 -0.001 -0.011 5.63 94.37

Source: Author’s calculation based on equation (7) using data from WIOD

Note: The sum of change in sector VS intensity and change in sector share of overall exports in this table might not equal to change in VS share of export due to rounding.

Based on the results in Table 3, changes in sectoral VS intensity account for most of the growth in overall VS share. The changes in VS intensity across all sectors contribute more than 60% to the change in VS share over time in countries with positive growth of VS share (Brazil, India and China). In countries where VS share of exports is decreasing (Indonesia and Russia), it is the change in sectoral share of exports that contributes more. This indicates a decline in the amount of imported input incorporated in producing exported goods in those countries, and implies that the sectors with decreasing export share are sectors which use imported intermediate goods quite intensively. This finding is in line with the result of export decomposition (see Table 2), which shows that the contribution of VS share of gross output to the change in export share of gross output is lower than the contribution of non-VS share of gross output.

21

Changes in sectoral VS share of export

Sector code Brazil Russia India Indonesia China

AtB 0.0065 -0.0005 -0.0008 0.0006 -0.0017 C 0.0122 0.0004 0.0003 0.0034 -0.0015 15t16 0.0059 -0.0003 -0.0003 0.0072 -0.0018 17t18 -0.0008 -0.0011 -0.0054 -0.0059 -0.0233 19 -0.0021 -0.0001 -0.0035 -0.0028 -0.0070 20 -0.0001 0.0000 -0.0002 -0.0070 -0.0019 21t22 -0.0011 -0.0012 -0.0036 0.0013 -0.0009 23 0.0050 0.0025 0.0164 -0.0094 0.0017 24 0.0021 -0.0013 -0.0006 0.0002 0.0104 25 0.0005 -0.0001 -0.0006 -0.0011 0.0006 26 0.0000 -0.0001 -0.0118 -0.0005 -0.0003 27t28 -0.0018 -0.0108 0.0092 -0.0030 0.0047 29 0.0010 -0.0030 0.0015 0.0100 0.0117 30t33 0.0024 -0.0005 0.0137 0.0027 0.0599 34t35 0.0071 -0.0009 0.0092 0.0012 0.0080 36t37 -0.0001 0.0000 0.0785 -0.0021 0.0009 E 0.0004 0.0001 0.0000 0.0000 -0.0001 F -0.0001 0.0000 0.0000 0.0000 0.0002 50 0.0000 0.0001 0.0000 0.0000 0.0000 51 0.0001 0.0038 0.0000 0.0004 0.0026 52 0.0001 0.0002 -0.0001 0.0003 0.0005 H 0.0002 0.0000 0.0025 -0.0031 -0.0008 60 0.0006 0.0007 0.0005 0.0030 -0.0002 61 0.0000 0.0001 -0.0001 0.0003 0.0020 62 0.0000 0.0004 -0.0001 -0.0035 0.0014 63 0.0003 -0.0002 -0.0002 -0.0004 -0.0017 64 0.0009 0.0001 0.0004 -0.0002 0.0001 J 0.0001 0.0000 0.0002 -0.0025 -0.0001 70 0.0000 0.0000 -0.0005 0.0016 0.0000 71t74 0.0007 0.0000 0.0088 -0.0001 0.0039 L 0.0001 0.0000 0.0000 0.0002 -0.0001 M 0.0000 0.0000 0.0000 0.0004 0.0000 N 0.0000 0.0000 0.0000 0.0000 0.0000 O 0.0003 0.0000 -0.0006 0.0011 -0.0013 P 0.0000 0.0000 0.0000 0.0000 0.0000 Total changesa _{0.0406 -0.0116 0.1126 -0.0076 0.0659}

Change of VS as share of export in:

Manufacturing sectors 0.0178 -0.0169 0.1024 -0.0092 0.0627

Service sectors 0.0035 0.0053 0.0108 -0.0026 0.0064

22

Brazil Russia India Indonesia China

Percentage of changes in VS share of export in:

Manufacturing sectors 44.0% 145.8% 90.9% 121.4% 95.1%

Service sectors 8.7% -45.4% 9.6% 34.5% 9.7%

Other sectors 47.3% -0.4% -0.5% -55.9% -4.7%

Source: Author’s calculation based on equation (7) using data from WIOD Note:

a. The sum of all changes in sectoral VS share of export in a country is equal to the change in VS share of export over time in the respective country.

23

Sectors with highest increase in VS share of export

Brazil

Sector _{dintens dexshare d vs share}

Mining and Quarrying 0.00359 0.00865 0.01224

Transport Equipment 0.00694 0.00014 0.00709

Agriculture, Hunting, Forestry and Fishing 0.00398 0.00253 0.00651

Food, Beverages and Tobacco 0.00547 0.00039 0.00586

Coke, Refined Petroleum and Nuclear Fuel 0.00073 0.00426 0.00499

Russia

Sector _{dintens dexshare d vs share}

Wholesale Trade and Commission Trade, Except of Motor Vehicles and

Motorcycles 0.00258 0.00125 0.00383

Coke, Refined Petroleum and Nuclear Fuel -0.00116 0.00371 0.00255

Inland Transport 0.00389 -0.00318 0.00072

Air Transport 0.00033 0.00009 0.00042

Mining and Quarrying -0.00458 0.00493 0.00035

India

Sector _{dintens dexshare d vs share}

Manufacturing, Nec; Recycling 0.05291 0.02559 0.07849

Coke, Refined Petroleum and Nuclear Fuel 0.00291 0.01345 0.01636

Electrical and Optical Equipment 0.00502 0.00872 0.01374

Basic Metals and Fabricated Metal 0.00363 0.00555 0.00918

Transport Equipment 0.00284 0.00634 0.00918

Indonesia

Sector _{dintens dexshare d vs share}

Machinery, Nec -0.00052 0.01055 0.01003

Food, Beverages and Tobacco 0.00121 0.00602 0.00723

Mining and Quarrying -0.00134 0.00472 0.00339

Inland Transport 0.00155 0.00147 0.00302

Electrical and Optical Equipment 0.00115 0.00152 0.00267

China

Sector _{dintens dexshare d vs share}

Electrical and Optical Equipment 0.02227 0.03768 0.05995

Machinery, Nec 0.00427 0.00739 0.01166

Chemicals and Chemical Products 0.00349 0.00690 0.01039

Transport Equipment 0.00207 0.00595 0.00802

Basic Metals and Fabricated Metal 0.00829 -0.00362 0.00467

Source: Author’s calculation based on equation (7) using data from WIOD Notes:

a. dintens is the change in sectoral vertical specialization intensity (within) b. dexshare is the change in sectoral export share of overall export (between)

24

Sectors with largest decrease in VS share of export

Brazil

Sector _{dintens dexshare d vs share}

Leather, Leather and Footwear 0.00012 -0.00226 -0.00214

Basic Metals and Fabricated Metal 0.00521 -0.00698 -0.00177

Pulp, Paper, Paper , Printing and Publishing 0.00096 -0.00208 -0.00112

Textiles and Textile Products 0.00050 -0.00127 -0.00077

Manufacturing, Nec; Recycling 0.00034 -0.00049 -0.00015

Russia

Sector _{dintens dexshare d vs share}

Basic Metals and Fabricated Metal -0.00407 -0.00671 -0.01079

Machinery, Nec 0.00023 -0.00327 -0.00304

Chemicals and Chemical Products -0.00046 -0.00082 -0.00127

Pulp, Paper, Paper , Printing and Publishing -0.00010 -0.00106 -0.00115

Textiles and Textile Products -0.00010 -0.00099 -0.00109

India

Sector _{dintens dexshare d vs share}

Other Non-Metallic Mineral 0.00067 -0.01247 -0.01180

Textiles and Textile Products 0.01103 -0.01640 -0.00536

Pulp, Paper, Paper , Printing and Publishing -0.00002 -0.00363 -0.00364

Leather, Leather and Footwear 0.00015 -0.00367 -0.00352

Agriculture, Hunting, Forestry and Fishing 0.00015 -0.00093 -0.00077

Indonesia

Sector _{dintens dexshare d vs share}

Coke, Refined Petroleum and Nuclear Fuel -0.00903 -0.00038 -0.00941

Wood and Products of Wood and Cork 0.00111 -0.00808 -0.00697

Textiles and Textile Products 0.00946 -0.01540 -0.00595

Air Transport -0.00177 -0.00170 -0.00346

Hotels and Restaurants -0.00020 -0.00286 -0.00307

China

Sector _{dintens dexshare d vs share}

Textiles and Textile Products -0.00540 -0.01792 -0.02333

Leather, Leather and Footwear -0.00170 -0.00529 -0.00699

Wood and Products of Wood and Cork 0.00008 -0.00202 -0.00194

Food, Beverages and Tobacco 0.00112 -0.00288 -0.00176

Agriculture, Hunting, Forestry and Fishing 0.00041 -0.00211 -0.00170

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V. Conclusion

Internationalization of production allows countries to take part in a vertically linked production chain and specialize in certain stages of production. Many studies provide evidence of increasing foreign outsourcing or fragmentation of production. In this thesis, we identify the presence of vertical specialization in Brazil, Russia, India, Indonesia and China (BRIIC) which are considered as five of the largest non-OECD economies that have gained more importance in global economy (Safadi and Lattimore, 2009).

The measure of vertical specialization is based on the measure developed by Hummels et al. (2001). It measures the imported input content of exports and is calculated using input-output framework. The data source is National Input-Output Tables (NIOT) which are available from World Input-Output Database (WIOD). We use the NIOTs for the BRIICs from 1995 until 2011.

Our measure indicates that overall, VS share of exports in BRIIC countries increased in the last two decades. This means that the composition of imported input embodied in export of those countries is increasing during that time. However, a more detailed analysis on each country shows that while the VS share of export in India, China and Brazil increased (India had the highest increase in the measure), the share is decreasing in Russia and Indonesia. This evidence suggests that both countries have less imported input embodied in their exports in 2011, compared to export in 1995.

The results obtained from decomposition of changes in export share of gross output suggest that vertical specialization is a key driver in China’s export growth while horizontal specialization is a dominant source of export growth in Brazil, Russia and Indonesia. Horizontal specialization also plays major role for export growth in India but participation in vertical specialization chain is important too. These findings could mean that China become more dependent on vertical linkage of production during the last two decades whereas India, apart from its proliferation in vertical specialization chain, is also producing own goods with high domestic value added for export. Nevertheless, the increase in vertical specialization among the BRIIC countries is evident.

26

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Appendix 1: Calculation results of VS share of export for BRIIC countries

Table A.1. VS share of export for BRIIC countries (1995-2011) Year Brazil Russia India Indonesia China 1995 0.079 0.0748 0.1051 0.1547 0.1599 1996 0.0829 0.0675 0.1046 0.1453 0.1449 1997 0.0846 0.0696 0.1041 0.1555 0.1422 1998 0.0872 0.0892 0.1138 0.2144 0.1301 1999 0.1107 0.105 0.1292 0.1671 0.1472 2000 0.1206 0.1029 0.1468 0.1915 0.1754 2001 0.1356 0.0991 0.1429 0.2057 0.1678 2002 0.1301 0.0905 0.1481 0.183 0.1819 2003 0.1242 0.0979 0.145 0.1693 0.2169 2004 0.1293 0.0798 0.177 0.1923 0.2597 2005 0.1193 0.0765 0.2019 0.1887 0.2649 2006 0.1178 0.0736 0.2112 0.1653 0.2624 2007 0.1192 0.0702 0.2121 0.1606 0.2559 2008 0.1309 0.0725 0.2201 0.1684 0.2359 2009 0.1021 0.0541 0.2339 0.1367 0.1994 2010 0.106 0.0541 0.2163 0.1388 0.2227 2011 0.1195 0.0633 0.2177 0.1472 0.2258

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Appendix 2: Aggregation of BRIIC’s VS share of export

Table A.2. BRIIC’s VS share of export between 1995 and 2011

Country

As share of export Export

1995 Export 2011 Level VS 1995 VS 2011 VS 1995 VS 2011 (1) (2) (3) (4) (5) (6) Brazil 0.079 0.120 55919.074 294453.382 4417.607 35187.179 Russia 0.075 0.063 82173.130 485518.209 6146.550 30733.303 India 0.105 0.218 42190.444 338087.931 4434.216 73601.743 Indonesia 0.155 0.147 54138.458 218789.157 8375.219 32205.764 China 0.160 0.226 167973.662 2086189.164 26858.989 471061.513 BRIIC 0.125 0.188 402394.768 3423037.844 50232.581 642789.502 Notes:

(1) and (2) are taken from Table A.1. for every country in year 1995 and 2011.

(3) and (4) are total exports for every country in year 1995 and 2011. Data are taken from WIOD.

(5) and (6) are the measure of vertical specialization, calculated by multiplying (1) and (3) for year 1995, and (2) and (4) for year 2011.

31

Appendix 3: Results of export decomposition (as share of gross output) for BRIIC countries

Table A.3. Calculation of export decomposition for Brazil

Year Total export VS share of export Export due to VS Export due

to non-VS Gross output

(3) as share of gross output (4) as share of gross output Export share of gross output (1)a ₍₂₎b _(3)=(1)*(2)c _(4)=(1)-(3)c ₍₅₎d _(6)=(3)/(5)e _(7)=(4)/(5)e _(8)=(1)/(5)f 1995 55919.074 0.079 4417.607 51501.468 1261526.441 0.004 0.041 0.044 1996 55162.196 0.083 4572.946 50589.250 1366247.234 0.003 0.037 0.040 1997 59446.552 0.085 5029.178 54417.374 1420617.918 0.004 0.038 0.042 1998 58540.882 0.087 5104.765 53436.117 1380365.390 0.004 0.039 0.042 1999 55558.945 0.111 6150.375 49408.569 969896.040 0.006 0.051 0.057 2000 64412.279 0.121 7768.121 56644.158 1096554.378 0.007 0.052 0.059 2001 67952.387 0.136 9214.344 58738.044 948116.049 0.010 0.062 0.072 2002 73652.596 0.130 9582.203 64070.393 897641.136 0.011 0.071 0.082 2003 83307.247 0.124 10346.760 72960.487 978595.755 0.011 0.075 0.085 2004 109195.005 0.129 14118.914 95076.091 1175437.158 0.012 0.081 0.093 2005 134029.798 0.119 15989.755 118040.043 1562385.442 0.010 0.076 0.086 2006 156508.080 0.118 18436.652 138071.428 1895074.579 0.010 0.073 0.083 2007 182673.134 0.119 21774.638 160898.496 2377320.842 0.009 0.068 0.077 2008 225925.787 0.131 29573.686 196352.102 2894929.564 0.010 0.068 0.078 2009 177168.146 0.102 18088.868 159079.278 2741154.201 0.007 0.058 0.065 2010 232982.116 0.106 24696.104 208286.012 3546809.948 0.007 0.059 0.066 2011 294453.382 0.120 35187.179 259266.203 4001071.528 0.009 0.065 0.074 Notes:

a. Total export is the sum of exports from all sectors in a country for a particular year, calculated every year

from 1995 to 2011. Data are taken from WIOD.

b. VS share of export for every country is taken from Table A.1.

c. Exports are divided into two categories: export of vertical specialization goods and export of non-vertical specialization goods. Export due to VS is the amount of export that contains imported input and is calculated as a multiplication of total export and VS share of export. Export due to non-VS is the rest of export that does not contain imported input, i.e. total export minus export due to VS.

d. Gross output is the total of output from all sectors in a country for a particular year, calculated every year

from 1995 to 2011

e. VS export and non-VS export are calculated as share of gross output in column (6) and (7), respectively.

f. Export share of gross output is calculated every year and is defined as total export divided with gross output.

32

Year Total export VS share of export Export due to VS Export due

to non-VS Gross output

33

Year Total export VS share of export Export due to VS Export due

to non-VS Gross output

34

Table A.6. Calculation of export decomposition for Indonesia

Year Total export VS share of export Export due to VS Export due

to non-VS Gross output

35

Year Total export

VS share of export

Export due to VS

Export due

to non-VS Gross output

36

Appendix 4: Structural decomposition analysis (SDA) of changes in VS share of export for BRIIC countries between 1995 and 2011

Table A.8. SDA of changes in VS share of export for Brazil

37

38

39

Table A.11. SDA of changes in VS share of export for Indonesia

Sector code 1995 2011 d VS Avg export share

40