INTRODUCTION
Background
The period from 1991 to 1995 marked a pivotal era in Vietnam's economic history, characterized by impressive growth averaging 8.2 percent This surge was driven by comprehensive economic reforms initiated in the late 1980s, focusing on foreign trade and investment to revitalize the economy Key milestones during this time included Vietnam's 1992 trade agreement with the EU, its establishment of full diplomatic relations with the US, and joining ASEAN in 1995, all of which played a crucial role in opening the economy and shaping its future trajectory.
Vietnam experienced significant economic growth following its reforms, with the economy booming by 9.3 percent in 1996 and averaging 7 percent from 1996 to 2000 Despite the Asian Financial Crisis affecting the ASEAN region, Vietnam maintained a resilient economic growth of approximately 6 percent Additionally, this period saw notable improvements in socio-economic indicators, including an increase in life expectancy from 70.5 years.
1990 to 73.3 years in 2000; GDP per capita increased to US$ 434 in 2000 from US$
From 1990 to 2002, poverty in the country significantly decreased from 60% to 38.78% This remarkable progress in socio-economic indicators was also evident in the Human Development Index (HDI), which improved from 0.477 in 1990 to 0.576 in 2000, according to UNDP (2016).
Over 30 years since the implementation of comprehensive economic reforms, Vietnam continues to demonstrate remarkable economic growth and improvement in socio-economic indicators, transitioning from a "poor country" to a "middle income country" by 2010 Numerous studies, such as those by Anwar and Nguyen (2010) and Hoang et al (2010), have identified key growth drivers, including foreign direct investment (FDI), exports, labor productivity, and macroeconomic reforms This study, however, shifts focus to the export dynamics of Vietnam using the "trade in value added" (TiVA) approach, examining how the characteristics of Vietnamese exports have fueled economic growth, particularly in terms of export competitiveness and integration into the global production network While broader aspects like trade balance and environmental impacts are acknowledged, this analysis specifically assesses the contribution of Vietnamese industries to value-added exports and their role in the global value chain.
The TiVA (Trade in Value Added) approach is essential for accurately assessing trade dynamics, particularly in export-led economies like Vietnam, where conventional trade measures have been criticized for exaggerating export values due to multiple counting Research by Dervis et al (2013) and Koopman et al (2013) highlights these discrepancies, revealing that traditional metrics may misrepresent the true comparative advantages of countries such as China and India By applying the TiVA methodology, we can better understand the contributions of various exporting industries, their competitiveness, and Vietnam's role in the global value chain This approach disaggregates gross exports into domestic and foreign value added, providing a clearer picture of actual exports and eliminating the issues associated with conventional trade statistics Consequently, TiVA statistics offer reliable insights for policymakers to formulate effective trade policies.
Statement of the problem
Conventional trade statistics only capture the value of exported products at national borders, neglecting the value of intermediate inputs used in production This leads to multiple counting in gross export values, raising concerns about the reliability of traditional trade data for policy formulation A notable example is the Apple iPhone 4, which has a factory gate price of US$178.96 when assembled in China, yet only US$6.50 of that value is contributed by China itself The majority of components are sourced from Japan, Germany, Korea, and the US, with respective contributions of US$60.60, US$30.15, US$22.96, and US$10.75, along with an additional US$48 from other countries Conventional measures inaccurately attribute the entire export value of the iPhone to China, resulting in a significant trade deficit for the US Utilizing the TiVA approach would provide a more accurate representation of trade relationships and potentially reduce the perceived trade deficit with China.
The article highlights the importance of re-evaluating international trade through the lens of value-added measurement, particularly in light of the U.S trade deficit with China and its implications for trade partners like Japan, Germany, and Korea A notable example is the European Commission's anti-dumping duty on Chinese and Vietnamese leather shoes in 2006, intended to protect European producers but later found to be misguided, as a significant portion of the value in those shoes originated from the EU This underscores that conventional trade statistics can misrepresent the true nature of manufacturing and trade relationships The study aims to assess Vietnam's export dynamics using the TiVA approach to identify any discrepancies in export competitiveness and to analyze the growing role of intermediate products in Vietnam's trade structure Additionally, it seeks to explore the origins of domestic value added in gross exports, the industries contributing to foreign value added, and the overall impact of domestic value added on Vietnam's economic growth.
Objectives of the study
This study aims to evaluate Vietnam's export dynamics through the TiVA approach, focusing on several specific objectives Firstly, it seeks to identify and assess the exporting industries that contribute to the domestic value added in Vietnam's gross exports Secondly, it aims to identify and evaluate the industries contributing foreign value added to these exports Additionally, the study will assess the cointegration between domestic value added exports and Vietnam's economic growth, as well as analyze the country's export competitiveness Finally, it will evaluate Vietnam's position within the global value chain.
Significances of the study
This study highlights three significant points regarding Vietnam's export dynamics through trade in value-added statistics Firstly, while previous works by Tran et al (2011) and Thanh et al (2015) provided quantitative estimations of import and domestic value-added content, they relied on restrictive assumptions and did not estimate Vietnam's forward linkages in the global value chain This research offers a more comprehensive view of the value-added components of Vietnam's gross exports and evaluates its forward and backward linkages Secondly, the conventional trade measurement approach often leads to multiple counting, making earlier assessments of Vietnam's export competitiveness potentially misleading This study re-evaluates the competitiveness of various exporting industries using the TiVA approach, presenting a clearer picture of their performance Lastly, this dissertation serves as a valuable resource for future researchers interested in Vietnam's international trade or utilizing the TiVA methodology for trade analysis.
Delimitations of the study
This study utilizes data on value-added exports from the OECD TiVA database (2016 edition), which is limited to the period from 1995 to 2011 Although the 2018 edition of the OECD TiVA indicators offers new data from 2005 to 2015, it is not directly comparable to the earlier version The analysis does not compare Vietnam's export dynamics with other ASEAN countries or economies Additionally, the research questions are broad, leading to the omission of certain aspects, such as trade balances, foreign exchange rates, and environmental impacts, which the researcher intends to explore in future studies.
Organisation of the dissertation
This dissertation is spread over EIGHT chapters, each summarised as below:
This introductory section of the dissertation outlines the study's background and thoroughly addresses the problem statement It leads to the formulation of research questions that guide the overall and specific objectives of the study Additionally, the significance and limitations of the research are discussed in the latter part of the introduction.
In the text, researcher has also discussed the motivation for this study.
LITERATURE REVIEW
Overview
This chapter explores the conceptual foundations and significance of the TiVA approach, while also outlining the development of its framework Additionally, it references other critical elements of the literature review, including research methodologies, analytical techniques, policy discussions, and related concepts, which are detailed in the corresponding chapters of the dissertation.
Advancements in information and communication technology (ICT), along with trade policy reforms and reduced regulatory barriers in global logistics, have led to the fragmentation of production across multiple locations worldwide Consequently, over the past thirty years, the share of intermediate products in international trade has risen significantly, now accounting for more than half of trade value Countries such as China, Mexico, and Vietnam have notably increased their participation in the global value chain compared to a decade ago Given these changes, the relevance of traditional trade statistics is increasingly questioned, as highlighted by Maurer and Degain, who suggest that "what you see is not what you get." Miroudot and Yamano identify three key issues with conventional trade statistics: the risk of multiple counting, the inability to accurately assess a sector's contribution to income and employment, and the failure to reflect the true impact of trade on economic growth.
Recent efforts, including papers, workshops, and conferences, have focused on addressing trade measurement issues by proposing the application of the TiVA (Trade in Value Added) approach The initial formalization of this concept can be credited to economist Wassily Leontief in the 1960s.
Leontief and Strout (1963) initially highlighted the significance of international trade in intermediate products, a notion further developed by Sanyal and Jones (1982), who emphasized that these products typically involve added value rather than just raw materials Recent surveys, particularly in Asia, have underscored the growing importance of trade in intermediates Pioneering work by Hummels et al (2001), Daudin et al (2009), Johnson and Noguera (2012), Foster et al (2011), and Koopman et al (2008, 2010, 2012) has been instrumental in decomposing the value-added content of gross exports and establishing a comprehensive framework for trade in value added.
Hummels et al (2001) introduced the concept of "vertical specialisation (VS)" to assess the imported content in a country's exports, relying on input-output tables under the assumption that production coefficients for exports and domestic consumption are identical However, this assumption often fails in "processing-based trade," where imported inputs are heavily utilized for exports China serves as a prime example, with processing exports constituting about half of its total exports, primarily driven by wholly foreign-owned firms and Sino-foreign joint ventures Similarly, Mexico exhibits even higher shares of processing-based exports, largely due to Maquiladora firms Additionally, Koopman et al (2008, 2010, and 2012) have raised concerns about Hummels et al.'s assumption, suggesting it may significantly underestimate the foreign value-added content in gross exports when processing exports are prevalent.
Daudin et al (2009) analyze the production and consumption dynamics across 113 countries and 55 sectors by reallocating the value added in final goods using the GTAP (Global Trade Analysis Project) database Their methodology builds upon the work of Hummels et al (2001) to assess vertical specialization trade (VS), which measures the proportion of imported inputs in a country's exports Additionally, Daudin et al introduce two new metrics: VS1, representing the share of exports utilized as inputs for further exports, and VS1*, which quantifies the domestic content within imports.
Johnson and Noguera (2011) utilize the value added to gross exports (VAX) ratio to assess the intensity of production sharing, employing input-output and bilateral trade data to calculate the value added content in bilateral trade Unlike Hummels et al (2001), their approach accommodates two-way trade in intermediates, allowing countries to both import and export intermediates, whereas the VS framework restricts the last country to exporting only final goods (as noted by Miroudot and Yamano, 2013).
Foster et al (2011) emphasize the importance of net trade in value added, demonstrating that a country's net exports in value added align with its net exports in gross trade, thereby connecting to national accounting identities Their framework categorizes trade in value added into distinct domestic and foreign components of exports and imports, bridging the gap between recent measures of vertical specialization in production networks and the literature on trade in value added and the factor content of trade.
Koopman et al (2008, 2010, 2012) present a comprehensive framework for decomposing the value added in exports, integrating previous measures of vertical specialization and value-added trade This framework breaks down a country's gross exports into four components of domestic value added: (i) value added in final goods and services consumed by the importing country, (ii) value added in intermediate inputs used for domestic production, (iii) value added in intermediate exports for goods destined for third countries, and (iv) value added in intermediate exports for goods returned to the source country, alongside one component of foreign value added Their findings confirm that the foreign value added in a country's exports aligns mathematically with the vertical specialization measure proposed by Hummels et al (2001), but without their restrictive assumptions Additionally, they establish that the total of domestic and foreign value added equals the gross exports of the country.
Recent research has enhanced our understanding of conceptual frameworks and estimation methods for "trade in value added" in exports, as well as a country's involvement in global value chains These insights have facilitated the calculation of various indicators that illuminate trade dynamics and participation in global production networks Dean (2013) emphasizes that as production tasks become more fragmented and dispersed based on comparative advantage, low-income countries can increase their participation in these chains Additionally, Saito and Salgado (2013) argue that using real effective exchange rates based on value-added trade weights provides a more accurate measure of competitiveness compared to gross trade weights, thereby improving exchange rate assessments and enhancing the ability to evaluate the impact of changes in relative prices.
Importance of „Trade in Value Added (TiVA)‟ approach
TiVA is a statistical method that assesses the origins of value added in exported goods and services, breaking down the value added in gross exports into domestic and foreign components This approach highlights the "domestic value added in gross exports" as the true measure of exports for the reference country.
Developing "trade in value added" statistics on international trade is essential due to the rising prominence of fragmented production processes and trade in intermediate goods, which challenge traditional views on trade and influence policy development By measuring trade in value added, we gain a fresh perspective that can significantly affect policy decisions in various areas.
2.2.1 A better understanding of bilateral trade imbalances
In 2009, the US reported a trade deficit of $48 billion with Mexico and $22 billion with Canada, but value-added calculations showed these figures were 25% lower Additionally, 12% of Mexico's and 8% of Canada's total exports to the world reflected US value-added trade (Dervis et al., 2013) Similarly, research by Koopman et al (2013) indicated that in 2010, the US had a 25% lower trade deficit with China in value-added terms ($131 billion versus $176 billion), while its deficit with Japan rose by 60% (from $23 billion to $36 billion) These examples highlight that conventional trade data not only suffers from double counting but also fails to adequately account for the contributions of third countries in bilateral trade relationships, as seen in the US-China iPhone trade, where countries like Japan and Korea play significant roles.
Benedetto's work (2012) emphasizes the importance of the value added approach in international trade, revealing that it does not alter a country's overall trade balance with the world Instead, this approach redistributes surpluses and deficits among trading partners, accurately reflecting the contributions of true trade partners Notably, at the bilateral trade level, the value added trade balance may differ from the conventional reported trade balance, as the terms do not necessarily offset each other.
The differences between reported and value-added bilateral trade relationships significantly influence trade policy For instance, in 2012, the US faced substantial trade deficits with countries like China (US$315 billion) and Japan (US$76 billion), while enjoying surpluses with Australia (US$22 billion) and Brazil (US$12 billion) Concerns regarding US competitiveness and job losses are often fueled by these deficits, particularly with China However, when assessed in value-added terms, the US trade deficit with China decreases by 25 percent This insight suggests that imposing trade barriers on Chinese imports could lead to higher prices for US consumers and increased costs for US manufacturers, ultimately harming competitiveness Additionally, reduced demand for Chinese imports due to US trade barriers would negatively impact the demand for US goods and services used in China's exports Similarly, it benefits China to lower its trade barriers, as this would enhance the competitiveness of its products both domestically and internationally This example illustrates how value-added data can reshape our understanding of trade dynamics and their implications for policy.
Table 2.1: The equivalence of reported and value added trade balances at the level of trade with the entire world
Domestic VA that stays overseas (+)
Foreign VA that stays home (+)
Domestic VA that stays overseas (-) Foreign VA that stays home
(1) Domestic VA that will return home in imports
(1) Domestic VA that is embedded in imports
(2) Foreign VA that is embedded in exports
(2) Foreign VA that will be embedded in exports Value added basis
Domestic value added that stays overseas
Foreign value added that stays home
Domestic VA that stays overseas
(-) Foreign VA that stays home
2.2.2 An effective measure of the efficacy of trade barriers and trade measures
In a global value chain, competition occurs between firms rather than nations, focusing on access to competitive inputs and technology Domestic value added can arise from both exports and imports, especially when exports are intermediate goods and imports are final products Consequently, tariffs, non-tariff barriers, and trade measures like anti-dumping duties can significantly affect domestic producers alongside foreign competitors.
The European Commission's imposition of an anti-dumping duty on Chinese and Vietnamese leather shoes in 2006 aimed to address unfair trade practices and protect European producers However, a 2012 study by the Swedish National Board of Trade revealed that 50 to 80 percent of the value in these shoes originated from the EU, suggesting they could be considered "made in Europe." This finding indicated that the anti-dumping measures actually harmed European shoe companies rather than providing protection Consequently, this case highlights the limitations of relying on traditional gross trade data for policy decisions, emphasizing the need for a trade in value-added approach to better assess the effectiveness of trade policies.
2.2.3 A better way to analyse job contribution of trade
Analyzing the job content of trade reveals where employment is generated, particularly through value-added trade metrics By examining the decomposition of imports by their source economies, we can identify who truly benefits from trade For instance, the anti-dumping case concerning the EU's shoe industry highlights concerns over job protection and potential job losses While conventional views may suggest that imports of leather shoes from China and Vietnam have led to job transfers from the EU, a value-added perspective shows that only assembly jobs have shifted, with research, development, design, and marketing roles remaining in the EU This shift underscores the importance of a fragmented production process that maintains low costs and competitiveness for EU companies, illustrating the application of comparative advantages to specific tasks rather than entire job categories.
If the initial analysis of leather shoes manufactured in China and Vietnam had utilized a trade in value-added approach, the justification for imposing anti-dumping duties may have been reconsidered.
2.2.4 A better measure of trade competitiveness
Gross exports often suffer from double counting, particularly in countries like China, Mexico, and Vietnam, which are positioned at the end of fragmented production processes This inflation of trade figures can lead to misleading indicators of trade competitiveness, such as revealed comparative advantage (RCA) A clear illustration of this issue is the assembly of the iPhone 4 in China, where, despite a factory gate price of US$178.96, only US$6.50 was contributed by China The majority of components were imported from Japan, Germany, Korea, and the US, contributing US$60.60, US$30.15, US$22.96, and US$10.75, respectively, with an additional US$48 from other countries Under traditional trade accounting, the entire gate price of US$178.96 is recorded as China's export per iPhone 4, highlighting the discrepancies in trade data.
China's trade specialization suggests a comparative advantage in iPhone production based on gross exports; however, this is misleading The true comparative advantage lies in the assembly work of iPhones, as highlighted by Johnson's empirical research.
Research indicates that China's comparative advantage in computers is affirmed through gross exports but reverses when assessed in value-added terms Similarly, a study by Koopman et al (2014) shows that while both China and India exhibit strong revealed comparative advantages in finished metal products based on gross exports, their rankings significantly decline when evaluated on domestic value-added exports Notably, India's position shifts from comparative advantage to comparative disadvantage in this sector These findings underscore the potential distortions caused by relying solely on gross export figures, which can lead to misguided industrial policies and misidentification of export sectors for promotion Therefore, producing trade statistics in value-added terms is essential for accurate policy formulation.
2.2.5 Measuring backward and forward linkages of an economy
Understanding the dynamics of global value chains (GVC) requires examining the domestic and foreign value added in gross exports, which highlight a country's involvement as either a buyer or supplier of intermediate products Backward linkage indicates the degree to which a country's exports rely on imported inputs, represented
2.2.6 Fair assessment of the environmental impact of trade
Rapid economic growth in countries like China and India, driven by increased exports, has significantly contributed to rising carbon emissions within their borders The Kyoto Protocol's territorial accounting principle attributes all emissions from production activities for exports to these nations' total emissions Notably, China argues that emission responsibility should also include final consumers of goods, as they produce items consumed globally while bearing the emissions in their national accounts The transfer of carbon emissions from developed to developing countries through trade has emerged as a significant issue, particularly as many carbon-intensive production activities have shifted to these developing regions A fair distribution of responsibility between emitters and consumers is essential Understanding the international fragmentation of production necessitates a value-added perspective on trade, revealing whether developed countries are effectively shifting their environmental burdens to others Thus, assessing the environmental impact of trade through value-added measures can aid policymakers in addressing environmental challenges.
RESEARCH METHODOLOGY
Research design
This study employs a longitudinal research design, analyzing time-series secondary data on various TiVA indicators from 1995 to 2011 The assessment of Vietnam's export dynamics utilizes the TiVA approach, focusing on the explanation and analysis of this secondary data.
This study outlines its research procedure in detail, utilizing data extracted from the OECD TiVA database (2016 edition) for comprehensive analysis After gathering trade in value added data for Vietnam's major exporting industries, several analytical methods were employed to interpret the findings.
- analysis of sources and destinations of value added exports of Vietnam,
- validation of export-led growth of Vietnam,
- assessing export competitiveness of exporting industries of Vietnam, and
- assessing exporting industries‟ and Vietnam‟s participation in global value chain.
Sources of data and study period
The data for this analysis primarily comes from the OECD TiVA database (2016 edition), supplemented by national accounts data from World Bank Indicators, UNCTAD Data Centre, and GSO Vietnam, as detailed in appendices B and C The OECD TiVA database features export series for 50 industries classified under the ISIC 3.1 nomenclature, specifically at the division level (two-digit level), covering the years 1995 to 2011 Among these industries, some are reported individually while others are aggregated.
The final draft of this dissertation was completed in December 2017, prior to the release of the 2018 edition of TiVA indicators, which covers the years 2005 to 2015 It is important to note that the 2016 and 2018 editions of TiVA indicators are not directly comparable due to their publication in different versions of the ISIC nomenclature, specifically ISIC3.1 and ISIC4.0.
Table 3.1: List of industries used in the text with their ISIC codes
1 Agriculture, hunting, forestry and fishing C01T05 Primary
3 Food products, beverages and tobacco C15T16 Manufactures
4 Textiles, textile products, leather and footwear C17T19 Manufactures
5 Wood and products of wood and cork C20 Manufactures
6 Pulp, paper, paper products, printing and publishing C21T22 Manufactures
7 Coke, refined petroleum products and nuclear fuel C23 Manufactures
8 Chemicals and chemical products C24 Manufactures
9 Rubber and plastics products C25 Manufactures
10 Other non-metallic mineral products C26 Manufactures
13 Machinery and equipment, nec C29 Manufactures
14 Computer, Electronic and optical equipment C30T33X Manufactures
15 Electrical machinery and apparatus, nec C31 Manufactures
16 Motor vehicles, trailers and semi-trailers C34 Manufactures
19 Electricity, gas and water supply C40T41 Utilities
21 Wholesale and retail trade; repairs C50T52 Services
27 Renting of machinery and equipment C71 Services
28 Computer and related activities C72 Services
29 R&D and other business activities C73T74 Services
30 Public admin and defence; compulsory social security C75 Services
32 Health and social work C85 Services
33 Other community, social and personal services C90T93 Services
34 Private households with employed persons C95 Services
The OECD TiVA database provides a detailed breakdown of gross export values into domestic value added (DVA) and foreign value added (FVA) by country and industry This disaggregation allows for a comprehensive analysis of Vietnam's export dynamics and highlights the country's role and scale in the global value chain.
The study focuses on the period from 1995 to 2011, as the TiVA indicators database only includes data up to that year However, to analyze the export-led growth of Vietnam, the researcher has extended the estimates for domestic value-added exports to include the years 2012, 2013, and 2014, thereby covering a comprehensive period from 1995 to 2014.
Estimation of „Trade in Value Added‟
The empirical estimation of „trade in value added‟ consists of two stages-
Stage1: Construction of an inter-country input output (ICIO) table; and
Stage2: Computation of trade in value added (domestic value added, and foreign value added)
This article presents a simplified model of a single country with multiple industries (1xN) to enhance conceptual clarity While real-world trade involves complex interactions among several countries and intricate matrices for estimating trade in value-added exports, this straightforward model aims to aid readers in grasping the fundamental process of computing trade in value added.
3.3.1 Construction of an inter-country input output (ICIO) table: one country, N industries case
In a single country input-output table featuring N industries, the gross output of each industry must equal the total of its intermediate and final demands, encompassing both domestic and foreign markets.
In an input-output analysis, let \(y_k\) represent the gross output of industry \(k\), \(t_{kl}\) denote the value of inputs from industry \(k\) utilized by industry \(l\), and \(d_k\) signify the net final demand for products from industry \(k\) The relationships among these variables can be expressed through a series of equations, where each equation corresponds to the total output of an industry being the sum of its inputs from other industries and its final demand This can be summarized in the following format: \(y_1 = t_{11} + t_{12} + + t_{1N} + d_1\), \(y_2 = t_{21} + t_{22} + + t_{2N} + d_2\), and so forth, culminating in \(y_N = t_{N1} + t_{N2} + + t_{NN} + d_N\) These equations can also be represented in matrix form for a more compact and analytical approach to understanding the interdependencies between industries.
(3.2) Y = T + D where Y is a (N×1) vector of gross outputs, T is a (N×N) matrix of intermediate demand and D is a (N×1) vector of final demand
Introducing a technical coefficient, denoted as a kl = y kl / y l, illustrates the proportion of inputs that industry l requires from industry k to produce one monetary unit of output This relationship allows for a clearer understanding of the interdependencies between industries, as expressed in relations (3.1) and (3.2).
(3.3) Y = AY + D where A is a (N×N) technical coefficient matrix whose elements are composed of the individual technical coefficients a kl for each industry
On solving for Y in relation (3.3) gives:
Estimation of this equation is necessary to compute „Trade in Value Added‟ embodied in gross exports as discussed in the next section
3.3.2 Computation of ‘Trade in Value Added’
Once equation (3.4) is defined from input-output table, following steps can be applied to compute the value added components of gross exports:
STEP1: Determine the multiplier matrix, L= (I-A) -1 , also known as Leontief
To compute the inverse matrix, we first define a diagonal matrix B, known as the "value added share matrix." This matrix is constructed using the value added numbers derived from the input-output table, where each diagonal element \( b_{ii} \) represents the share of value added in the total output of sector i Consequently, the diagonal matrix B will consist of these elements, reflecting the contribution of each sector to the overall economic output.
STEP3: Define value added multiplier matrix V such that V = L*B
STEP4: Define gross export matrix X in diagonal form as:
STEP5: Multiply X by V, thus H = V*X = L*B*X gives the value added embodied in the gross exports
In the matrix H from step (5), the main diagonal elements represent the "domestic value added (DVA)" included in the gross exports of each industry Conversely, the sum of the off-diagonal elements reflects the "foreign value added (FVA)" content present in the gross exports of the respective industry.
The ICIO table and TiVA data series, which include domestic and foreign value-added components, are readily available for Vietnam and other economies in the OECD TiVA database (2016 edition) Researchers have primarily utilized this data to analyze the export dynamics of Vietnam rather than calculating the values independently The methodologies and research techniques employed in this analysis are detailed in the corresponding chapters, with key outlines provided below.
Validating export-led growth of Vietnam
Validation of the export-led growth of Vietnam has followed a three steps procedure:
STEP1: Use „unit root test with structural break‟ based on Perron‟s work
(1989) to determine the order of GDP and exports series, both measured in real terms
STEP2: Use „ARDL (autoregressive distributed lag) bounds test of cointegration‟ to examine the degree of long-run relationship between GDP and exports series
The ARDL approach does not necessitate prior testing of the order of integration of variables; however, researchers often choose to conduct this testing in advance This is because, at later stages of the ARDL analysis, it is essential to ensure that none of the variables are integrated of order 2.
STEP3: Examine whether a short-run causality exists between them
The methodological framework for this has been discussed in detail in chapter V, which has been presented as „An empirical analysis of export-led growth of Vietnam‟.
Assessing export competitiveness of Vietnam
This section utilizes Balassa’s (1965) index to assess the revealed comparative advantage (RCA) of various Vietnamese industries across multiple markets, including the World, ASEAN, East Asia, the European Union, NAFTA, and BRIS (BRICS minus China) The methodology involves applying Balassa’s index to 34 exporting industries to calculate RCA indices using both domestic value-added exports and gross exports Subsequently, comparative conclusions are drawn regarding the export competitiveness of these industries, followed by an examination of the stability of export specialization through beta estimates derived from Galtonian regression analysis on RSCA indices.
The Balassa‟s index (1965) can be presented as below for Vietnam:
X where BI j stands for Balassa‟s RCA index for industry j; X stands for exports, t and
T refer to year and total exports value, and „v' and „R‟ stand for the „Vietnam‟ and the „Reference market‟ respectively such that-
= Vietnam‟s exports of industry j in period t
= Vietnam‟s total exports value in period t
= Reference market‟s exports of industry j in period t
= Reference market‟s total exports value in period t
Thus, the numerator represents the proportionate share of a given industry in Vietnam‟s exports; and the denominator represents the proportionate share of the same industry in the reference market‟s exports
Once Balassa‟s indices were computed, Dalum et al.‟s (1998) „revealed symmetric comparative advantages (RSCA)‟ index has been used to observe the pattern of specialisation applying the following Galtonian regression equation:
The revealed symmetric comparative advantage (RSCA) of an industry, denoted as RSCA j,t, is calculated using the formula RSCA j = (BI j - 1) / (BI j + 1), where superscripts j, t, and (t-k) represent the industry, final year, and initial year, respectively In this context, RSCA j,t-k reflects the comparative advantage of industry j in the initial year (t-k), while RSCA j,t indicates the advantage in the final year t The parameters α and β are used in the regression model, and the term ϵ j,t represents a normally distributed residual.
The value of beta (β) and the coefficient of correlation (ρ) are crucial for analyzing Vietnam's export specialization patterns and dispersion over two periods (t-k) and t The "pattern of specialization" refers to changes in Vietnam's export specialization compared to the initial year, indicating whether it has strengthened, weakened, or remained unchanged Specifically, if β=1, the export specialization pattern is unchanged; if β>1, it indicates a strengthening of specialization, where specialized industries become more so, termed β-specialization by Dalum et al (1998) Conversely, if 0