Introduction
Research context and problem statement
In recent decades, trade has experienced significant growth, as evidenced by statistics from the World Trade Organization (WTO) showing a remarkable upward trend in both exports and imports of merchandise products This surge in trade underscores the increasing importance of international economics, with many economists highlighting trade as a key driver of economic growth (Frankel & Romer, 1999; Irwin & Terviử, 2002; Wacziarg & Welch).
Trade openness enhances economic efficiency through labor division, allowing firms to benefit from economies of scale and modern technology via foreign partnerships Additionally, it attracts capital investment to low-capital countries The growth of trade is driven by technological advancements that reduce transportation and communication costs, as noted by Baier & Bergstrand (2001) and Krugman et al (1995) Moreover, governments are increasingly adopting policies that promote trade integration, such as bilateral and multilateral agreements However, despite the overall trend towards openness, nations may impose temporary barriers like antidumping measures to protect domestic industries in the short term.
Table 1.1 Merchandise exports by selected economy (USA, Canada, Mexico, Brazil, Argentina, China, Japan, India, Australia and New Zealand, South Africa, Germany, United Kingdom, France, Italia) in billion USD
Source: author collected from WTO report
Antidumping duties (AD) were relatively rare in the 1960s, with an average of only ten cases per year (Schott, 1994) However, their usage surged in the 1970s and 1980s as countries favored AD over traditional tariffs, largely due to the more flexible interpretation of AD rules under GATT/WTO (Blonigen & Prusa, 2001) By the 1980s, over 1,600 AD petitions were recorded (Finger & Artis, 1993), and the use of AD among WTO members tripled from the early 1980s to the late 1990s (Prusa, 2005) The global crisis of 2008 further prompted developed countries to adopt AD measures to protect domestic producers (Kee, Neagu, & Nicita, 2010) The motivations behind the use of AD include the clear GATT/WTO regulations aimed at eliminating or reducing tariffs and the significant increase in countries entering bilateral and multilateral trade agreements, which impose constraints on raising tariffs and exacerbate tensions among domestic suppliers Additionally, there is a notable lack of alternative solutions for protection aside from AD.
AD are flexible and easy to interpret (Hansen & Prusa, 1995).
Numerous studies have examined the impact of antidumping (AD) measures on target countries Prusa (1994) found that AD pressures foreign firms to raise their prices during the initial stages of petition tax processes Cuyvers and Dumont (2005) demonstrated that Asian exports to the EU significantly decreased in both quantity and value following the filing of petitions Between 1981 and 2001, 74% of European Commission investigations resulted in either increased taxes or price undertakings Antidumping serves as a valuable case for studying microeconomic issues, including signaling, moral hazard, adverse selection, and pricing theory (Blonigen & Prusa, 2001) AD discriminates between "named" and "non-named" countries, potentially diminishing the comparative advantages of "named" firms while enhancing those of non-AD firms, leading to adjustments in pricing policies Furthermore, while governments may believe that AD benefits producers, it often results in reduced consumer surplus, as non-AD firms can sell more despite offering lower-quality products This necessitates optimal taxation for AD to maintain a balance between these groups The effects of AD can be observed even during the announcement phase of investigations, serving as a signal for exporters and importers to modify their behaviors Empirical research supports these findings, such as Brambilla, Porto, and Tarozzi (2012), who identified spillover effects of U.S duties on catfish on Vietnamese household income, and Moore and Zanardi (2009), who argued that AD could lead to decreased trade liberalization.
This paper examines how enterprises in developing countries, specifically Vietnam, respond to antidumping (AD) measures imposed by developed countries, using the European Union's duty on Vietnamese footwear as a primary case study Since implementing economic reforms in 1986, Vietnam has experienced a significant increase in trade with the global market However, the country has faced numerous AD investigations, with over 40 cases reported by 2011, resulting in taxes imposed on one-third of these cases Notable examples include the US imposing AD on catfish in 2002 and shrimp in 2003, as well as the EU's tax on bicycles in 2004 The EU remains one of Vietnam's key trading partners, alongside the US, China, and other Asian nations.
Between 1995 and 2004, the European Union (EU) saw a significant increase in imports, particularly from Vietnam, which is known for its key exports of textiles and footwear In July 2005, the EU initiated antidumping duties on footwear from China and Vietnam, specifically targeting products with rubber or plastic soles and uppers, classified under code 6403 (CN8) (553/2006) The tax rate started at 4.2% in April 2006 and escalated to 16.8% by September of the same year, leading to a notable decline in footwear exports to the EU This research examines how firms are adjusting their strategies to mitigate the adverse effects of rising taxes on their export activities.
Table 1.2 Vietnam Merchandise Trade in percent over GDP
Source: author collected from World Bank Data Indicators
Table 1.3 Vietnam export to EU in million USD
Source: author collected from Vietnam General Statistics Office
Vietnam's footwear industry serves as a prime example of how firms in developing countries adapt to anti-dumping duties The European Union represents a significant market, comprising 65% of Vietnam's total footwear exports Additionally, this sector is a key component of Vietnam's overall industrial landscape.
The significant sector in Vietnam's economy plays a crucial role in exports and job creation According to Krugman et al (1995), assessing the impact of protectionist measures like tariffs and anti-dumping duties can be challenging due to difficulties in interpreting historical data However, this study benefits from firm-level data collected by the General Statistics Office (GSO) during 2003, 2004, and 2006, 2007, providing a comprehensive view before and after the implementation of these taxes for both control and affected groups.
“treatment” group In addition to firm-level data, we also have sufficient products level data at 8-digit CN codes and 10 digit HTS codes level from Eurostat and USITC, respectively.
On those given, it would be concluded that unique and ideal opportunity to identify the firm’s adjustments under antidumping case.
Research objectives
Explore how the Vietnam footwear industry and Vietnam footwear firms response to antidumping duty from EU.
Research questions
1 How much does EU AD alleviate to export value, quantity and price of Vietnam footwear industry?
2 How much does EU AD reduce revenue of Vietnam footwear firms?
3 How much does AD effect on the firm’s input decision: firm’s size and labor payroll?
4 How protectionist measure in EU can adversely affect another economy (US)?
Research methodology, data and scope
Double differences (DD) method is applied to estimate effect of AD on Vietnam footwear DD is frequently used for evaluate impact of a policy or program It compares
This study analyzes the "control" and "treatment" groups before and after the implementation of a policy intervention, leveraging the advantages of eliminating time-invariant factors Adjustments have been made to incorporate firm characteristics to address potential selection biases The control group consists of light manufacturing industries, such as textiles, paper, and wood, which helps satisfy the parallel assumption of the Difference-in-Differences (DD) approach Data for this research is sourced from the Vietnam Enterprise Surveys, collected by the Vietnam General Statistics Office (GSO) and its provincial sub-institutions Additionally, product-level data is utilized, categorized by 8-digit CN codes and 10-digit HTS codes from Eurostat and the USITC The analysis focuses on the period surrounding the initiation of Anti-Dumping (AD) investigations in 2005 and the subsequent tax increases in 2006, employing panel data to compare pre- and post-intervention effects, as detailed in Chapter 3.
Thesis structure
This paper is structured into five chapters Chapter I introduces the study, outlining its objectives and research questions while highlighting its significance Chapter II reviews existing literature, covering both theoretical and empirical backgrounds Chapter III provides an overview of the impact of EU Anti-Dumping measures on Vietnam's footwear industry, along with a summary of relevant data Chapter IV details the research methodology and results, and Chapter V concludes with a brief summary of the findings.
Literature Review
Theoretical Review
Free trade generally benefits economies, but it also creates winners and losers, prompting some countries to implement protective policies for their industries These policies often aim to achieve not only economic objectives but also political ones Key trade measures adopted in recent decades include import tariffs, export subsidies, and dumping practices A significant policy within the World Trade Organization framework is the antidumping duty, which provides essential protection for local producers in the short term.
2.1.1 Market analysis in context of Trade in a single industry
This paper utilizes partial equilibrium theory to analyze two markets: Home and Foreign, each with producers and consumers of a single product, A Prices for product A are expressed in Home currency, with the price in the Home country (P) being higher than that in the Foreign market (P*) This price disparity results in the Home country importing product A from Foreign.
To have transparent view, we use supply and demand curve as figure 1.
The domestic market's demand and supply curves are illustrated in Figure 1a, while Figure 1b presents the Home import demand curve (MD), which is derived from the initial figure Specifically, Home import demand reflects the Home demand in relation to Home supply At price P0, the demand is represented as D0, and the domestic supply is S0, indicating a specific quantity demanded for imported goods.
When the price rises from P0 to P1, home demand decreases to D1 while home supply increases to S1 This shift results in a decline in home import demand to D1 - S1 Generally, the import demand curve slopes negatively, indicating that as prices increase, the quantity demanded decreases.
Import demand is equal to zero at the equilibrium price of Domestic supply and demand, PE,
At this price, Home country does not need to import goods.
The foreign export supply curve, illustrated in Figure 2, shows the relationship between price and quantity exported In Figure 2a, at price P0, foreign suppliers produce S0 while demand stands at D0, creating a need to export the difference D0f - S0f As the price rises to P1, foreign consumption decreases to D1, and supply increases to S1, leading to a larger exportable quantity of D1f - S1f This indicates that the export supply curve (XS) has a positive slope, as higher prices incentivize foreign producers to increase exports However, at price PE, there is no motivation for exports, as all goods are consumed domestically, resulting in zero quantity available for export.
Figure 2.2 Foreign Export Supply Curve
2.1.2.1 Effects of tariff on Volume and
The home government has implemented a specific tax (t) on each unit of imported product A In the absence of this tariff, the price of product A in the domestic market aligns with the world price (PE), as depicted in the center of figure 2.3 However, with the introduction of the tariff t, mediators will only be motivated to transport products from foreign markets to the home country if the price difference between the two markets is equal to or exceeds the tariff amount.
Consequently, there is an excess supply in Foreign and shortest supply in
The phenomenon leads to adjustments in both Home and Foreign prices, resulting in an increase in Home prices and a decrease in Foreign prices until the price difference reaches a specific threshold.
Home Market World Market Foreign Market
Quantity, Q Qt Qe Quantity, Q Quantity, Q
Figure 2.3 Impact of tariff on import price and volume
The introduction of a tariff (t) increases the price in Home to Pt, which is higher than the original price P, leading Home producers to increase their production while reducing the demand for imports As illustrated in figure 2.3, this shift causes imports to decrease from point E to point A In Foreign, the price drops from P to Pf (where Pf = Pt – t), prompting Foreign suppliers to reduce exports from point E to point B on the XS curve Additionally, the lower price in Foreign stimulates greater demand Consequently, the traded quantity decreases from Qe to Qt, establishing a new equilibrium point where Home's import demand and Foreign's export supply meet at Qt, resulting in Home's price remaining higher than Foreign's price.
In economic terms, a country is classified as small or large based on its demand's effect on world prices A small country is one whose demand for a product does not influence global pricing, while a large country exerts a significant impact on world prices The following section will discuss how tariffs affect social welfare.
2.1.2.2 Consumer surplus and producer surplus
A tariff impacts both domestic and foreign prices, leading to an increase in domestic prices while foreign prices decrease As a result, domestic consumers face losses, whereas domestic producers benefit from the tariff Conversely, foreign consumers gain from lower prices, while foreign producers experience losses To effectively compare the costs and benefits of tariffs for these distinct groups, it is essential to quantify the effects using the concepts of consumer and producer surplus, which are fundamental in microeconomics.
Consumer surplus refers to the difference between what consumers are willing to pay for a product and what they actually pay, representing the benefit they receive from purchasing at a lower price For example, if a customer is willing to pay $100 for a pair of shoes but buys them for $80, the consumer surplus is $20 Conversely, producer surplus is the benefit producers receive when they sell a product for a price higher than their minimum acceptable price.
A product might be sold with 15$ while manufacturer is willing to sell with 12$, then 3$ is producer surplus Total consumer surplus and producer surplus is called as social welfare.
2.1.2.3 Effects of tariff on Social welfare
The impact of tariffs on the social welfare of a large importing country can be significant When a tariff is imposed, domestic prices rise from P to Pt, while foreign prices decrease to Pf This leads to an increase in domestic supply from S1 to S2 and a decrease in demand from D1 to D2 As a result, producer surplus increases by area 'a' due to the higher price, whereas consumer surplus declines by the total area of (a + b + c + d) The government benefits by collecting tariff revenue, calculated as (D2 - S2) * t, which equals c + e Assuming the government utilizes this revenue for public services, the net social welfare can be expressed as producer benefits plus government tariff revenue minus consumer losses, resulting in e - (b + d) Here, the rectangle 'e' represents the terms of trade gains due to the market power of the large importing country, while triangles 'b' and 'd' indicate the efficiency losses caused by the tariff distortion.
Figure 2.4 Effect of tariff on social welfare in case of large country
In a small importing country, the tariff imposed does not influence the world price, resulting in a domestic price of P0 + t, where P0 represents the original price before tax As a result, the terms of trade gains are zero, leading to an efficiency loss represented by areas b and d Therefore, the net welfare of the small importing country is calculated as - (b + d).
Home deman d in case of small countr y
Research by Brander and Spencer (1992, 1984) and Dixit (1984) indicates that government-imposed tariffs, whether specific or ad valorem, lead to increased home prices They demonstrate that in large home countries, a portion of the tax burden may be passed on to domestic consumers, while the remainder benefits foreign producers Additionally, Krugman (1979) provides evidence supporting the implications of tariffs in monopolistic markets These studies provide a robust theoretical foundation for this paper.
Export subsidies are financial incentives provided by governments to promote exports, which can take the form of specific or ad valorem subsidies These subsidies raise the price for goods in the exporting country while lowering prices in the importing country, creating a price gap equal to the subsidy amount While producers may benefit from increased gains, consumers face losses, and the overall net welfare is negatively impacted due to efficiency losses resulting from distorted market behaviors Additionally, if the exporting country influences world prices, export subsidies can lead to a decrease in global prices, contributing to terms of trade losses, although this effect is negligible for small countries.
Figure 2.6 Effect of export subsidy on export country
Empirical Review
Numerous empirical studies have explored the topic of antidumping, with a comprehensive summary provided by Blonigen and Prusa (2001) Pierce (2011) indicates that antidumping measures can reduce physical productivity in host countries, prolonging the existence of low-productivity firms and ultimately decreasing resource efficiency Egger and Nelson (2011) analyzed panel data from 1948 to 2001 to assess the effects of antidumping on trade volume and welfare within the GATT/WTO framework, finding that while the negative impact exists, it is relatively modest Additionally, Prusa (2006) highlights that the East Asia region faces a higher incidence of antidumping duties compared to other regions Anderson, Schmitt, and Thisse (1995) utilized the Bertrand-Cournot model to demonstrate that antidumping policies diminish consumer surplus while enhancing domestic producer surplus, leading to a conflict where consumers typically oppose antidumping laws, whereas producers advocate for increased duties Furthermore, governments may seek to optimize total domestic surplus, which could be positively influenced by the implementation of antidumping measures.
Exploring the determinants of Anti-Dumping (AD) measures is a compelling area of research Numerous studies have investigated the motivations behind AD actions A primary factor is the clear mandate of GATT/WTO rules, which aim to eliminate or reduce tariffs, consequently increasing imports and creating pressure on domestic suppliers Additionally, there is a notable absence of effective solutions to safeguard domestic industries against the implications of AD.
In addition, GATT/WTO conditions to raise AD are flexible and easy to interpret (Hansen & Prusa, 1995), As discussed by (Blonigen & Prusa, 2001; Herander & Schwartz, 1984; Sabry,
Three primary factors influence antidumping (AD) filing: the employment levels in the affected sector, the capital intensity of that sector, and the impact of foreign product competition Blonigen and Prusa (2001) conducted a comprehensive review of prior research, while the other two studies utilized industry-level data and single equations to derive their conclusions.
Research by economists has highlighted the significant impact of antidumping measures on foreign firms Prusa (1994) found that antidumping actions initially pressure foreign companies to raise their prices during the petition process Cuyvers and Dumont (2005) demonstrated that Asian exports to the EU experienced substantial declines in both quantity and value following the filing of petitions Notably, 74% of European Commission antidumping investigations between 1981 and 2001 resulted in increased tariffs or price adjustments Brambilla et al (2012) examined the U.S antidumping duties on Vietnamese catfish, revealing that imports plummeted by 85% two years post-tariff, leading to a reduction in household income for catfish producers by 36.7% to 74%, depending on their reliance on catfish for income Consequently, investments in catfish farming decreased significantly, ranging from -28.3% to -61.9% Additionally, Prusa (2003) confirmed these findings.
AD causes a 30-50% declines of import In general, previous studies are quite consistent in belief that AD might harm import.
Anti-dumping (AD) measures create discrimination between named and non-named countries, leading to trade diversion, particularly towards non-EU firms in the case of the EU (Brenton, 2001) Research by Ganguli (2008) highlights a significant decline in imports from named countries to India, accompanied by an increase in imports from non-named countries Similarly, Park (2009) provides strong evidence of trade depression and diversion in China, attributing these changes to rising prices of dumped products In the USA, studies by Krupp & Pollard (1996) and Prusa (1996) also confirm substantial trade diversion Conversely, Konings, Vandenbussche, & Springael (2001) suggest limited trade diversion caused by the EU from 1985-1990, although this finding is challenged by Konings & Vandenbussche (2005), who utilized extensive panel data from thousands of EU producers If trade diversion is minimal, AD measures may positively impact domestic firm markups While many studies focus on import diversion, there is a notable lack of research on export diversification from named countries, which may adapt by diversifying products or markets to circumvent AD regulations.
Economists widely agree that anti-dumping (AD) measures negatively impact foreign countries, particularly developing nations, by increasing the prices of imported products, which subsequently reduces demand While home firms may benefit from AD, these advantages vary based on trade diversion effects However, existing studies primarily utilize aggregate or industry-level data, leaving a gap in understanding the firm-level impact of AD on foreign enterprises This paper addresses this gap by employing unique ex-ante and ex-post Enterprise Survey data from Vietnam to assess the effects of AD imposed by the European Commission on Vietnam's footwear industry Additionally, there is a scarcity of research on the market diversion effects of AD, and our analysis further explores how protectionist measures in the European Union can adversely affect the economy of the United States.
Conceptual Framework
Given theories and empirical studies indicate a conceptual framework, which is demonstrated in figure 1.9, for this study.
Market 2 increases Antidumping Market 1 declines
Price Export to Market 1 increases
Effect on Vietnamese Footwear Firms
Market 2 increases Value Export to Market 1 decreases
Total export to market 1 and market
Antidumping duties lead to a decrease in exports from foreign countries within targeted industries Both theoretical and practical evidence supports this assertion Theoretical perspectives, as discussed in section II.1.2, highlight insights from Akerlof and Yellen (1986) and Feenstra (2003), which effectively explain how antidumping duties impact the exports of specific industries.
Economists widely recognize the influence of Aggregate Demand (AD) on import prices, as highlighted in various studies (Akerlof & Yellen, 1986; J Brander & Spencer, 1992; J A Brander, 1981; A.J Brander & Spencer, 1984; Dixit, 1988; Feenstra, 2003) They differentiate between two scenarios: when import countries are small versus when they are large In the case of small countries, AD may have little to no effect on foreign prices Conversely, for large importing nations, AD can lead to a significant drop in import prices This distinction is further supported by empirical research (Brambilla et al., 2012; Cuyvers & Dumont, 2005; Prusa, 1994, 1996, 2003).
The decline in import quantities may prompt foreign firms to take strategic actions, such as diversifying their markets or product offerings to circumvent tariffs While there is limited research specifically addressing this phenomenon, numerous studies have explored trade diversion towards non-targeted countries (Brenton, 2001; Ganguli, 2008; Park, 2009) As a result of anti-dumping measures, non-named countries may experience an increase in market share within the home country, suggesting a significant shift in trade dynamics.
Antidumping (AD) measures can lead targeted firms to shift their focus towards new markets or similar products that are not affected by tariffs If these firms are unable to identify alternative markets, they may experience significant declines in both output and revenue According to Mankiw (2012), output is highly correlated with input, meaning that a reduction in output may compel firms to decrease their production inputs, such as workforce size and labor wages, in an effort to maximize profits.
Textile, sewing products Rice Footwear Fishery productsWood and wooden products
An overview of Vietnamese Footwear Industry
EU tax rising on Vietnamese footwear
Vietnam's footwear industry is a significant contributor to the country's exports, with a reported export value of 2.5 billion USD in 2004, ranking third after textiles and rice The industry employs approximately 500,000 workers, primarily from the agricultural sector, many of whom lack college degrees and earn low wages Footwear enterprises are concentrated in major cities like Hanoi, Ho Chi Minh City, and Da Nang Vietnam produces a diverse range of footwear, including leather and sports shoes, known for their high quality and affordability due to low labor costs As a result, these products are well-received in markets such as the EU, US, and Japan.
Figure 3.1 Top five Vietnamese export goods exclude oil in 2004
Source: author collected data from Vietnam General Statistics Office
China ,People's Republic ofVietnam India Indonesia Tunisia
Figure 3.2.Top five footwear exporters to EU
Source: author collected data from EU Trade market access database
In 2004, the European Union emerged as the largest importer of Vietnamese footwear, with imports valued at approximately 2,198,294 thousand Euros, equivalent to nearly 1.77 million US dollars, representing 68% of Vietnam's total footwear export value According to EU commission trade data, Vietnam ranks as the second-largest footwear exporter, following China However, Vietnam faces intense competition from countries such as China, India, Indonesia, and Tunisia Additionally, the footwear industry in Vietnam relies heavily on imported materials and machinery One of the major products exported by Vietnam is footwear with outer soles of leather or upper leather, classified under code 6403 in the 8-digit Combined Nomenclature (CN8).
On July 7, 2005, the European Commission (EC) announced the initiation of an anti-dumping investigation into leather shoes imported from Vietnam and China, following a complaint from the European Confederation of the Footwear Industry (CEC), which represents 40% of EU suppliers The complaint is based on Article 5 of European Regulation 384/96, last amended by EC No 384/96 (461/2004), focusing on footwear classified under CN8 code 64032000.
The study examines the tax implications for a selection of firms, specifically focusing on 64039116, 64039118, 64039191, 64039193, 64039196, 64039198, 64039911, 64039931, 64039933, 64039936, 64039938, 64039991, 64039993, 64039996, 64039998, and 64051000 during the investigation period from April 1, 2004, to March 31, 2005 The sample consists of eight Vietnamese firms and twelve Chinese firms, totaling 163 and 86 respondents, respectively The findings were published in (EC) No 553/2006, with the overall tax details outlined in Table 3.1.
Table 3.1 EU AD on Vietnam and People Republic China Footwear
The tax requisition significantly impacts the export activities of both countries to the EU As illustrated in Figure 3.3, the number of products under EU investigation has notably decreased since 2005 In 2003, Vietnam's AD footwear exports to the EU experienced a remarkable increase, rising 15% in value and 35.5% in quantity This upward trend continued into 2004, with exports growing by 9.2% in value and 15.8% in quantity.
The European Union's announcement of anti-dumping (AD) measures resulted in a significant decline in value, with decreases of 0% in 2005, -8.5% in 2006, and -13.8% in 2007, alongside corresponding quantity reductions of -5.5%, -12.78%, and -13.05% These trends align with theoretical findings from researchers such as Dale (1980), Feenstra (2003), and Staiger & Wolak (1994), as well as empirical evidence provided by Brenton (2001) and Messerlin (1989) Additionally, Prusa (2003) noted a similar pattern, reporting a drop of 30% to 50% in AD product imports to the U.S., which is further supported by Brenton's (2001) observation of a 20% decrease in the first year following the implementation of tax measures.
Figure 3.3 EU import Vietnam AD footwear and non-AD footwear
Source: author collected data from http://epp.eurostat.ec.europa.eu/newxtweb/
Data Description
My analysis bases on three dataset: EU import data, Vietnam Enterprise Survey and
US import data This section gives a description for each dataset.
3.2.1 EU Import 8-digit (CN8) Data
Data on EU footwear imports is sourced from the European Commission's EUROSTAT website, encompassing comprehensive export and import statistics for EU member states, defined here as EU25 This includes countries such as Belgium, Denmark, France, Germany, Greece, Ireland, Italy, Luxembourg, the Netherlands, Portugal, Spain, the United Kingdom, Austria, Finland, Sweden, Cyprus, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Slovakia, and Slovenia The analysis utilizes 8-digit Combined Nomenclature (CN8) data, specifically for antidumping products The import data includes values in Euros and quantities in kilograms, excluding tariffs, freight, insurance, and other surcharges Price calculations are derived by dividing the total value by the volume, with data available from 1999 to 2012.
Table 3.2.Vietnam AD footwear export value, volume, price to US compareto control groups
Groups Obs Mean Std.dev Min Max Growth
Table 3.2 presents a comparative analysis of the import value, volume, and price of Vietnamese anti-dumping (AD) footwear to the EU, alongside similar data from Thailand and Indonesia The analysis is divided into two periods: before 2004 and after 2006 This segmentation is significant, as the announcement of the anti-dumping tax occurred in July 2005, with the AD measures being lifted at the end of that year.
Between 1999 and 2011, Vietnam's 8-digit footwear export value to the EU increased by only 8.2%, from 26,559 thousand euros in 1999-2004 to 28,842 thousand euros in 2006-2011 In contrast, Thailand and Indonesia experienced growth rates of 47.6% and 77.8%, respectively, while India saw a remarkable increase of 146.6% The average growth rate for 8-digit apparel, a comparable category, was significantly higher at 91.5% In terms of volume, Vietnam's AD footwear exports declined by 6.2%, whereas Thailand, Indonesia, and India recorded substantial growth rates of 44.7%, 21.8%, and 104.8%, respectively Vietnam's apparel exports also surged by 134.4% Notably, while the price of Vietnam's AD footwear rose by 24.1%, indicating the highest price growth, the overall trend reveals a concerning decline in both volume and value of footwear exports compared to other countries and the apparel sector.
Table 3.3 provides insights into Vietnam's Non-AD footwear products compared to those from India, Indonesia, and Thailand The EU has announced a petition and imposed taxes on 31 product lines, with 75 footwear lines at the 8-digit level, of which 44 are exempt from penalties Following the duty implementation, Vietnam's Non-AD footwear exports increased by 6.6%, while Thailand experienced a significant decline of 60.8%, and Indonesia and India saw decreases of 21.8% and 0.6%, respectively In contrast, Vietnam's export quantity and price dropped by 15.5% and 37.2% During the same period, Thailand and Indonesia's export quantities decreased by 61.3% and 35.3%, while India experienced a slight increase of 2.6% Regarding price changes, India and Indonesia saw modest increases of 9.9% and 6.5%, respectively, whereas Thailand recorded a small decrease of 5.3%.
Table 3.3.Vietnam Non- AD footwear export value, volume, price to US compareto control groups
Groups Obs Mean Std.dev Min Max Growth
V alue in th ou san d
To assess the impact of advertising on Vietnam's footwear industry, we utilize the Vietnam Enterprise Survey data collected by the General Statistics Office (GSO) Our analysis focuses on panel data from the years 2004 and 2006, which include 91,755 observations in 2004 and 131,347 firms in 2006, with 329 footwear firms recorded in 2004 and 369 instances of treatment in 2006 The dataset encompasses crucial information such as firm revenue, labor, and capital details To ensure robustness, we expand our sample by incorporating data from 2003 and 2007 However, a challenge arises when merging data from 2006 and 2007 with that from 2003 and 2004, as the business classification system in Vietnam changed in 2006, necessitating a concordance of codes between the years.
Table 3.4 Descriptive Statistics of Vietnam Firms Characteristics
Year Variables Groups No.obs Mean Std.dev Minimum Maximum
Pr ice in E ur osov er
In our analysis, we focus exclusively on apparel products as the control group and footwear as the treatment group, utilizing a survey structured around SITC 4-digit classifications Footwear serves as a proxy for firms under AD, while we enhance our control group to include textile, paper, and wooden products for robustness Table 4 provides a comprehensive data description of the variables involved, detailing the mean, standard deviation, maximum, minimum, and number of observations for each group across the years 2003, 2004, 2006, and 2007 Revenue and payroll are measured in millions of Vietnamese Dong, with capital also expressed in millions of Vietnamese Dong The female ratio is calculated as the fraction of female employees to total employees, and firm size is represented by labor metrics Our study encompasses three groups: one treatment group (footwear firms) and two control groups (apparel and W.P.T, which stands for wood, paper, and textile products).
3.2.3 US Import 10-digit (HTS10) Data
US import data, specifically the 10-digit Harmonized Tariff Schedule (HTS10) information, is sourced from the US International Trade Commission's website This data encompasses all imports and exports involving the US and is categorized at the 10-digit level, which represents the smallest unit for analysis The values are presented in thousands of US dollars, while quantities vary by product line, with footwear measured in either dozens or kilograms The average price per unit is also provided Notably, Vietnam's footwear exports have seen a remarkable increase of 629.6% in value and 422.8% in volume, paralleling the growth of Vietnamese apparel exports at 657.8% in value and 483% in volume Additionally, India has demonstrated significant growth in its footwear exports.
In recent market analysis, Vietnam's footwear sector has shown a significant increase, with prices rising by 66.9%, while Indonesia and Thailand experienced declines of 35% in value and 30% in quantity Additionally, the apparel markets in Vietnam, Thailand, Indonesia, and India also followed a similar upward trend, with price increases recorded at 81.9%, 70.4%, and 75.2%, respectively.
Table 3.5.Vietnam footwear export value, volume, price to US compareto control groups
Groups Obs Mean Std.dev Min Max Growth
Val uein thou sa nd
Model Estimation and Research Findings
Double Difference Approach
This research utilizes the Double Difference (DD) method to assess the impacts of antidumping (AD) measures on the footwear industry By comparing treatment and control groups before and after the intervention, the DD method effectively captures the policy's effects The variable YEAR_t distinguishes between the ex-ante (0) and ex-post (1) periods, allowing for the control of year fixed effects, which encompass macroeconomic factors such as exchange rates and inflation The outcomes of interest for both groups, including revenue, profit, costs, labor payroll, and firm size, are analyzed for each year (t) As noted by Khandker et al (2010), the effects of antidumping measures can be clearly identified through this methodology.
DD = E(YT1 – YC1|T1 =1) – E(YT0- YC0|T0 = 0) (4.1)
Where T1 =1 stands for “named” AD group after intervention while T0 =0 represents for “non-named” AD group This DD assumes unobserved heterogeneity is time-invariant.
The expression E(YT0 - YC0 | T0 = 0) is referenced in the context of the difference-in-differences (DD) formula, highlighting that this assumption is less stringent than the conditional exogeneity assumption Unlike the before-after method, the DD approach effectively removes time-invariant biases, making it a more robust analytical tool The DD regression can be illustrated to support these findings.
Yit = α + β*Ti1*YEAR_t + � ∗ �i1+ � ∗ ����_ t + εit (4.2) Substitute T1 = 1 and T1 = 0 into (4.2),
As such, equation (4.1) could be equal to
The Difference-in-Differences (DD) approach combines the treatment group with a specific year, allowing us to interpret the coefficient β as the policy's effect on individual i in group T during year t A key assumption of the DD method is that the bias remains time-invariant, expressed as Cov(Ti1*YEAR_t,εit) = 0 To meet this assumption, the control group must share common characteristics with the treatment group Additionally, the Difference-in-Differences model can be adjusted as suggested by Brambilla et al (2012).
The model LnYit = α + Ai + β*Ti*YEAR_t + γ*xi + δ*lnxit + εit incorporates individual characteristics, including firm age, size, capital per employee, and location, which evolve over time By integrating fixed effects (Ai) and individual characteristics, the model effectively controls for observed biases, ensuring a more accurate analysis of the data.
An illustration of DD method could be seen as figure 11 We reveal case of Appling
The DD method is employed to assess the impact of Antidumping Duty (AD) on the revenue of Vietnamese footwear firms by comparing periods before and after the intervention Initially, the revenue of Vietnamese footwear firms is denoted as YiA, while the revenue of a control group is represented as YiB Following the implementation of AD, the revenues are recorded as YiA2 for the footwear sector and YiB1 for the control group, allowing for a comprehensive analysis of the AD's effects on revenue.
Figure 4.1 Difference in Difference Method
The expected revenue of a footwear enterprise without antidumping (AD) measures, referred to as YiA1, is a theoretical concept not observed in practice The DD approach posits that the difference in revenue between two scenarios, (YiA – YiB), is equivalent to the difference in expected revenues, (YiA1 – YiB1) Consequently, the impact of EU antidumping on the revenue of Vietnamese footwear firms can be expressed as (YiA2 – YiA) - (YiB1 - YiB) This methodology can similarly be applied to assess the effects of AD on various aspects of footwear firms, including profit, labor payroll, and firm size.
Double Difference in Multiple Years
Model (4.4) could be generalized for multiple years as described in (Blanchflower,Oswald, & Sanfey, 1996)
LnYit = α + Ai + β*Ti*YEAR_t+ _ ∗ ����_t + �*lnxit+ εit (4.5)
YEAR_t represents year fixed effects, with a slight variation in its values between equations (4.4) and (4.5) Unlike (4.4), which uses only two values (0 and 1), (4.5) encompasses a range of years for which data is available We apply first differences to both sides of the equation, eliminating the influence of time-invariant heterogeneity, represented as (Ai – Ai), which equals zero Additionally, Xit accounts for the control of time-variant individual characteristics.
This study incorporates year fixed effects to estimate the influence of policy on the outcome of interest, Yit We modify the original model by adjusting the covariate from β*Ti*YEAR_t to β*Ti*AfterAD_t, where AfterAD_t takes on values of 0 and 1 to indicate periods before and after the policy intervention Additionally, we include controls for country fixed effects to facilitate a comparison of Vietnam's footwear industry with other countries The variable Ai serves as a control for industry fixed effects.
LnYst = α +Ai+ Countrys+ ω_t*YEAR_t + β * Countrys* AfterAD_t + δ*Xst + εst (4.6)
Besides that, to make our results stronger, we also run regression for only VN industries as described in 4.6b Footwear is treatment; other industries are control.
LnYit = α + Ai+ ω_t*YEAR_t + β * Industry_i * AfterAD_t + δ*X_it + εit(4.6b)
Industry_i is dummy variable control industry which is equal to 1 if industry is footwear;otherwise it takes value of zero.
Estimation Impact of EU Antidumping on Vietnam Footwear Export
To evaluate influence of EU AD on Vietnam footwear Export at industry level, we employ equation4.6 with a slight adjustment To assess AD effects on value import 4.7 is modified as
LogValueist= α + Ai+ Vn+ β*ddVN+ _ ∗ ����_t +εit (4.7)
LogValueist represents the logarithm of value imports to the EU from industry i in country s during year t The variable Vn indicates country-fixed effects, assigning a value of one for Vietnam and zero for other countries The binary variable ddVN reflects the interaction between industry i and country s (Tis) and the AfterAD_t variable Specifically, Tis equals one if the industry is included in the EU's "named" AD list and originates from Vietnam; otherwise, it is zero YEAR_t, AfterAD_t, and εit are defined in previous sections In equations 4.8, 4.9, and 4.10, ddVN serves as the difference-in-differences (DD) variable, while Ai accounts for industry time-invariant fixed effects A similar approach to equation 4.8 is utilized to assess the impact of anti-dumping measures on Vietnam's export quantities to the EU.
LogQuantiyist= α + Ai + Vn+ β*ddVN+ _ ∗ ����_t + εit (4.8)
LogQuantityist measures the quantity of imports to the EU in industry i from country s during year t This study also examines the effect of EU anti-dumping (AD) measures on the pricing of AD footwear imported from Vietnam, as reflected in equation 4.10.
LogPriceist= α + Ai + Vn+ β*ddVN+ _ ∗ ����_t+ εit(4.9)
LogPriceist stands for log of price import to EU in industry i from country s in year t In short, a summary for variables and their definitions was illustrated in table1 of Appendix A
The analysis of Vietnamese AD footwear and apparel exports to the EU, alongside those from Thailand, Indonesia, and India, reveals significant trends from 1999 to 2004 Among these countries, India closely mirrors Vietnam's footwear performance in terms of value, quantity, and price, making it a key control group for evaluating claims about Vietnamese footwear pricing Since 2007, Thailand's footwear exports have declined, likely due to political instability following the 2006 prime ministerial coup Additionally, from 2001 to 2004, there was a notable decrease in apparel export values for Indonesia, Thailand, and Vietnam compared to the treatment group Indonesia experienced a rapid rise in quantity from 2000 to 2002, but this was followed by a sharp decline from 2002 to 2004, while Thailand's exports also suffered a significant drop post-2007 Both Indonesia and Vietnam's apparel prices have seen a marked decline during this period.
Between 2000 and 2004, India serves as the most suitable control group for our analysis To enhance robustness, we also conduct regressions on the apparel sectors of Indonesia, Thailand, and Vietnam, examining how varying control groups affect results aligned with their respective trends Furthermore, we analyze data from 2003 to 2007 to assess the short-term impact of antidumping (AD) measures, which aids in validating the Difference-in-Differences (DID) methodology and strengthening our research conclusions.
Figure 4.2 Trend of export value, quantity, price of Vietnam AD Footwear and control groups to EU
The results presented in Tables 4.1, 4.2, and 4.3 demonstrate the impact of antidumping (AD) measures on the export value, quantity, and price of Vietnamese AD footwear to the EU, utilizing equations 4.7, 4.8, and 4.9 All regression analyses yield F-test probabilities below 1%, allowing us to reject the null hypothesis that all coefficients are equal to zero The R-squared values range from 0.0816 to 0.6133, indicating the percentage of variance in the logarithm of value, quantity, and price explained by independent variables, with the exception of 0.0386 in column (8) of Table 4.3 The intercept values, representing the dependent variables when both Vn and ddVN are zero, are statistically significant at the 1% level across all tables Additionally, year-fixed and product-fixed effects are fully accounted for in the regressions.
The analysis of the influence of EU tax on Vietnam's export value reveals significant findings, particularly in the context of the covariate ddVN, which shows effect estimations of antidumping (AD) measures Statistically significant results at the 1% level are observed across all columns, with the exception of column (3), potentially due to the political crisis in Thailand in 2007 When focusing on the period from 2003 to 2007, column (7) indicates a notable 34.6% reduction in export value, also statistically significant at the 1% level Furthermore, the data from columns 1 and 5 illustrate that AD measures correspond to a drastic decline of 105.6% and 88.8% in exports to India, respectively, since 1999.
Between 2003-2007, the impact of antidumping measures (AD) was notably greater for Indonesia and Vietnam, with apparel export rates reaching 52.8% and 69.5% for Indonesia and 88.6% and 97.4% for Vietnam, respectively This period marked a significant surge for Vietnam's apparel sector and a strong recovery for Indonesia compared to the average trends from 1999-2011 However, both countries exhibited lower export estimations than India, likely due to declines experienced from 2001-2003 The variable for Vietnam accounts for country fixed effects, indicating that Vietnam's exports were 87.8% and 181.5% higher than those of Indonesia and Thailand during 1999-2011 When focusing on the 2003-2007 timeframe, Vietnam's exports were 143.3% and 209.7% higher than Indonesia and Thailand, respectively In contrast, columns (1) and (4) reveal no statistically significant differences between India and Vietnam.
Table 4.1.Vietnam AD footwear export value to EU compares to control groups
Year FE Yes Yes Yes Yes Yes Yes Yes Yes
Product FE Yes Yes Yes Yes Yes Yes Yes Yes
R-Square 0.2213 0.1834 0.4558 0.1021 0.0928 0.4075 0.5886 0.1032 Note: *, **, *** indicate 1%, 5%, and 10% significance level, respectively (* p