**1. Introduction**

The textile and clothing industry is of great importance worldwide. In the case of countries such as Mexico or the United States, it is a relevant activity currently boosted by the advantages of the United States–Mexico–Canada Agreement (USMCA). The significant increase in the demand for textile products has opened the door to complex production processes that met international quality standards and paved the way to produce complete packages. This stimulates the formation of linkages between members of the production chain and provides opportunities for domestic producers. This process has led to the emergence of Global Value Chains (GVCs), a complex phenomenon reflecting the importance of global production linkages for access to new technologies, training, and innovation (Morrison et al. 2008).

The concept of GVCs provides a better understanding of the value creation process and helps understand how this value is captured, held, and leveraged in all industries. The GVC approach offers a global view of the World's industries from two perspectives: governance and upgrading. The former focuses mainly on leading companies and how their supply chains are organized on a global scale. At the same time, the latter involves the strategies that countries, regions, companies, and other actors use to maintain or improve their positions in the global value chain (Gereffi and Lee 2016). From this perspective, the case of the textile and apparel industry can be seen as a clear example of the strategic use of GVCs in a competitive and dynamic business world.

**Citation:** Rodil-Marzábal, Óscar, Ana Laura Gómez Pérez, and Hugo Campos-Romero. 2022. The Global Textile and Apparel Value Chain: From Mexico–US–China Linkages to a Global Approach. *Economies* 10: 258. https://doi.org/10.3390/ economies10100258

Academic Editor: Sajid Anwar

Received: 30 June 2022 Accepted: 12 October 2022 Published: 18 October 2022

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**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

<sup>1</sup> ICEDE Research Group, Departamento de Economía Aplicada, Universidade de Santiago de Compostela, Av. do Burgo, s/n, 15782 Santiago de Compostela, A Coruña, Spain

<sup>2</sup> Instituto Politécnico Nacional (IPN), Escuela Superior de Economía (ESE), Av. Plan de Agua Prieta 66, Plutarco Elías Calles, Miguel Hidalgo, 11350 Ciudad de México, CDMX, Mexico

**<sup>\*</sup>** Correspondence: oscar.rodil@usc.es

The theoretical definition of GVCs covers the full range of activities required to bring a good or service to the final consumer, from the acquisition of raw materials to delivery to the final consumer (Antrás 2020; Del Prete et al. 2017; Rodil 2017). In this sense, in the context of international fragmentation and the dynamism of production in the textile sector, labor seems to be a crucial factor, especially in manufacturing tasks. However, the progressive cheapening of products means that no country can forever maintain its comparative advantage in producing labor-intensive garments as its economy industrializes and advances (Lu 2018). Furthermore, these GVCs have expanded due to liberalization, the rise of ICTs, and lower transport costs. This has allowed the management of multiple geographically dispersed tasks in a value chain (Baldwin 2016). Thus, the GVC concept covers all value chain stages following an Input–Output structure. It is also defined by a governance structure, which refers to the power relations between the participating firms, and an institutional context, which refers to the local, national, and international political conditions that affect the different stages of the value chain (Gereffi and Fernandez-Stark 2016).

For decades, developing countries have imported parts and components from countries with more advanced technology, although usually only for the assembly of goods sold locally, forming part of a global network (Taglioni and Winkler 2014). However, several developing countries have managed to move up the chain to more advanced and higher value-added tasks (Pahl and Timmer 2020).

Trade in the supply chain is determined by international differences in production and unbundling costs, while technology determines how the different stages of production are linked (Amador and Cabral 2014). For example, a key part of China's success that has allowed it to achieve economies of scale and scope in GVCs is the constant interaction with various nations for the acquisition of inputs and technology to reduce production costs (Gereffi 2019). Thus, GVCs for developing countries are a fast path to industrialization, as internationally fragmented production allows them to join existing supply chains instead of building them, by sophisticating their goods and expanding their product range (Raei et al. 2019).

An essential factor for insertion in GVCs is industrial competitiveness, which is increasingly defined by international production networks (fragmented and spatially dispersed) and less by national borders (Ponte et al. 2019). In this sense, FDI also plays a central role, representing an opportunity for insertion in GVCs for developing countries. However, according to the WTO (2014), not all countries succeed in joining GVCs. Only those whose production is close enough to the global standards of quality and efficiency succeed. Knowledge and technology transfers, usually fostered by FDI and trade openness, tend to trigger the initial integration.

As a key global player, China has shown a trend as the World's leading exporter of manufactured goods and the largest importer of many raw materials, contributing to its status as an important country in the GVCs (Gereffi 2019). Moreover, the increase in Chinese trade in GVCs has been associated with significant changes in wages and employment in China's trading-partner countries (Robertson et al. 2020). Therefore, the dynamics of GVCs depend on the direction of current trade flows (Durand and Milberg 2020). Regardless of the specific type of GVC, the fragmentation of production results in a greater international division of labor and higher specialization gains exploited by the textile industry (Antrás 2020).

Traditionally, the textile sector has been seen as an ideal way for developing countries to enter GVCs. Although markets have become more complex and competitive, the work done by Whitfield et al. (2021) shows that it is still possible to promote industrialization through trade in textiles. This is due to the potential of this activity to generate intra-sectoral networks and generate industrial upgrading trajectories, initially based on a labor cost advantage. Moreover, successful upgrading processes can lead to greater resilience of companies to external shocks (Choksy et al. 2022).

The process of value creation in different countries generates a comparative advantage and a new division of labor, produces new sources for the flow of trade, and increases the level of innovation during the production process, where the main sources of value added are the industries. Therefore, according to Rodil (2017), measuring trade in value added is a fundamental tool for analyzing international trade in this fragmented context. This methodology is based on the decomposition of gross trade into value-added flows that capture the way and intensity in which international productive fragmentation affects the participating countries. Likewise for Banga (2014), domestic and foreign value added is created during manufacturing, so value-added exports will differ from gross exports and can be estimated by subtracting foreign value added.

Value-added trade is a series of measures that provide a better understanding of production networks and supply chains through statistical data. Thus, for this measure of trade, several indicators assess the participation of countries within the GVC: the backward participation index, which indicates the share of foreign value added as a percentage of gross exports; the forward participation index, which indicates the share of domestic value added embodied in foreign exports as a percentage of gross exports; and the total participation index, which is the sum of former.

This paper aims to analyze the participation of countries in textile and apparel GVC with special attention, first, to the case of three dynamic and interrelated economies (Mexico, the United States, and China); and second, extending the analysis to a larger sample of countries in the textile and apparel GVC through trade in value-added approach. The first part focuses on the changing role of the three selected economies, on their performance as value-added suppliers of the final global demand for textile products, and, especially, on verifying the rise of Chinese leadership in this global industry. Meanwhile, the second part includes an econometric analysis with panel data (61 countries, 24 years: 1995–2018) of some relevant factors explaining this GVC participation.

The main source of data is the TiVA database (December 2021 edition) provided by the Organization for Economic Co-operation and Development (OECD), which provides information on trade in value-added for 66 economies and 45 industrial sectors, covering the period of 1995–2018. Such information can be used, among others, to analyze the integration of economies into GVCs, as well as the country of origin of the value-added embodied in gross trade flows and final demand. Other databases used are UNCTAD for data on FDI flows, and the WTO for data on textile tariff rates.

The remainder of the paper is structured as follows. Section 2 describes the paper's methodology, highlighting the usefulness of trade in value-added approach for analyzing country participation in GVCs. Section 3 presents and discusses the empirical results, analyzing the participation of Mexico, the United States, and China in GVC from a general (all industries) and sectoral (textiles and apparel) perspective. It also analyzes the contribution of these countries as value-added suppliers to the World's final demand for textile products and adopts an extended econometric analysis with panel data (61 countries, 24 years: 1995–2018) to explore relevant factors explaining the participation of countries in this GVC. Finally, Section 4 presents the conclusions of the paper.

### **2. Data and Methodology**

The empirical study of GVC participation has a growing number of works analyzing the role played by various explanatory factors (among others, Rahman and Zhao 2013; Arrighetti et al. 2014; Stehrer and Stöllinger 2015; Kowalski et al. 2015; Jona-Lasinio et al. 2016; Vrh 2018). However, the analysis of GVCs from a macroeconomic perspective usually follows the work of Koopman et al. (2014). Their methodology decomposes a country's gross exports into nine components of trade, providing several indicators. These include forward (export-linked) and backward (import-linked) participation indices, the sum of which is considered an indicator of total GVC participation (see Appendix A for the corresponding OECD TiVA indicators). This methodology allows for the tracing of each country's value-added flows to its final consumption destination.

The local supply of intermediate products is one of the main direct export channels attracting FDI, and specialization in the early stages is associated with the production of local inputs obtained by foreign investors (Amendolagine et al. 2017). Hence, one aspect to be considered as a possible explanatory factor for participation in GVCs is the degree of tariff protection, as this factor acts as a barrier to trade flows, among which trade in intermediate products associated with the GVC linkages is becoming increasingly essential. Thus, it is interesting to verify if there is a negative relationship between the level of tariff protection and participation in GVC.

As Yi (2003) points out, vertical specialization may have enhanced the reduction in tariff rates. Through this strategy, characteristic of GVCs, countries specialize in certain stages of a product's value chain. As a result, a slight reduction in tariff rates has multiple multiplier effects on trade growth. Conversely, increasing tariff rates can reduce trade in GVCs as parts and components pass multiple times across different national borders (OECD 2013).

Among the explanatory factors of GVC participation, FDI stands out as a determining element when analyzing the insertion of countries in the framework of international productive fragmentation. In this regard, various studies (Stehrer and Stöllinger 2015; Kowalski et al. 2015) point to a positive relationship between inward FDI stock and participation in GVC. However, no conclusive results can be found in the literature on the role played by outward FDI stock. Therefore, studying the relationship between FDI and GVC participation is interesting. In general, it is assumed that there is a positive relationship between them. This hypothesis is based on the role of multinational companies as major actors in GVCs.

Another explanatory factor of GVC participation is the labor cost, since labor has traditionally been a critical factor, especially in manufacturing or assembly tasks, usually offshored to developing countries. However, the progressive cheapening of global products has led to an unstable competitive framework (Lu 2018), and the explanatory relevance of this factor may sometimes be unclear. Hence, it is also interesting to analyze the influence of labor costs on countries' participation in GVCs.

Based on these assumptions, an econometric model has been estimated using panel data. This empirical analysis considers a group of 61 countries at different development levels, observed for 24 years (1995–2018). The division of the 61 countries into two development groups is based on the World Bank's most recent criteria (2021–2022). Countries classified as "high income" have been considered developed countries. All other cases have been included in the group of developing countries. This division divides the sample into two groups of 39 and 22 countries, respectively (see Appendix B). The general model to be estimated is specified as follows:

$$\gamma\_{\text{it}} = \beta\_0 + \beta\_1 TARIF\_{\text{it}} + \beta\_2 FDI\_{\text{it}} + \beta\_3 LABC\_{\text{it}} + \varepsilon\_{\text{it}} \tag{1}$$

where *i* refers to the country and *t* refers to the period. Two dependent variables have been considered for estimation: total participation in GVCs (TPART), expressed as a percentage of gross exports, and backward participation (BPART), also expressed as a percentage of gross exports.

A total of four independent variables have been selected. The two first regressors are TARIF1 and TARIF2, which refer to the average tariff on textile raw materials and the main textile products, respectively. TARIF1 refers to 51 and 52 textile raw material groups and TARIF2 refers to 61 and 62 textile product groups, according to HS classification. Due to multicollinearity problems between both variables, two different models are considered: Model I, including only TARIF1 as the tariff variable, and Model II, including only TARIF2.

The other two independent variables considered are FDI, which refers to the inward foreign direct investment stock, expressed as a percentage of GDP, and LABC, which is the labor cost, expressed as a percentage of value-added. Except for FDI, all variables refer to the textile sector (ISIC Rev.4 codes 13, 14, and 15). FDI is obtained from UNCTAD, labor cost and GVC share variables are obtained from TiVA (OECD 2021), and TARIF data is obtained from WTO.

Therefore, the two considered models are as follows, where the expression relating to the dependent variable (PART) is a generic expression of the GVC participation, which can refer indistinctly to total participation (TPART) or backward participation (BPART):

$$\begin{array}{l}\text{Model I}: \text{ }PART\_{it} = \beta\_0 + \beta\_1 TARIF1\_{it} + \beta\_2 FDI\_{it} + \beta\_3 LABC\_{it} + \varepsilon\_{it} \\\text{Model II}: \text{ }PART\_{it} = \beta\_0 + \beta\_1 TARIF2\_{it} + \beta\_2 FDI\_{it} + \beta\_3 LABC\_{it} + \varepsilon\_{it} \end{array} \tag{2}$$

The consideration of backward participation in GVCs (BPART) is due to its relevance for most developing economies, which, in the textile sector, tend to take on manufacturing tasks of lower value added, relative to other tasks, such as garment design and conception.

The reason for using panel data is motivated by the suspicion that participation in GVC is influenced by unobservable factors that correlate with observed variables, such as the factors mentioned above. Therefore, it is assumed that the panel techniques contribute to obtaining consistent estimates of the effect of the variables observed, offering greater possibilities at the time of facing the usual problems in this type of empirical approach.

The joint significance of differing group means and Breusch-Pagan statistic tests point to a panel data structure. The Hausman statistic test points to a fixed effects model. One of the immediate implications of this is that the error term *εit*, in Equations (1) and (2), is now broken down into two different effects: a specific country effect (*mi*) and the remaining error (*vit*). A relevant advantage of this econometric technique is that it allows us to obtain unbiased estimators.

#### **3. Results**

#### *3.1. The Participation of Mexico, the United States, and China in GVC: General Perspective*

International trade allows economies to integrate and increase their participation in GVC trade flows, so that activities along a value chain can be carried out by FDI or outsourcing (Kowalski et al. 2015). For example, in apparel, China has been the most dynamic exporter worldwide in clothing since 2001, when it joined the World Trade Organization (WTO).

It adopted a position that has not favored Mexico, due to the displacement of U.S. imports from that country with such a growth that they surpassed Mexican imports (Pino 2020). As a result, in 2003, Mexico dropped from first to second place as a textile and clothing supplier because of its dependence on the economic ups and downs of the United States (Rodríguez and Fernández 2006).

Trade through GVCs offers opportunities to developing countries, especially smaller ones, for global integration, changing the nature of competitiveness (Pathikonda and Farole 2017). This is because much of the labor-intensive production moved to the World developing in the last wave of globalization, with textiles being highly tradable products (Lund et al. 2019).

As can be seen in this paper, the analysis of the participation of Mexico, the United States, and China in the global textile and apparel value chain presents relevant changes in the last decades. Lu (2013) points out that one of the reasons for these changes is that a country's apparel industry gradually upgrades following the path of Cut, Make and Trim (CMT), Original Equipment Manufacturing (OEM), Original Design Manufacturing (ODM), or Original Brand Manufacturing (OBM). In the case of Mexico, for example, the textile industry has been transforming by assuming mainly assembly tasks (e.g., cutting and sewing) and abandoning a series of risk- and knowledge-intensive coordination and design tasks (Pipkin and Fuentes 2017).

The comparative analysis of the participation of Mexico, the United States, and China in the GVC in the period of 1995–2018 shows different participation levels, insertion patterns, and trends. In this sense, Figure 1 provides a clear picture of the different patterns observed. The first difference refers to the total participation rate, with high participation in Mexico in 2018 (46.4% of gross exports), compared to China (36.6%) and the United States (35.6%) but at the same time with a strong predominance of backward linkages in Mexico (35.9% of gross exports), compared to China (17.2%) and the United States (9.5%).

**Figure 1.** GVC participation index (%). Total participation (all sectors) 1995–2018. Source: Authors based on TiVA (OECD 2021).

However, this gap in the level of total participation differs significantly from that observed more than a decade earlier (2008), when Mexico started from a higher level (44.7%) than China (40.2%) and the United States (36.9%). Furthermore, another difference is given by the opposite trends observed in GVC participation; that is, Mexico's participation increased by more than seven percentage points during the study period, while the U.S. and China decreased their participation in GVC between 2008 and 2018 (even though their participation rates are higher in 2018 than in 1995).

The observation of the predominant type of production linkage is fundamental since this analysis is given by decomposing the total participation in its two components: backward and forward participation. Thus, the predominance of China's forward participation (12.6% of gross exports) in 1995 increased by more than six percentage points by 2018 (19.3%); in comparison, Mexico increases by two percentage points from 1995 to 2018 (from 8.5% to 10.5%) while the U.S. shows an increase of more than six percentage points (from 19.4% to 26.1%).

China's rapid growth has made it a major player in virtually all goods produced in GVCs, accounting for 20% of global gross output (Lund et al. 2019), which was initially due to cheap Chinese labor due to low wages (Gereffi and Memedovic 2003). In this sense, one of the causal factors contributing to the reduction in costs and the increase in production rates has been the supply of cheap Chinese labor, which brings low wages (Gereffi and Memedovic 2003).

However, the trend observed for Mexico reveals that its foreign trade operates more as a carrier of value added originating in other countries than as a channeler of domestic value added to later stages of production in the framework of international fragmentation of production. This is, to some extent, a direct consequence of China's productive strategy of gradually substituting foreign value added for domestic value added (Rodil 2017).

Therefore, the reduction in the intensity of participation in GVCs is due to the deepening of the domestic division of labor and the lengthening of domestic value chains (Li et al. 2019). In this sense, the GVC participation trends in Mexico, the United States, and China offer an interesting perspective on their behavior in the GVCs of developed and developing countries, highlighting the case of Mexico's backward linkages that are characteristic of a manufacturing country.

This predominance of backward participation could be associated with countries' participation in production stages close to the final demand, for example, in the case of

assembly tasks (assembly line). However, it is also important to note that countries can show high rates of backward participation by doing non-manufacturing activities that generate high value-added, related to marketing and distribution (Rodil and Gómez 2021).
