Integration into Global Value Chains: Evidence from Mexico, 1995–2020

Abstract

This paper examines Mexico’s integration into Global Value Chains (GVCs) and its implications for structural change over the period 1995–2020. Using a multiregional input–output framework, the analysis decomposes gross exports into domestic and foreign value added and combines these indicators with weighted forward and backward production linkages to assess the relationship between sectoral GVC participation patterns and sectors’ roles within the domestic production structure. The results show that Mexico’s integration into GVCs has been characterized by strong and persistent backward participation, reflecting a high dependence on imported intermediate inputs, alongside comparatively lower and more stable forward participation. Multi-stage integration has been particularly relevant in a limited number of manufacturing activities—most notably in the automotive sector—both in terms of its contribution to domestic value added and its dynamism. However, this form of integration has remained highly concentrated, and changes in sectoral GVC participation have not translated into generalized shifts in the dynamic hierarchy of sectors. Sectoral roles within the production structure exhibit a high degree of persistence over time, with only a small number of nongeneralized cases of upgrading. By jointly examining GVC participation typologies and sectoral linkage dynamics, the paper contributes to bridging trade-in-value-added analyses and structuralist approaches to productive change. From a policy perspective, while the results do not establish causal relationships, they point to differentiated structural patterns with relevant implications for industrial policy. Overall, the analysis suggests that deeper integration into GVCs, in the absence of targeted industrial policies, does not by itself guarantee structural transformation or sustained gains in domestic value added.

1. Introduction

Mexico’s integration into Global Value Chains (GVCs) has been widely examined in relation to its implications for long-term economic development. Early assessments assumed that a manufacturing-export-led growth model would promote modernization, stimulate technological innovation, and ultimately support convergence with developed economies (Moreno-Brid et al., 2005; Moreno Brid, 2016; Murillo Villanueva et al., 2022). From this perspective, participation in the international fragmentation of production was expected to facilitate integration into GVCs and to foster the expansion of internationally competitive sectors. However, a substantial body of literature has emphasized that the developmental outcomes of such integration depend critically on countries’ functional positions within value chains and on chain-governance arrangements, which shape the scope for domestic value-added generation and structural transformation (Kaplinsky, 2000; Gereffi, 2019; Schteingart et al., 2017).

Since 1986, integration into GVCs has been actively promoted by national governments and supported by international organizations such as the Organisation for Economic Co-operation and Development (OECD), the Economic Commission for Latin America and the Caribbean (ECLAC), and the World Bank. This strategy was grounded in the exploitation of comparative and competitive advantages—particularly Mexico’s geographic location, natural resource endowments, and manufacturing-oriented labor force—and aimed to consolidate an export-led, labor-intensive industrial structure (Contreras Montellano, 2000; Moreno-Brid et al., 2005, 2009; Cadestin et al., 2016; Garrido, 2022). To support this transition, a set of orthodox reforms—including trade and financial liberalization, exchange-rate liberalization, deregulation, and privatization—was implemented to accelerate the shift from state-led industrialization toward growth driven by global demand for manufactured goods (Pacheco-López & Thirlwall, 2004; Williamson, 2008; Calva, 2019).

Mexico’s integration into GVCs accelerated after the entry into force of the North American Free Trade Agreement (NAFTA), consolidating the country’s position as a strategic node within “Factory North America” in a context of increasing competition from manufacturing platforms in Asia and Europe (Baldwin & López-González, 2015). During the 1990s and 2000s, a growing body of empirical work documented the dynamism of this integration process, particularly within manufacturing activities (Blyde, 2014; De Backer & Miroudot, 2014; Cadestin et al., 2016). Several studies highlight the role of technology-intensive manufacturing segments associated with relatively higher value added, drawing parallels with the experiences of Brazil and Costa Rica (Blyde, 2014; Rivera-Basques, 2022; Pérez Akaki et al., 2023). Nevertheless, Mexico’s trajectory differs from that of most Latin American economies, where GVC participation has tended to remain concentrated in primary, extractive, or low-processing activities, reflecting distinct patterns of specialization and functional integration (Cadestin et al., 2016; Zaclicever, 2017).

By the late 2000s, Mexico’s integration into GVCs began to exhibit signs of relative weakening, reflecting both the rise of competing manufacturing hubs—particularly China and South Korea—and the cumulative effects of major external shocks, including the 2008 global financial crisis, subsequent U.S.–China trade tensions, and, more recently, the COVID-19 pandemic (Chiquiar & Tobal, 2019; Murillo-Villanueva, 2022; Dussel Peters, 2022; Pérez-Santillán & Arriaga Navarrete, 2024). The Mexican experience thus reveals a pattern of GVC participation marked by strong sectoral concentration in processing and assembly activities with limited domestic value-added content, alongside a high dependence on imported intermediate inputs. This configuration has been reinforced by the expansion of U.S.-owned firms, positioning Mexico within manufacturing segments oriented toward the assembly of higher-value final goods, albeit within production stages that remain functionally constrained and weakly articulated with the domestic productive structure.

From a value-added perspective, Mexico’s participation in GVCs has involved persistently high levels of foreign value added and comparatively lower domestic value added, reflecting structural constraints in the domestic generation and supply of intermediate inputs to third markets (Chiquiar & Tobal, 2019). These features underscore the limited effectiveness of industrial policy in fostering technological capabilities and deeper domestic production linkages (Dussel Peters, 2018). More broadly, four decades after the onset of liberalization, outcomes in terms of economic growth, domestic value-added generation, and progress toward structural transformation have fallen short of the optimistic expectations that prevailed in the early 2000s (Cadestin et al., 2016; Dussel Peters, 2018; Garrido, 2022; Vidal & Pandiella, 2024). GVC participation has not translated into higher growth rates than those observed during the period of state-led industrialization (Calva, 2019). Overall, the evidence suggests that GVC integration, in the absence of active industrial policy, does not guarantee convergence or a reduction in productive heterogeneity; rather, it may reproduce specialization patterns marked by technological dependence, exposure to external shocks, and limited scaling capacity.

Against this backdrop, this paper examines Mexico’s sectoral integration into GVCs and its relationship with changes in sectors’ roles as drivers of the production structure over the period 1995–2020. The central hypothesis is that, despite deepening integration into GVCs, Mexico’s productive structure has exhibited a high degree of persistence, with limited and non-generalized transitions in sectors’ dynamic roles, reflecting structural constraints in domestic value-added generation and production linkages.

This paper makes three specific contributions to the literature on GVCs and structural change. First, from a methodological perspective, it integrates trade-in-value-added indicators derived from a MRIO framework with a Rasmussen-type classification of sectoral forward and backward linkages. While existing studies typically analyze GVC participation or production linkages in isolation, this paper combines both dimensions within a unified analytical framework, enabling an explicit assessment of whether changes in GVC participation patterns are associated with shifts in sectors’ roles within the domestic production structure.

Second, the paper contributes analytically by moving beyond the measurement of GVC participation intensity to examine the structural implications and quality of integration. Specifically, it evaluates whether sectoral trajectories of forward, backward, or multi-stage integration are linked to upward transitions in sectoral dynamism—such as shifts toward key or driver positions—or whether integration tends to reproduce existing productive hierarchies. In doing so, the study directly engages with the debate on whether GVC participation fosters structural transformation or instead reinforces enclave-type integration patterns.

Third, the paper provides new long-run empirical evidence for Mexico over the period 1995–2020, encompassing the consolidation of NAFTA, the rise of China as a global manufacturing hub, the 2008 global financial crisis, and the initial impact of the COVID-19 shock. By systematically tracking sectoral integration patterns and dynamic roles over this extended horizon, the analysis documents a high degree of structural persistence alongside a small number of notable but non-generalized cases of upgrading, most prominently in the automotive sector.

Accordingly, the main research question guiding the empirical analysis is as follows: To what extent are the intensity and evolution of Mexico’s sectoral integration into GVCs associated with changes in the dynamic hierarchy of sectors within the national production structure over the period 1995–2020?

Methodologically, the analysis proceeds in three steps. First, it examines the intensity and evolution of sectoral GVC integration, distinguishing four integration patterns: multi-stage integration, dominant backward integration, dominant forward integration, and low integration. Second, it establishes the hierarchy of sectoral dynamism using weighted forward and backward linkages and identifies changes in sectoral roles over time. Finally, it assesses whether observed integration trajectories are systematically associated with transitions in sectors’ positions as drivers of the production structure.

The remainder of the paper is organized as follows: Section 2 reviews the relevant literature and presents the MRIO framework and the indicators used to characterize sectoral participation in GVCs and dynamic production linkages. Section 3 reports and discusses the empirical results, focusing on aggregate trends, sectoral patterns of GVC integration, and the relationship between integration trajectories and changes in sectors’ roles within the Mexican production structure over the period 1995–2020. Section 4 summarizes the main findings, discusses the limitations of the analysis, and outlines the main implications for industrial policy.

2. Methodology

2.1. Literature Review

Fragmented production at the global level is organized through GVCs, which allocate specific functions—such as design, manufacturing, assembly, logistics, and after-sales services—across countries (Sturgeon, 2001; Gereffi & Fernández-Stark, 2011). Analytically, the GVCs framework represents a shift in the analytical unit from entire industries to the functions and tasks that constitute distinct production stages (Feenstra, 1998).

GVCs-based analysis makes it possible to identify not only where value is produced, but also how it is generated and appropriated across the different segments of the value chain (Phillips, 2016). In this regard, Gereffi and Fernández-Stark (2011) propose four key dimensions for examining GVCs: (i) the structure of inputs and outputs across intermediate and final goods; (ii) the geographical distribution of production stages; (iii) governance structures and power relations within the chains; and (iv) the institutional framework that support the international fragmentation of production. From this perspective, the functional position of national economies within GVCs is not neutral; rather, it is shaped by comparative advantages, productive capabilities, and—crucially—the governance exercised by lead firms (Gereffi et al., 2005).

Building on this logic, Kaplinsky (2000) argues that upgrading within GVCs depends on institutional conditions and national capacities for technological absorption. In the absence of active industrial policies and stronger endogenous capabilities (Cimoli et al., 2019), GVCs integration may foster technological dependence and reinforce structural heterogeneity, a pattern widely documented in Latin America (Cimoli, 2005). This interpretation is consistent with the Latin American structuralist tradition, which emphasizes that international integration based on primary activities or low-value-added manufacturing tends to reproduce productive and technological asymmetries and to concentrate the gains from integration among external actors.

Fröbel et al. (1980) early highlighted that the new international division of labor entailed the relocation of labor-intensive manufacturing processes to developing countries, thereby positioning these economies in subordinate roles within production systems governed by lead firms based in advanced economies. Subsequent empirical research has shown that the developmental outcomes of integration into GVCs have been highly heterogeneous and critically mediated by the presence—or absence—of active industrial policy.

In several Asian economies, including South Korea, Taiwan, and China, integration into GVCs has been strategically leveraged to consolidate domestic innovative capabilities and advance toward activities of greater technological complexity and higher value added (Pahl & Timmer, 2020). By contrast, Latin American countries have tended to integrate into natural-resource-intensive chains and, in some cases, into manufacturing segments centered on the processing and assembly of intermediate and final goods, with limited effects on productive upgrading and structural transformation (Blyde, 2014; Rivera-Basques, 2022). Moreover, continued reliance on primary exports has exposed these economies to international price volatility, often shaped by transnational actors, thereby reinforcing external vulnerability (Morett-Sánchez & Cosío Ruiz, 2023).

These contrasting trajectories become particularly evident in sector-specific comparisons. For instance, Lowe and Kenney (1999) show that while Mexico specialized in the assembly of electronic devices, Taiwan succeeded in developing domestic supplier networks and innovation capabilities within the same industry, thereby reconfiguring electronics GVCs and relocating higher-value-added production stages away from Mexico. A similar pattern is observed in the textile and apparel industry, where Mexico’s participation weakened over time as coordination, design, and branding functions shifted to the United States and China, while cutting and assembly activities remained domestically. This configuration suggests that Mexico’s position within these chains has largely involved embodying foreign value added rather than generating it domestically (Rodil-Marzábal et al., 2022).

Overall, evidence on the distribution of gains and losses from GVCs integration reinforces the view that countries combining coherent industrial policies with effective coordination among firms are better positioned to scale up within production chains (Kaplinsky, 2000). By contrast, economies characterized by passive forms of integration tend to remain confined to low-value-added segments, as documented by Giuliani et al. (2005) and Fernández-Stark and Gereffi (2011). In a similar vein, Kowalski et al. (2015) caution against assuming automatic development gains from GVCs participation, particularly in low-income economies where structural constraints persist.

In the case of Mexico, GVCs integration has been examined through a variety of theoretical and methodological lenses. A growing body of research based on multiregional input–output frameworks has focused on identifying the country’s functional position within GVCs (De La Cruz et al., 2013; Boundi Chraki, 2016; Murillo Villanueva et al., 2022; Pérez-Santillán & Arriaga Navarrete, 2024). Related work by Fuentes Flores et al. (2023) analyzes productive linkages between Mexico and U.S. border states such as Texas and California, highlighting a high density of interregional connections. In addition, sector-specific studies—covering agri-food activities, mining, manufacturing, and selected services—confirm Mexico’s significant degree of GVCs integration while also documenting a persistent reliance on imported intermediate inputs and limited domestic value-added generation (Medina Chamorro & De La Peña Cárdenas, 2020; Cairó-i-Céspedes & Cortés Torres, 2022).

In addition, econometric approaches have been employed to analyze Mexico’s participation in GVCs, incorporating factors such as tariffs, foreign direct investment flows, labor costs, and other determinants; examples include studies focused on the textile industry (Rodil-Marzábal et al., 2022). At the microeconomic level, Moreno et al. (2020) identify firm-level characteristics—such as size and technological capabilities—that facilitate the development of local suppliers within household-appliance production chains. Looking ahead, simulation-based analyses have also been applied to assess the economic and environmental implications of developing upstream stages in strategic sectors, including photovoltaic energy (Birlain-Escalante et al., 2023).

Overall, the literature on Mexico’s integration into GVCs converges around three central findings. First, participation has been concentrated in low-value-added segments, with scaling processes limited to a narrow set of activities and reflecting constrained decision-making capabilities within chains. Second, integration has reinforced a production pattern characterized by strong dependence on imported intermediate inputs, limited domestic value-added generation, and a weak capacity to activate broader domestic production linkages. Third, while Mexico’s participation in GVCs has been relatively intense compared with that of most Latin American economies—positioning the country as a major exporter of automobiles and electronic and electrical goods—it continues to lag Asian economies in higher-value-added segments related to design, innovation, and technological development.

Taken together, these contributions underscore the need to examine not only the intensity of Mexico’s integration into GVCs, but also its quality, functional configuration, and implications for domestic productive structures—an analytical gap that this study aims to address.

From a methodological perspective, existing studies on Mexico’s integration into GVCs can be broadly grouped into three strands. A first group of MRIO-based analyses focuses primarily on aggregate or sectoral measures of domestic and foreign value added, providing detailed descriptions of Mexico’s position within international production networks but without explicitly examining how such integration relates to changes in the domestic production structure. A second strand consists of sector-specific or case-study approaches—particularly in automotive, electronics, and agri-food industries—which offer rich institutional and historical insights but are not designed to assess economy-wide structural dynamics. A third group relies on econometric or firm-level approaches to identify determinants of GVC participation, often abstracting from intersectoral production linkages and multiplier effects.

While these contributions have significantly advanced the understanding of Mexico’s GVC integration, they do not directly address whether changes in the intensity and configuration of GVC participation have been associated with systematic transformations in sectoral hierarchies and domestic production linkages over time. By jointly examining sectoral GVC participation patterns and Rasmussen-type forward and backward linkages within a unified MRIO framework, this study bridges trade-in-value-added analyses and structuralist approaches to productive change. In doing so, it contributes to adjudicating between interpretations that emphasize export dynamism and those that stress structural persistence by explicitly assessing whether integration into GVCs has translated into changes in sectors’ roles as drivers of the Mexican production structure.

2.2. Multiregional Input-Output Model

Mexico’s participation in GVCs is analyzed using a MRIO framework (Leontief & Strout, 1963; Miller & Blair, 2009), which is widely adopted in empirical research on the international fragmentation of production and is compatible with different theoretical perspectives. The MRIO framework allows the decomposition of gross exports into their domestic and foreign value-added components and provides a consistent basis for tracing intersectoral and cross-country production linkages (Johnson & Noguera, 2012; Koopman et al., 2014; Timmer et al., 2013, 2015). The starting point of the analysis is the standard input–output relationship between output, intermediate inputs, and final demand:

$$\mathbf{x}=\mathbf{A}\mathbf{x}+\mathbf{y}$$

(1)

where $\mathbf{x}$ denotes the vector of gross output, $\mathbf{A}$ is the technical coefficient matrix, and $\mathbf{y}$ represents final demand. Solving for output yields

$$\mathbf{L}={\left(\mathbf{I}-\mathbf{A}\right)}^{-1}$$

(2)

where L is the Leontief inverse, capturing the total (direct and indirect) production required to satisfy a unit of final demand. So that

$$\mathbf{x}=\mathbf{L}\mathbf{y}$$

(3)

In an MRIO framework with multiple countries and sectors, the Leontief inverse is partitioned into country–sector blocks, allowing production linkages to be traced across national boundaries. Accordingly, the elements ${\mathsf{\alpha }}_{\mathrm{i}\mathrm{j}}^{\mathrm{r}\mathrm{s}}$ of the Leontief inverse L, in a setting with m countries and n sectors, represent the total (direct and indirect) output of sector i in country r embodied in one unit of final demand for the output of sector j in country s. Equation (3) therefore captures the total effect of a unit increase in final demand on the production structure, quantifying the additional output required along the value chain to satisfy that demand. Value added is subsequently mapped onto final demand through the following matrix:

$$\mathsf{\Omega }=\widehat{\mathbf{V}}\mathbf{L}\widehat{\mathbf{Y}}$$

(4)

where $\widehat{\mathbf{V}}$ is a diagonal matrix of value-added coefficients, and $\widehat{\mathbf{Y}}$ is a diagonal matrix of final demand. The elements ${\mathsf{\omega }}_{ij}^{rs}$ of Ω measure the value added generated by sector i in country r embodied in the production of sector j in country s to satisfy final demand. This matrix underpins the mapping of total value added embodied in international trade and is organized in n × n blocks, each representing relationships between a pair of countries (including the domestic case).

More explicitly, $\widehat{\mathbf{V}}$ consists of m diagonal blocks ${\widehat{\mathbf{v}}}^r$ (each of size n × n), and $\widehat{\mathbf{Y}}$ has the same structure, with diagonal blocks ${\widehat{\mathbf{y}}}^r$. The Leontief inverse can be written in block form as L = ${\left[{\mathbf{L}}^{rs}\right]}_{r,s=1}^m$, where each ${\mathbf{L}}^{rs}$ is an n × n matrix that captures the link from producer country r to purchasing country s. Thus, value-added flows through trade can be traced as

$$\mathsf{\Omega }=\widehat{\mathbf{V}}\mathrm{L}\widehat{\mathbf{Y}}=\left[\begin{array}{cccc}{\widehat{\mathrm{V}}}^1{\mathrm{L}}^{\mathrm{1,1}}{\widehat{\mathrm{Y}}}^1& {\widehat{\mathrm{V}}}^1{\mathrm{L}}^{\mathrm{1,2}}{\widehat{\mathrm{Y}}}^2& \dots & {\widehat{\mathrm{V}}}^1{\mathrm{L}}^{1,m}{\widehat{\mathrm{Y}}}^m\\ {\widehat{\mathrm{V}}}^2{\mathrm{L}}^{\mathrm{2,1}}{\widehat{\mathrm{Y}}}^1& {\widehat{\mathrm{V}}}^2{\mathrm{L}}^{\mathrm{2,2}}{\widehat{\mathrm{Y}}}^2& \dots & {\widehat{\mathrm{V}}}^2{\mathrm{L}}^{2,m}{\widehat{\mathrm{Y}}}^m\\ ⋮& ⋮& \ddots & ⋮\\ {\widehat{\mathrm{V}}}^m{\mathrm{L}}^{m,1}{\widehat{\mathrm{Y}}}^1& {\widehat{\mathrm{V}}}^m{\mathrm{L}}^{m,2}{\widehat{\mathrm{Y}}}^2& \dots & {\widehat{\mathrm{V}}}^m{\mathrm{L}}^{m,m}{\widehat{\mathrm{Y}}}^m\end{array}\right]$$

(5)

The partitioned blocks of the matrix Ω allow the disaggregation of value added generated by sector i in country r and embodied in the final demand of sector j in country s. Let 1n be an n-vector of ones. Then country-r value added embodied in its own final demand (domestic component) and in other countries’ final demand (foreign component) can be summarized as

$${\mathsf{\Omega }}_{\mathrm{d}}^{\mathrm{r}}={{\mathbf{1}}^{\prime }}_n\left({\widehat{\mathbf{V}}}^{\mathrm{r}}{\mathbf{L}}^{\mathrm{r}\mathrm{r}}{\widehat{\mathbf{Y}}}^{\mathrm{r}}\right){\mathbf{1}}_n,$$

(6)

$${\mathsf{\Omega }}_{\mathrm{f}}^{\mathrm{r}}=\sum _{\mathrm{s}\ne \mathrm{r}}{\mathbf{1}}_n^{\prime }\left({\widehat{\mathbf{V}}}^{\mathrm{r}}{\mathbf{L}}^{\mathrm{r}\mathrm{s}}{\widehat{\mathbf{Y}}}^{\mathrm{s}}\right){\mathbf{1}}_n,$$

(7)

so that total value added generated by country r is ${\mathsf{\Omega }}^{\mathrm{r}}={\mathsf{\Omega }}_{\mathrm{d}}^{\mathrm{r}}+{\mathsf{\Omega }}_{\mathrm{f}}^{\mathrm{r}}.$ In matrix form,

$$\mathsf{\Omega }=\widehat{\mathbf{V}}\mathbf{L}{\widehat{\mathbf{Y}}}_{\mathit{d}}+\widehat{\mathbf{V}}\mathbf{L}{\widehat{\mathbf{Y}}}_{\mathit{f}}$$

(8)

This decomposition quantifies the value added generated in each economy to satisfy both domestic and international final demand (Timmer et al., 2013, 2015). In short, Ω provides the architecture of GVCs and their country-sector breakdown, facilitating the tracking of the origin and destination of total value added embodied in final demand.

From Mexico’s perspective, GVC participation is summarized using Domestic Value Added (DVA) and Foreign Value Added (FVA) shares, normalized by gross exports (E^r). Forward participation (DVA share) captures the domestic value added embodied in other countries’ final demand, while backward participation (FVA share) measures the foreign value added embodied in Mexico’s exports. The DVA of country r embodied in other countries’ final demand is

$${\mathbf{D}\mathbf{V}\mathbf{A}}^{\mathit{r}} \mathbf{S}\mathbf{h}\mathbf{a}\mathbf{r}\mathbf{e}={\displaystyle \frac{{\sum }_{\mathit{s}\ne \mathit{r}}\left({\sum }_{\mathit{i}=\mathbf{1}}^{\mathit{n}}{\sum }_{\mathit{j}=\mathbf{1}}^{\mathit{n}}{\mathit{\omega }}_{\mathit{i}\mathit{j}}^{\mathit{r}\mathit{s}}\right)}{{\mathit{E}}^{\mathit{r}}}}\times \mathbf{100}$$

(9)

while the FVA embodied in country r’s exports is

$${\mathbf{F}\mathbf{V}\mathbf{A}}^{\mathit{r}} \mathbf{S}\mathbf{h}\mathbf{a}\mathbf{r}\mathbf{e}={\displaystyle \frac{\sum _{\mathit{s}\ne \mathit{r}}\left(\sum _{\mathit{i}=\mathbf{1}}^{\mathit{n}}\sum _{\mathit{j}=\mathbf{1}}^{\mathit{n}}{\mathit{\omega }}_{\mathit{i}\mathit{j}}^{\mathit{s}\mathit{r}}\right)}{{\mathit{E}}^{\mathit{r}}}}\times \mathbf{100}$$

(10)

where E^r denotes the gross exports of country r (Mexico). Mexico’s degree of GVC integration is assessed by comparing forward and backward participation with the corresponding world averages (DVA^W and FVA^W shares). This comparison allows sectors to be classified into four GVC participation patterns: multi-stage integration, dominant backward integration, dominant forward integration, and low integration.

Table 1. Mexico’s Integration into GVCs: Sectoral Classification.

	${\mathbf{D}\mathbf{V}\mathbf{A}}_{\mathbf{r}} \mathbf{S}\mathbf{h}\mathbf{a}\mathbf{r}\mathbf{e}$ $\mathbf{\ge }$ ${\mathbf{D}\mathbf{V}\mathbf{A}}_{\mathbf{W}}$ Share	${\mathbf{D}\mathbf{V}\mathbf{A}}_{\mathbf{r}} \mathbf{S}\mathbf{h}\mathbf{a}\mathbf{r}\mathbf{e}$ $\mathbf{<}$ ${\mathbf{D}\mathbf{V}\mathbf{A}}_{\mathbf{W}}$ Share
${\mathbf{F}\mathbf{V}\mathbf{A}}_{\mathbf{r}} \mathbf{S}\mathbf{h}\mathbf{a}\mathbf{r}\mathbf{e}$ $\ge$ ${\mathbf{F}\mathbf{V}\mathbf{A}}_{\mathbf{W}} \mathbf{S}\mathbf{h}\mathbf{a}\mathbf{r}\mathbf{e}$	Multi-stage	Dominant backward
${\mathbf{F}\mathbf{V}\mathbf{A}}_{\mathbf{r}} \mathbf{S}\mathbf{h}\mathbf{a}\mathbf{r}\mathbf{e}$ $<{\mathbf{F}\mathbf{V}\mathbf{A}}_{\mathbf{W}} \mathbf{S}\mathbf{h}\mathbf{a}\mathbf{r}\mathbf{e}$	Dominant forward	Low

Source: Own elaboration.

presents the classification criteria by degree of integration, which allow for the identification of Mexico’s relative position in GVCs at both the aggregate and sectoral levels over the study period.

These indicators describe Mexico’s forward and backward participation relative to world averages. Dominant forward integration indicates a position in upstream stages, as a supplier of inputs, raw materials, or components that other countries use and re-export. Dominant backward integration indicates a position in midstream or downstream stages (assembly and final production), characterized by a strong dependence on imported intermediate inputs. In summary, combining dominant forward and backward integration reveals the country’s relative position and the predominant type of integration in GVCs.

From a structural perspective, and complementing the analysis of GVC integration, the analysis relies on Rasmussen’s (1956) forward and backward linkage indicators to assess the role of sectors within the domestic production structure, computed from the Mexico-specific block of the Leontief inverse. Based on this framework, sectors are classified as key, driver, strategic, and non-key. First, unit backward linkages (BL) for industry j are defined as the column sum of the Mexico block of $\mathbf{L}$:

$${\mathbf{BL}}_j=\sum _{i=1}^n{\mathbf{\propto }}_{ij}$$

(11)

Unit forward linkages (FL) for industry i are defined as the row sum:

$${\mathbf{FL}}_j=\mathrm{ }\sum _{j=1}^n{\mathbf{\propto }}_{ji}$$

(12)

Relative indicators are then obtained as

$$BL{r}_J=\mathrm{ }{\displaystyle \frac{{\sum }_{i=1}^n{\mathbf{\propto }}_{ij}}{\frac{1}{n}{\sum }_{j=1}^n{\sum }_{i=1}^n{\mathbf{\propto }}_{ij}}},\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }FL{r}_i=\mathrm{ }{\displaystyle \frac{{\sum }_{j=1}^n{\mathbf{\propto }}_{ij}}{\frac{1}{n}{\sum }_{j=1}^n{\sum }_{i=1}^n{\mathbf{\propto }}_{ij}}}$$

(13)

Next, indicators are weighted by Mexico’s final demand $\left({\overline{y}}_i\right)$ (Rasmussen, 1956; Duarte Pac et al., 2011):

$$BL{R}_j=\mathrm{ }{\displaystyle \frac{{\sum }_{i=1}^n{\mathbf{\propto }}_{ij}{\overline{y}}_j}{\frac{1}{n}{\sum }_{j=1}^n{\sum }_{i=1}^n{\mathbf{\propto }}_{ij}{\overline{y}}_j}}\mathrm{ },\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }FL{R}_i=\mathrm{ }{\displaystyle \frac{{\sum }_{j=1}^n{\mathbf{\propto }}_{ij}{\overline{y}}_i}{\frac{1}{n}{\sum }_{j=1}^n{\sum }_{i=1}^n{\mathbf{\propto }}_{ij}{\overline{y}}_i}}$$

(14)

Weighted versions of these indicators—using sectoral final demand—are used to classify sectors as key, driver, strategic, or non-key (See

Table 2. Mexico: Sector Classification Based on Weighted Forward and Backward Linkages.

	$\mathbf{F}\mathbf{L}{\mathbf{R}}_{\mathbf{i}} \mathbf{\ge } \mathbf{1}$	$\mathbf{F}\mathbf{L}{\mathbf{R}}_{\mathbf{i}} \mathbf{<} \mathbf{1}$
$\mathrm{B}\mathrm{L}{\mathrm{R}}_{\mathrm{j}}\ge 1$	Key	Driver
$\mathrm{B}\mathrm{L}{\mathrm{R}}_{\mathrm{j}}<1$	Strategic	Non-key

Source: Own elaboration.

). This classification captures the extent to which sectors generate multiplier effects through their demand for intermediate inputs (backward linkages) and their supply of inputs to other sectors (forward linkages).

By applying this framework consistently over the period 1995–2020, the analysis identifies changes in GVC participation patterns and sectoral roles over time. Importantly, transitions in sectoral classifications are interpreted as indicators of shifts in relative structural importance, rather than as evidence of causal upgrading processes.

Finally, the empirical application draws on the OECD Inter-Country Input–Output tables covering the period 1995–2020 (11 benchmark years), including 76 countries plus the Rest of the World (RoW) and 45 sectors (See Appendix A 

Table A1. Geographical coverage of inter-country input-output tables.

Number	Countries	Code	Number	Countries	Code	Number	Countries	Code
1	Argentina	ARG	31	Hungary	HUN	61	Romania	ROU
2	Australia	AUS	32	Indonesia	IDN	62	Russian Federation	RUS
3	Austria	AUT	33	India	IND	63	Saudi Arabia	SAU
4	Belgium	BEL	34	Ireland	IRL	64	Senegal	SEN
5	Bangladesh	BGD	35	Iceland	ISL	65	Singapore	SGP
6	Bulgaria	BGR	36	Israel	ISR	66	Slovakia	SVK
7	Belarus	BLR	37	Italy	ITA	67	Slovenia	SVN
8	Brazil	BRA	38	Jordan	JOR	68	Sweden	SWE
9	Brunei Darussalam	BRN	39	Japan	JPN	69	Thailand	THA
10	Canada	CAN	40	Kazakhstan	KAZ	70	Tunisia	TUN
11	Switzerland	CHE	41	Cambodia	KHM	71	Türkiye	TUR
12	Chile	CHL	42	Korea	KOR	72	Chinese Taipei	TWN
13	China (People’s Republic of)	CHN	43	Lao (People’s Democratic Republic)	LAO	73	Ukraine	UKR
14	Côte d’Ivoire	CIV	44	Lithuania	LTU	74	United States	USA
15	Cameroon	CMR	45	Luxembourg	LUX	75	Viet Nam	VNM
16	Colombia	COL	46	Latvia	LVA	76	South Africa	ZAF
17	Costa Rica	CRI	47	Morocco	MAR	77	Rest of the World	ROW
18	Cyprus	CYP	48	Mexico	MEX
19	Czechia	CZE	49	Malta	MLT
20	Germany	DEU	50	Myanmar	MMR
21	Denmark	DNK	51	Malaysia	MYS
22	Egypt	EGY	52	Nigeria	NGA
23	Spain	ESP	53	Netherlands	NLD
24	Estonia	EST	54	Norway	NOR
25	Finland	FIN	55	New Zealand	NZL
26	France	FRA	56	Pakistan	PAK
27	United Kingdom	GBR	57	Peru	PER
28	Greece	GRC	58	Philippines	PHL
29	Hong Kong, China	HKG	59	Poland	POL
30	Croatia	HRV	60	Portugal	PRT

Source: Prepared by the authors based on OECD (2023).

and

Table A2. Sectoral coverage of inter-country input-output tables.

Code	Sector	Code	Sector
A01_02	Agriculture, hunting, forestry	D	Electricity, gas, steam and air conditioning supply
A03	Fishing and aquaculture	E	Water supply; sewerage, waste management and remediation activities
B05_06	Mining and quarrying, energy producing products	F	Construction
B07_08	Mining and quarrying, non-energy producing products	G	Wholesale and retail trade; repair of motor vehicles
B09	Mining support service activities	H49	Land transport and transport via pipelines
C10T12	Food products, beverages and tobacco	H50	Water transport
C13T15	Textiles, textile products, leather and footwear	H51	Air transport
C16	Wood and products of wood and cork	H52	Warehousing and support activities for transportation
C17_18	Paper products and printing	H53	Postal and courier activities
C19	Coke and refined petroleum products	I	Accommodation and food service activities
C20	Chemical and chemical products	J58T60	Publishing, audiovisual and broadcasting activities
C21	Pharmaceuticals, medicinal chemical and botanical products	J61	Telecommunications
C22	Rubber and plastics products	J62_63	IT and other information services
C23	Other non-metallic mineral products	K	Financial and insurance activities
C24	Basic metals	L	Real estate activities
C25	Fabricated metal products	M	Professional, scientific and technical activities
C26	Computer, electronic and optical equipment	N	Administrative and support services
C27	Electrical equipment	O	Public administration and defence; compulsory social security
C28	Machinery and equipment, nec	P	Education
C29	Motor vehicles, trailers and semi-trailers	Q	Human health and social work activities
C30	Other transport equipment	R	Arts, entertainment and recreation
C31T33	Manufacturing nec; repair and installation of machinery and equipment	S	Other service activities
T	Activities of households as employers; undifferentiated goods- and services-producing activities of households for own use

Source: Prepared by the authors based on OECD (2023).

). The analysis ends in 2020 because the OECD Inter-Country Input–Output tables available at the time this study was conducted provide benchmark years up to 2020.

2.3. Methodological Limitations and Scope of Interpretation

While the combined MRIO–linkage framework is well suited to describing patterns of GVC participation and intersectoral production linkages, several methodological limitations should be acknowledged when interpreting the results (Miller & Blair, 2009; Wiedmann, 2009; Wiedmann et al., 2011).

First, the MRIO approach is inherently descriptive and static. It relies on fixed technical coefficients and linear production relationships, capturing average intersectoral dependencies at each point in time (Miller & Blair, 2009). As a result, the analysis does not identify causal mechanisms underlying changes in GVC participation or sectoral roles, nor does it capture firms’ strategic behavior, price dynamics, or governance structures within value chains. The findings should therefore be interpreted as evidence of structural patterns and associations, rather than as estimates of causal effects.

Second, the classification of sectoral roles based on weighted forward and backward linkages depends on relative thresholds derived from national averages (Wiedmann, 2009; Wiedmann et al., 2011). Although this methodology provides a transparent and internally consistent basis for identifying key, driver, strategic, and non-key sectors, classifications may be sensitive to marginal variations around these thresholds. Consequently, observed changes in sectoral roles—particularly those occurring over short subperiods or involving small deviations—should be interpreted with caution.

Third, the typology of GVC participation based on sectoral DVA and FVA shares relative to world averages offers a useful comparative benchmark but does not capture qualitative dimensions of integration, such as learning processes, technological upgrading, or the nature of governance relations within specific chains. High levels of participation may therefore coexist with limited domestic capability building.

Despite these limitations, the uniform application of the MRIO–linkage framework over the period 1995–2020 provides a coherent basis for identifying long-run patterns of structural persistence, sectoral concentration, and a limited number of non-generalized transitions in the Mexican economy. The policy implications discussed in the final section are intended to be consistent with these empirical patterns, rather than to establish causal claims.

3. Results and Discussion

The Mexican economy held a prominent position in the expansion of GVCs over the period 1995–2020 (See Appendix A 

Table A3. Forward Participation by Country in Global Value Chains, 1995–2020.

1995		1998		2000		2003		2005		2008		2010		2013		2015		2018		2020
CYP	25.1	BGD	20.7	BGD	19.3	BGD	18.6	BGD	20.7	MLT	16.4	MLT	16.4	MLT	12.1	MLT	13.4	MLT	15.5	MLT	15.6
KHM	25.6	HRV	24.5	HUN	24.1	KHM	23.2	MLT	22.4	BGD	19.8	BGD	19.4	BGD	17.5	BGD	16.7	BGD	17.5	LUX	17.1
MLT	25.8	MLT	25.7	KHM	24.6	MLT	25.2	KHM	22.4	KHM	22.2	KHM	19.8	KHM	20.9	LUX	21.2	LUX	18.6	BGD	19.9
BGD	26.1	CYP	27.4	MLT	26.5	JOR	25.7	JOR	22.7	LUX	24.6	LUX	24.5	LUX	21.0	KHM	22.4	JOR	21.7	JOR	24.3
TUN	26.3	TUN	27.5	HRV	26.5	HRV	27.6	LUX	25.4	JOR	25.0	JOR	25.4	JOR	25.9	JOR	24.9	KHM	24.8	KHM	25.5
JOR	27.0	HUN	27.7	JOR	27.5	HUN	27.8	HUN	27.5	HUN	27.1	HUN	26.7	HKG	26.9	VNM	28.5	CYP	25.4	CYP	26.9
HRV	29.5	KHM	27.8	CYP	27.8	TUN	28.9	HRV	28.8	BGR	28.3	BLR	27.6	THA	27.9	THA	28.6	HRV	27.1	VNM	27.3
GRC	30.2	JOR	28.3	TUN	28.2	BLR	29.8	THA	30.1	BLR	28.9	VNM	27.9	IRL	28.5	HUN	28.6	VNM	27.2	SVK	28.3
HUN	31.1	GRC	28.8	LUX	29.1	LUX	30.5	BLR	30.7	HRV	29.0	IRL	28.6	HUN	28.9	SVK	29.0	HKG	27.3	HUN	29.7
SGP	31.4	BLR	29.9	BLR	30.1	CYP	31.0	SGP	31.3	IRL	29.0	HRV	29.6	SVK	29.0	CYP	29.6	GRC	27.6	TUN	31.2
THA	31.5	PHL	31.5	THA	30.2	GRC	31.3	IRL	31.4	VNM	29.0	THA	29.8	CYP	29.1	IRL	29.7	SVK	28.3	IRL	31.4
IRL	31.9	IRL	31.9	GRC	30.2	IRL	31.3	TUN	31.9	THA	30.2	SVK	30.3	HRV	29.2	HKG	29.8	THA	28.5	SGP	33.1
SVN	32.3	THA	32.4	SGP	31.5	THA	31.7	GRC	32.0	SGP	30.6	HKG	31.5	BLR	29.8	HRV	29.8	HUN	30.2	CZE	33.4
MYS	33.0	MYS	32.4	MAR	31.6	TUR	32.4	VNM	32.4	SVK	30.6	BGR	31.6	SGP	29.9	GRC	31.0	ISL	30.2	GRC	33.8
PRT	33.6	LUX	32.7	IRL	32.2	MAR	33.3	BGR	32.6	HKG	31.3	SGP	31.7	VNM	30.1	CZE	32.2	BLR	30.9	MEX	34.6
MAR	33.9	PRT	32.8	CRI	32.4	SVK	33.7	SVN	33.0	CRI	32.1	CZE	31.7	BGR	30.7	TUN	32.3	TUN	31.2	BLR	34.9
HKG	34.1	SVN	32.8	SVN	33.3	VNM	34.0	SVK	33.1	KOR	33.2	CYP	32.7	GRC	31.3	SGP	32.6	IRL	31.4	THA	35.0
EST	34.2	LTU	33.6	PRT	33.8	CRI	34.1	CRI	33.2	SVN	33.7	SVN	33.4	CZE	31.3	BLR	32.7	PRT	31.6	DNK	35.1
LTU	35.5	MAR	33.9	MYS	34.0	PRT	34.5	TUR	33.5	CZE	34.0	TWN	33.5	PRT	33.5	BGR	33.0	SGP	32.0	BGR	36.5
TUR	35.8	EST	34.6	BGR	34.6	CHN	34.7	MAR	33.8	GRC	34.1	KOR	33.7	TUN	34.2	PRT	33.1	CZE	32.1	ISL	36.6
ISL	36.5	SGP	35.8	ESP	35.4	SVN	34.8	CYP	34.1	TWN	34.7	GRC	33.7	ISL	34.2	ISL	33.3	BGR	32.7	PRT	37.0
CRI	36.5	CRI	35.8	VNM	35.6	BGR	34.8	CZE	34.3	TUR	34.7	TUN	34.5	SVN	34.3	MEX	33.8	CRI	33.7	MAR	37.8
ITA	36.6	ESP	35.8	KOR	35.8	SGP	35.5	ISL	34.3	LTU	35.7	CRI	34.5	EST	35.2	CRI	35.6	MEX	33.8	HKG	37.8
PHL	36.6	BGR	35.9	CHN	36.4	KOR	36.3	CHN	34.5	ITA	35.8	TUR	34.7	CRI	35.2	SVN	35.7	SVN	34.7	SVN	38.0
KOR	36.7	MEX	36.1	TUR	36.6	ESP	36.3	PRT	35.5	ESP	36.0	PRT	35.2	KOR	35.3	DNK	35.9	MAR	34.8	HRV	38.4
ESP	36.9	SVK	36.5	ITA	36.8	MEX	36.3	ESP	35.6	PRT	36.2	ITA	35.7	CHN	35.7	MAR	36.0	DNK	34.9	TUR	38.4
ISR	37.3	HKG	37.1	SVK	37.1	ISL	37.0	HKG	35.9	CYP	36.3	CHN	36.4	MAR	35.9	TUR	36.0	ESP	36.6	CRI	38.5
SVK	37.4	KOR	37.2	PHL	37.1	NZL	37.2	MYS	36.6	CHN	36.3	LTU	36.6	TUR	36.1	ITA	36.4	TUR	36.9	CHE	38.9
DNK	37.6	ITA	37.2	MEX	37.5	PHL	37.3	TWN	36.9	TUN	36.4	ESP	36.7	LTU	36.2	EST	37.0	ITA	37.4	PAK	39.2
LUX	37.9	DNK	37.3	TWN	37.5	ITA	37.6	NZL	37.1	ISR	36.9	DNK	37.3	DNK	36.2	ESP	37.3	CHE	38.0	POL	39.3
TWN	37.9	TUR	37.6	HKG	37.5	TWN	37.7	KOR	37.4	DNK	37.5	EST	37.7	ESP	36.5	CHN	38.0	POL	38.4	EST	39.7
POL	38.0	ISL	37.7	ISL	37.5	MYS	38.0	ISR	37.5	NZL	37.5	MEX	37.7	ITA	36.9	NZL	38.2	CHN	38.6	CHN	39.8
CHN	38.1	VNM	37.8	ISR	38.2	LTU	38.7	ITA	37.5	POL	38.1	SEN	37.8	TWN	36.9	LTU	38.3	NZL	38.8	ITA	39.9
VNM	38.3	ISR	38.0	LTU	38.7	CZE	39.1	EST	38.5	MAR	38.2	ISR	38.0	POL	38.1	KOR	39.3	BEL	39.1	BEL	40.0
MEX	39.4	CHN	38.0	FRA	38.9	DNK	39.2	LTU	38.6	SEN	38.4	NZL	38.4	SEN	38.2	POL	39.6	FRA	39.1	ESP	40.5
ROU	39.5	TWN	38.8	NZL	39.2	HKG	39.4	FRA	39.2	PAK	38.6	MAR	38.4	BEL	38.9	AUT	40.1	EST	39.2	AUT	40.6
BEL	39.8	BEL	39.3	BEL	39.2	FRA	39.4	PAK	39.2	CHE	38.6	FRA	38.4	AUT	39.1	CHE	40.1	LTU	39.2	FRA	41.3
AUT	40.1	POL	39.3	DNK	39.2	ISR	39.5	PHL	39.4	FRA	38.6	MYS	38.4	MEX	39.1	TWN	40.1	TWN	39.2	LTU	41.5
FRA	40.8	LAO	39.4	EST	39.5	POL	40.3	MEX	39.5	BEL	38.8	POL	38.7	CHE	39.1	FRA	40.1	AUT	39.7	ROU	41.7
CZE	41.1	CZE	39.7	UKR	40.0	PAK	40.5	DNK	39.7	MYS	39.1	CHE	39.3	FRA	39.2	DEU	40.7	PAK	39.9	NLD	41.7
BLR	41.4	FRA	39.8	CZE	40.5	EST	41.1	LAO	39.9	ISL	39.1	AUT	39.7	IND	39.3	IND	40.8	KOR	40.3	NZL	42.3
CHE	41.6	ROU	40.2	PAK	40.8	UKR	41.2	CHE	40.1	FIN	39.9	ISL	39.8	ISR	39.9	PAK	40.9	ROU	40.3	DEU	42.4
LAO	41.8	NZL	40.3	AUT	41.2	CHE	41.4	AUT	40.6	EST	39.9	PAK	40.2	DEU	40.4	MYS	41.0	MYS	40.5	IND	42.4
PAK	42.4	AUT	40.5	CHE	41.6	AUT	41.6	BEL	40.7	SWE	40.2	BEL	40.3	NZL	40.5	BEL	41.4	NLD	40.7	KOR	42.9
UKR	42.4	CAN	41.2	POL	41.7	BEL	41.6	POL	40.8	AUT	40.7	DEU	40.6	UKR	41.3	ISR	41.5	DEU	40.9	SWE	43.6
SWE	42.9	CHE	41.3	DEU	42.1	SWE	42.8	SWE	40.8	DEU	41.0	ROU	41.2	MYS	41.8	UKR	41.8	IND	40.9	TWN	43.8
NZL	43.1	UKR	41.6	SWE	42.4	SEN	43.1	UKR	41.3	MEX	41.5	IND	41.4	FIN	41.9	ROU	42.1	ISR	41.8	MYS	44.0
NLD	43.2	SWE	42.0	IND	42.7	DEU	43.2	FIN	41.9	UKR	41.6	LAO	41.5	PAK	42.2	NLD	42.5	SWE	42.3	ARG	44.1
MMR	43.2	PAK	42.4	NLD	42.8	IND	44.1	DEU	42.4	IND	42.4	UKR	42.2	ROU	42.7	SEN	43.3	PHL	42.7	FIN	44.8
USA	43.8	DEU	43.0	CAN	42.9	ROU	44.5	ROU	44.0	ROU	42.4	FIN	42.4	ARG	42.9	LVA	43.5	UKR	43.2	ISR	45.1
DEU	43.8	NLD	43.8	ROU	44.6	NLD	44.8	SEN	44.1	PHL	44.4	SWE	43.2	LVA	42.9	ARG	45.0	ARG	43.3	UKR	46.1
IND	44.5	IND	44.1	FIN	45.1	FIN	44.9	IND	44.1	NLD	44.9	ARG	43.3	LAO	43.4	SWE	45.1	LVA	44.3	LVA	46.8
CAN	44.5	USA	44.3	USA	45.2	LAO	45.8	NLD	44.2	ARG	45.3	PHL	43.7	NLD	44.0	FIN	46.1	FIN	44.8	PHL	47.2
BGR	45.0	LVA	45.5	LAO	45.7	CAN	45.9	USA	46.8	USA	45.8	NLD	44.9	SWE	44.8	PHL	46.5	SEN	44.8	MMR	47.3
SEN	46.0	GBR	45.6	SEN	45.9	BRA	46.9	ARG	46.9	LAO	45.9	EGY	45.7	GBR	46.4	CAN	46.8	EGY	45.1	CAN	47.4
GBR	46.1	FIN	45.8	BRA	46.9	USA	47.1	JPN	47.5	JPN	46.4	LVA	46.5	USA	47.1	GBR	47.2	MMR	45.2	ZAF	49.0
ARG	46.8	ARG	46.0	MMR	47.1	GBR	48.6	BRA	47.9	LVA	46.9	USA	46.7	PHL	47.2	JPN	47.5	ZAF	46.1	GBR	50.3
JPN	47.5	SEN	46.1	GBR	48.2	JPN	49.0	LVA	48.4	GBR	48.9	JPN	47.7	JPN	47.6	USA	47.7	GBR	46.3	JPN	50.3
FIN	47.9	MMR	46.1	ARG	48.3	ARG	49.9	GBR	48.4	BRA	50.6	GBR	47.7	BRA	50.8	MMR	47.8	JPN	46.8	SEN	51.2
BRA	48.9	BRA	48.0	JPN	48.9	LVA	50.1	CAN	48.4	CIV	50.8	CIV	48.8	CAN	51.0	EGY	48.5	CAN	47.3	EGY	52.3
EGY	49.4	JPN	48.5	LVA	49.9	EGY	50.7	CIV	50.1	EGY	52.5	CAN	50.3	ZAF	53.5	LAO	48.5	USA	48.3	USA	52.3
LVA	51.4	IDN	51.9	AUS	52.0	MMR	51.9	EGY	51.0	ZAF	53.7	BRA	52.0	EGY	53.6	BRA	49.9	BRA	52.5	BRA	54.2
AUS	53.2	CIV	52.2	CIV	53.7	CIV	52.0	MMR	52.8	CAN	53.9	MMR	55.8	MMR	54.6	ZAF	51.5	IDN	53.5	LAO	55.4
CIV	53.8	AUS	53.0	EGY	54.4	AUS	52.1	AUS	56.2	MMR	55.9	ZAF	58.0	CIV	55.2	CIV	54.7	CIV	55.3	IDN	56.1
IDN	56.2	EGY	54.6	IDN	54.8	IDN	55.8	IDN	56.8	IDN	57.7	CMR	58.4	IDN	58.7	IDN	55.4	LAO	56.0	CIV	57.5
CMR	59.4	NOR	56.7	COL	57.9	ZAF	57.2	ZAF	57.1	CHL	58.5	IDN	60.2	CMR	59.4	CMR	58.2	CMR	59.5	CMR	59.4
NOR	60.4	CHL	58.4	ZAF	59.0	COL	57.4	COL	58.9	AUS	60.3	AUS	61.6	PER	62.7	AUS	60.9	COL	63.1	COL	59.7
RUS	60.8	ZAF	58.8	CHL	60.7	CMR	60.0	CMR	59.7	PER	60.6	PER	64.4	CHL	62.8	COL	62.3	PER	64.0	NOR	63.5
ZAF	61.0	CMR	60.5	CMR	62.4	CHL	60.4	CHL	62.9	CMR	60.6	CHL	65.6	AUS	64.0	PER	62.5	AUS	64.9	CHL	68.0
CHL	61.2	RUS	60.6	RUS	63.2	NOR	64.4	PER	65.2	COL	61.6	RUS	66.4	RUS	65.2	NOR	64.0	NOR	65.0	AUS	69.2
PER	61.6	PER	61.0	PER	63.4	RUS	64.5	RUS	67.1	RUS	66.4	COL	66.8	NOR	69.3	CHL	64.5	CHL	65.2	RUS	69.7
COL	62.5	COL	61.9	KAZ	64.9	PER	64.6	NOR	68.6	NOR	68.8	NOR	68.1	COL	70.4	RUS	65.7	RUS	69.4	PER	69.9
KAZ	65.1	KAZ	70.6	NOR	66.7	KAZ	66.6	KAZ	70.1	KAZ	70.9	KAZ	71.2	KAZ	72.3	KAZ	72.1	KAZ	70.8	KAZ	71.8
BRN	83.1	NGA	82.9	NGA	85.7	NGA	83.8	BRN	87.2	SAU	85.1	NGA	84.4	BRN	82.6	BRN	80.5	SAU	81.9	BRN	74.4
NGA	83.8	SAU	84.5	SAU	87.2	SAU	86.6	NGA	87.6	NGA	85.8	BRN	87.2	NGA	85.5	SAU	83.6	BRN	83.3	NGA	83.6
SAU	86.3	BRN	85.8	BRN	87.5	BRN	87.7	SAU	87.9	BRN	87.2	SAU	87.5	SAU	88.3	NGA	84.6	NGA	83.5	SAU	83.6
RoW	60.3	RoW	57.6	RoW	63.7	RoW	63.1	RoW	66.3	RoW	69.9	RoW	69.4	RoW	69.9	RoW	63.9	RoW	65.3	RoW	66.3

Source: Own elaboration.

and

Table A4. Backward Participation by Country in Global Value Chains, 1995–2020.

1995		1998		2000		2003		2005		2008		2010		2013		2015		2018		2020
NGA	13.8	LUX	20.8	NGA	7.8	NGA	15.4	NGA	9.7	NGA	7.5	BRN	12.0	NGA	16.2	BRN	23.2	SAU	20.7	IRL	26.6
SAU	19.5	SAU	21.2	BRN	17.3	SAU	15.4	SAU	10.7	BRN	8.9	NGA	12.9	BRN	16.5	NGA	24.1	BRN	23.5	SAU	27.2
LUX	21.1	NGA	21.6	RUS	17.3	BRN	15.7	BRN	10.7	SAU	13.8	SAU	18.7	SAU	18.4	TWN	28.9	NGA	26.1	SGP	28.4
BRN	24.2	RUS	24.5	SAU	17.4	ARG	23.1	MMR	21.8	KAZ	18.2	NOR	28.1	NOR	27.4	SGP	29.2	RUS	27.2	CHL	30.2
BGR	26.6	BGR	29.9	NOR	22.6	RUS	23.8	RUS	21.8	NOR	22.8	CHL	28.9	CHE	31.3	RUS	29.3	IRL	27.4	BRN	30.3
RUS	28.1	BRN	30.4	LUX	23.0	LUX	25.2	NOR	22.1	RUS	27.8	RUS	29.3	TWN	31.9	CHE	30.8	SGP	28.2	SVN	30.4
CMR	28.8	SGP	32.6	KAZ	28.1	NOR	25.7	KAZ	25.0	MMR	29.8	SGP	30.2	RUS	31.9	SAU	30.9	CHE	31.1	TWN	30.6
CHL	32.3	IDN	33.6	IDN	34.1	KAZ	28.3	SGP	27.2	SGP	31.0	LUX	30.2	CIV	32.5	IRL	31.1	SVN	31.5	AUS	32.3
NOR	32.6	MYS	34.1	MYS	34.8	SGP	29.6	LUX	28.9	CHE	31.8	CHE	31.4	SGP	32.7	SVN	32.2	TWN	31.8	CHE	34.0
IRL	33.7	THA	34.4	CHE	34.9	CIV	30.4	CHL	30.6	LUX	31.9	KAZ	32.3	KAZ	33.5	LUX	32.5	NOR	31.9	LTU	34.9
MLT	34.9	CIV	34.7	CIV	35.5	MYS	32.1	PER	32.5	MYS	32.0	CIV	32.5	SVK	33.8	CYP	32.6	CYP	33.3	BLR	35.5
SGP	35.6	IRL	34.9	CHL	35.8	CHE	35.0	CIV	32.9	TWN	34.2	ISL	32.9	IRL	34.3	NOR	33.1	AUS	33.6	RUS	35.9
NLD	35.8	CMR	35.2	FIN	35.9	TWN	35.7	ARG	33.2	CIV	34.4	PER	34.1	LTU	34.4	DEU	34.3	BGR	35.2	CRI	36.1
CIV	35.9	FIN	35.4	IRL	36.2	CHL	36.2	MYS	33.2	CHL	35.7	TWN	34.3	LUX	34.6	ISL	35.3	BLR	35.4	DEU	36.6
CHE	36.0	SWE	35.6	SWE	36.5	FIN	36.3	TWN	34.2	AUT	35.7	MYS	35.5	SVN	34.7	CHL	35.4	AUT	35.5	PER	36.6
FIN	36.1	MLT	36.1	DNK	36.5	IRL	36.3	CHE	34.4	DEU	36.2	AUT	36.3	BGR	35.1	AUT	35.7	CHL	35.7	ARG	36.9
SWE	37.2	CHE	36.1	MLT	37.3	HKG	36.5	BLR	34.7	NLD	37.0	DEU	36.3	ISL	35.2	BLR	36.0	DEU	35.7	POL	37.4
KAZ	38.2	KAZ	36.4	NLD	37.3	DNK	36.7	DEU	35.9	SWE	37.0	IRL	36.8	CYP	36.1	SVK	36.7	PER	36.1	BGR	37.4
DNK	38.8	KOR	36.5	SGP	37.5	DEU	36.7	HKG	36.3	ARG	37.4	SVK	36.9	DEU	36.3	SWE	36.9	CRI	37.2	CYP	37.5
BEL	38.8	NLD	37.0	AUT	37.5	SWE	36.7	NLD	36.5	SVK	37.9	EST	37.4	BLR	36.6	LTU	38.2	LVA	38.2	AUT	37.6
CAN	39.7	NOR	37.1	ARG	38.3	AUT	37.4	AUT	36.7	CAN	38.2	SWE	37.9	MYS	37.2	BGR	38.2	SVK	38.3	LVA	37.6
MYS	40.6	DEU	38.8	CAN	38.4	NLD	37.5	SWE	36.8	BLR	38.3	LTU	38.3	CHL	37.2	NLD	38.3	LTU	38.3	NLD	37.7
DEU	40.7	BEL	39.2	NZL	38.7	MMR	37.5	BEL	37.2	PER	38.9	DNK	38.9	NLD	37.5	CIV	38.5	NLD	38.3	ZAF	38.1
AUT	40.7	AUT	39.3	TWN	39.0	BEL	37.7	IRL	38.0	BEL	39.1	SVN	39.0	AUT	37.7	LVA	38.5	KAZ	38.4	CZE	38.6
NZL	40.8	CHL	39.5	BEL	39.1	IDN	37.8	EGY	38.4	HKG	39.1	NLD	39.4	SWE	37.8	EST	38.7	LUX	38.5	ISR	38.8
ITA	40.8	NZL	39.7	HKG	39.6	EGY	38.6	SVK	38.5	IRL	41.0	ARG	40.0	LVA	39.2	CZE	38.7	EST	39.1	SWE	38.9
ARG	41.1	TUR	40.1	CYP	39.7	MLT	39.0	CAN	39.4	SVN	41.0	LVA	40.1	PER	39.4	CRI	38.8	SWE	39.5	DNK	39.5
POL	42.3	FRA	40.3	CMR	40.1	BLR	39.1	FIN	40.5	AUS	41.2	AUS	40.2	DNK	40.0	MYS	39.1	ISL	39.5	LUX	39.5
ISL	42.3	DNK	40.4	ZAF	40.5	NZL	39.2	BRA	40.9	DNK	41.6	BEL	40.2	CZE	40.1	HUN	39.8	CZE	39.8	EST	40.4
ZAF	42.3	CAN	40.9	THA	40.7	CAN	39.9	CYP	41.2	FIN	41.9	NZL	40.5	EST	40.1	AUS	40.3	POL	40.2	BEL	40.5
TWN	42.5	ITA	40.9	DEU	41.7	SVK	40.3	DNK	41.2	EST	42.1	CYP	41.0	AUS	40.2	DNK	40.3	DNK	40.3	MEX	40.7
SVK	42.7	ZAF	41.1	SVK	41.9	CYP	41.6	SVN	41.3	EGY	42.2	EGY	41.1	HUN	40.3	NZL	40.7	MYS	40.5	SVK	40.7
GBR	43.4	TWN	41.1	PHL	42.2	SVN	41.7	CZE	41.6	CZE	43.1	BGR	41.3	NZL	41.2	ISR	40.8	BEL	41.4	MYS	41.3
MEX	43.5	JPN	41.6	CRI	42.5	FRA	42.9	CRI	43.4	ISL	43.5	HKG	41.4	BEL	41.6	BEL	41.0	HUN	41.5	ITA	41.5
FRA	43.8	CRI	42.3	UKR	43.0	CRI	43.0	NZL	43.5	NZL	43.6	MMR	41.5	POL	41.9	POL	41.2	NZL	41.8	HUN	42.1
JPN	44.1	CYP	42.5	AUS	43.1	THA	43.3	IDN	44.1	HUN	44.5	HUN	41.7	ESP	42.0	ESP	41.6	ESP	41.9	NGA	43.2
AUS	44.6	AUS	43.5	BLR	43.5	ZAF	43.4	TUN	44.4	ZAF	45.1	MLT	42.4	ROU	42.3	HKG	41.7	LAO	42.1	CIV	43.5
IDN	44.7	HKG	43.6	JPN	43.6	PER	43.5	CMR	44.5	CMR	45.2	CZE	42.6	HKG	44.2	THA	42.2	HKG	42.2	NOR	43.9
CRI	44.8	GBR	43.7	FRA	43.7	BRA	45.1	FRA	45.8	CHN	45.3	ZAF	43.0	CRI	44.4	PER	42.5	THA	42.8	LAO	44.8
BLR	45.2	ISL	44.6	SVN	44.5	JPN	45.4	AUS	46.3	LTU	45.3	CRI	44.3	ISR	44.6	HRV	43.0	ISR	43.2	BRA	45.0
EGY	45.4	SVN	45.3	GBR	44.9	GBR	45.6	EST	46.3	TUN	45.7	PHL	44.6	MEX	44.8	KOR	43.7	KHM	43.6	KHM	45.1
TUR	45.5	BLR	45.9	EST	45.3	CMR	45.6	HUN	46.8	GBR	46.3	CAN	45.9	EGY	45.0	UKR	44.1	ROU	44.3	THA	45.2
CYP	46.2	CHN	46.9	CZE	46.0	AUS	47.3	PHL	46.8	PHL	46.8	FIN	46.2	CAN	45.5	ROU	44.2	ITA	44.4	NZL	45.2
SVN	46.2	HUN	47.4	ITA	47.8	PAK	47.6	GBR	46.9	IDN	47.3	GBR	46.3	CMR	45.6	ITA	44.3	CIV	45.0	GBR	45.5
HUN	46.6	CZE	47.4	ISR	48.9	EST	47.7	ZAF	47.2	THA	48.7	IDN	46.7	PRT	47.5	PRT	45.4	KOR	45.0	ESP	45.6
EST	47.3	EST	47.8	KOR	49.0	ISL	47.7	LTU	47.3	MEX	48.9	TUN	47.0	HRV	47.6	GBR	45.6	PRT	45.0	HKG	45.7
CZE	47.9	ARG	48.0	TUN	49.1	PHL	48.2	POL	48.2	MLT	49.1	POL	47.3	ITA	47.8	CAN	45.9	MEX	45.2	MMR	45.9
HKG	48.0	TUN	48.1	HUN	49.1	UKR	48.6	CHN	48.9	CYP	49.2	THA	48.1	KOR	48.4	GRC	46.5	CAN	45.2	ISL	46.4
USA	49.4	USA	49.8	VNM	50.3	HUN	48.9	THA	49.4	FRA	49.4	ISR	48.5	ARG	48.4	MEX	46.7	ZAF	45.5	KOR	46.8
TUN	50.5	ESP	49.9	ISL	50.5	ITA	48.9	JPN	49.5	LVA	50.4	MEX	49.2	GBR	48.6	KAZ	47.3	GBR	45.8	UKR	47.0
THA	50.5	PAK	50.1	PER	51.1	TUN	49.0	UKR	49.6	KHM	50.7	BLR	49.5	COL	48.7	LAO	47.6	EGY	45.9	CAN	47.9
PAK	53.5	SVK	50.6	PAK	51.2	LTU	49.2	ISR	50.0	CRI	51.7	COL	49.7	KHM	48.9	CHN	47.7	HRV	46.6	IDN	49.0
ROU	54.2	PHL	51.6	LVA	51.4	POL	49.8	VNM	50.0	POL	51.8	CHN	50.4	FIN	49.1	CMR	47.8	BRA	47.3	ROU	49.3
ESP	54.4	LAO	51.9	BGR	52.2	CZE	49.9	MEX	50.3	BRA	52.2	ESP	50.8	PHL	49.3	PHL	48.2	GRC	47.7	CMR	49.9
LVA	54.9	LVA	53.0	EGY	52.4	VNM	50.7	MLT	50.9	ITA	53.1	HRV	51.2	VNM	49.8	FRA	48.2	CMR	47.8	KAZ	50.1
PHL	55.2	ISR	53.6	COL	52.7	MAR	50.8	ITA	51.0	ISR	53.4	KOR	51.7	ZAF	50.4	KHM	48.6	ARG	48.2	VNM	50.4
KOR	55.4	MEX	54.1	LTU	53.3	ISR	51.1	KOR	51.6	KOR	54.3	CMR	51.8	THA	50.5	FIN	49.9	FRA	49.2	FRA	50.9
CHN	56.1	VNM	54.4	MEX	53.9	KOR	52.2	HRV	53.1	COL	54.5	FRA	52.5	FRA	51.0	USA	50.2	MLT	50.1	MAR	51.6
UKR	57.3	POL	55.3	TUR	54.0	LAO	52.9	KHM	53.1	BGR	55.7	JPN	52.5	GRC	52.0	IDN	50.5	TUN	50.3	PRT	51.8
BRA	58.2	MAR	55.6	HRV	54.3	CHN	52.9	LVA	54.9	MAR	56.6	KHM	52.7	TUN	52.3	MLT	51.4	UKR	50.8	FIN	51.9
MAR	59.7	SEN	55.7	MMR	54.4	MEX	53.7	MAR	55.5	VNM	57.0	MAR	53.7	IDN	52.4	ZAF	52.0	MMR	51.0	CHN	52.0
SEN	59.9	UKR	56.2	CHN	54.7	TUR	54.8	COL	57.4	LAO	57.0	VNM	54.6	USA	53.8	VNM	52.5	VNM	51.1	TUN	53.6
PER	62.0	EGY	58.4	ESP	55.4	ESP	55.2	LAO	57.4	JPN	57.7	ITA	55.1	MLT	54.0	ARG	52.6	FIN	51.3	IND	54.0
LTU	62.9	LTU	58.9	KHM	57.0	KHM	55.5	BGR	58.1	HRV	58.7	UKR	55.6	CHN	55.6	JPN	54.5	USA	51.3	HRV	54.1
IND	63.2	COL	59.1	USA	57.5	BGR	56.5	TUR	60.4	TUR	60.8	BRA	57.3	LAO	55.8	TUN	55.2	IDN	52.1	GRC	54.1
PRT	64.4	ROU	61.3	POL	57.5	LVA	57.1	ESP	60.8	ESP	61.1	USA	58.7	UKR	55.9	MAR	55.4	MAR	52.3	USA	55.0
LAO	65.2	HRV	61.4	LAO	58.9	HRV	57.4	ISL	62.3	UKR	63.3	ROU	58.9	MMR	58.9	BRA	55.9	JPN	53.8	MLT	55.3
VNM	65.3	PER	61.9	MAR	59.6	PRT	60.6	GRC	63.0	ROU	64.3	LAO	60.9	MAR	59.2	EGY	56.5	CHN	55.1	JPN	55.5
KHM	66.9	BRA	64.4	ROU	60.2	COL	61.3	BGD	63.7	PRT	66.1	GRC	61.1	BRA	61.8	MMR	56.7	TUR	55.3	PHL	57.8
ISR	67.2	PRT	64.8	BRA	61.8	ROU	62.8	PRT	65.5	BGD	66.8	PRT	62.6	IND	63.2	IND	57.4	PHL	55.4	EGY	58.6
COL	68.2	IND	65.9	GRC	65.4	IND	63.0	IND	66.9	GRC	67.3	BGD	66.1	JPN	66.1	COL	61.1	COL	57.0	TUR	59.8
JOR	69.3	KHM	69.3	BGD	66.9	USA	64.1	PAK	67.6	USA	68.8	TUR	66.1	TUR	66.5	BGD	69.3	IND	60.0	COL	67.0
HRV	72.0	BGD	70.3	PRT	67.4	BGD	65.6	ROU	67.7	IND	71.8	JOR	68.0	BGD	67.0	TUR	69.5	BGD	76.1	BGD	75.5
BGD	80.1	JOR	70.5	IND	67.4	JOR	71.6	USA	72.1	JOR	75.8	IND	73.2	PAK	83.5	SEN	76.5	SEN	79.5	JOR	82.8
GRC	81.0	GRC	76.6	JOR	82.3	GRC	73.1	SEN	85.4	PAK	90.9	PAK	73.9	JOR	85.3	JOR	80.1	JOR	83.0	SEN	83.9
MMR	109.9	MMR	92.6	SEN	85.1	SEN	88.3	JOR	92.3	SEN	99.3	SEN	86.5	SEN	85.5	PAK	84.5	PAK	115.0	PAK	102.2
RoW	42.9	RoW	46.8	RoW	31.6	RoW	34.8	RoW	32.3	RoW	31.7	RoW	33.5	RoW	34.2	RoW	43.7	RoW	38.8	RoW	50.8

Source: Own elaboration.

). The FVA share increased from 43.5% in 1995 to 53.9% in 2000, declined to 50.3% in 2005, and displayed subsequent fluctuations, reaching a low of 40.7% by 2020. By contrast, the DVA share decreased from 39.4% in 1995 to 37.5% in 2000, recovered to levels close to its initial value in 2005 (39.5%), and fell to 34.6% at the end of the period.

In comparative terms, considering a sample of 76 countries and average values over the period 1995–2020, Mexico registered a higher DVA share than the global average (48.3% versus 44.6%), while its FVA share was 7.2 percentage points below the corresponding world average (See

Table 3. Mexico’s Position in Global Value Chains, 1995–2020.

	World		Mexico
	DVA (FVA) Participation	Change (%)	DVA Participation	Change (%)	FVA Participation	Change (%)
1995	44.0	--	39.4	--	43.5	--
1998	43.2	−0.6	36.1	−2.9	54.1	7.5
2000	44.4	1.4	37.5	1.9	53.9	−0.2
2003	44.7	0.2	36.3	−1.1	53.7	−0.1
2005	45.1	0.5	39.5	4.2	50.3	−3.2
2008	45.4	0.2	41.5	1.7	48.9	−1.0
2010	45.3	−0.2	37.7	−4.7	49.2	0.4
2013	45.3	0.0	39.1	1.2	44.8	−3.1
2015	44.0	−1.5	33.8	−7.0	46.7	2.0
2018	44.1	0.1	33.8	−0.0	45.2	−1.1
2020	45.4	1.4	34.6	1.3	40.7	−5.2
Average	44.6	0.2	37.2	−0.5	48.3	−0.4

Notes: (1) Domestic Value Added (DVA) refers to the portion of value added generated domestically and embodied in a country’s gross exports, expressed as a percentage of the total value added embodied in exports. (2) Foreign Value Added (FVA) refers to the portion of value added generated abroad and embodied in a country’s gross exports. Source: Own elaboration.

). Finally, between 2018 and 2020, Mexico experienced a sharper decline than the global average in its FVA share, with a reduction of 4.5 percentage points compared to a global decrease of 1.3 percentage points.

These findings are consistent with Vidal and Pandiella (2024), who demonstrate that Mexico ranks among the OECD countries with the highest levels of backward participation in GVCs. With respect to the evolution of integration, three contrasting phases can be identified over the period 1995–2017: an initial expansion following the entry into force of NAFTA (1995–2001); a deceleration coinciding with China’s growing prominence in the global economy (2001–2008); and a renewed, though uneven, expansion between 2008 and 2017 (Chiquiar & Tobal, 2019). During 2017–2020, Mexico’s level of integration declined more sharply than the global average, reflecting the effects of the first year of the COVID-19 pandemic. Finally, Pérez-Santillán and Arriaga Navarrete (2024) report that Mexico’s relative position within GVCs remained broadly unchanged between 1995 and 2018.

At the sectoral level, observed integration patterns correspond closely to the typology introduced in the methodology section: integration across multiple segments of the value chain, ranging from product design and development to input procurement and final assembly; dominant backward integration; dominant forward integration; and low integration, characterized by backward and forward participation shares persistently below global averages. A salient feature across these categories is the predominance of backward participation throughout the period, except for sectors classified under dominant forward integration (See Figure 1).

Integration across multiple GVCs segments averaged 8.0% in forward participation and 21.8% in backward participation over the period. This pattern is characteristic of activities such as motor vehicles, trailers, and semi-trailers; electronic, optical, and computer equipment; electrical equipment; basic metals; and land transportation services. These activities exhibit an intensive reliance on imported inputs, parts, and components for the processing and assembly of intermediate and/or final goods; however, they show marked heterogeneity in their backward and forward linkages. At one extreme, the automotive industry records the highest backward linkages, while basic metals manufacturing lies at the opposite end of the spectrum. In terms of forward linkages, land transportation services rank the highest, whereas electrical equipment manufacturing shows the weakest performance.

Within this category, the evolution of integration also diverges across activities. Motor vehicles, trailers, and semi-trailers show greater dynamism over time, whereas electronic, optical, and computer equipment—as well as electrical equipment—experience a relative slowdown in integration (See Figure 2).

These findings underscore the central role of the automotive industry in Mexico’s integration into GVCs, both through auto-parts manufacturing and automobile assembly. What remains uncertain, however, is the extent to which this industry has been able to drive the development of related sectors and to promote the integration of domestic suppliers into these chains (Hernández et al., 2014; Pérez-Santillán & Arriaga Navarrete, 2024). Nevertheless, its importance for domestic production, exports, and formal employment is indisputable (Chiquiar & Tobal, 2019). By contrast, this dynamism stands in sharp contrast to the trajectory of computer, electronic, and optical equipment manufacturing, whose contraction across production stages within GVCs has been associated with a strong dependence on imported inputs from China and other Asian economies (García González & Márquez Mendoza, 2025). Even so, De La Cruz et al. (2013) document increases in the domestic content of Mexico’s exports linked to strengthened backward linkages.

Complementarily, the manufacturing-oriented profile of Mexico’s GVCs integration (Pérez-Santillán & Arriaga Navarrete, 2024) is reflected in average participation rates of 10.2% in FVA and 3.7% in DVA. This group includes industries such as food, beverages, and tobacco; textiles, textile products, leather, and footwear; and chemicals and chemical products, among others. Support services for mining are also classified within this category (See Figure 3). Finally, land transportation and telecommunications exhibit notable dynamism in their integration—across multiple segments and under dominant backward integration, respectively—given their role in providing logistical connectivity and communication services that link geographically dispersed firms. This highlights the importance of physical and digital infrastructure as a key determinant of participation in global markets (Kaplinsky, 2000).

By contrast, dominant forward integration in GVCs characterizes sectors such as mining and quarrying, energy products, and trade, with average participation shares of 17.7% in DVA and 1.7% in FVA, respectively (See Figure 4). Low levels of GVCs integration are observed in other activities, including agriculture, livestock, forestry, and fishing; administrative and support services; and non-energy mining and quarrying, among others. These sectors consistently remain below global averages in both forward and backward participation throughout the period analyzed. Detailed sectoral results for forward and backward participation by integration category are reported in the Appendix A (See

Table A5. Mexico into GVCs: Forward Participation by Sector, 1995–2020. (DVA, % Total Gross Exports).

	1995	1998	2000	2003	2005	2008	2010	2013	2015	2018	2020
Total	39.45	36.14	37.51	36.31	39.46	41.46	37.68	39.06	33.77	33.76	34.64
Multi-Stage Integration	8.38	9.52	9.16	7.78	7.49	7.37	7.00	7.39	8.01	7.87	7.83
Basic metals	1.59	1.41	1.23	1.19	1.62	1.91	1.69	1.68	1.52	1.53	1.60
Computer, electronic and optical equipment	2.29	3.47	3.31	2.41	1.80	1.47	1.19	1.17	1.56	1.36	1.43
Electrical equipment	0.97	0.92	0.87	0.73	0.70	0.73	0.61	0.57	0.62	0.60	0.62
Motor vehicles, trailers and semi-trailers	1.40	1.56	1.54	1.42	1.34	1.34	1.50	1.84	2.27	2.44	2.36
Land transport and transport via pipelines	2.12	2.16	2.20	2.02	2.03	1.94	2.01	2.13	2.03	1.94	1.82
Dominant Backward Integration	4.84	4.41	3.93	3.81	3.61	3.61	3.44	3.62	3.40	3.11	3.16
Mining support service activities	0.05	0.04	0.06	0.14	0.14	0.13	0.12	0.13	0.07	0.08	0.12
Food products, beverages and tobacco	0.35	0.32	0.28	0.33	0.34	0.36	0.37	0.43	0.42	0.40	0.40
Textiles, textile products, leather and footwear	0.87	0.79	0.60	0.45	0.32	0.22	0.22	0.19	0.21	0.19	0.15
Paper products and printing	0.34	0.28	0.25	0.25	0.23	0.22	0.20	0.18	0.19	0.19	0.19
Chemical and chemical products	0.90	0.74	0.67	0.66	0.75	0.97	0.95	0.97	0.78	0.60	0.61
Rubber and plastics products	0.65	0.63	0.52	0.48	0.43	0.38	0.37	0.39	0.42	0.40	0.40
Other non-metallic mineral products	0.42	0.40	0.37	0.35	0.30	0.25	0.22	0.25	0.26	0.25	0.27
Fabricated metal products	0.63	0.64	0.60	0.56	0.61	0.64	0.56	0.55	0.54	0.53	0.55
Manufacturing; repair and installation 1	0.46	0.44	0.43	0.44	0.34	0.30	0.31	0.32	0.33	0.32	0.30
Telecommunications	0.16	0.14	0.14	0.15	0.16	0.13	0.12	0.21	0.18	0.15	0.17
Dominant Forward Integration	18.14	15.21	17.86	17.79	21.10	22.80	19.51	19.59	13.98	14.35	14.26
Mining and quarrying, energy producing products	9.11	6.17	8.75	9.17	12.15	13.75	10.85	10.16	4.22	4.26	4.03
Wholesale and retail trade; repair of motor vehicles	9.03	9.03	9.11	8.62	8.95	9.05	8.66	9.43	9.76	10.09	10.22
Low Integration	8.08	7.01	6.56	6.93	7.25	7.68	7.73	8.45	8.39	8.43	9.39
Agriculture, hunting, forestry	1.51	1.41	1.17	1.20	1.11	1.11	1.08	1.15	1.15	1.14	1.20
Fishing and aquaculture	0.04	0.04	0.04	0.04	0.03	0.02	0.01	0.02	0.02	0.02	0.02
Mining and quarrying, non-energy producing products	0.62	0.38	0.30	0.31	0.67	0.80	1.15	1.45	1.36	1.39	1.93
Wood and products of wood and cork	0.15	0.14	0.13	0.11	0.10	0.07	0.08	0.08	0.08	0.07	0.07
Coke and refined petroleum products	0.34	0.21	0.21	0.15	0.07	0.25	0.21	0.19	0.29	0.27	0.26
Pharmaceuticals, medicinal chemical and botanical products	0.14	0.14	0.14	0.18	0.11	0.08	0.06	0.05	0.05	0.04	0.04
Machinery and equipment, nec	0.41	0.39	0.33	0.37	0.46	0.52	0.54	0.57	0.55	0.55	0.51
Other transport equipment	0.10	0.11	0.11	0.12	0.12	0.12	0.08	0.13	0.19	0.18	0.18
Electricity, gas, steam and air conditioning supply	0.40	0.37	0.34	0.43	0.47	0.54	0.44	0.55	0.57	0.73	0.79
Water supply; sewerage, and other activities 2	0.05	0.04	0.04	0.06	0.05	0.04	0.05	0.07	0.07	0.07	0.08
Construction	0.06	0.04	0.04	0.06	0.06	0.05	0.04	0.08	0.07	0.07	0.08
Water transport	0.09	0.07	0.06	0.05	0.05	0.04	0.03	0.04	0.03	0.03	0.03
Air transport	0.05	0.07	0.07	0.06	0.07	0.06	0.06	0.03	0.03	0.03	0.03
Warehousing and support activities for transportation	0.34	0.30	0.30	0.35	0.33	0.27	0.28	0.30	0.30	0.31	0.29
Postal and courier activities	0.01	0.01	0.01	0.01	0.01	0.02	0.02	0.02	0.02	0.02	0.03
Accommodation and food service activities	0.14	0.12	0.13	0.13	0.12	0.08	0.07	0.10	0.10	0.09	0.07
Publishing, audiovisual and broadcasting activities	0.11	0.10	0.09	0.08	0.08	0.06	0.05	0.05	0.05	0.04	0.03
IT and other information services	0.01	0.01	0.01	0.02	0.02	0.02	0.01	0.01	0.01	0.01	0.01
Financial and insurance activities	0.69	0.44	0.46	0.42	0.48	0.62	0.61	0.67	0.72	0.78	0.84
Real estate activities	0.77	0.62	0.53	0.59	0.57	0.58	0.73	0.49	0.48	0.42	0.42
Professional, scientific and technical activities	0.60	0.62	0.68	0.85	0.85	0.84	0.71	0.86	0.81	0.80	0.86
Administrative and support services	1.40	1.32	1.30	1.27	1.36	1.47	1.38	1.52	1.42	1.35	1.58
Public administration and defense 3	0.02	0.01	0.01	0.01	0.01	0.00	0.00	0.00	0.00	0.00	0.00
Education	0.00	0.01	0.01	0.01	0.01	0.01	0.00	0.00	0.00	0.00	0.00
Human health and social work activities	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00
Arts, entertainment and recreation	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.01	0.00	0.00	0.00
Other service activities	0.06	0.04	0.04	0.04	0.04	0.01	0.01	0.01	0.01	0.01	0.01
Activities of households as employers; and other 4	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00

Notes: ¹ Manufacturing NEC; repair and installation of machinery and equipment. ² Water supply; sewerage, waste management and remediation activities. ³ Public administration and defense; compulsory social security. ⁴ Activities of households as employers; undifferentiated goods- and services-producing activities of households for own use. Source: Own elaboration.

and

Table A6. Mexico into GVCs: Backward Participation by Sector, 1995–2020. (FVA, % Total Gross Exports).

	1995	1998	2000	2003	2005	2008	2010	2013	2015	2018	2020
Total	43.55	54.15	53.90	53.71	50.30	48.88	49.23	44.83	46.69	45.22	40.66
Multi-Stage Integration	19.95	26.12	25.69	23.71	21.89	20.54	21.80	19.45	21.12	20.55	19.07
Basic metals	0.17	0.17	0.12	0.11	0.18	0.20	0.24	0.16	0.21	0.19	0.16
Computer, electronic and optical equipment	8.90	12.61	12.17	10.54	9.77	9.24	9.48	6.38	6.52	6.17	6.38
Electrical equipment	1.25	1.61	1.53	1.49	1.46	1.21	1.41	0.98	1.15	1.04	1.08
Motor vehicles, trailers and semi-trailers	8.13	9.96	10.11	9.67	8.64	8.04	8.66	9.87	11.01	10.99	9.74
Land transport and transport via pipelines	1.51	1.77	1.75	1.90	1.84	1.84	2.02	2.06	2.23	2.16	1.71
Dominant Backward Integration	9.90	11.32	11.30	11.86	11.12	10.76	10.35	9.55	9.35	8.75	8.12
Mining support service activities	0.07	0.15	0.19	0.27	0.28	0.40	0.42	0.36	0.36	0.22	0.28
Food products, beverages and tobacco	3.94	4.57	4.67	4.81	4.62	4.65	4.49	4.46	4.24	4.07	3.97
Textiles, textile products, leather and footwear	1.69	2.05	2.07	2.11	1.67	1.25	1.18	1.04	0.97	0.82	0.59
Paper products and printing	0.42	0.44	0.43	0.38	0.36	0.34	0.36	0.37	0.35	0.34	0.32
Chemical and chemical products	0.99	1.01	0.93	1.32	1.23	1.15	0.97	0.80	0.88	0.88	0.75
Rubber and plastics products	0.32	0.37	0.35	0.36	0.38	0.40	0.44	0.41	0.44	0.42	0.39
Other non-metallic mineral products	0.29	0.35	0.34	0.34	0.32	0.32	0.30	0.10	0.11	0.11	0.10
Fabricated metal products	0.54	0.64	0.62	0.51	0.53	0.54	0.57	0.43	0.47	0.45	0.42
Manufacturing; repair and installation 1	1.18	1.33	1.19	1.17	1.10	0.96	0.87	0.91	0.96	0.92	0.80
Telecommunications	0.46	0.42	0.51	0.58	0.64	0.75	0.74	0.67	0.56	0.51	0.50
Dominant Forward Integration	1.89	2.13	2.12	2.18	1.78	1.33	1.26	1.43	1.50	1.50	1.30
Mining and quarrying, energy producing products	0.04	0.02	0.02	0.01	0.02	0.02	0.03	0.02	0.02	0.05	0.03
Wholesale and retail trade; repair of motor vehicles	1.85	2.11	2.10	2.17	1.76	1.31	1.24	1.41	1.48	1.45	1.26
Low Integration	11.80	14.58	14.79	15.96	15.52	16.25	15.82	14.41	14.73	14.42	12.17
Agriculture, hunting, forestry	0.41	0.53	0.54	0.55	0.53	0.56	0.56	0.60	0.60	0.60	0.58
Fishing and aquaculture	0.07	0.05	0.05	0.06	0.05	0.05	0.05	0.04	0.06	0.06	0.05
Mining and quarrying, non-energy producing products	0.03	0.02	0.01	0.00	0.01	0.01	0.01	0.01	0.01	0.01	0.01
Wood and products of wood and cork	0.03	0.03	0.03	0.02	0.02	0.02	0.02	0.02	0.02	0.02	0.02
Coke and refined petroleum products	0.27	0.25	0.30	0.71	0.79	1.06	0.89	1.07	0.87	1.11	0.78
Pharmaceuticals, medicinal chemical and botanical products	0.32	0.35	0.32	0.47	0.61	0.70	0.72	0.51	0.65	0.52	0.55
Machinery and equipment, nec	1.22	1.46	1.21	1.09	1.07	0.91	1.09	0.96	1.12	1.04	1.07
Other transport equipment	0.35	0.34	0.31	0.24	0.27	0.24	0.23	0.41	0.50	0.47	0.44
Electricity, gas, steam and air conditioning supply	0.15	0.19	0.28	0.41	0.41	0.54	0.47	0.19	0.14	0.16	0.14
Water supply; sewerage, and other activities 2	0.04	0.06	0.07	0.08	0.09	0.09	0.10	0.09	0.09	0.08	0.08
Construction	4.14	5.84	6.07	6.14	5.86	6.41	6.11	4.76	4.76	4.35	3.42
Water transport	0.03	0.02	0.02	0.05	0.06	0.06	0.09	0.03	0.05	0.06	0.06
Air transport	0.19	0.20	0.23	0.24	0.32	0.32	0.29	0.29	0.41	0.52	0.26
Warehousing and support activities for transportation	0.10	0.12	0.14	0.16	0.17	0.21	0.23	0.18	0.18	0.18	0.18
Postal and courier activities	0.03	0.04	0.04	0.04	0.03	0.02	0.02	0.02	0.03	0.03	0.03
Accommodation and food service activities	0.70	0.74	0.80	0.81	0.73	0.70	0.62	0.70	0.72	0.68	0.47
Publishing, audiovisual and broadcasting activities	0.17	0.21	0.22	0.25	0.20	0.21	0.22	0.20	0.19	0.18	0.11
IT and other information services	0.03	0.06	0.06	0.05	0.05	0.05	0.05	0.05	0.06	0.06	0.05
Financial and insurance activities	0.75	0.70	0.56	0.69	0.60	0.61	0.63	0.65	0.63	0.70	0.65
Real estate activities	0.55	0.88	0.86	0.90	0.89	0.74	0.61	0.55	0.52	0.47	0.50
Professional, scientific and technical activities	0.11	0.13	0.14	0.16	0.13	0.10	0.10	0.10	0.10	0.09	0.09
Administrative and support services	0.05	0.07	0.07	0.07	0.07	0.07	0.06	0.06	0.06	0.05	0.04
Public administration and defence 3	0.62	0.77	0.96	0.97	0.94	1.09	1.20	1.04	1.15	1.22	1.01
Education	0.27	0.28	0.28	0.32	0.28	0.28	0.28	0.36	0.35	0.33	0.28
Human health and social work activities	0.69	0.73	0.75	0.91	0.86	0.80	0.81	1.15	1.10	1.07	1.10
Arts, entertainment and recreation	0.21	0.21	0.19	0.20	0.17	0.17	0.17	0.15	0.15	0.13	0.06
Other service activities	0.27	0.30	0.31	0.36	0.28	0.23	0.21	0.21	0.22	0.21	0.15
Activities of households as employers; and other 4	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00

Notes: ¹ Manufacturing NEC; repair and installation of machinery and equipment. ² Water supply; sewerage, waste management and remediation activities. ³ Public administration and defense; compulsory social security. ⁴ Activities of households as employers; undifferentiated goods- and services-producing activities of households for own use. Source: Own elaboration.

).

To what extent do the degree and type of sectoral integration into GVCs shape sectors’ roles in driving the national production structure over the period 1995–2020? Among sectors exhibiting the highest levels of multi-stage integration, three stand out as key: basic metals; computer, electronic, and optical equipment; and motor vehicles, trailers, and semi-trailers. The first two show high and relatively balanced weighted multipliers—strong backward and forward linkages—indicating both substantial demand for upstream inputs and a significant supply of intermediates to the rest of the economy. Within the same category, motor vehicles, trailers, and semi-trailers maintain persistently high backward linkages and, during the second half of the period, exceed the forward-linkage threshold, suggesting a convergence between backward and forward linkages (See

Table 4. Mexico: Sectoral Classification According to its Role in the Productive Structure.

Driving Sector	Key Sector
Electrical equipment	Basic metals
Food products, beverages and tobacco	Computer, electronic and optical equipment
Pharmaceuticals, medicinal chemical and botanical products	Motor vehicles, trailers and semi-trailers 1
Other non-metallic mineral products	Chemical and chemical products
Manufacturing; repair and installation of machinery and equipment	Coke and refined petroleum products
Wood and products of wood and cork
Machinery and equipment, nec
Other transport equipment
Air transport
Paper products and printing 2
Textiles, textile products, leather and footwear 2
Fabricated metal products 2
Rubber and plastics products 2
Water transport
Publishing, audiovisual and broadcasting activities 2
IT and other information services
Non-Key Sector	Strategic Sector
Construction	Land transport and transport via pipelines
Mining support service activities *	Mining and quarrying, energy producing products
Telecommunications	Wholesale and retail trade; repair of motor vehicles
Fishing and aquaculture	Real estate activities
Water supply; sewerage, waste management and remediation activities	Professional, scientific and technical activities
Warehousing and support activities for transportation	Administrative and support services
Postal and courier activities	Agriculture, hunting, forestry
Accommodation and food service activities	Electricity, gas, steam and air conditioning supply
Public administration and defence; compulsory social security	Mining and quarrying, non-energy producing products 1
Education	Financial and insurance activities 1
Human health and social work activities
Arts, entertainment and recreation
Other service activities
Activities of households as employers *

Note: * Activities of households as employers; undifferentiated goods- and services-producing activities of households for own use. ¹ Sectors that began to play a more dynamic role in the economy. ² Sectors that recorded a weakening in their role in the economy. Source: Own elaboration.

). Disaggregated results by integration category—by sector, year, and role within the Mexican production structure—are presented in the Appendix A (See

Table A7. Mexico: Role of sectors in productive structure according to integration into GVCs, 1995–2020.

						Key				Driving					Strategic				Non-Key
Integration	Sector	Weighted Forward Linkages (FLRr)											Weighted Backward Linkages (BLRr)
		1995	1998	2000	2003	2005	2008	2010	2013	2015	2018	2020	1995	1998	2000	2003	2005	2008	2010	2013	2015	2018	2020
Multi-Stage	Basic metals	1.8583	1.6306	1.5281	1.5493	1.6775	1.8984	1.7259	1.6026	1.5924	1.5572	1.6176	1.2678	1.2485	1.2342	1.2464	1.2337	1.2441	1.2281	1.2223	1.2207	1.1963	1.1967
	Computer, electronic and optical equipment	1.4618	1.9217	1.9524	1.6890	1.5258	1.4279	1.3806	1.2444	1.3109	1.3096	1.3982	1.3310	1.2939	1.3045	1.3536	1.4163	1.5049	1.5464	1.5159	1.4889	1.4878	1.5369
	Electrical equipment	0.8844	0.9449	0.9112	0.8482	0.8371	0.8619	0.8453	0.8459	0.8382	0.8182	0.8367	1.4108	1.4228	1.4047	1.3973	1.4091	1.4219	1.4428	1.4116	1.3844	1.3739	1.3937
	Motor vehicles, trailers and semi-trailers	0.9630	1.0397	1.0801	1.0356	0.9665	0.9485	0.9835	1.0730	1.1080	1.2083	1.1750	1.4454	1.4187	1.4185	1.4074	1.4167	1.4338	1.4253	1.4182	1.4104	1.3898	1.3991
	Land transport and transport via pipelines	1.1637	1.1946	1.2538	1.2248	1.1885	1.1586	1.2441	1.2676	1.2529	1.2300	1.1677	0.9065	0.8773	0.8750	0.8790	0.8609	0.8678	0.8804	0.8917	0.8794	0.8828	0.8635
Dominant Blackward	Mining support service activities	0.5923	0.5916	0.6018	0.6362	0.6177	0.6058	0.6342	0.6417	0.6536	0.6502	0.6770	0.9791	1.0062	1.0041	0.9794	0.9782	0.9695	0.9694	0.9753	0.9759	0.9667	0.9715
	Food products, beverages and tobacco	0.8418	0.8071	0.7837	0.8194	0.8132	0.8165	0.8629	0.8432	0.8794	0.8656	0.9111	1.1349	1.1245	1.1131	1.0885	1.0868	1.0976	1.0900	1.0879	1.0886	1.0812	1.0944
	Textiles, textile products, leather and footwear	1.1180	1.0978	1.0191	0.9339	0.8662	0.7860	0.8042	0.7626	0.7754	0.7552	0.7244	1.1666	1.1895	1.2021	1.2051	1.2037	1.1776	1.1665	1.1531	1.1431	1.1313	1.1405
	Paper products and printing	1.2367	1.1248	1.1051	1.0764	1.0166	0.9724	0.9671	0.9351	0.9585	0.9516	0.9682	1.3108	1.3085	1.3152	1.2962	1.2971	1.3033	1.2838	1.2792	1.2682	1.2554	1.2572
	Chemical and chemical products	1.8876	1.7955	1.7532	1.7902	1.9689	2.0806	1.8982	1.7338	1.6908	1.5807	1.4549	1.1761	1.1502	1.1443	1.2053	1.2146	1.2058	1.1792	1.1411	1.1892	1.2394	1.2087
	Pharmaceuticals, medicinal chemical and botanical products	0.8157	0.8325	0.8213	0.8645	0.7802	0.6785	0.6854	0.7003	0.7639	0.7171	0.7434	1.1681	1.1388	1.1268	1.1329	1.2012	1.1950	1.2096	1.1777	1.2434	1.2031	1.2206
	Rubber and plastics products	1.0142	0.9835	0.9469	0.9028	0.8628	0.8194	0.8269	0.8267	0.8466	0.8319	0.8376	1.2624	1.2428	1.2643	1.2706	1.2753	1.2863	1.2706	1.2634	1.2380	1.2339	1.2298
	Other non-metallic mineral products	0.8581	0.8405	0.8226	0.8225	0.7904	0.7534	0.7594	0.7841	0.8191	0.8177	0.8309	1.1618	1.1758	1.1760	1.1907	1.1991	1.2203	1.2111	1.2204	1.2042	1.1993	1.1775
	Fabricated metal products	1.0416	1.0521	1.0219	0.9331	0.9372	0.9609	0.9350	0.9178	0.9305	0.9300	0.9374	1.3600	1.3418	1.3397	1.3237	1.3138	1.3327	1.3351	1.3151	1.3141	1.3013	1.2976
	Manufacturing nec /1	0.8247	0.8600	0.8202	0.8312	0.8026	0.7691	0.7806	0.7600	0.7917	0.7799	0.7719	1.2316	1.2341	1.2222	1.2066	1.2426	1.2366	1.2449	1.2627	1.2635	1.2499	1.2628
	Telecommunications	0.7651	0.7307	0.7451	0.7935	0.7939	0.7795	0.8024	0.8052	0.8084	0.7824	0.8176	0.9044	0.8662	0.8932	0.8837	0.8630	0.8466	0.8457	0.8777	0.8936	0.9106	0.9335
Dominant Forward	Mining and quarrying, energy producing products	2.2060	2.4870	2.7138	2.2118	2.6389	2.6024	2.1850	2.3069	1.7042	1.7592	1.3670	0.6539	0.6357	0.6328	0.6436	0.6460	0.6444	0.6451	0.6353	0.6889	0.7923	0.7855
	Wholesale and retail trade; repair of motor vehicles	3.3821	3.5047	3.5753	3.4541	3.4936	3.4809	3.4849	3.6342	3.8149	3.8995	3.9289	0.7349	0.7433	0.7362	0.7319	0.7098	0.6909	0.6926	0.6887	0.6905	0.6827	0.6889
Low	Agriculture, hunting, forestry	1.2440	1.2077	1.1428	1.1918	1.0937	1.0603	1.0567	0.9894	1.0265	1.0285	1.0948	0.8478	0.8382	0.8597	0.8499	0.8550	0.8567	0.8636	0.8708	0.8741	0.8538	0.8603
	Fishing and aquaculture	0.5764	0.5688	0.5672	0.5802	0.5722	0.5663	0.5879	0.5733	0.5976	0.5995	0.6096	0.8722	0.8624	0.8627	0.8846	0.8942	0.9161	0.9210	0.9789	0.9524	0.9696	0.9384
	Mining and quarrying, non-energy producing products	1.0317	0.9648	0.8572	0.8755	0.9672	1.0331	1.1242	1.1673	1.1899	1.1735	1.2908	0.8111	0.8752	0.9105	0.9150	0.9116	0.8970	0.8328	0.8682	0.8528	0.8305	0.8093
	Wood and products of wood and cork	0.7660	0.7643	0.7509	0.7209	0.7086	0.6828	0.7263	0.7108	0.7312	0.7170	0.7303	1.1072	1.0977	1.1063	1.0900	1.0879	1.1036	1.1049	1.1048	1.0929	1.0814	1.0880
	Coke and refined petroleum products	1.1105	1.0291	1.0797	1.1377	1.3822	1.8286	1.8042	2.0557	1.5465	1.6128	1.2632	1.0562	1.0949	1.0907	1.1888	1.2527	1.2501	1.2805	1.3123	1.2407	1.2939	1.2275
	Machinery and equipment, nec	0.7441	0.7377	0.7095	0.7275	0.7343	0.7547	0.7705	0.7717	0.7702	0.7772	0.8025	1.2401	1.2529	1.2588	1.2160	1.2282	1.2412	1.2331	1.2171	1.2327	1.2147	1.2735
	Other transport equipment	0.7301	0.6757	0.6717	0.6700	0.6723	0.6681	0.6716	0.7059	0.7406	0.7511	0.7708	1.3752	1.3495	1.2828	1.2158	1.2286	1.2378	1.2588	1.2891	1.2660	1.2706	1.2647
	Electricity, gas, steam and air conditioning supply	0.9828	0.9803	1.0259	1.1657	1.1345	1.0953	1.0590	1.2368	1.2040	1.3583	1.3651	0.8319	0.8229	0.8899	0.9008	0.9298	0.9456	0.9303	1.0067	0.8987	0.8726	0.8354
	Water supply; sewerage /2	0.6508	0.6306	0.6413	0.6726	0.6649	0.6428	0.6904	0.6719	0.6996	0.6978	0.7196	0.9268	0.9685	0.9437	0.9179	0.9227	0.9316	0.9239	0.9446	0.9188	0.9062	0.9101
	Construction	0.7075	0.6782	0.6799	0.7419	0.7040	0.6747	0.7119	0.7494	0.7641	0.7733	0.7855	1.0229	1.0180	1.0035	0.9828	0.9740	0.9794	0.9829	0.9526	0.9546	0.9330	0.9431
	Water transport	0.6002	0.5886	0.5846	0.6068	0.5950	0.5693	0.5892	0.5722	0.5933	0.5970	0.6073	0.8638	0.8750	0.8909	1.1069	1.0844	0.9359	1.0315	0.8825	1.0077	1.0524	1.0640
	Air transport	0.6248	0.6283	0.6388	0.6550	0.6596	0.6606	0.6678	0.6095	0.6379	0.6460	0.6412	1.2774	1.2448	1.2435	1.2471	1.2355	1.2646	1.2313	1.2528	1.2257	1.2559	1.2209
	Warehousing and support activities for transportation	0.7571	0.7344	0.7407	0.8011	0.7779	0.6990	0.7503	0.9109	0.9816	0.9831	0.9502	0.8618	0.8767	0.8935	0.8692	0.8597	0.8825	0.8789	0.9047	0.9180	0.9104	0.9678
	Postal and courier activities	0.5880	0.5827	0.5814	0.5934	0.5890	0.5874	0.6116	0.6078	0.6324	0.6400	0.6616	0.9246	0.9469	0.9448	0.9256	0.8941	0.8593	0.9063	0.9407	0.9338	0.9486	0.9054
	Accommodation and food service activities	0.7078	0.6936	0.6978	0.7149	0.6940	0.6724	0.6877	0.7174	0.7587	0.7495	0.7294	0.8658	0.8352	0.8351	0.8248	0.8226	0.8357	0.8293	0.8350	0.8333	0.8237	0.8450
	Publishing, audiovisual and broadcasting activities	0.7078	0.6935	0.6989	0.7221	0.6855	0.6516	0.6677	0.6549	0.6782	0.6740	0.6581	1.1075	1.0994	1.0869	1.0739	1.0350	1.0134	0.9992	0.9891	0.9950	0.9943	0.9969
	IT and other information services	0.5792	0.5777	0.5812	0.5994	0.5952	0.5932	0.6137	0.5875	0.6087	0.6122	0.6249	0.8944	0.9743	0.9836	0.9825	0.9685	0.9779	0.9717	0.9909	1.0097	1.0066	1.0184
	Financial and insurance activities	0.8690	0.7712	0.7974	0.8722	0.8823	1.0425	1.0747	1.0184	1.0614	1.0966	1.1369	0.7727	0.8737	0.8603	0.8518	0.7954	0.8070	0.8077	0.7922	0.7967	0.7753	0.7872
	Real estate activities	1.2377	1.1437	1.0698	1.1594	1.1288	1.1098	1.2695	1.1223	1.1657	1.0923	1.1115	0.6252	0.6405	0.6384	0.6344	0.6280	0.6205	0.6059	0.5986	0.6057	0.6027	0.6289
	Professional, scientific and technical activities	1.2044	1.2512	1.3270	1.5512	1.5136	1.4875	1.4526	1.3200	1.3805	1.3282	1.3788	0.8633	0.8355	0.8187	0.7841	0.7670	0.7416	0.7466	0.7485	0.7524	0.7512	0.7498
	Administrative and support services	2.1340	2.1863	2.2335	2.2640	2.1822	2.1088	2.0750	2.1150	2.1208	2.0671	2.2700	0.7536	0.7502	0.7471	0.7396	0.7211	0.7052	0.6898	0.6933	0.6985	0.7024	0.7000
	Public administration and defence; compulsory social security	0.5800	0.5716	0.5715	0.5861	0.5725	0.5593	0.5799	0.5683	0.5884	0.5908	0.6010	0.7772	0.7829	0.8001	0.7642	0.7699	0.7859	0.7838	0.7718	0.7968	0.8232	0.7984
	Education	0.5795	0.5726	0.5724	0.5889	0.5759	0.5650	0.5851	0.5709	0.5914	0.5936	0.6034	0.6611	0.6462	0.6397	0.6237	0.6165	0.6135	0.6138	0.6154	0.6189	0.6242	0.6246
	Human health and social work activities	0.5836	0.5738	0.5727	0.5882	0.5781	0.5680	0.5894	0.5706	0.5905	0.5927	0.6031	0.8700	0.8634	0.8503	0.8332	0.8471	0.8342	0.8278	0.8547	0.8585	0.8546	0.8572
	Arts, entertainment and recreation	0.5825	0.5760	0.5757	0.5922	0.5811	0.5762	0.5956	0.5861	0.6075	0.6079	0.6099	0.8930	0.8760	0.8630	0.8509	0.8478	0.8472	0.8417	0.8162	0.8281	0.8213	0.7951
	Other service activities	0.6350	0.6138	0.6118	0.6294	0.6113	0.5828	0.6024	0.5844	0.6064	0.6068	0.6158	0.7484	0.7432	0.7538	0.7550	0.7339	0.7227	0.7173	0.7183	0.7319	0.7338	0.7035
	Activities of households as employers /3	0.5703	0.5643	0.5632	0.5754	0.5661	0.5591	0.5796	0.5667	0.5867	0.5890	0.5992	0.5427	0.5373	0.5346	0.5295	0.5210	0.5148	0.5193	0.5129	0.5208	0.5153	0.5282

/1 Manufacturing nec; repair and installation of machinery and equipment. /2 Water supply; sewerage, waste management and remediation activities. /3 Activities of households as employers; undifferentiated goods- and services-producing activities of households for own use. Source: Own elaboration.

).

Within the dominant backward integration category, multiplier spillover effects are prevalent, particularly in food and beverage processing; textiles, clothing, and footwear; paper and printing; plastics; non-metallic mineral products; and other manufacturing activities not classified elsewhere. Other sectors—such as chemicals and chemical products—appear as key in certain years; however, their forward linkages gradually deteriorate and weaken toward the end of the period. By contrast, within the dominant forward integration category, forward-oriented sectors include mining and quarrying, energy-producing products, and, most notably, wholesale and retail trade. These activities operate as systemic suppliers to the rest of the economy, yet generate relatively limited spillover effects into domestic production linkages.

Sectors classified as having low GVCs integration play heterogeneous roles in stimulating the national economy (See Appendix A Table A7). First, coke and refined petroleum products serve as a key sector due to their cross-cutting role in production, despite relatively limited international integration. Second, machinery and other transport equipment show strategic backward-oriented effects on other sectors. Third, electricity, gas, steam, and air-conditioning supply, together with most private and public services, consolidate their role as drivers of the production structure throughout the period.

Overall, these findings are broadly consistent with Boundi Chraki (2016), underscoring the central role of manufacturing as an economic driver, the limited number of key sectors, and the predominance of non-key sectors—patterns that together indicate constrained productive diversification and persistent structural weaknesses.

Over the period 1995–2020, sectoral roles as drivers of growth exhibit a high degree of stability, with only limited episodes of upgrading or weakening observed in a small number of sectors. Sectors integrated across multiple GVCs segments remain classified as key. By contrast, the chemicals and chemical products sector experiences a reduction in forward linkages toward the end of the period, implying weaker multiplier effects through the supply of intermediates. Driving sectors maintain notable stability—particularly wholesale and retail trade and land transport and pipelines—the latter showing integration across multiple production stages within GVCs. There are also signs of strengthening among knowledge-intensive services (professional, scientific, and technical services; administrative and support services), mainly driven by increases in forward (driving) linkages rather than backward linkages. Meanwhile, non-key sectors remain largely unchanged—such as education, public administration, health, and personal services—consistent with their limited productive articulation with other sectors or their predominantly non-intermediate nature.

Although a small number of sectors cross classification thresholds—most notably Motor vehicles, trailers, and semi-trailers, and to a lesser extent coke and refined petroleum products and non-energy mining—these changes are not generalized across the production structure and do not alter the overall stability of sectoral hierarchies. Accordingly, the evidence supports a pattern of limited and non-systematic transitions rather than an absence of transitions.

In terms of scaling, the most significant case is motor vehicles, trailers, and semi-trailers. Its multiplier spillovers cross the relevant threshold from 2015 onward, positioning the sector as key and suggesting a broader diffusion of demand toward backward-integrated activities, including auto parts, metalworking, technical plastics, and specialized services. The electricity and gas sector also gains momentum from the early 2000s, reflecting its growing enabling role within the production structure. Information technology and other information services nearly reach the spillover threshold toward the end of the period, foreshadowing potential upgrading if local sourcing and linkages with manufacturing deepen. Coke and refined petroleum products temporarily strengthen their driving role during 2008–2013 and subsequently consolidate as key. Non-energy mining follows a similar trajectory, emerging as a driving sector during the 2010s.

Regarding forward linkages, fabricated metal products and paper and printing lose key status as their driving role declines from the early 2000s onward, remaining follower sectors characterized by high dependence on intermediate inputs but lower sales of intermediates to the rest of the economy. Textiles and footwear exhibit a comparable pattern, reinforcing the hypothesis that several traditional manufacturing activities preserved domestic supplier networks without expanding their role as cross-cutting suppliers.

Relating these sectoral changes to the integration categories reveals three distinct patterns. First, manufacturing activities integrated across multiple segments of GVCs—and some sectors classified under dominant backward integration—tend to be identified as key or to generate significant multiplier spillovers. The positioning of motor vehicles, trailers, and semi-trailers as a key sector confirms that, under multi-stage integration, the strengthening of domestic downstream linkages is feasible and can materialize within relatively short time spans. Second, sectors characterized by predominant forward integration sustain long-term driving roles within the production structure, reflecting strong spillovers into domestic intermediate demand but limited spillovers toward local suppliers; in such cases, raising multipliers would require import substitution strategies based on quality upgrading, standardization, and competition in services. Third, persistent functional imbalances in low-integration sectors (e.g., coke and refined petroleum products) coexist with their key role in the national economy, while predominantly backward-integrated sectors have not strengthened their momentum effects, suggesting the presence of downstream bottlenecks associated with limited local intermediate uses, insufficient standards and aggregation, or incomplete industrial clienteles.

In summary, the evidence points to a dual pattern in the Mexican economy. Manufacturing sectors that are strongly integrated across multiple GVCs links—and predominantly backward integrated—also maintain relatively strong productive ties with domestic structures, whereas energy-related activities and productive services contribute to the national economy mainly through systemic impulse linkages. These findings are consistent with Murillo-Villanueva (2020), who reports the coexistence of dual productive structures and the disarticulation of certain GVCs integrated sectors from those oriented toward domestic markets. Finally, instances of upgrading amid weakening integration suggest that sectors’ structural roles have been shaped by their functional insertion into GVCs. In this sense, the slow pace of sectoral change in the Mexican economy is consistent with the functional logic of its integration into GVCs throughout the period under analysis.

4. Conclusions

This study analyzed Mexico’s participation in GVCs based on international trade in value added over the period 1995–2020. A first finding is that multi-stage integration has been particularly relevant, both in terms of its contribution to domestic value added and its dynamism. However, this form of integration has remained highly concentrated in a limited number of sectors throughout the period, revealing one of the main structural constraints of Mexico’s integration into GVCs. A second key finding is that the sectoral dynamics of integration have not translated into a significant process of structural transformation; the dynamic roles of productive sectors within the domestic production structure show only limited variation over time, with few non-generalized cases of upgrading.

The results further suggest that high sectoral concentration and weak production linkages between manufacturing and service activities have constrained the potential for sustained expansion and structural change in the Mexican economy. This configuration has reproduced a dual productive structure: on the one hand, a modern export-oriented sector closely linked to transnational corporations through GVCs; on the other, a large set of activities oriented toward domestic demand with limited articulation to internationally integrated segments. The persistence of this duality during the outward-oriented growth phase largely reflects the disconnect between production segments that supply global markets and those driven by domestic demand.

These structural characteristics help explain both the limited impact of GVC integration on productive diversification and restructuring, and the high vulnerability of the Mexican economy to external shocks, given the weakness of domestic demand as a driver of growth. While these outcomes are shaped by multiple internal factors—including structural heterogeneity, capital scarcity, technological gaps, and uneven firm capabilities—the results highlight the central role played by the disarticulation between GVC-integrated and non-integrated sectors. From a value-added perspective, the analysis reveals circular patterns of external dependence, whereby imported inputs are used for export production and global demand largely determines both import and export volumes. In this sense, Mexico’s slow pace of structural transformation cannot be attributed solely to recurrent external shocks but is consistent with persistent gaps in industrial policy.

From a policy perspective, while the empirical results do not establish causal relationships, they point to differentiated structural patterns that are relevant for the design of industrial policy. In particular, the coexistence of multi-stage integration with relatively strong domestic linkages in a small number of sectors suggests that deeper forms of integration may be compatible with upgrading when backward and forward linkages are simultaneously strengthened. By contrast, sectors characterized by dominant backward integration display a strong dependence on imported intermediates, indicating the presence of downstream bottlenecks that limit the diffusion of GVC-related demand toward domestic suppliers. Finally, sectors with dominant forward integration tend to play a systemic role in the economy, providing inputs to a wide range of activities, yet with relatively limited spillovers toward domestic capability building. Taken together, these patterns highlight the importance of aligning industrial policy with the structural dynamics of GVC participation, ensuring that integration contributes to sustainable and inclusive economic upgrading.

Against this background, the findings are consistent with three broad industrial policy priorities: developing local suppliers through selective import substitution in activities with potential for strengthening domestic linkages; facilitating access to productive financing to support the expansion of domestic firms’ participation in GVCs, particularly in sectors exhibiting multi-stage integration; and investing in industrial, transport, and digital infrastructure to enhance coordination between manufacturing activities and business-intensive services. While integration into GVCs does not, by itself, guarantee sustained growth or structural transformation, the results suggest that targeted industrial policies aimed at reinforcing domestic linkages may enhance the capacity of GVC participation to generate higher domestic value added and reduce exposure to external shocks.

In short, beyond optimistic narratives about Mexico’s insertion into GVCs, the process has largely reflected the profit-maximization logic of multinational corporations, which control chain governance and often overlook the needs of the territories where industries are located. Major global realignments nevertheless open a window to rethink Mexico’s role in GVCs. In this context, the policy priorities discussed above—aimed at strengthening domestic linkages, expanding local supplier capabilities, improving access to productive financing, and investing in industrial and digital infrastructure—are consistent with both the empirical patterns identified in this study and with international experience (Gereffi et al., 2005; OECD, 2013; World Bank, 2020). Together, these measures may enhance the capacity of GVC participation to generate higher domestic value and reduce exposure to external shocks.