Revista de economía mundial 65, 2023, 115-139
ISSN: 1576-0162
The ReducTion of The GendeR Gap ThRouGh Global Value chains:
poliTical commiTmenT oR peRpeTuaTion of GendeR Roles?
La reducción de La brecha de nero en cLave de cadenas gLobaLes
de vaLor: ¿apuesta poLítica o perpetuación de Los roLes de género?
Hugo Campos-Romero
Universidade de Santiago de Compostela
Bruno Blanco-Varela
Universidade de Santiago de Compostela
Recibido: agosto 2023; aceptado: septiembre 2023
Premio Jose Luís Sampedro, 2023
The relationship between international trade and the gender gap is complex.
On one hand, foreign insertion can generate economic opportunities for
women in the export sector. On the other hand, it can also result in heightened
competition and the relocation of jobs, especially in the context of global
value chains (GVCs). The study on the gender gap through GVCs examines
the mechanisms within production networks that contribute to enhance
women’s economic empowerment and gender equality. The paper analyzes
the relationship between the gender gap, GVCs, technological intensity of
exports, and female empowerment in the EU-27, investigating whether GVCs
could reduce or worsen gender disparities. The aim of this paper is to expand
the gender gap studies incorporating the effects of trade in value added in
the European Union. The study used a panel of data from various sources,
including Eurostat, Trade in Employment (TiM), and the World Bank. The results
suggest that an increase in exports, regardless of the level of technological
intensity, tends to exacerbate the gender gap in export sectors by increasing
the proportion of male workers relative to female workers. However, a higher
female participation rate in medium-low technology sectors could reduce the
gender gap in export sectors. The study identified obstacles to female insertion
in export markets, including the need to improve education and training for
women in high-demand areas, promote STEM (science, technology, engineering
and mathematics) education and labor participation for women. This paper
makes significant contributions to the literature by incorporating global value
GVCs and considering the European context. Additionally, it provides an in-
depth analysis of socioeconomic factors that are crucial for designing policies
aimed at addressing gender inequality.
Keywords: gender gap, global value chain, employment, gender roles,
technology intensity, EU-27.
La relación entre el comercio internacional y la brecha de género es
compleja. Por un lado, la inserción extranjera puede generar oportunidades
económicas para las mujeres en el sector exportador. Por otro lado, también
puede dar lugar a una mayor competencia y a la deslocalización de puestos
de trabajo, especialmente en el contexto de las cadenas globales de valor
(CGV). El estudio sobre la brecha de género a través de las CGV examina los
mecanismos dentro de las redes de producción que contribuyen a mejorar
el empoderamiento económico de las mujeres y la igualdad de género. El
trabajo analiza la relación entre la brecha de género, las CGV, la intensidad
tecnológica de las exportaciones y el empoderamiento femenino en la UE-
27, investigando si las CGV pudieran reducir o empeorar las disparidades de
género. El objetivo de este trabajo es ampliar los estudios sobre la brecha
de género incorporando los efectos del comercio en el valor añadido en la
Unión Europea. El estudio está basado en un panel de datos elaborado a
partir de diversas fuentes, entre ellas Eurostat, Trade in Employment (TiM) y el
Banco Mundial. Los resultados sugieren que un aumento en las exportaciones,
independientemente del nivel de intensidad tecnológica, tiende a exacerbar la
brecha de género en los sectores exportadores al aumentar la proporción de
trabajadores masculinos en relación con las trabajadoras. Sin embargo, una
mayor tasa de participación femenina en los sectores de tecnología media-
baja podría reducir la brecha de género en los sectores de exportación. El
estudio identificó obstáculos para la inserción femenina en los mercados de
exportación, incluida la necesidad de mejorar la educación y la capacitación de
las mujeres en áreas de alta demanda, promover la educación STEM (ciencia,
tecnología, ingeniería y matemáticas) y la participación laboral de las mujeres.
Este documento hace contribuciones significativas a la literatura al incorporar
CGV de valor global y considerar el contexto europeo. Además, proporciona
un análisis en profundidad de los factores socioeconómicos que son cruciales
para diseñar políticas destinadas a abordar la desigualdad de género.
Palabras clave: brecha de género, cadena global de valor, empleo, roles de
género, intensidad tecnológica, UE-27.
Clasificación JEL / JEL Clasification: F14, J16, J21, J78.
Revista de economía mundial 65, 2023, 115-139
1. inTRoducTion
Reducing the gender gap can lead to greater economic growth. In turn,
economic growth contributes to the reduction of the gender gap through
increased labor participation, productivity, and human capital. In addition,
international trade, and integration into global value chains (GVCs) can
be articulated as an engine of economic growth through innovation, the
emergence of new business opportunities and improved labor conditions for
the companies that participate in them.
The relationship between international trade and the gender gap is
complex. On the one hand, a greater degree of foreign insertion can create new
economic opportunities for women, especially in the export sector. This can
lead to an increase in their income, a reduction in poverty and an improvement
in their overall economic situation. On the other hand, international trade can
also lead to increased competition and offshoring of jobs, which can affect
women in insecure and less skilled jobs to a greater extent. This is particularly
relevant in a trade context defined to a large extent by GVCs, insofar as they
imply a profound fragmentation of production chains.
The aim of this paper is to analyze the relationship of the gender gap
with global value chains, the technological intensity of exports and female
empowerment in the EU-27. Specifically, it analyzes how integration in GVCs
affect gender disparities. This paper contributes to the literature on the effects
of international trade on the gender gap. In addition, it brings novelty by
approximating foreign trade from GVCs in relation to the gender gap.
To meet the objective, a panel of data has been designed from Eurostat,
Trade in Employment (TiM, OECD) and the World Bank including export
variables in domestic value added, other economic variables and variables of a
social nature, such as the number of women in management positions, among
The results reveal some of the factors affecting the gender gap in
employment in export sectors embedded in GVCs. The female activity rate, the
number of women in executive positions and the gap between men and women
in the degree of success in tertiary studies (which points to a higher attainment
rate among women) reveal a significant effect and reduce the gender gap.
However, an increase in the fertility rate would lead to an increase in the gap.
This effect may be due to traditional care-giving gender roles.
118 Hugo Campos-Romero · Bruno Blanco-Varela
This paper introduces several contributions. Firstly, it expands the existing
literature on the relationship between GVCs and the gender gap in the
European context, which has received reduced attention in previous studies.
In this sense, it should be noted that addressing the effect of GVCs represents
a contribution itself. Secondly, it examines a range of economic and social
variables that provide valuable insights to design public policy measures.
Thirdly, it delves deeper into the gender patterns in the domestic and foreign
labor markets, shedding light on their differences.
The structure of this article starts with this introduction and continues with
the second section which deals with the literature review on gender gap and
the effect of trade and global value chains. Thirdly, the methodology and data
sources used are explained in detail. Fourthly, descriptive variables and the
results of the econometric model are presented. Finally, a discussion section is
carried out, detailing the results and conclusions of the study. This structured
approach has enabled a clear and well-organized presentation of the research
conducted on the gender gap and the impact of trade and global value chains,
allowing for a rigorous evaluation of the topic and providing meaningful insights
for further investigation.
2. liTeRaTuRe ReView
The gender gap in the labor market is a critical global issue that has been
extensively studied by scholars. International trade has been recognized as
one of the factors influencing this gap, but its impact on gender disparities
is multifaceted and not yet fully understood. On the one hand, greater trade
openness can enhance the working conditions of workers, including women
(Gilles, 2018). On the other hand, participation in international trade may
affect the gender gap in terms of the sexual division of labor and access to
productive assets, leading to significant differences in wages, employment
opportunities, and career advancement.
The interest in reducing the gender gap is not only justified on social but also
on economic grounds. Morais (2017) argues that improving gender equality
would have a positive effect on economic growth and women’s employment. The
positive impacts are due to an increase in productivity and an improvement in
the potential productive capacity of the European economy. While traditionally
viewed as a national issue, globalization and economic integration have made
gender disparities a global concern (Ghosh et al., 2022), underscoring the
need for a comprehensive approach to address these inequalities.
The issue is considered in the classic models that deal with international
trade. However, this methodology is insufficient to explain gender disparity
factors (Papyrakis et al., 2012). For example, the Heckscher-Ohlin (HO) model
does not consider the social factors that influence women’s role in the labor
market. Instead, it focuses on determining wages as a function of external
demand and the mobility of factors of production. In the same way, the work
of Manning (2003) points to two characteristics of women in the labor market
The ReducTion of The GendeR Gap ThRouGh Global Value chains: poliTical commiTmenT oR peRpeTuaTion of GendeR Roles?
ReVisTa de economía mundial 65, 2023, 115-139
that may accentuate the wage gap. Firstly, because they are willing to accept a
lower reservation wage and, secondly, because of their lower labor elasticity, in
both cases due to various socio-cultural factors. Therefore, a broader and more
inclusive approach that considers gender inequalities and other relevant social
variables is necessary for a more complete understanding of international
trade relations.
Black and Brainerd (2004) work builds upon Becker’s (1957) traditional
model, which posits that increased market competition can lead to a reduction
in discrimination against women and minority groups over time. To address
this issue, the authors develop a model that identifies changes in market
competitiveness through imports and firm concentration at the sectoral level.
Their findings suggest that wage differentials narrowed more in sectors that
experienced increased competition through foreign trade at the beginning of
the period, compared to firms that were already operating in a competitive
environment. Sauré and Zoabi (2014) challenge the common assumption that
trade expansion in female-intensive sectors (FIS) leads to an increase in female
labor force participation (FLFP). Instead, the paper argues that FLFP may
decrease if trade expands FIS in capital-abundant economies, resulting in a
widening gender wage gap. This highlights again the importance of considering
the broader economic context when examining the effects of competition on
reducing discrimination.
While greater trade openness generally implies better working conditions
for employees in companies with some degree of external insertion, it does
not necessarily lead to a narrowing of the wage gap. Initially, greater external
insertion could lead to greater facilities for the incorporation of women into
working life (Bussmann, 2009). However, several studies have found that the
wage gap increases in sectors with a higher relative participation in foreign
trade (Chowdhury et al., 2021; Li et al., 2020; Orkoh et al., 2022). Furuta et
al. (2018) and Menon and Rodgers (2009) found that trade openness in India
resulted in an increase in the gender gap, although this effect varied depending
on whether labor-intensive or capital-intensive sectors were considered, with
the gap increasing in the former. Some studies have pointed to fundamental
causes differences in gender pay, such as the productivity differential between
men and women. However, not all studies reach this same conclusion. For
example, Almasifard (2018) and Sepehrivand (2017) indicate that greater
external integration may not only increase the income level of competitive
sectors but also decrease the gender gap. This suggests that the effects of
trade openness on employment and the gender gap may be contingent upon
national policies and the type of external integration (Dluhosch, 2021).
Other studies have explored how the origin of capital can impact the
gender pay gap. Vahter and Masso (2019) analyzed gender pay gaps in foreign
and domestic firms, with a focus on multinational acquisitions. They utilized
propensity score matching to compare the differences between the two groups
and found a larger wage gap in firms owned by multinationals. This difference
may be attributed to greater demands for employee commitment from these
120 Hugo Campos-Romero · Bruno Blanco-Varela
companies, consistent with Manning’s (2003) discussion of factors contributing
to wage differentials. Fernández (2020) analyzes the effect of foreign ownership
on female employment. Results show that foreign ownership increases the
proportion of female workers within the company. Foreign acquisition increases
the proportion of skilled women only when the acquired company was not an
exporter before its acquisition, supporting Becker’s (1957) theory of taste-
based discrimination.
Regarding foreign direct investment (FDI), Kodama et al. (2018) shows
how, in the case of Japan, foreign-owned firms have a higher participation of
women in leadership and management positions. According to the authors,
this contrast between domestic versus foreign-owned domestic firms has to
do with the culture and social norms imported through FDI. It is worth noting
that family reconciliation is easier in foreign-owned companies, facilitating the
attraction of talent not only among the male audience. In addition, Lee and Shin
(2020) notes that women see FDI as an opportunity insofar as it can entail not
only new jobs for women, but also better working conditions and, ultimately,
greater equality. In this sense, the analysis conducted by Pantelopoulos (2022)
for a set of OECD countries points out that women’s access to the labor market
is a factor of attraction for FDI. Bui et al.(2018) research shows that promoting
gender equality is a crucial factor in attracting foreign direct investment (FDI)
to developing nations.
However, Helble and Takeda’s (2020) research on the manufacturing sector
in Cambodia did not provide clear evidence that FDI influences the gender gap.
Nonetheless, they acknowledged that FDI can lead to wage improvements and
increased formal employment opportunities. Thus, while competition can play
a role in reducing discrimination, it is not a silver bullet, and policymakers and
researchers must consider a wide range of factors when striving to achieve
greater equality. In contrast, other studies have found that the free trade and
capital flows may not always lead to an increase in gender disparities.
Some literature considers the export orientation to explain the gender
gap (Bonfiglioli & De Pace, 2021; Busse & Spielmann, 2006; Ozler, 2000).
In the exporting sectors, the sexual division of labor often involves women
being concentrated in lower-paying and lower-status jobs, such as sewing and
assembly work in the clothing and textile industries. This division is a result
of gender-based discrimination and a lack of equal opportunities for women
in these industries. Women are also underrepresented in leadership and
management positions in exporting sectors. The study by Granitoff and Hong
Tiing Tai (2022) highlights the differences that exist between exporting and
domestically traded firms. The results find that exporting firms have a positive
impact on wages, while being a woman reduces wages.
To address this issue, it is important to promote gender equality and
increase women’s participation in STEM education and careers. This can include
initiatives aimed at breaking down gender-based stereotypes and increasing
girls’ access to educational resources and opportunities in these fields.
Encouraging women to pursue careers in STEM and promoting a supportive
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and inclusive work environment is also critical in reducing the sexual division of
labor according to technological level.
Related to exports is technological intensity. In this sense, it is worth
noting the interpretative framework implied by the sexual division of labor.
The gender gap is influenced by several factors, including care work and entry
into the labor market under more precarious working conditions, such as part-
time contracts. According to Morais (2017) the reasons that can reduce the
gender gap are: active participation in the labor market, matching their male
counterparts; reduction of wage gaps; and larger presence in STEM jobs.
The sexual division of labor according to technological level refers to the
way in which tasks and responsibilities within different industries are divided
based on the level of technology used. In many cases, higher-skilled and
higher-paying jobs that utilize advanced technology are dominated by men,
while women are concentrated in lower-skilled and lower-paying positions
that involve manual labor or routine tasks. This division is often a result of
gender-based biases and a lack of equal opportunities for women in STEM
fields (Donmez, 2020). It should be noted that access to certain sectors may
be determined by access to productive assets by virtue of social stereotypes.
This can be seen when analyzing access to credit by gender (Andrés Alonso et
al., 2019; Wang et al., 2022; Morais, 2017).
Although there has been extensive literature on the influence of exports,
trade openness, and even FDI flows on the gender gap, the role of GVCs in
this regard remains relatively unexplored. McCarthy et al. (2021) argue
that despite the potential for analysis of governance patterns, the role of
gender roles in GVCs has been largely overlooked. Given the dominance of
men in decision-making positions within GVCs, the authors propose a shift in
methodologies and a more profound analysis of the social relations and gender
roles surrounding these chains.
A handful of studies have delved into the relationship between GVCs
and gender equality. For example, Szymczak and Wolszczak-Derlacz (2022)
examine the impact of GVCs on wages and employment levels, finding a negative
correlation between these variables. The study suggests that the increasing
competition resulting from external integration under these international
networks puts downward pressure on wages, especially in backward linkages.
Deb (2022) also explores this issue focusing on the gender wage gap. Her
findings indicate that increased participation in GVCs has led to a reduction in
women’s wages relative to men’s in India. The findings of Gagliardi et al. (2019)
and Nikulin and Wolszczak-Derlacz (2022) also suggest that GVCs contribute
to greater gender inequalities.
Despite the negative results found by some studies regarding GVC
participation and gender inequality, not all studies show negative effects of
GVC participation. For instance, Said-Allsopp and Tallontire (2015) approached
the issue of female employment in GVCs from a different perspective than that
of employment level and wage gender gaps. Based on a case study conducted
in Kenya, the study concludes that increased female employment in GVCs
122 Hugo Campos-Romero · Bruno Blanco-Varela
can empower women in three ways: by enabling them to adopt different ways
of being, different ways of doing things, and by sharing experiences. These
changes can alter the way women fit into society and their roles within the
family, leading to positive societal transformations.
To summarize, the gender gap is a complex and multifaceted phenomenon
that can be examined from various angles. Although the literature has
primarily focused on wage and employment disparities, there are many other
dimensions to consider (Jehn et al., 2021; Ma et al., 2021; Wolszczak-Derlacz,
2013). Women’s participation in certain sectors, participation in positions of
greater economic relevance and representation or changes in social roles.
For instance, the gender gap can be analyzed in terms of differences in labor
market participation or access to education and healthcare (Yamamura, 2016).
To address this issue, policies and initiatives aimed at promoting gender
equality and empowering women in the workplace are necessary. This includes
equal pay for equal work, access to education and training, and opportunities
for career advancement. Challenging gender-based stereotypes and promoting
diversity and inclusion in the workplace are also important steps in breaking
down the sexual division of labor in the exporting sectors.
3. daTa and meThodoloGy
This section describes the methodology of the study. To achieve the
objective established in the Introduction, data was collected on employment
levels by gender and technological intensity of manufacturing sectors, exports
by technological intensity, GVC, educational level, fertility, and social status of
women. Table A1 in Appendix A defines the selected variables along with their
sources. The data collected covers the period 2008-2018 and includes all
EU27 countries. Next, some of these indicators are discussed in more detail.
Starting with the employment dimension, the employment gap is defined
as female to male employees ratio. This research differentiates between
total, export, and domestic employment by gender. The first two indicators
are obtained from Trade in Employment (TiM OECD, 2021 edition), while the
third can be obtained by difference between the two previous ones. The input-
output methodology for the calculation of the employment variables related to
foreign trade is detailed below. The complete methodology can be consulted
at (Horvát etal., 2020).
For a set of c countries and s sectors, the following basic input-output
entities are defined: Tcsxcs is the intermediate transactions matrix, Ycsxc is the
final demand vector and Xcsx1 is the total output vector obtained as the row-
wise sum of T and Y. From these entities, the technical coefficients matrix
Acsxcs can be defined, where each aij=tij/xj represents the fraction of value
incorporated in the production of sector j from sector i (being possible i=j).
Then, the Leontief inverse matrix, Lcsxcs=(I-A)-1, can be obtained, where I is the
identity matrix. Each element Iij of the Leontief inverse represents the total
requirements (both direct and indirect) for a given sector, indicating how much
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ReVisTa de economía mundial 65, 2023, 115-139
the production of that sector will grow with an increase in final demand by one
monetary unit.
In order to obtain the number of employees resulting from foreign trade, it
is necessary to calculate the employment intensity. E1xcs is defined as a vector
that collects, for each sector, the number of employees. The employment
intensity, e1xcs, is defined as follows:
Where X
is a square matrix that diagonalizes the total output vector. To
differentiate between the total employment and the employment linked to
a country’s exports, adjustments need to be made to the Leontief inverse
matrix. The diagonal submatrices of the matrix, with size sxs, represent the
domestic market, whereas the remaining elements depict foreign relations. To
determine the impacts on the domestic employment market, only the diagonal
submatrices’ elements are needed, with all other values null. The resulting
Leontief inverse matrix is called Lcsxcs.
Also, gross exports, EXPbcsx1, can be obtained by making similar
modifications to T and Y matrices, i.e., making the domestic market elements
null. Thus, the domestic employment resulting from foreign trade, Et
1xcs, can be
obtained as follows:
After obtaining E and Et, the level of domestic employment, Ed, can be
derived by determining the difference between the two elements. This value
represents the employment generated by domestic transactions. Additionally,
by distinguishing between employment by gender, the intensity and
employment variables defined in expressions (1) and (2) can be recalculated
for each gender. For instance, the number of employed men and women is
represented by Em and Ef respectively, while their employment intensities are
em and ef (e=em+ef). Finally, Et
m and Et
f are used to denote the employment
associated with foreign trade by gender and Ed
m and Ed
f to denote the
employment associated with domestic transactions.
Moving on to foreign trade indicators, the participation and position indexes
within GVCs require special attention. These indicators are conceptually
defined in Table A1. To calculate these indices, one should start by determining
the forward and backward participation ratios in the GVC, known as and
respectively. The forward participation is calculated as the ratio of domestic
value-added exports re-exported by third countries over gross exports, while
the backward participation is determined as the ratio of foreign value-added
exports over gross exports. From these ratios, the participation and position
indexes are usually obtained as follows:
124 Hugo Campos-Romero · Bruno Blanco-Varela
In order to meet the established objective, an econometric model was
developed using some of the variables outlined in Table A1. Due to the nature
of the data, a panel data estimation was chosen. Based on Hausman test, a
fixed effects versus random effects estimation is deemed more appropriate.
The employment gap, defined as Et
f /Et
m, is the dependent variable. Values
below unity indicate a higher proportion of male presence in export sectors.
The specification of the model is shown below, for countries in years:
The objective of this model is to study the impact of export specialization
in manufacturing and the type of participation in GVCs on the gender gap in
employment in export sectors. In addition to the variables related to technology
intensity, trade, and GVCs, various control variables are included, such as
the female activity rate, fertility rate, women’s participation in management
positions and national parliaments, and disparities in tertiary education
attainment between men and women. It also incorporates female participation
rates in different sectors of activity grouped by technological intensity. For
example, high-tech sectors may require specific skills and knowledge that
may not be available to women due to barriers in access to education and
training. Additionally, in some cases, the work culture and social norms may
discourage women from working in certain sectors. Finally, Table 1 shows the
main descriptive statistics of the variables used in the model.
Table 1. descRipTiVe sTaTisTics. n. of obseRVaTions: 297
Variable Mean Std. Dev. Min Max
GAP 0.66 0.10 0.44 0.92
GDP 33308.29 22664.48 6853 123678.7
PI -0.12 0.10 -0.41 0.02
ACT 65.96 7.11 40.4 81
FER 1.56 0.20 1.21 2.06
FPAR 25.76 10.08 8.7 46.99
FMNG 29.63 8.93 0 46.3
EDU 1.38 0.25 0.84 1.86
FHT 0.4 0.14 0 0.96
FMHT 0.22 0.11 0 0.47
FMLT 0.15 0.07 0 0.28
FLT 0.39 0.11 0 0.63
XH 7.29 5.61 0.68 28.39
XMH 19.57 9.9 3.09 45.19
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Variable Mean Std. Dev. Min Max
XML 13.01 4.7 2.73 30.96
XL 18.62 8.54 5.86 50.32
Source: Authors.
4. ResulTs
This section presents the key findings of the research and their implications
in two parts. The first subsection provides descriptive statistics on some of
the most relevant indicators outlined in section 3. Following this analysis, the
second subsection presents the results of the econometric analysis developed
using a panel data model relating the relationship between the employment
gap in foreign trade and various factors, such as the technological intensity
of exports, female empowerment, and comparative education outcomes,
among others.
4.1. descRipTiVe analysis
The term gender gap refers to the differences between men and women
in the labor market, including disparities in salaries and employment rates
(Morais, 2017). Despite progress in protecting women’s rights and promoting
work-life balance, there is still much to be done to achieve gender equality.
As mentioned in the literature review, trade liberalization has been found
to increase the number of women employed and to change the gender
composition of certain sectors in foreign trade. However, this does not always
lead to a decrease in the disparity between genders. Figure 1 shows the ratio of
female to male employment in export sectors across EU27 countries. A value
below unity indicates a greater male presence. This is used as the dependent
variable in the econometric model described in the following subsection.
On average across the EU, the results show that for every 10 men employed
in export sectors, there are only 7 women. In other words, approximately 40%
of the foreign trade workforce involves women. It is worth noting that none of the
countries in the sample have a value above unity. In 2018, the highest female
labor force participation rates in export sectors were observed in Slovenia, Italy,
Ireland, Romania, and Luxembourg, with rates close to 45% of the total. In
contrast, Greece, the Czech Republic, Portugal, Estonia, and others had rates
below 35%. Regarding changes between 2008 and 2018, it can be observed that
female participation remained relatively stable, with a few exceptions. Romania,
Hungary, Cyprus, and Sweden experienced a decrease in female participation
after the financial crisis, while Spain’s female participation increased.
Although a gender gap in employment exists in foreign trade sectors,
the situation in the domestic market is often different for many European
countries. When referring to the domestic market, only the level of domestic
employment is considered, excluding from the total the number of employees
in export sectors for each gender. Even in cases where there is still a disparity
126 Hugo Campos-Romero · Bruno Blanco-Varela
in employment between genders, the difference is typically smaller than in
export sectors. Figure 2 displays the ratio of female to male employment for
the domestic markets of the EU27 countries.
In 2018, the European average was at gender parity in 2018, improving
since 2008. Regarding the member countries, 14 out of the 27 had a higher
level of female participation than male employment volume, while a gender
gap continued to exist in the remaining 13. It is worth noting that gender
gaps in the domestic market are generally smaller compared to the foreign
market, except for Italy, Malta, Romania, and Greece, where the differences in
female participation are around 45% or less (still smaller than those revealed
by Figure 1 for these countries). Looking at the evolution of the indicator over
time, it’s worth noting that female participation in domestic employment has
increased in most European countries.
The literature review also examined the impact of technological intensity on
the gender gap. Descriptive analysis of the EU context shows that regardless
of the technological level of each sector, male participation is higher in
industry and manufacturing (see Figure 3). These differences are particularly
pronounced in medium-high and medium-low technology intensity sectors,
where women’s participation is less than 25% and 20%, respectively. However,
these differences are less significant in high and low technology sectors, which
traditionally have had a greater female presence, such as the pharmaceutical,
textile, and certain food industries (Blickenstaff, 2005; Wang & Degol, 2017).
On this occasion, no significant differences were found in female participation
between the two periods considered. Note that Figure 3 measures female
participation as a percentage of the total number of employees, not as a
percentage of male employees.
fiGuRe 1. GendeR Gap in foReiGn TRade employmenT, eu27 counTRies, 2008 and 2018
Source: Authors based on TiM (OECD, 2021 edition).
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Table A2 in Appendix A presents the percentage of domestic value-added
exports by technological intensity over total manufacturing exports. The results
show that, on average, 47.5% of total European manufacturing exports (both
intra- and extra-zone) are concentrated in sectors of medium-high technology
intensity, which have a low female participation in employment. In contrast,
high-tech exports, which have higher female representation, account for only
12.5% of domestic value-added manufacturing exports. Furthermore, most
female manufacturing jobs are concentrated in low technology-intensive
sectors, representing, on average, 53% in the EU (see Table A3 in Appendix A).
Finally, Figure 4 illustrates the GVC position index as defined in Expression
(4). This index reflects the kind of participation of each country in this type of
foreign trade, where a positive value indicates a greater progressive or forward
participation –higher share of domestic value-added reexported by third
countries–, while a negative value indicates a greater regressive or backward
participation in GVCs –higher share of foreign value-added exported–. The
position index is a complex indicator to interpret in terms of a country’s
competitiveness. Various factors must be taken into account, such as the stage
of development and the role of each country in the supply chain, or more
specifically, each sector of activity in each territory. All member countries
show some degree of backward participation, although there are significant
differences among them. Notably, Luxembourg and Malta stand out due to
their singular production structures.
If a country specializes in activities more closely linked to the final stages of the
value chain (such as marketing, sales, and after-sales), the position index tends
towards negative values. Conversely, countries that specialize in the exploitation
fiGuRe 2. female shaRe oVeR ToTal employmenT by TechnoloGy inTensiTy, eu27, 2008 and 2018
souRce: auThoRs based on Tim (oecd, 2021 ediTion).
128 Hugo Campos-Romero · Bruno Blanco-Varela
of natural resources and manufacturing, as well as R&D and design, tend to
show positive values (Rodil-Marzábal, 2017). In developed economies, industries
tend to specialize in R&D, design, and the final stages of the production chain,
leading low positive or negative values, close to 0. Note that most European
economies show values above -0.1, with a few exceptions. When interpreting the
results for Europe, it is important to consider the region’s strong dependence on
external resources. The GVC participation index (see Table A4 in Appendix A) is a
complementary indicator that measures the chains’ contribution to total foreign
trade. European countries have a high participation rate, averaging over 50%
For example, Italy, France, and Spain stand out, with a share of over 60%. The
country with the lowest share is the Slovak Republic, with 37%.
To understand its impact on gender participation in employment, it’s crucial
to consider the relevance of the productive sector. The productive structure is
conditioned by the sexual division of labor and the type of activities performed
by both genders. If women have lower participation in R&D or manufacturing
activities, their involvement in GVCs may lead to further disadvantages. This
concern is compounded by the low presence of women in manufacturing, as
shown in Figure 3. Furthermore, among European countries, medium-high
technology value-added exports are prominent (see Table A1), precisely one
of the sectors with the lowest female representation in employment.
Several factors influence the gender gap in employment, including the
technological intensity of different sectors and the importance of considering a
country’s position in GVCs. The GVC position index is mentioned as a complex
indicator reflecting a country’s position in foreign trade and competitiveness.
Furthermore, the low participation of women in higher value-added activities,
combined with Europe’s dependence on external resources, could limit
women’s empowerment in GVCs.
fiGuRe 3. female shaRe oVeR ToTal employmenT by TechnoloGy inTensiTy, eu27, 2008 and 2018
Source: Authors based on Eurostat (dataset: LFSA_EGAN22D).
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ReVisTa de economía mundial 65, 2023, 115-139
To provide a more comprehensive understanding of the gender gap
between socio-economic factors in the economies of the EU27 and their impact
on participation in foreign trade, a detailed examination is proposed in the
following section. This analysis will delve into various aspects of the relationship
between gender, socio-economic factors, and foreign trade, including but not
limited to the role of education. By examining these factors in depth, we aim to
provide a more nuanced perspective on the complex interplay between gender
and foreign trade participation in the EU27, and to identify potential avenues
for addressing the gender gap in this context.
fiGuRe 4. posiTion index in GVcs, eu27 counTRies, 2008 and 2018
Source: Authors based on TiVA (OCDE, 2021 edition).
130 Hugo Campos-Romero · Bruno Blanco-Varela
4.2. economeTRic ResulTs
This subsection describes the main results obtained from the estimation
of Expression (5) using a panel data and fixed effects model with the variables
described in Section 3 and Table A1 (see Table 2). The findings indicate that an
increase in exports, regardless of the level of technological intensity, tends to
worsen the gender gap in export sectors by increasing the proportion of male
workers relative to female workers. This effect is particularly pronounced in the
medium-high technology sectors, which not only have the highest export levels
within the manufacturing industry but also exhibit lower female participation rates.
These findings are consistent with the research conducted by Chowdhury
etal. (2021) and Granitoff and Hong Tiing Tai (2022), who suggest that an
increase in exports and trade openness contributes to an increase in gender
disparities. Similarly, Li etal. (2020) also supports this claim, albeit with more
nuanced results. Considering first that Li’s research focuses on Asian countries,
it suggests that initial increases in trade openness and foreign competition
may lead to higher female labor market participation. However, beyond a
certain threshold of trade openness, the gender gap may widen once again in
favor of men. Additionally, depending on the import substitution effect, these
inequalities could further increase.
The model produces varied results when it comes to the variables that
measure the proportion of female employment in manufacturing sectors by
technological intensity. Only participation in high and medium-low intensity
sectors shows significant results with opposite signs. Greater female participation
in high-tech intensity sectors would not help reduce the gender gap, while greater
participation in medium-low technology sectors would reduce the gender gap in
export sectors. These results can be explained by the findings depicted in Figure
3, where women’s participation in high-tech sectors is relatively high (around
40%) compared to medium-low intensity sectors, where there is still a significant
gender gap (less than 20% female representation).
Regarding the position index in GVCs, the results point out in the opposite
direction than technology intensive exports. Interpreting the effects of this index
is complex and requires relying on the results shown in Figure 4. Changes in this
index that result in increased forward participation appear to indicate a reduction
in the gender gap, while the opposite –greater backward participation– would
tend to increase the gap. An increase in forward participation would imply
greater involvement in global markets in the initial and intermediate stages of
the production chain, which could boost activity in sectors with higher female
participation (such as certain manufacturing and high-tech industries).
However, an intensification of the regressive position could lead to the
replacement of certain productive tasks by imports. If this substitution occurs in
sectors with a relatively higher female presence, it could lead to an increase in
the number of female workers. Conversely, if it occurs in sectors with a relatively
lower female presence, it could result in greater job losses among the female
population. In this regard, Dluhosch (2021) study suggests that an increase in
The ReducTion of The GendeR Gap ThRouGh Global Value chains: poliTical commiTmenT oR peRpeTuaTion of GendeR Roles?
ReVisTa de economía mundial 65, 2023, 115-139
import penetration would result in a wider gender gap, consistent with Li etal.
(2020) findings. Regarding its link with the position index, a greater quantity of
imports would correspond to a more regressive position within GVCs. Gagliardi
etal. (2019) also points out that a higher progressive position in GVCs would lead
to better salaries, although the distribution between men and women depends
to a large extent on gender parity in each case. This insightful finding highlights
the necessity of further exploring the impacts of GVCs on gender disparities.
Table 2. esTimaTion ResulTs. dependenT VaRiable: women To men woRkinG in expoRTinG secToRs
souRce: auThoRs fRom Tim
Variable Coefficient Standard error t
GDP -1.31E-06 4.31E-07 -3.04*
PI 0.5189563 0.1202727 4.31*
ACT 0.0003655 0.000623 0.59
FER -0.0584337 1.79E-02 -3.270*
FPAR -0.000897 0.0004 -2.140**
FMNG 0.0024537 0.0006 4.370*
EDU -0.0334915 0.0261 -1.280
FHT -0.0392383 0.0131 -2.990*
FMHT -0.0141325 0.0203 -0.700
FMLT 0.1361949 0.0425 3.200*
FLT 0.0373118 0.0376 0.990
XH -0.0030893 0.0010 -3.050*
XMH -0.0055916 0.0012 -4.580*
XML -0.0025853 0.0012731 -2.03**
XL -0.0018247 0.0011046 -1.65***
cons 1.008535 0.0882868 11.42
Rho 0.97 R2 within 0.27
F-prob 0 R2 between 0.06
Source: Authors based on TiM (OECD, 2021 edition), TiVA (OECD, 2021 edition), World Bank and
As for the GDP per capita, the econometric results indicate its statistical
significance with a negative coefficient, implying that an increase in income
level would exacerbate the gender gap within the export sectors. Nonetheless,
to make a conclusive statement based solely on the evolution of GDP per capita
would be oversimplifying. However, one can infer that further economic growth
in European countries cannot be considered a sufficient factor in reducing the
gender gap. However, multiple studies have agreed that policies targeted at
diminishing gender gaps can foster higher levels of economic growth (Agénor
etal., 2021; Agénor & Canuto, 2015; Dheer etal., 2019).
Regarding the control variables, the analysis indicates that the female activity
rate is not a significant factor, while the proportion of women in parliament has
yielded counterintuitive results. Therefore, it is possible that this variable is
inadequate in explaining the employment gap in export sectors. Meanwhile, the
132 Hugo Campos-Romero · Bruno Blanco-Varela
fertility rate and the proportion of women in management positions were both
significant at the 1% level, with negative and positive signs, respectively.
The finding that a higher fertility rate leads to a larger gender gap may
be attributed to established gender roles in society. Despite advances in
work-life balance policies (Goldin & Mitchell, 2017), in addition to the time
women have to devote to pregnancy, they tend to take more time off work or
assume the primary responsibility for caregiving and household duties (Cortés
& Pan, 2020). When examining individual countries, it is important to take into
account the effectiveness of work-life balance policies, as they can facilitate
the simultaneous increase of fertility rates and women’s participation in the
labor market (Vitali & Billari, 2017). The proportion of women in management
positions serves as a proxy variable for the gender gap’s evolution and the
situation with respect to the so-called glass ceiling effect (Bear etal., 2017;
Haveman & Beresford, 2012; Said-Allsopp & Tallontire, 2015). A better value
for this variable reflects greater gender parity in society.
Finally, the rho indicator measures the proportion of variance attributable
to individual effects in the panel data model, indicating the extent to which
unobserved heterogeneity factors across countries explain the variance of
the dependent variable. A higher value suggests the existence of substantial
differences among the analyzed countries. This finding emphasizes the
importance of considering not only the variables included in the model but
also the specific circumstances of each economy. Additionally, the index
underscores the relevance of employing a panel data and fixed effects model
to examine this matter in the European context. Moreover, this could provide
an explanation for the results obtained from certain variables, such as the lack
of significance of the education variable, which may be heavily influenced by
the specific demand for human capital in each country, as well as the non-
significant impact of the female activity rate. The differences between the R2
within (which explains how the model fits for each country) and the R2 between
(which explains how the model fits to understand the differences between the
different countries) are consistent with the rho index obtained, since these
variables do not capture the differences between the results of each country.
5. conclusions
The gender gap represents a significant impediment to the development
of nations, affecting not only developing economies but also persisting
within more developed ones. Therefore, it is crucial to examine the impact of
international relations, particularly participation in GVCs on gender inequality.
On the one hand, increased participation in foreign markets can create new
economic opportunities for women, particularly in the export sector. This can
result in higher incomes, reduced poverty, and overall economic improvement.
However, international trade can also lead to intensified competition and the
relocation of jobs, affecting women in precarious and low-skilled positions
disproportionately. This is especially pertinent in the current trade landscape,
The ReducTion of The GendeR Gap ThRouGh Global Value chains: poliTical commiTmenT oR peRpeTuaTion of GendeR Roles?
ReVisTa de economía mundial 65, 2023, 115-139
heavily defined by GVCs, which entail a significant fragmentation of production
processes. Thus, the aim of this paper is to delve into the relationship between
the gender gap, global value chains, technological intensity of exports and
female empowerment in the EU-27. Specifically, it analyzes how integration in
GVCs affects gender inequalities.
This paper uncovers several significant findings. Firstly, the results indicate
that an increase in exports, regardless of the level of technological intensity,
tends to worsen the gender gap in export sectors by amplifying the proportion of
male workers compared to female workers. This effect is particularly noticeable
in medium-high technology sectors, which not only exhibit the highest export
levels within manufacturing but also display lower female participation rates.
Secondly, we demonstrate the intricate and nuanced nature of the effects
GVCs on gender inequalities. Depending on the type of participation (forward
or backward), the impact on inequalities may vary. Thirdly, a priori, increasing
manufacturing exports contributes to widening the gender gap. This finding
aligns with the observation of disparities between internal and external labor
The study revealed various obstacles to women’s integration into export-
driven markets, which justify the development and implementation of policies.
Firstly, enhancing women’s education and training is crucial to improve their
skills and knowledge in high-demand areas of the labor market, which are
vital for future economic growth. Additionally, promoting women’s education
in STEM fields and ensuring their access to technology training and education
are essential. Secondly, ensuring social protection for women in vulnerable and
precarious sectors, particularly in low-tech export-intensive sectors, is imperative.
This may entail implementing social security policies, combating workplace
discrimination and harassment, and implementing measures to support work-
life balance. Lastly, it is recommended that institutions facilitate women’s entry
into traditionally male-dominated industries by promoting their representation
in decision-making bodies associated with international trade, such as ministries
of commerce, chambers of commerce, and business organizations.
This work arises future lines of research. Firstly, it is crucial to delve deeper
into the effects of global value chains (GVCs) by differentiating between types
of participation and examining their potential impact on gender inequalities.
Secondly, considering the indication of variations among European countries,
it becomes necessary to analyze these variables within groups of countries
sharing similar characteristics.
This research has been supported by the ICEDE research group, to which
the authors belong, Galician Competitive Research Group ED431C 2022/15
financed by Xunta de Galicia and project “REVALEC” REFERENCE PID2022-
141162NB-I00 Financed by MCIN/ AEI / 10.13039/501100011033 / EFRD,
134 Hugo Campos-Romero · Bruno Blanco-Varela
annex a
tabLe a1. description of variabLes incLuded in the research
Dimension Indicator Description Source
Employment embodied
in trade Gap in employ-
ment embodied in
trade (GAP)
Gap in domestic
Number of employees linked to export sectors. In-
cludes direct and indirect jobs (see Expression (2))
Ratio between the number of women and men working
in export sectors. If the ratio is less than 1, it indicates
a greater representation of men in exporting workforce
Ratio between the number of women and men working
in non-export sectors. If the ratio is less than 1, it
indicates a greater representation of men in domestic
female social
Women in management
Women in national
parliaments (FPAR)
Fertility rate (FER)
Female activity rate
Proportion of females in total employment in senior
and middle management
Proportion of parliamentary seats in a single or lower
chamber held by women
Number of children that would be born to a woman if
she were to live to the end of her childbearing years
and bear children in accordance with age-specific fertil-
ity rates of the specified year
Percentage of active women in relation to the total
comparable population between 15 and 64 years of
World Bank
High-technology VAD
exports (XH)
gy VAD exports (XMH)
gy VAD exports (XML)
Low-technology VAD
exports (XL)
Domestic value-added exports of high technological
intensity. Only includes the value generated in the
domestic country
Domestic value-added exports of medium-high techno-
logical intensity. Only includes the value generated in
the domestic country
Domestic value-added exports of medium-low techno-
logical intensity. Only includes the value generated in
the domestic country
Domestic value-added exports of low technological
intensity. Only includes the value generated in the
domestic country
Female em-
ployment by
High-technology (FHT)
gy (FMHT)
gy (FMLT)
Low-technology (FLT)
Ratio of women to total employment in high-technol-
ogy sectors
Ratio of women to total employment in medium-high-
technology sectors
Ratio of women to total employment in medium-low-
technology sectors
Ratio of women to total employment in low-technology
Gap in tertiary educa-
tion (EDU)
GDP per capita (GDP)
Participation Index
Position Index (PI)
Ratio between males and females in the success rate in
tertiary education (ISCED 5-8)
GDP share over population
The participation index in GVCs reflects the degree to
which a country performs in this category of foreign
trade with respect to its total exports. It is measured
as the sum of the backward and forward participation
indexes (see Expression (3))
Measure of a country’s position in GVCs. A score
above 0 indicates a higher relative volume of domestic
value-added exported by third countries while a lower
score indicates a higher relative volume of foreign
value-added exports (see Expression (4))
World Bank
Source: Authors.
Note 1: Eurostat sectoral classification has been used to determine the degree of technological intensity.
Note 2: The column “indicator” specifies the abbreviations of the variables employed in the
econometric model.
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Table a2. shaRe of domesTic Value-added expoRTs by TechnoloGy inTensiTy oVeR ToTal manufacTuRinG,
eu27 counTRies, 2018
High-tech Medium-high-tech Medium-low-tech Low-tech
Austria 8.72 41.08 24.97 25.23
Belgium 20.14 32.75 24.89 22.22
Bulgaria 6.47 28.43 32.65 32.45
Croatia 8.49 19.52 28.59 43.41
Cyprus 22.01 12.93 10.82 54.23
Czech Republic 9.48 52.14 21.90 16.49
Denmark 31.68 29.36 11.24 27.72
Estonia 8.10 22.00 18.04 51.86
Finland 10.90 34.40 21.90 32.80
France 12.63 51.05 15.09 21.23
Germany 11.19 61.38 14.73 12.69
Greece 6.48 15.73 43.41 34.38
Hungary 16.39 47.48 19.29 16.84
Ireland 47.64 15.49 12.98 23.90
Italy 6.22 45.02 20.45 28.31
Latvia 6.55 15.36 13.29 64.80
Lithuania 3.54 21.18 19.10 56.18
Luxembourg 2.36 15.57 64.09 17.98
Malta 39.89 9.17 7.72 43.22
Netherlands 11.78 41.26 16.23 30.74
Poland 5.65 35.65 24.63 34.07
Portugal 5.91 27.84 23.31 42.94
Romania 6.98 54.19 13.51 25.32
Slovak Republic 5.44 51.47 27.79 15.30
Slovenia 14.29 37.84 28.44 19.43
Spain 6.28 43.07 22.82 27.82
Sweden 8.99 49.73 19.24 22.04
Source: Authors based on TiVA (OECD, 2021 edition).
Table a3. female employmenT by TechnoloGy inTensiTy oVeR ToTal female manufacTuRinG employmenT
(%), eu27 counTRies, 2018
High-tech Medium-high-tech Medium-low-tech Low-tech
Austria 11.00 24.24 24.30 40.46
Belgium 13.91 21.52 15.09 49.48
Bulgaria 4.23 13.96 14.25 67.57
Croatia 6.68 11.59 8.46 73.28
Cyprus 19.30 - 15.79 64.91
Czechia 7.82 33.83 23.78 34.57
Denmark 26.96 24.04 11.69 37.32
Estonia 8.60 10.93 9.30 71.16
Finland 11.61 23.80 15.58 49.01
France 10.30 20.76 19.90 49.04
136 Hugo Campos-Romero · Bruno Blanco-Varela
Germany 11.51 31.81 17.18 39.50
Greece 7.59 5.77 10.26 76.39
Hungary 15.37 30.29 12.97 41.37
Ireland 40.00 - - 60.00
Italy 6.93 22.98 19.24 50.85
Latvia ----
Lithuania 2.14 10.18 11.36 76.31
Luxembourg ----
Malta 26.79 10.71 8.93 53.57
Netherlands 6.16 17.90 16.08 59.86
Poland 5.95 22.94 18.94 52.16
Portugal 3.80 14.75 13.43 68.03
Romania 3.04 24.39 9.45 63.12
Slovakia 8.86 38.72 20.39 32.02
Slovenia 10.93 33.54 23.60 31.93
Spain 7.87 22.98 16.18 52.97
Sweden 8.99 36.47 19.15 35.39
Source: Authors based on Eurostat (dataset: LFSA_EGAN22D).
Table a4. GVc paRTicipaTion index, eu27 counTRies, 2018
Participation Index in GVC
Austria 53.97 Italy 78.59
Belgium 59 Latvia 55.49
Bulgaria 61.81 Lithuania 53.65
Croatia 48.94 Luxembourg 46.73
Cyprus 54.38 Malta 67.02
Czech Republic 52.19 Netherlands 56.74
Denmark 46.3 Poland 42.45
Estonia 46.25 Portugal 47.68
Finland 46.47 Romania 54.06
France 63.31 Slovak Republic 37
Germany 53.57 Slovenia 48.92
Greece 43.01 Spain 63.01
Hungary 45.54 Sweden 47.67
Ireland 52.23
Source: Authors based on TiVA (OECD, 2021 edition).
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