Empowering Absence? Assessing the Impact of Transnational Male Out-Migration on Left behind Wives

Abstract

Experiences of left-behind family members of transnational migrant workers have been in the shadow of academic discourse on migration. To contribute to the slowly growing body of literature, this study explores the impact of male out-migration on left-behind wives. The study proposes and applies a novel framework to estimate Women Empowerment Index (WEI) for comparing the empowerment level across households with and without men in transnational labor. Cross-sectional surveys and unstructured interviews were used to collect data from 373 respondents from three selected areas in Nepal. Results indicate that left-behind wives experience a higher degree of decision-making authority, physical mobility, and involvement in socio-political spheres compared to women with husbands at home. However, left behind wives were found to experience increased unpaid workload and decreased access to information, together with emotional and psychological costs in the absence of their husbands.

1. Introduction

The impact of male out-migration for transnational labor on the life and wellbeing of left-behind women is profound (Ullah 2017). On the one hand, financial transfer from migrating members benefits left-behind family members, including women, economically and reduces financial vulnerability. Such changes in financial stability in the household due to remittance inflow also impact the economic behavior and labor force participation of left-behind members (Mishra et al. 2022). On the other hand, male out-migration also involves social costs with substantial physical, psychological, and social consequences on left-behind members, especially wives (Mahapatro 2018). Some prior studies investigating the migration-left-behind nexus have reported mixed and sometimes contradictory results in terms of its impacts on the well-being of women. Some studies indicated that male out-migration could enhance mobility, decision-making power, and social participation as well as improve access to assets and resources of left-behind wives (Iqbal et al. 2014; Fleury 2016; Agadjanian and Hayford 2018), while some have also indicated that left-behind wives are physically and economically more vulnerable given their limited job opportunities, high dependence on remittances, increased unpaid domestic work and institutionalized patriarchy (Torres and Carte 2016; Wu and Ye 2016; Mahapatro 2018). These differences in results could be due to diverse geo-social contexts, household structures, and differences in research approach and methods used by different researchers (Ghimire et al. 2021b).

Brink (1991) investigated the effects of Egyptian men’s emigration on their wives and found that rural Arab women whose husbands have emigrated experience a greater degree of decision-making ability and autonomy if they live in a nuclear family. Furthermore, De Snyder (1993) studied the lives of Mexican wives left-behind following male migration and found that they experience stress associated with the acquisition of new responsibilities and obligations, family disintegration, as well as social and emotional isolation due to the absence of their husbands. Bever (2002) looked at the transformation of gender roles and hierarchies in Yucatan, Mexico, following male migration. Domestic and social roles of women in Yucatan are re-defined following the migration process; however, traditional gender relations continue to be upheld and defended by both men and women. Nguyen et al. (2006) reviewed the well-being of left-behind women in Asia and reported that left-behind women are often vulnerable to increased workload and exploitation, as well as mental and physical health issues due to their husbands’ absence. Biao (2007) examined the effects of male migration on left-behind women in rural China and found that left-behind women are vulnerable to exploitation and poverty due to their lack of education, employment opportunities, and access to social support networks. In the Lamerd district, Iran, Aghajanian et al. (2014) did not find any conclusive pattern on the impact of husband’s migration on women’s domestic and agricultural workload. Desai and Banerji (2008) examined the identities and roles of left-behind wives in India and found that wives often have to redefine their identities and roles in the absence of their husbands. Graham et al. 2015) looked at the mental health of those left behind and found that left-behind women often experience depression and anxiety due to increased financial and emotional burdens.

The impacts of male out-migration on left-behind wives are more distinct in impoverished households, where gender roles are defined by conservative patriarchic values (Mahapatro 2018), such as in rural Nepal. In the absence of males, apart from performing traditional gender roles, women are supposed to assume additional domestic and social responsibilities that were undertaken by their husbands prior to the out-migration (Saha et al. 2018). Such increased responsibility in the absence of males could result in the gradual breakdown of the conventional gender roles leading to the expansion of women’s involvement in different spheres of society (Radel et al. 2010). Maharjan et al. (2012); Pandey (2021); Gartaula et al. (2010) and Kaspar (2005) explored the impact of male out-migration on rural women in Nepal. Maharjan et al. (2012) found that rural women who stayed behind benefit from male out-migration in terms of increased access to resources and decision-making power; however, they also experience increased workload and decreased social support. Pandey (2021) conducted a study in the Kaligandaki Basin, Nepal, and found that male out-migration has altered gender roles and increased food insecurity in the basin. Gartaula et al. (2010) conducted a study in Jhapa District, Eastern Nepal, and found that male out-migration has led to the feminization of agriculture, with an increased number of women working in the agricultural sector. Kim et al. (2019) indicated that male out-migration could lead to an increase in food insecurity due to a decrease in male agricultural labor in rural Nepal. Kaspar (2005) found that female-headed households are more vulnerable to poverty, but male out-migration can bring increased autonomy and empowerment to women. However, how exactly and to what extent the absence of males impacts the well-being of left-behind women is still under-discussed in academic discourse, specifically in the context of rural Nepal. It has now become a highly relevant topic also in need of a comprehensive and robust framework for investigation.

To contribute to the above-discussed academic discourse, this study investigated the impacts of male out-migration for transnational labor on left-behind wives. The study uses the concept of women empowerment as an indicator of the well-being of left-behind women. Cross-sectional survey data from three selected areas of Nepal were used to estimate and compare the empowerment of women among the households with and without male migrants. A pragmatic approach for estimating the women empowerment index (WEI) is proposed and used in the study as a framework for estimating and comparing the impact of male out-migration. In addition, information and data from unstructured interviews and group discussions were used for triangulating and further exploring the underlying dynamics of male out-migration and its consequent effects on left-behind wives.

2. Contextual Background

2.1. Transnational Labor Migration (TLM)

It is estimated that globally over one billion people are migrants (Bachmann et al. 2019), of which around 763 million have migrated within their own country (Bell and Charles-Edwards 2013), while 272 million (3.5% of the global population) have migrated internationally (IOM 2020). In recent decades, the international labor market has become a major driver of transnational mobility as transnational migrant workers constitute around 62.5% (164 million) of the internationally migrated population, contributing up to 18.5% of the workforce of high-income countries (ILO 2018). Today, transnational labor migration (TLM) has grown widespread, having significant socio-economic, cultural, political, and environmental implications for sending and receiving countries (Ghimire et al. 2021a).

The population from the South Asian region makes up an ample proportion of the transnational migrant workers as the region is characterized by the interminable loop of economic distress, natural hazards, and increasing vulnerabilities associated with climate change (Basnet et al. 2021). In return, remittances to South Asia have risen significantly over the last few decades contributing significantly to the economic, social, political, and technological transformations of the countries in the region (IOM 2020). In 1995, the region received just USD 5 billion as remittances, but the amount has increased by 2520 percent (to USD 131 billion in 2018) in the subsequent two and a half decades (Basnet et al. 2021).

Nepal, a mountainous country in South Asia, has been undergoing unprecedented changes in its socio-economic, cultural, and ecological landscape in past decades, largely driven by TLM. Agriculture has been the largest and broadest sector in Nepal, contributing about 25% of the national GDP (MOALD 2020) providing direct employment for more than 65% of the population (Ghimire et al. 2018). As the slowly growing and largely subsistence style of agriculture has not substantially served rural mountain communities of Nepal (Gauchan 2008), an increasing number of households have been changing and diversifying their livelihood strategy in the contemporary context of financial vulnerability and socio-environmental change (Chapagain and Gentle 2015). Migration for transnational labor has been the most preferred strategy for the majority of people for income generation and upward mobility. As a result, 56% of households in Nepal have at least one family member working and living abroad (CBS 2011).

In a country with a population of 29.1 million, the Department of Foreign Employment (DOFE) of Nepal issued over 4 million labor approvals for Nepali workers to work abroad in the last decade (Figure 1), the majority of which was for the time-bound employment contracts, concentrated in the oil-rich Gulf countries and Malaysia (MLESS 2020). In return, TLM has become a significant component of Nepal’s ‘remittance economy’ (Seddon et al. 1998), with remittances accounting for up to 30 percent of the national GDP (Sunam et al. 2021). According to the World Bank (2021), Nepal ranks as the top remittance-receiving country in South Asia and the seventh largest in the world in terms of GDP share. TLM has also been seen as a major driver of poverty reduction in Nepal as remittances have played a key role in reducing poverty rates, with the poverty rate falling from 42% in 1996 to 32% in 2004, 25% in 2011 (Adhikari and Hobley 2015) and 17.4% in 2019 (UNDP 2021).

2.2. TLM in Academic Discourse

There exists an ever-growing body of academic literature focusing on the various dimensions of TLM. However, academic output on migration is dominated by perspectives from destination countries, especially in relation to Europe (IOM 2020). The studies on the impacts of TLM in relation to Nepal have also increased in the past decade, and the trend of discourses can be traced in three distinct trajectories. Firstly, increasing international migration is creating acute shortages of labor, a phenomenon leading to “empty villages” in sending regions of Nepal. Impacts of the declining population, predominantly of young men, upon the socio-cultural and agroecological aspects of rural and mountain regions of Nepal have received substantial attention in academic discourse (Fox 2018, Sunam 2020; Chhetri et al. 2021; Sugden et al. 2021). Secondly, the development of an extensive diasporas population around the world has connected them with the extended, transnational communities that have opened a new possibility of resources and networks for domestic developmental purposes (Gamlen et al. 2019; Kapri and Ghimire 2020; Sunam 2020). The contribution of remittances sent by the migrant population to the domestic economy, rural livelihood, food security, and the labor force participation of those left behind has also been studied significantly (Sharma 2020). Thirdly, the fate of labor migrants in various destination countries in terms of working conditions, labor rights, and other opportunities has also gained attention in academic discourse (Paudyal et al. 2020; Khatiwada et al. 2021; Pereira et al. 2021; Sharma et al. 2022; Valenta 2022).

2.3. TLM and Gender

TLM from Nepal is predominantly driven by males, as the share of female migrant workers accounted for only a little above 5% of total transnational labor migrants in the last decade (Figure 1) (MLESS 2020). The male-dominated nature of TLM from Nepal is partly explained by the patriarchal structure of Nepalese society, where males supposedly are the breadwinner for the family participating in the migration process, and women stay behind and take care of the family and children (Rajkarnikar 2020). Lower access to education and lack of relevant skills have also restricted women’s migration chances and mostly limited their employment opportunities to the domestic work sector in destination countries. In addition, the domestic work sector in foreign labor has been highly regulated for women in Nepal. The restrictions were employed as an effort to reduce vulnerabilities such as long working hours, physical abuse, and economic exploitation of women in transnational labor (MLESS 2020), specifically in the Gulf countries, where the welfare of migrant workers is mostly compromised. Such a restrictive policy has also made gender involvement in TLM disproportionately male-dominated.

As the TLM, migration research and related academic discourse have also been heavily gendered with a disproportionate focus on male migration experiences in early years (Pessar and Mahler 2003; Sultana 2014). The body of literature is slowing growing in the area of TLM and gender in the past decade; however, most of the studies have focused on the experience of migrating women and with relatively scant attention on the experience of women left behind (Sultana 2014; Rajkarnikar 2020; Sharma 2020; Ghimire et al. 2021b). Most of the literature among the few who looked into the impact of male out-migration on the left-behind women have cited Shrestha and Conway’s (2001) allegory of “living in the shadow”, which rightly summarizes their situation in Nepal: “Migrants’ wives exist in the shadow… in the shadow of their husbands, in the shadow of the mountains, and in the shadow of the academic discourse on migration”.

2.4. Theoretical Context

Prior discussions indicate that the impact of male out-migration on the status of left-behind women is complex and multifaceted and can depend on a range of factors, including cultural context, economic conditions, and the specific arrangements and support available to the left-behind spouse. The theoretical debate on the impacts of male out-migration on left-behind women can be broadly divided into two categories: (1) the gendered effects of male out-migration on the power dynamics of family structures and (2) the psychological effects of male out-migration on left-behind women. In terms of the gendered effects of male out-migration, the present consensus is more inclined towards the argument that male out-migration can lead to changes in the power dynamics of family structures, with left-behind women taking on new roles as primary caregivers and breadwinners (Bever 2002; Brink 1991; De Snyder 1993). This can have implications for the economic, social, and psychological well-being of left-behind women (Nguyen et al. 2006). In terms of the psychological effects of male out-migration, contemporary research work suggests that the separation of men from their families can have a negative emotional impact on left-behind women, leading to anxiety and depression (Desai and Banerji 2008; Aghajanian et al. 2014; Graham et al. 2015).

3. Methods

3.1. Study area and Data Collection

Although TLM is prevalent in all regions of Nepal, three districts (Sarlahi, Gulmi and Kailali) among 77 districts were selected as the study area in this research (Figure 2). While selecting the study areas, three criteria were considered. Firstly, selection was made on the basis of the predominance and intensity of TLM as indicated by the number of total male absentee population referring to the Nepal census report 2011 (CBS 2011). Secondly, geographical heterogeneity was considered such that the finding could be extrapolated to larger and more diverse population groups. Thirdly, researcher’s own judgments were also used depending upon the convenience and constraints associated with logistics, budget, and time factors.

A structured questionnaire survey was administered among women in 373 households of 3 selected study areas. Sample households with and without males in transnational labor were identified and selected purposively, ensuring the participation of respondent women from diverse ethnic groups, castes, household structures, and age groups. A research team of 4 enumerators led by the author conducted a survey in the selected households during the last two weeks of February 2022. The enumerators were fluent in the local language with skills in ethnographic research methods. Each household survey was accompanied by direct observations, life histories, and informal interviews. A total of 6 (2 in each study area) group discussions were conducted on the topic of male out-migration, empowerment, mobility, decision-making, and social participation of women. The group discussions involved the participation of women from diverse backgrounds, including farmers, housewives, members of local women’s organizations, mother groups, and saving cooperatives.

3.2. Women Empowerment-Concept and Framework

While there exist numerous definitions of women empowerment in academic discourse, adhering to an emic perspective rather than an etic view seems very sensible (Meinzen-Dick et al. 2019; Doss et al. 2022) but equally problematic. Some authors have criticized the use of quantitative studies, especially the index-based approach to estimate empowerment levels, for being too etic, rigid, and not grounded upon the sensitivity and reality of the local context. However, Moser (1993) argues that the origins of the empowerment approach are derived from the emergent feminist writings and grassroots organizational experience of the third world rather than the research of the first world women. This article argues that the concept of women empowerment is, therefore, sensible and more grounded upon the reality of the third world context and attempts to study it in relation to any other phenomenon in the society and with any methodological approaches that are not only justifiable but imperative. While developing the index-based approach for estimating the women empowerment index, I, therefore, chose to consider the theoretical underpinning of the empowerment approach as well as its relevance to the local context of our study area (Kabeer 1999).

From Women in Development (WID) to the Gender and Development (GAD) concept of gender theory, the central debate has been on whether economic advancement alone increases the empowerment of women. The empowerment approach points out that the existing structures and agencies in societies are the sources of subordination of women that shapes the status of women in society (Kabeer 1999). Some authors have argued that economic development does not necessarily empower women and that factors such as mobility, decision-making power, time/work burden, and control of income may affect empowerment (Simon-Kumar 2011). On the other hand, World Bank (2011); Kabeer et al. (2011); and Morshed and Haque (2015), amongst others, have argued that economic advancement does, in fact, lead to women’s economic independence, control over funds, mobility, decision-making, and participation in public domains of society.

In the background of our TLM context, what happens to the empowerment status of left-behind wives after the migration of their husbands? Are they more empowered in terms of their decision-making authority, freedom of mobility, participation in public spheres, and unpaid workload? A pragmatic approach to empirically estimate the empowerment level in the form of the women empowerment index (WEI) is developed to answer the above-mentioned questions.

3.3. Women Empowerment Index (WEI)

There have previously been some attempts to estimate and express women’s empowerment in the form of composite indices that could be applied for assessing and comparing empowerment levels across spatial and temporal scales. Gender-related Development Index (GDI), Gender Empowerment Measure (GEM), and Gender Inequality Index (GII) developed by UNDP (United Nations Development Program) between 1995–2010 were among the attempts that used a combination of different components such as gender gaps in life expectancy, education, women’s relative income, participations in high paying economic positions, power and access to professional and parliamentary positions as indicators of empowerment (Roy et al. 2018). However, these indices of empowerment typically provide an estimation at the aggregate country level, define gender empowerment in a broad set of domains and do not measure empowerment directly at the individual or community level, and cannot be disaggregated by age, region, or other social groups (Alkire et al. 2013). Women’s Empowerment in Agriculture Index (WEAI), developed in 2012, provides a survey-based alternative with multi-dimensional, comprehensive, and standardized measures to directly measure women’s empowerment and inclusion, however, limited to the agricultural sector. Nevertheless, the development of a multidimensional tool such as WEAI has opened the possibility of estimating context-specific WEI in several fields, integrating the context-specific indicators associated with empowerment (Roy et al. 2018).

On the foundation of previous tools such as WEAI, this article proposes a new multidimensional and comprehensive framework for estimating WEI for our research context of male out-migration and left-behind women. WEI was categorized into 5 major components and 17 indicators, as illustrated in Figure 3. While selecting the indicators of WEI, 3 major criteria were considered: (a) relevancy to the study context; (b) review of literature, and (c) experts’ judgment. While estimating the composite WEI, our assumption is that the selected component and their respective indicators have either a positive or negative impact (as described in

Table 1. WEI components, indicators, indicators’ relation to empowerment, and criteria for selection of indicators. RSC and EJ refer to Relevance to Study Context and Experts’ Judgement, respectively.

WEI Component	Indicator	Relation with WEI	Criterion for Selection of Indicator
Decision- Making Index (DMI)	Decision regarding own health (DMI1)	(+)	Yogendrarajah (2013); Cunningham et al. (2015); Rajkarnikar (2020), RSC
	Decision regarding health and education of children (DMI2)	(+)
	Decision regarding important purchases and sales (DMI3)	(+)
	Decision regarding agricultural activities or business (DMI4)	(+)
Mobility Index (MI)	Mobility for education for self and children (MI1)	(+)	Doss et al. (2022); Malapit et al. (2013), RSC
	Mobility for work (MI2)	(+)
	Mobility for visiting friends and relatives (MI3)	(+)
	Mobility to participate in social events and festivals (MI4)	(+)
Unpaid Work Index (UWI)	Time used in child and elderly care (UWI1)	(−)	Ghosh and Chopra (2019); John (2020), RSC
	Time used in fetching water and firewood (UWI2)	(−)
	Time used in cooking, cleaning, and washing (UWI3)	(−)
Information Index (II)	Education level (II1)	(+)	RSC and EJ
	Access to TV, newspaper, or a radio (II2)	(+)
	Access and ability to use internet (II3)	(+)
Leadership and Participation Index (LPI)	Membership of local NGO/CBO (LPI1)	(+)	Acharya et al. (2007), RSC, EJ
	Positive attitude and acceptance of women leaders (LPI2)	(+)
	Involvement in local politics (LPI3)	(+)

) upon the empowerment aspect of women shaped/influenced by the migration status of husbands.

3.4. Calculating the Indices

The individual indicators of WEI components were quantified and standardized based on the responses to the specific questions asked during the survey. The process involved in calculating indices is discussed below.

3.4.1. Decision-Making Index (DMI)

While calculating DMI, four indicators of decision-making regarding (a) own health (DMI1), (b) health and education of children (DMI2), (c) important purchases/sales (DMI3), and (d) agricultural activities or business (DMI4) were considered. Questions were formulated in a simple local language and asked the respondents who makes the final decision regarding DMI1, DMI2, DMI3, and DMI4 in the household. To answer the question, the respondent could choose one category out of 3 possible categories, i.e., (i) husband and/or other family members, (ii) respondent and husband, and (iii) respondent alone. Respondents making final decisions alone were given a score of 2, respondents making decisions jointly with husbands were given a score of 1, while respondents not involved in decision-making were given a score of 0. The score from each response was added together to generate the final score of each respondent. Finally, for standardization of the score, the following formula was used to estimate the final DMI for individual households:

DMI_i = [(X_i − X_min)/(X_max − X_min)] × 100

where DMI_i is Decision Making Index for respondent i, X_i is the observed individual score of respondent “i” on decision-making, and X_min and X_max are the maximum and minimum scores on decision-making among all respondents.

3.4.2. Mobility Index (MI)

For Mobility Index (MI), four indicators of mobility associated with freedom of mobility for (a) education for self and children (MI1), (b) work (MI2), (c) visiting friends and relatives (MI3), and (d) participation in social events and festivals (MI4) were considered. Questions were formulated in a simple local language and asked the respondents whether they felt they had the autonomy to travel regarding MI1, MI2, MI3, and MI4. To answer the question, the respondent could choose one category out of 3 possible categories, i.e., (i) Yes, (ii) No, and (iii) Partly yes and no. Respondents reporting full autonomy on mobility were given a score of 2, respondents with partial autonomy on mobility were given a score of 1, while respondents with no autonomy on mobility were given a score of 0. The score from each response was added together to generate the final score of each respondent. Finally, for standardization of the score, the following formula was used to estimate the final MI for individual households:

MI_i = [(X_i − X_min)/(X_max − X_min)] × 100

where MI_i is the mobility index for respondent i, X_i is the observed individual score of respondent “i” on mobility, and X_min and X_max are maximum and minimum scores on mobility among all respondents.

3.4.3. Unpaid Work Index (UWI)

Respondents were asked how many hours per day they use in child and elderly care (UWI1), fetching water and firewood (UWI2) and cooking, cleaning, and washing (UWI3). To calculate the total unpaid domestic workload, UWI1, UWI2 and UWI3 were added together and expressed in terms of the total number of hours per week spent by a woman in a household on unpaid domestic work. Finally, for standardization of the score, the following formula was used to estimate the final UWI for individual households:

UWI_i = [(X_i − X_min)/(X_max − X_min)] × 100

where UWI_i is the unpaid work index for respondent i, X_i is an observed total unpaid domestic workload (hours/week) for respondent “i”, X_min and X_max are the maximum and minimum unpaid domestic workload (hours/week) among all respondents.

3.4.4. Information Index (II)

Respondent’s education level (II1), access to TV, newspaper, or radio (II2), and access and ability to use the internet (II3) were considered as the indicators of II. Depending on their education status, each respondent was assigned the following score (II1): university education = 5, secondary school = 4, lower secondary school = 3, primary education = 2, informal education = 1, and never been to school = 0. Respondents with and without access to TV, newspaper, or radio were given a score of 1 and 0, respectively (II2). Similarly, respondents with and without access and the ability to use the internet were given a score of 1 and 0, respectively (II3). The score from each response (II1, II2, and II3) was added together to generate the final score of each respondent. Finally, for standardization of the score, the following formula was used to estimate final II for individual households:

II_i = [(X_i − X_min)/(X_max − X_min)] × 100

where II_i is the information index for respondent i, X_i is the observed individual score of respondent “i” on access to information, and X_min and X_max are maximum and minimum scores on access to information among all respondents.

3.4.5. Leadership and Participation Index (LPI)

Three indicators regarding socio-political engagement and attitude of women were used to estimate LPI depending on their (a) affiliation to local NGO/CBO (LPI1), (b) attitude and acceptance of women leaders (LPI2), and (c) involvement in local politics (LPI3). Respondents with and without affiliation with at least one NGO/CBO were assigned a score of 1 and 0, respectively (LPI1). Respondents were asked whether they believed there should be more women leaders in their society. Respondents with the answer “yes” were given a score of 1 and “no” with 0 (LPI2). Similarly, respondents engaged and not engaged in local politics were given a score of 1 and 0, respectively. The score from each response (LPI1, LPI2, and LPI3) was added together to generate the final score of each respondent. Finally, for standardization of the score, the following formula was used to estimate final II for individual households:

LPI_i = [(X_i − X_min)/(X_max − X_min)] × 100

where LPI_i is the leadership and participation index for respondent i, X_i is the observed individual score of respondent “i” on leadership and participation, and X_min and X_max are the maximum and minimum scores on leadership and participation among all respondents.

3.4.6. Weighting of Components and Final WEI Calculation

For this study, equal weights were assigned to all five components to calculate the final WEI, implying that each component equally affects the empowerment aspect of women. Despite the limitation and criticism, assigning equal weights avoids subjectivity and bias and makes indexes more comparable and transparent (Pandey et al. 2012). Assigning equal weights can be considered justifiable also because arbitrarily assigning random weights or even statistically produced weights could produce unjustifiable weight values and questionable results. However, a rigorous participatory approach including stakeholder’s and expert’s judgment could have been used to produce unequal weights.

The equation expressed below was used to calculate the final WEI. As the Unpaid Work Index (UWI) has a negative relation with WEI, its expressed in terms of inverse function in the equation. The final WEI score range from 0 to 100 (0 being the least empowered and 100 being the most empowered situation):

WEI = [DMI + MI + II + LPI + (UWI)−1]/5

4. Result and Discussion

4.1. Descriptive Statistics and Influence of Household Structure

The socio-economic and cultural context of our study areas provides a unique opportunity to examine the influence of transnational out-migration of men on family dynamics, traditional gender roles, and dimensions of women empowerment. The heterogeneous background (

Table 2. Descriptive characteristics of the respondents.

Respondent’s Background	Men in TLM		Men not in TLM		Total
Age	No. of HHs	% of HH	No. of HHs	% of HH	No. of HHs	% of HH
15–24	25	6.70	52	13.94	77	20.64
25–34	78	20.91	76	20.38	154	41.29
35–44	57	15.28	40	10.72	97	26.01
45+	25	6.70	20	5.36	45	12.06
Total	185	49.60	188	50.40	373	100
Ethnicity
Bramhin/chettri	50	13.40	73	19.57	123	32.98
Janajati	80	21.45	55	14.75	135	36.19
Madeshi	39	10.46	42	11.26	81	21.72
Dalit	16	4.29	18	4.83	34	9.21
Total	185	49.60	188	50.40	373	100
Education level
No education	20	5.36	26	6.97	46	12.33
Primary	74	19.84	56	15.01	130	34.85
Secondary	72	19.30	85	22.79	157	42.09
University	11	2.95	9	2.41	20	5.36
Informal	8	2.14	12	3.22	20	5.36
Total	185	49.60	188	50.40	373	100
Household structure
Living with in-laws (Extended)	142	38.07	157	42.09	299	80.16
Not living with in-laws (Nuclear)	43	11.53	31	8.31	74	19.84
Total	185	49.60	188	50.40	373	100
Involved in income-generating activities
Yes	76	20.38	63	16.89	139	37.27
No	109	29.22	125	33.51	234	62.73
Total	185	49.60	188	50.40	373	100

) of the respondents also provides an opportunity to document the role of various factors coupled with male out-migration on the empowerment aspects of left-behind women. Most of the respondents were Janajati (36.19%), followed by Brahmin/Chhetri (32.98%), Madeshi (21.72%), and Dalit (9.21%) ethnic background. Among the respondents, very few (5.36%) had a university education, while most of them had a secondary (42.09%), followed by a primary (34.85%) level of education. About 12.33% of respondents had never been to school, while 5.36% had some form of informal education. Respondent’s education level was found to be consistently identical among both households with and without men in transnational labor.

The majority of the respondents (80.16%) lived in an extended family together with in-laws, while the rest, 19.84%, lived in a nuclear family. Further disaggregating nuclear households, the data indicates a trend that a higher proportion of left-behind women with husbands in TLM tend to live in a nuclear family (59.46%) compared to respondents with husbands at home (40.54%) (Figure 4). This tendency was also coherent with the narratives presented by the participants in interviews and group discussions. During unstructured interviews, women living in a nuclear family and with husbands in TLM reported that they had to move to cities and urban centers, most commonly for the purpose of educating their children in private schools. A typical respondent in Sarlahi said, “Our children are our only hope, and we would do anything to provide them good education in private schools (…which we could not get) so that they will take care of us well in future. We now live separately near Milanchowk (local urban center) as it is convenient to send my children to school. I often visit my in-laws, but happy that I am able to live together with my children…”. Similar results and narratives were also reported by Doss et al. (2022), that looked into the strong effect of women’s social location in terms of family structure on their empowerment.

During the interviews and discussion, we noted that male TLM had been the leading reason for the disintegration of the extended family into small nuclear families in all the study areas. More than 90% of the respondents living in the nuclear family reported that they separated from their extended family after 2–5 years of their husband’s migration. When inquired about the impact of the transition from extended to the nuclear family, most respondents reported an experience of increased decision-making autonomy, mobility, and access/control over remittance income, together with changes in responsibility and domestic workload.

4.2. TLM and WEI

Respondents with husbands in TLM scored marginally higher overall WEI (32.02) compared to respondents with husbands at home (WEI = 30.39) (Figure 5). The result was consistent in Sarlahi and Kailali, while in Gulmi, WEI for women with men at home (32.64) was marginally higher than for women with husbands in TLM (29.34). Looking at the aggregate values of WEI components, respondents with husbands in TLM scored higher in decision- making index (DMI), mobility index (MI), and leadership index (LI), while respondents with husbands at home scored higher in the information index (II) and unpaid work index (UWI). This result was consistent in all three-study areas except for one component in Gulmi, where respondents with men in TLM scored higher in the information index (II).

The comparison of WEI for both categories of HHs indicates that, on average, women with husbands in TLM have higher decision-making authority than women with husbands at home. A two-sample t-test showed a significant difference in WEI score between HHs with men in TLM (DMI = 25.38, SD = 15.90) and men not in TLM (DMI = 20.68, SD = 19.06); t(361) = 2.59 and p < 0.01. The finding holds consistent across three study areas, confirming a significantly higher degree of decision-making power for women in migrant households. This finding is also consistent with narratives reported by respondents during interviews and group discussions. Most of the respondents implied that the presence of men in HHs limits women’s capacity to make important household decisions as men are conventionally entitled to make a final decision in a family, authorized by patrilineal norms. Our finding is coherent with Rajkarnikar (2020), who expected that women in households with a migrant male have higher decision-making power in a similar study context in Nepal.

In terms of freedom for physical mobility, corresponding MI scores indicate that wives with husbands in TLM are more likely to exercise significantly greater autonomy in mobility (MI = 20.09, SD = 21.17) compared to women with men at home (MI = 13.58, SD = 16.22); t(345) = 3.37 and p < 0.01. During interviews, we noted three possible explanations for the higher degree of mobility among women with men in TLM. First, the absence of a husband necessitates women to take over unconventional domestic and social roles that enable them to become more mobile. Most of the respondents reported that they had to take over the chores and responsibilities outside the household, previously being taken care of by the husband. Second, the compounded effect of increased decision-making capacity, inclination to live in a nuclear family, and a greater sense of freedom in the absence of men have led women to stay more mobile by their own choice. Third, the inflow and access to remittance income have enhanced the financial capacity of women to become increasingly mobile. Similar results were reported by Fakir and Abedin (2021); Desai and Banerji (2008); and (Rajkarnikar 2020) in identical contexts of Bangladesh, India, and Nepal, respectively.

Women with husbands in TLM also scored significantly higher LI (27.73, SD = 30.36, t(368) = 2.45, p < 0.05), indicating a higher degree of socio-political engagement and positive attitude towards women leadership compared to women with husbands at home (LI = 20.24, SD = 28.5). Conventionally, the socio-political realm of rural Nepal has been a male-dominated enterprise with inadequate women’s involvement. The decade-long armed conflict led by Maoist insurgents between 1996–2005, the subsequent people’s movement in 2006, the abolition of the monarchy, and the establishment of the federal democratic republic of Nepal in 2008 all vowed to increase participation of women and marginalized groups in every sphere of society. Except for a few exceptions and promising policies, the decades-long aspirations are still unrealized and slowly transitioning. From our observations during this fieldwork, we noted that TLM of men has alone contributed significantly to expanding social engagement and political participation of women with unprecedented volume and intensity during the last decades. We argue that the transition is happening out of necessity in the absence of men rather than through the conscious attempts mandated by historical political transformations in past decades.

The increasing engagement of women in unconventional domains of HH and community has resulted in the feminization of various sectors. While the feminization of politics has been a slowly growing phenomenon, sectors such as agriculture have seen exceptional transformation caused by male out-migration. Feminization of agriculture has received increasing attention in academic discourse in recent years, and the evidence from Nepal can be an important and equally interesting topic for further exploration.

The calculated scores of UWI indicate that the absence of a husband increases the unpaid work burden on the left-behind wife. On average left-behind wives of migrant workers spend around 62.61 h per week in unpaid labor, while women with their husbands at home spend only 54.26 h per week (Figure 6). Findings from field observation and interviews show that the conventional gender division of labor and norms in Nepalese society disadvantage women by expecting them to assume most of the unpaid domestic responsibilities involving household chores, agricultural activities, and child and elderly care. Although women’s engagement in remunerative employment has increased in recent decades, the absence of men in households due to TLM has significantly affected labor force participation and the unpaid domestic workload of left-behind wives. During interviews, two major mutually reinforcing causes were identified. Firstly, the inflow of remittance from the migrating member has enhanced the financial capabilities and reduced the household’s necessity to engage left behind members, especially wives, in remunerative employment. This has led left-behind wives to spend more time at home and invest more time in unpaid domestic work. Secondly, the absence of a husband instinctively has added domestic responsibilities that were previously carried out by husbands on left-behind wives.

During the unstructured interview conducted throughout the survey, left-behind wives appeared satisfied with the enhanced financial capacity due to the inflow of remittances. Most of the respondents asserted that migration was an inevitable step for the “secure future” of their families and children. It was also noted that many women with their husbands at home also wanted their husbands to go abroad for transnational labor, as it has apparently been the most successful strategy for upward mobility for rural households. However, most of the left-behind wives also reported mixed experiences in terms of physical and mental well-being. Issues such as increased domestic and agricultural workload, difficulties disciplining young children, loneliness, and mental stress were most frequently reported by left-behind wives. Although through our objective indicators, we reported an enhanced empowerment level of left-behind wives, the question of subjective well-being is equally important and requires further investigation with a proper methodological approach.

Based on the results presented, it appears that transnational out-migration of men can have an impact on the family dynamics, traditional gender roles, and levels of empowerment for women. The majority of the respondents in the study were from Janajati and Brahmin/Chhetri ethnic backgrounds and had secondary or primary levels of education. Most respondents lived in extended families, but a higher proportion of women with husbands in transnational labor lived in nuclear families. These women reported increased decision-making autonomy, mobility, and access to remittance income as a result of the transition to nuclear family structures. Overall, women with husbands in transnational labor had higher levels of empowerment, as measured by the Women’s Empowerment Index (WEI), compared to those with husbands at home. However, this difference was only statistically significant for the decision-making and mobility components of the WEI. Additionally, the WEI scores for women with husbands in transnational labor were higher in Sarlahi and Kailali, but not in Gulmi. It is also worth noting that the WEI scores for women with husbands in transnational labor were lower in the unpaid work and leadership components compared to those with husbands at home.

5. Conclusions

Consistent with several studies conducted in the region, our study reveals that the husband’s migration status, together with household structure, plays a detrimental role in the overall empowerment of women. Wives of husbands in TLM are more inclined to live in a nuclear family that enables them to live independently and make independent decisions regarding daily life and children. They are more likely to have greater physical mobility as well as more social and political engagements than women living with their husbands. However, left-behind wives experience increased unpaid workloads and suffer more emotional and mental stress.

To sum up, the transnational migration of men has far-reaching effects on the lives of wives left behind. As transnational migration is often driven by a need for economic betterment, and when men move abroad, the gender roles and responsibilities within households often become more unconventional and unequal. In many cases, the women left behind become the sole managers of their households and are often forced to assume additional responsibilities, which can result in increased labor and psychological burden. This also leads to a decrease in economic and educational opportunities for women, as their time and resources are diverted to the upkeep of their families.

This study suggests that although male out-migration has positive effects on left-behind wives in rural Nepal, such as increased mobility and increased decision-making power, it has also had some negative effects, such as increased workload, psychosocial stress, risk of de-agrarianization, and food insecurity. It is important to understand the complexities of the situation and develop policies that can address the negative impacts of male out-migration and ensure that rural women are able to benefit from the opportunities that male out-migration offers. Based on the findings and discussion of this study, there is an immediate necessity to establish a social policy framework to protect the rights of migrant laborers and their families, including left-behind wives, that ensure their access to the resources needed to support themselves and their families. Ensuring and/or expanding educational opportunities for left-behind wives of transnational laborers, specifically on topics such as financial literacy, entrepreneurship, and job skills, could produce substantial benefits to left-behind women and their households. Similarly, expanding access to financial services such as microcredit and microfinance would help left-behind wives become more financially independent and better able to support themselves and their families. Promoting the access of left-behind wives to social networks and support systems, such as social clubs and networks of other wives of transnational laborers, can be highly beneficial. Ensuring access to mental health services such as counseling and treatments can help them to cope with the stress of being left behind.