A blurred mapping of internal female migration 

The Periodic Labour Force Survey (PLFS) is an important survey conducted by the National Sample Survey Organisation (NSSO) under the Ministry of Statistics and Programme Implementation (MoSPI) of the Government of India. It provides valuable data on employment and unemployment in India, which is crucial for understanding labour market dynamics and informing policy decisions.

Key Findings of the PLFS 2022-23 Report

• Overall improvement in the labour market: The PLFS 2022-23 report showed an overall improvement in the labour market compared to previous years. The Worker Population Ratio (WPR) increased from 39.2% in 2021-22 to 40.0% in 2022-23, and the Labor Force Participation Rate (LFPR) increased from 57.4% to 58.0%. The Unemployment Rate (UR) also decreased from 8.3% to 7.8%.
• The gender gap persists: However, the report also found that the gender gap in the labour market persists. The male WPR was 54.4% in 2022-23, compared to only 25.7% for females. The male LFPR was 68.9%, compared to only 47.2% for females. While there has been some improvement in recent years, the gender gap in the labour market remains a significant challenge.
• Rural-urban disparities: The report also found that there are significant disparities in employment and participation rates between rural and urban areas. The WPR in urban areas was 44.8% in 2022-23, compared to only 35.8% in rural areas. The LFPR in urban areas was 60.5%, compared to only 55.9% in rural areas. These disparities highlight the need for targeted policies to improve employment opportunities in rural areas.

Economic factors

• Lack of employment opportunities and low wages in rural areas is a major push factor, especially for young men looking for better livelihoods.
• With a high population density, many rural families struggle to make a living from agriculture, leading them to seek opportunities elsewhere.
• Cities offer more diverse job opportunities, higher incomes, and access to better education, healthcare, and other amenities.
• Many people, especially from drought-prone regions, engage in seasonal migration to find work in construction, agriculture, or other sectors.

Social factors

• Marriage is a significant reason for migration, particularly for women who move to their husband's village after marriage.
• Students often migrate to cities for higher education, sometimes staying on for work opportunities afterwards.
• People belonging to disadvantaged castes or religious minorities may migrate to escape discrimination or violence.

Environmental factors

• Droughts, floods, cyclones, and other natural disasters can displace people from their homes and livelihoods, forcing them to migrate.
• The increasing frequency and intensity of extreme weather events due to climate change are also pushing people to migrate, particularly from areas experiencing desertification or rising sea levels.

The Female Labour Force Participation Rate (FLFPR) in India has been a topic of much discussion and concern in recent years. As of October 2023, the FLFPR in India stands at 37.0%, according to the latest Periodic Labour Force Survey (PLFS). This is a significant increase from the 32.8% recorded in 2021-22. The FLFPR in India has historically been low compared to other countries. It declined from 34.1% in 1999-00 to 27.2% in 2011-12 but has seen a recent upward trend.

Variations

1. Urban vs Rural: The rate is higher in urban areas (42.3%) compared to rural areas (31.7%).
2. Age Groups: The rate is highest for women aged 25-29 (52.4%) and lowest for those aged 15-19 (20.8%).
3. Sectors: The rate is highest in agriculture (45.3%) and lowest in construction (10.7%).

Factors Affecting FLFPR

• Gender stereotypes and societal expectations can limit women's mobility and participation in the workforce.
• Limited access to affordable and quality childcare and education can restrict women's ability to work outside the home.
• A large proportion of women work in the informal sector, which often has lower wages and less job security.
• Women may lack the skills required for formal sector jobs.

4. Challenges in Capturing Accurate Data on Female Migration and Employment

Inadequacies in Primary Reason for Migration Data

National surveys like the Periodic Labour Force Survey (PLFS) often present an incomplete picture of female migration by focusing solely on the primary reasons for relocation. According to PLFS data, 81% of female migrants cite marriage as their main reason for migration, with family-related reasons and employment trailing behind at 10% and 2.42%, respectively. Notably absent from such surveys are secondary motivations like climate shocks and food insecurity, which can significantly influence women's decision to migrate.

Misleading Labour Force Participation Figures

The PLFS data on the labour force participation of migrant women may be misleading due to various factors. During the data collection period coinciding with the COVID-19 pandemic, approximately three-quarters of migrant women were reported as unemployed, 14% were in self or wage-employed positions, and 12% were engaged in casual labour. However, anecdotal evidence and research by scholars like Sonalde Desai and Ashwini Deshpande indicate that many migrant women are involved in casual employment, suggesting an underestimation of their participation in sectors such as agriculture, construction, and domestic work.

Definitional Issues and Underreporting

Definitional challenges contribute to the underreporting of employment among migrant women. National surveys typically consider only those with formal contracts as part of the labour force, leading to the classification of many women as unemployed. Overlooking the fact that women often choose flexible employment options to balance domestic responsibilities and contribute to household income, these surveys miss capturing women working as unpaid family workers or in self-employed capacities. Women may view such contributions as an extension of their domestic duties rather than formal employment, resulting in a misrepresentation of their employment status.

5. Human and Social Capital Barriers to Female Labor Force Entry

Educational Disparities and Employment Challenges

Despite the arguments presented, the entry of women into the formal labour force faces significant challenges, and a crucial factor limiting their participation is the need for enhanced human and social capital. According to PLFS data, 85% of women have less than 10 years of education, potentially creating obstacles to their employment opportunities. Although there is no substantial difference in the educational levels between migrant and non-migrant women, migrant women are proportionally less employed than their non-migrant counterparts.

Social Networks and Post-Migration Challenges

The lack of social networks, particularly after migration, further compounds the difficulties faced by women in securing employment. The absence of strong social connections can significantly impede their chances of finding suitable work opportunities.

Impact of Barriers on Post-Pandemic Recovery

These barriers may also contribute to the slow recovery of women's labour activity post the COVID-19 pandemic. A study conducted by Yale University found that after the pandemic-induced lockdown, 55% of women never returned to their workplaces. For those who did return, their earnings were only 56% of pre-pandemic income levels.

Invisibility and Marginalization of Female Migrants

Despite the significant increase (101%) in female migration for labour/employment between 2001 and 2011, migrant women remain largely invisible in official labour force counts, facing substantial hurdles and marginalization. This invisibility results in unaddressed challenges and a lack of targeted policies. From a political perspective, migrant women are not a substantial vote bank, leading to neglect of their needs by political parties. This neglect is reflected in policy-making that inadequately considers the unique needs, motivations, and conditions of female migrants.

Policy Gaps and Gender Disparities

Current policies, such as One Nation One ration card, eShram, and affordable rental housing complexes, primarily target the male migrant population, reflecting a lack of awareness and consideration for the distinct challenges faced by female migrants. The absence of targeted policies perpetuates gender disparities and reinforces the misconception that migrant men and women have identical needs. Addressing these issues is crucial to developing well-informed policies that cater to the diverse requirements of both male and female migrants.

6. Steps to Address the Challenges Faced by Female Migrants

Enhanced Data Compilation in National Surveys

To address the inadequacies in understanding the socio-economic conditions of female migrants, national surveys should expand their scope to compile more comprehensive information post-migration. Currently, the Periodic Labour Force Survey (PLFS) reports that only about 7% of female migrants have access to social security benefits, leaving a significant portion unaccounted for. The inclusion of additional data on social and economic conditions will provide a more accurate representation of the challenges faced by female migrants.

Incorporation of Time-Use Data

The incorporation of time-use data is crucial to advancing knowledge about unemployed female migrants. Presently, India lacks comprehensive time-use data for migrants. Making time-use data a standard component of surveys will offer valuable insights into how female migrants allocate their time and can contribute to a better understanding of their challenges and opportunities.

Shift in Narrative and Increased Female-Specific Data Collection

A fundamental change in narrative is essential, starting with an increased focus on collecting female-specific data. This shift will help dispel anecdotal perceptions and raise awareness about the unique challenges faced by female migrants. By highlighting their experiences and struggles, there is an opportunity to encourage progressive policymaking that addresses the specific needs of this vulnerable demographic.

7. Conclusion