case studies on gender inequality in india

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Gender equality.

Every child deserves to reach her or his full potential, but gender inequalities in their lives and in the lives of those who care for them hinder this reality.

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Accelerating progress and opportunities across India for every girl and every boy

Wherever they live in India girls and boys see gender inequality in their homes and communities every day – in textbooks, in movies, in the media and among the men and women who provide their care and support.

Across India gender inequality results in unequal opportunities, and while it impacts on the lives of both genders, statistically it is girls that are the most disadvantaged.

Globally girls have higher survival rates at birth, are more likely to be developmentally on track, and just as likely to participate in preschool, but India is the only large country where more girls die than boys . Girls are also more likely to drop out of school.

In India girls and boys experience adolescence differently. While boys tend to experience greater freedom, girls tend to face extensive limitations on their ability to move freely and to make decisions affecting their work, education, marriage and social relationships.

As girls and boys age the gender barriers continue to expand and continue into adulthood where we see only a quarter of women in the formal workplace.

Some Indian women are global leaders and powerful voices in diverse fields but most women and girls in India do not fully enjoy many of their rights due to deeply entrenched patriarchal views, norms, traditions and structures.

India will not fully develop unless both girls and boys are equally supported to reach their full potential.

There are risks, violations and vulnerabilities girls face just because they are girls. Most of these risks are directly linked to the economic, political, social and cultural disadvantages girls deal with in their daily lives. This becomes acute during crisis and disasters.

With the prevalence of gender discrimination, and social norms and practices, girls become exposed to the possibility of child marriage, teenage pregnancy, child domestic work, poor education and health, sexual abuse, exploitation and violence. Many of these manifestations will not change unless girls are valued more.                   

The solution

It is critical to enhance the value of girls by investing in and empowering them, with education, life skills, sport and much more.

By increasing the value of girls we can collectively contribute to the achievement of specific results, some short-term (increasing access to education, reducing anaemia), others medium-term (ending child marriage) and others long-term (eliminating gender-biased sex selection).   

Changing the value of girls has to include men, women and boys. It has to mobilize many sectors in society. Only when society’s perception changes, will the rights of all the girls and all the boys in India be fulfilled.

Empowering girls requires focused investment and collaboration. Providing girls with the services and safety, education and skills they need in daily life can reduce the risks they face and enable them to fully develop and contribute to India’s growth.

Girls have an especially difficult time accessing life-saving resources, information and social networks in their daily life.  Access to programmes specifically tailored to the needs of girls – with a focus on education and developing life skills, ending violence and incorporating the needs and contributions of girls from vulnerable groups, including those with disabilities, can strengthen the resilience of millions of girls. Long-term solutions designed with and for girls can further strengthen this resilience and be a pathway of transformational and lifelong opportunity for girls.

All girls, especially adolescent girls, need platforms to voice the challenges they face in everyday life and explore the solutions that work for them so they can build better futures for themselves and their communities.

UNICEF India’s 2018-2022 Country Programme has been developed in response to the identification of deprivations that Indian children face, including gender based deprivations. Each programmatic outcome is committed to a gender priority that is noted explicitly in its programme, budget and results. These include:  

• Health: Reducing excess female mortality under five and supporting equal care-seeking behaviour for girls and boys. (Example: front-line workers encourage families to take sick baby girls to the hospital immediately) 
• Nutrition: Improving nutrition of women and girls, especially by promoting more equitable eating practices (Example: women cooperatives develop and implement their own micro-plans for improved nutrition in their villages) 
• Education: Gender responsive support to enable out-of-school girls and boys to learn and enabling more gender-responsive curricula and pedagogy (Example: implementing new strategies for identifying vulnerable out of school girls and boys, overhaul of textbooks so that the language, images and messages do not perpetuate gender stereotypes) 
• Child protection: Ending child and early marriage (Example: supporting panchayats to become “child-marriage free”, facilitating girls and boys clubs that teach girls sports, photography, journalism and other non-traditional activities) 
• WASH: Improving girls’ access to menstrual hygiene management, including through well-equipped separate toilets in schools (Example: developing gender guidelines from Swacch Bharat Mission, supporting states to implement MHM policy) 
• Social policy: Supporting state governments to develop gender-responsive cash transfer programmes and supporting women’s leadership in local governance (Example: cash transfer programme in West Bengal to enable girls to stay in school, a Resource Centre for women panchayat leaders in Jharkhand) 
• Disaster risk reduction: Enabling greater gender disaggregation of information management for disaster risk reduction and more leadership and participation of women and girls (Example: greater women’s leadership and participation in Village Disaster Management Committees) 

In addition, three cross-cutting themes will support all outcomes: 

• Joint C4D-Gender strategy: UNICEF’s Communication for Development (C4D) team develops social and behaviour change communication to support each outcome. These communications prioritize efforts to change negative gender norms like unequal feeding, unequal investment in young girls and boys, harmful MHM practices and perpetuation of lower value of girls than boys through wedding dowry. 
• Advocating for and promoting equal value of girls: UNICEF’s Communications, Advocacy and Partnerships team works with media, influencers and gamechangers to advocate for UNICEF priorities, which, in the 2018-2022 programme, includes Equal Value of Girls and Boys. 
• Increasing and improving girls’ and women’s safe mobility: UNICEF India has begun work in some states to work on new programmes with new partners to improve the ability and freedom of women and girls, including to access government services like schools and hospitals.  

Strategic partnerships  

Key partners include the Ministry of Women and Child Development, especially its leadership of the Beti Bachao Beti Padao Programme, which UNICEF India is supporting at the national and state level. UNICEF India works closely with other UN agencies to support gender equality, especially with United Nations Population Fund and UN Women. Civil society organizations, including gender experts and activities are also key partners.  

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Platform work and gender inequalities - A case study from India

Over the past decade, the world has witnessed a rise in platforms and the growing platformization of work. These trends are also pervasive in India. While these developments have resulted in increased access to work for women, they are also characterized by a number of challenges. This episode examines these issues and offers some policy considerations for overcoming these challenges.

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Gender equality in India hit by illiteracy, child marriages and violence: a hurdle for sustainable development

Kishor parashramji brahmapurkar.

1 Department of Community Medicine, Government Medical College, Jagdalpur, Bastar, 494001 Chhattisgarh, India

Introduction

Gender equality is fundamental to accelerate sustainable development. It is necessary to conduct gender analyses to identify sex and gender-based differences in health risks. This study aimed to find the gender equality in terms of illiteracy, child marriages and spousal violence among women based on data from National Family Health Survey 2015-16 (NFHS-4).

This was a descriptive analysis of secondary data of ever-married women onto reproductive age from 15 states and 3 UTs in India of the first phase of NFHS-4. Gender gap related to literacy and child marriage among urban and rural area was compared.

In rural area all states except Meghalaya and Sikkim had the significantly higher percentage of women's illiteracy as compared to male. Bihar and Madhya Pradesh had higher illiterate women, 53.7% and 48.6% as compared to male, 24.7% and 21.5% respectively (P < 0.000). Child marriages were found to be significantly higher in rural areas as compared to urban areas in four most populated states.

There is a gender gap between illiteracy with women more affected in rural areas with higher prevalence of child marriages and poor utilization of maternal health services. Also, violence against women is showing an upward trend with declining sex-ratio at birth.

Gender refers to the socially constructed characteristics of women and men-such as the norms, roles and relationships that exist between them [ 1 ]. Gender inequality limits access to quality health services and contributes to avoidable morbidity and mortality rates in women, also gender inequality is unacceptable [ 1 , 2 ]. The Convention on the Elimination of All Forms of Discrimination against Women requires that women are accorded rights equal to those of men (equality) and that women be able to enjoy all their rights in practice [ 3 ]. Realizing the significance of the issue, the policy makers have included the issue of gender equality as one among seventeen Sustainable Development Goals (Goal-5) [ 3 ]. Encouraging gender equality is fundamental to accelerating sustainable development [ 3 ]. Some of the elements of gender equality are to abolish all forms of violence against all women and girls along with all destructive practices, such as child marriage and guarantee worldwide access to reproductive health and reproductive rights [ 3 ]. Social determinants of health such as education and gender equality are significantly responsible for health-seeking behavior and overall health outcomes. It has been known that improved education, partly reproduced by higher literacy rates is associated with higher incomes and better health indicators such as lower infant mortality rates (IMRs) and lesser population growth rate. Education of families, particularly of women has a 'multiplier effect' on development [ 4 ]. Child marriage and adolescent pregnancy, gender-based violence are among the many barriers that stand in the way of woman's' fully exercising their right to education [ 4 ]. No education limits hopes, declines family income, diminishes health, puts women at risk of trafficked and exploitation and bounds the economic advancement of entire countries [ 5 ]. Education for girls and women is the single most successful way to progress the lives of individual families as well as to bring economic expansion to poor communities worldwide [ 5 ]. Globally 31 million girls are out of school and two-thirds of illiterate adults are women [ 6 ]. Poverty, adolescent pregnancy, child marriage and prejudiced gender norms are some of the reasons that prevent girls from going to school [ 6 ]. Globally 39000 child marriages (marriage before the age of 18) occur daily and it is more common to young girls [ 7 ]. Child marriages not only contribute to illiteracy but also have complications related to pregnancy and childbirth. These complications are the leading cause of death in young women aged 15-19 [ 7 ]. Child marriages also make girls more susceptible to intimate partner violence(IPV) [ 7 ]. Marrying girls less than 18 years old has been embedded in gender discrimination, cheering premature and uninterrupted child-bearing and giving the predilection for boys' education [ 8 ]. Current worldwide prevalence figures indicate that about 1 in 3 (35%) of women worldwide have experienced intimate partner violence (IPV) [ 9 ]. Gender inequality and poor education are some of the reasons for IPV [ 9 ]. IPV can lead to unplanned pregnancies, induced abortions, gynecological problems and sexually transmitted infections [ 9 ]. It is necessary to disaggregate data and conduct gender analyses to identify sex and gender-based differences in health risks [ 1 ]. The overall aim of the study was to find the gender equality in terms of illiteracy, child marriages and spousal violence among women based on data from National Family Health Survey 2015-16 (NFHS-4).

Study design : The present study was a cross-sectional secondary data analysis of information that has been available from the first phase of National Family Health Survey 2015-16 (NFHS-4) [ 10 ]. NFHS-4, has given information on population, health and nutrition each State/Union Territory.

Setting : Primary data onto NFHS-4 had been collected from January 2015 to December 2015. The Ministry of Health and Family Welfare, Government of India assigned International Institute for Population Sciences, Mumbai as the nodal organization to conduct NFHS-4. In the first phase of NFHS-4, 15 states and 3 union Territories were covered (56% of total population). Fifteen States/Union Territories had been selected for study purpose was those, which were covered in first phase of NFHS-4; Maharashtra (MH), Bihar (BR), West Bengal (WB), Madhya Pradesh (MP), Tamil Nadu (TN), Karnataka (KA), Andhra Pradesh (AP), Telangana (TS), Assam (AS), Haryana (HR), Uttarakhand (UK), Tripura (TR), Meghalaya (ML), Manipur (MN) and Sikkim (SK). UTs were Goa (GA), Puducherry (PY) and Andaman and Nicobar (AN) [ 11 ].

Sample size : First phased of NFHS-4 had collected information about 2,91,431 households, 3,37,658 women and 48,342 men.

Variables : NFHS-4 had provided updates and evidence of developments in key population, health and nutrition indicators out of which literacy, child marriage; adolescent reproductive health, maternal health, domestic violence and sex-ratio had been included for the study purpose.

Data analysis : First the data for the above-mentioned variables of all States/UTs has been entered in Microsoft Office Excel worksheet and the gender gap for illiteracy was calculated using Chi-square test for urban and rural area. Then the prevalence of child marriages among girls was compared for area of residence (Urban versus Rural) and Chi-square value was calculated using Epi Info. For statistical tests, P < 0.05 was taken as the significant level. Data were then presented using tables, bar and line diagrams.

Ethical considerations : The study had utilized freely-available record available on the website of the following organization: the National Family Health Survey (NFHS)-4 [ 10 ], National Crime Record Bureau (NCRB) [ 12 ] and Census 2011 [ 13 ]. Because publicly-available database was used in this analysis, no ethical approval was sought.

Definitions : Literate: a person that can read and write with understanding in any language [ 13 ]. Child marriage: according to the prohibition of child Marriage Act, 2006 a child is a male who has not completed twenty-one years of age and a female who has not completed eighteen years of age. Child marriage is a contract between any two people of which either one or both party are a child [ 14 ]. Full antenatal care was defined as at least four antenatal visits, at least one tetanus toxoid (TT) injection and iron-folic acid tablets or syrup took for 100 or more days [ 10 ] . Intimate partner violence refers to behavior by an intimate partner or ex-partner that causes physical, sexual or psychological harm, including physical aggression, sexual coercion, psychological abuse and controlling behaviors [ 9 ].

Total population covered by phase I of NFHS-4 was 678.2 million over 15 states and 3 Union Territories (UTs).

Women's illiteracy (%) as compared to men's illiteracy (%) in urban and rural areas : Women's illiteracy in an urban area has been found to be significantly higher in 8 states and 2 UTs as compared to men's illiteracy and in the rural area; it was significantly higher in 13 states and 1 UT respectively ( Table 1 ). In an urban area, Bihar had a higher percentage of illiterate women (29.5%) as compared to men (11.2%), (P < 0.001), followed by Andhra Pradesh and Madhya Pradesh (MP). In the rural area, all states except Meghalaya and Sikkim had a significantly higher percentage of women's illiteracy as compared to male. Bihar and MP had higher illiterate women, 53.7% and 48.6% as compared to male, 24.7% and 21.5% respectively. (P < 0.000). Bihar and MP state with the population of total 176.7 million had higher women illiteracy in both urban and rural areas. This indicates gender inequality in education.

Distribution of states of India according to the gender gap in illiteracy among urban area as compared to rural area

Child marriages to women (%) in urban and rural areas : Child marriages to women were found to be significantly higher in rural areas as compared to urban areas in 4 most populated states (Maharashtra, Bihar, West Bengal and MP). West Bengal had a higher percentage of child marriages in both urban and rural area, 27.7% and 46.3% and the difference between urban and rural area was significant (P < 0.005) followed by Bihar, 26.9% and 40.9% of child marriages among urban and rural women respectively. (P < 0.026), though no statistically significant difference was observed in Andhra Pradesh, Assam and Tripura, the prevalence of child marriage among women was more than 20% in urban and more than 33% in rural areas of concerned states. The above findings point of the harmful practice of child marriages to women prevalent in most of the states and UTs of India. Goa was the only exception with child marriages significantly higher in an urban area as compared to a rural area as shown in Table 2 .

Child marriages of girls in rural and urban areas of some states and UTs of India

Reproductive health : Full Antenatal care (ANC) was lower in a rural area of states, Bihar (03%), followed by Tripura (6.8%) and MP (8.3%) as compared to the rural area of Tamil Nadu (43.8%). Also, full ANC coverage was found to be lower in an urban area of Bihar (6.6%), Tripura (9.8%), Uttarakhand (15.6%) and MP (19.5%) as compared to Telangana and Tamil Nadu with full ANC coverage of 47.7% and 46.3% respectively. Postnatal care (PNC) to mothers within 2 days of delivery was found lower in rural area of states with Bihar state in which only 41.1% of mothers received PNC from health personnel followed by Meghalaya (42.6%), Uttarakhand (49.1%) and MP (50.3%) as compared to better Post Natal Care in state of Telangana (79.1%) and Andhra Pradesh (77.8%) among states and 90.5% among UT (Goa).

Ever-married women that have ever experienced spousal violence (%) and adolescent pregnancy : The overall percentage of spousal violence among ever-married women was 25.2% in urban area and 31.2% in rural area. Spousal violence was higher in the rural area of Manipur (56.1%) followed by Telangana (47.6%), Tamil Nadu (44.2%) and Bihar (43.7%). Similar observations were noted in an urban area as shown in Figure 1 . Figure 2 shows a number of cases reported under the head of cruelty by husband and rape. There was an upward trend in a number of cases reported to the head of cruelty by husband and rape from the year 2010 to 2014. Percentage of adolescent pregnancy was higher in Tripura and West Bengal in the rural area (20.7% and 20.6%) as compared to an urban area (13.7% and 12.4%) respectively.

Distribution of states and UTs of India according to percentage of ever-married women who have experienced spousal violence

Distribution of number of cases reported as per National Crime Record Bureau (NCRB), India, under head of cruelty by husband and rape from the year 2005 to 2014

Sex ratio at birth for children born in the last five years (females per 1,000 males) : Sex ratio at birth was better in the rural area except for Telangana (865 females/1000 males), Haryana (867 females/1000 males) and Andhra Pradesh (880 females/1000 males). In urban areas, it was lower than 900 females/1000 males in all UTs and 8 states. It was lower in Sikkim (632 females/1000 males), Andaman and Nicobar (708 females/1000 males) and Haryana (785 females/1000 males) as summarized in Figure 3 .

Distribution of states and UTs of India according to sex-ratio at birth in urban and rural areas

In present study female literacy has been significantly lower as compared to male literacy in rural areas of 15 states and 3 UTs except for Meghalaya and Sikkim state and Goa and Andaman and Nicobar UTs. The reason for this may be several parents did not have permitted their female children to go to schools and another reason could be child marriage of girls [ 15 ]. Another reason might be that most people are below the poverty line and weren't conscious that children should get the free education according to the law [ 15 ]. Hence there is a gender gap between educations. The 11 th five-year plan had decided to reduce the gender gap in literacy to 10% points by 2012 [ 16 ]. However in present study gender gap was observed in rural areas of all states except Meghalaya and Sikkim. Also according to censuses held in 2001 and 2011, the percentage of female literacy in the country was 54.16% and 65.46% respectively. An increase in 11.3% during the period 2001-2011, however, this was 3.6% lower than that during the period of 1991-2001. This declining trend over a decade is a matter of concern for sustainable development as it affects women empowerment [ 17 ]. In a country like India, literacy is the core basis of social and economic growth. Though the government has made an act that each child under the age of 14 should get free education, the setback of illiteracy is still at large [ 15 ]. Similarly, Lailulo YA et al had observed gender gap between education in the Ethiopia and also noted that educated women with educational attainment of primary education and above are less likely got married at an early age than those who are uneducated [ 18 ]. Raj Anita et al had studied the prevalence of child marriage using National Family Health Survey-3 data and had found that the maximum frequency of child marriage among women having less than a secondary education and residing in the rural area [ 19 ]. Similar findings were noted in NFHS-4 data phase 1, among top 4 most populated states. West Bengal and Bihar had a higher percentage of child marriage, 46.3 and 40.9% respectively in rural areas. David R et al had also similar observations related to higher prevalence of child marriage to girls with less education and residing in rural areas [ 20 ]. Adolescent pregnancy or 'motherhood in childhood' is one of the gravest health hazards to young women in India. Patra S et al had observed that stillbirth and abortion were more widespread among younger adolescents and the proportion of live births (vs. stillbirth or abortion) was also advanced among women having 10 years or more education [ 21 ]. As per UNFPA, the girl with adolescent pregnancy bears end of her education along with shrinking away from her job prospects and her vulnerability to poverty and exclusion increases [ 22 ]. Impediments from pregnancy and childbirth were the leading cause of death among adolescent girls [ 22 ]. In the present study, it was observed that coverage of full antenatal care (ANC) in states was the lowest in rural Bihar 03% compared to rural Tamil Nadu, 43.8%.Ahmed S et al had observed that women with complete primary education are almost three times more likely to have made at least four ANC visits [ 23 ]. Bihar had 53.7% of women illiteracy in the rural area as compared to Tamil Nadu, 27.1%. Kawaguchi L et al. had noted that women that married young were less likely to utilize ANC [ 24 ]. Bihar had 40.9% of child marriages to the rural area as compared to Tamil Nadu, 18.3%. Birmeta K et al had observed that women with education were more than twice likely to attend ANC as compared with those who had no education [ 25 ]. Ensuring universal accesses to sexual and reproductive health and reproductive rights as agreed in accordance with the Programme of Action of the International Conference on Population and Development and the Beijing Platform for Action and the outcome documents of their review conferences. 'Gender equality means that the different behaviors, aspirations, and needs of women and men are considered, valued and favored equally' [ 26 ]. Gender equality is a matter of human rights. It is also a driver of development progress. Gender equality, rooted in human rights, is increasingly recognized both as an essential development goal on its own and as vital to accelerating sustainable development overall [ 27 ]. Sex ratio is defined as the number of females per 1000 males in the population and is an important social indicator to measure the extent of prevailing equity between males and females [ 28 ]. Though the overall sex ratio of the Country is showing a trend of improvement, the child sex ratio is showing a declining trend, which is a matter of concern. Child sex ratio (0-6 years) at country level was 945 in 1991, 927 in 2001 and has now declined to 914 in Census 2011 [ 27 ]. The sex ratio of birth is an indicator of the discrimination against the girl child and dreadful crimes such as female feticide. As per NFHS-4 child sex ratio was the lowest in urban Sikkim, 632 followed by Andaman and Nicobar and Haryana with child sex-ratio of 708 and 785 respectively. Gender inequality manifests itself in various forms, the most obvious being the tendency towards the continuously declining female ratio of the population of the last few decades [ 29 ]. Further research is needed to study the factors associated with declining female ratio of the population.

Limitations : This study had not covered all states and UTs of India. The datasets were not available for NFHS-4 at present, so detailed analysis was not done.

There is the gender gap between illiteracy with women more affected in rural areas with higher prevalence of child marriages and poor utilization of maternal health services. Also, the violence against women is showing an upward trend with declining sex-ratio at birth.

What is known about this topic

• 11 th five year plan of India had decided to reduce the gender gap between literacy to 10% points by 2012;
• Child sex ratio of India was 919 females/1000 males (as per Census 2011).

What this study adds

• 11 out of 15 States/Union Territories (73%) had gender gap of more than 10% in literacy ranging from 10% to 29% in the rural area as compared to urban areas in 6 States/Union Territories (40%) with the range of 10.7% to 18.2%;
• But as per the analyses of primary data of NFHS-4 which was collected from January 2015 to December 2015, child sex ratio of India is declining with lowest, 632/1000 females in urban area of Sikkim and below 800/1000 females in urban area of 5 states States/Union Territories.

Competing interests

The author declares no competing interests.

Acknowledgments

The author is obliged to the Ministry of Health and Family Welfare, Government of India and International Institute for Population Sciences, Mumbai for the data for research purpose from National Family Health Survey 2015-16 (NFHS-4).

Authors’ contributions

The author had participated sufficiently in the intellectual content, conception and design of this work and the analysis and interpretation of the data, as well as the writing of the manuscript. All the authors have read and agreed to the final manuscript.

Press release

Transforming MENtalities and Promoting Gender Equality in India

New Delhi, 18 December: Against the background of the global and pervasive epidemic of violence against women, the United Nations Educational, Scientific and Cultural Organization (UNESCO) organized a Partners’ Dialogue on Engaging Men and Boys for Gender Equality on 18 December 2019, at the UNESCO House, New Delhi.

The Dialogue witnessed the convergence of media, civil society organizations, donor agencies, bi-lateral and multi-lateral organizations, research institutions, and the private sector to discuss the challenges of addressing gender based violence in India and share lessons on engaging men and boys to work for Sustainable Development Goal 5 on Gender Equality.

A UNESCO preliminary stakeholders’ analysis presented during the Dialogue, identifies organizations and interventions working with men and boys across India to transform masculinities. The non-exhaustive analysis highlights the positive impact of campaigns like HeForShe (UnWomen), Mardon Waali Baat (The YP Foundation) and Bell Bajao (Breakthrough India), among many others. This analysis underscores the need for engagement with boys and men to eradicate gender based violence in India. The report further states that the social development ecosystem needs to prioritize the transformation of mentalities among boys and men.

The Dialogue began with academics and thought leaders deliberating on the historical roots and conceptualization of masculinities (i.e. what it is to be a man in a given society), in India. A major barrier highlighted during the dialogue was lack of awareness on these issues together with the lack of alternative models for what it is to be a man, to counter balance the hegemonic or prevailing conception of masculinities, which contribute to gender inequality or violence against women.

Subsequently, civil society and research organizations like the YP Foundation and The Abdul Latif Jameel Poverty Action Lab (J-PAL) presented findings of interventions that worked with men to address gender based violence and masculinities. The role of the private sector, multi-lateral bodies and national policy frameworks, was discussed in the final session of the day. 

The Dialogue concluded with the stakeholders identifying priority areas such as educational reforms, shifts in societal values and the role of community leaders. These thus delineates the path to move towards a society where men at the same time do not see their self-realization hindered by stereotypes or social constraints, and are empowered to make positive contributions to a peaceful and prosperous world where men and women can equally thrive.

For further information contact:

Rekha Beri, Public Information ( &#114;&#46;&#98;&#101;&#114;&#105;&#64;&#117;&#110;&#101;&#115;&#99;&#111;&#46;&#111;&#114;&#103; ) Nitya Agarwal, Public Information( &#110;&#46;&#97;&#103;&#97;&#114;&#119;&#97;&#108;&#64;&#117;&#110;&#101;&#115;&#99;&#111;&#46;&#111;&#114;&#103; )

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• Country page: India
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This article is related to the United Nation’s Sustainable Development Goals .

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What Happened When India Mandated Gender Diversity on Boards

• Ruth V. Aguilera,
• Venkat Kuppuswamy,
• Rahul Anand

New research found that while the policy did increase diversity, it didn’t necessarily change company cultures.

In recent research on diversity quotas in India, one of the first instances of an emerging market adopting gender quotas, the authors found that firms’ gender quotas represented a step in the right direction but did not go far enough. Firms which, at face value, seemed to be complying with gender quotas by appointing women on merit from outside the organization still “buffer” their existing activities through selective committee appointments, relegating the new female quota fillers to less consequential committees. For gender quotas to achieve their purpose as an internal corporate governance mechanism, corporate boards must embrace the appointment of well-qualified women who bring a valuable perspective to the board.

Gender quotas on corporate boards have emerged as a popular tool for policymakers to promote gender equality in the workplace. The movement began in 2003 when Norway instituted a 40 percent quota for women on its country’s corporate boards. Spain, Finland, Iceland, France, Israel, Kenya, Italy, Belgium, Portugal, Germany, and Austria have followed suit with their own quotas. In March 2020, the European Commission announced it would attempt to reach a gender balance of 50 percent within its own management structure by the end of 2024. In 2018, California became the first U.S. state to mandate gender quotas for publicly traded companies incorporated in the state or risk facing heavy fines. But do these top-level initiatives produce substantive change, or are they merely symbolic?

• RA Ruth V. Aguilera is the Darla and Frederick Brodsky Trustee Professor in Global Business at the D’Amore-McKim School of Business, Northeastern University. Her research interests are at the intersection of international corporate governance and sustainability. She is a Fellow at the Academy of International Business and the Strategic Management Society.
• VK Venkat Kuppuswamy is an Assistant Professor of Entrepreneurship & Innovation at the D’Amore-McKim School of Business, Northeastern University. His research investigates the influence of race and gender in entrepreneurship and other economic domains, including the evaluation of interventions that seek to mitigate racial and gender biases in these contexts.
• RA Rahul Anand is an Assistant Professor at Aarhus BSS, Denmark. His research interests revolve around corporate strategy and corporate governance in developing as well as developed economies.

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Good Practices in Gender Mainstreaming Case Studies from India

April 9, 2012.

The resource book collates a series of innovative initiatives undertaken by states/civil/ women groups to address discrimination and gender inequalities to facilitate experience sharing, mutual learning and replication in other parts of the country.

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The multiple faces of inequality in India

Post-doctoral research fellow in economics, Centre de Sciences Humaines de New Delhi

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Known for its caste system, India is often thought of as one of the world’s most unequal countries. The 2022 World Inequality Report (WIR), headed by leading economist Thomas Piketty and his protégé, Lucas Chancel, did nothing to improve this reputation. Their research showed that the gap between the rich and the poor in India is at a historical high, with the top 10% holding 57% of national income – more than the average of 50% under British colonial rule (1858-1947). In contrast, the bottom half accrued only 13% of national revenue. A February report by Oxfam noted 2021 alone saw 84% of households suffer a loss of income while the number of Indian billionaires grew from 102 to 142.

Both reports highlight not only the problem of revenue inequality but also of opportunity. While there may be disagreement between left and right on the ethics of equality, there is a consensus that everyone should be given the chance to succeed and the principle of fairness – and not factors such as birth, region, race, gender, ethnicity or family backgrounds – ought to lay the foundations of a level playing field for all.

Drawing from the latest pre-pandemic database from the Periodic Labour Force Survey of 2018-19, our research confirms this is far from the case in India. On the one hand, the country has had a consistently high GDP growth rate of more than 7% for nearly two decades, the exception being the period around the 2008 financial crisis. On the other hand, this income has failed to trickle down to India’s marginalised communities, with preliminary results pointing to a higher level of inequality of opportunity in the country than in Brazil or Guatemala.

Precarity as well as a large shadow economy also plague the country’s labour market. Even before the pandemic, only 30% to 40% of regular salaried adult Indian earners had job contracts or social securities such as national pension schemes, provident fund or health insurance. For self-employed workers, the situation is even more critical, even though these constituted nearly 60% of the Indian labour force in 2019.

Castes, gender and background still determine life chances

Our research indicated that at least 30% of earning inequality is still determined by caste, gender and family backgrounds. The seriousness of this figure becomes clear when it’s compared with rates of the world’s most egalitarian countries, such as Finland and Norway, where the respective estimates are below 10% for a similar set of social and family attributes.

The caste system is a distinctive feature of Indian inequality. Emerging around 1500 BC, the hereditary social classification draws its origins from occupational hierarchy. Ancient Indian society was thought to be divided in four Varnas or castes: Brahmins (the priests), Khatriyas (the soldiers), Vaishyas (the traders) and Shudras (the servants), in order of hierarchy. Apart from the above four, there were the “untouchables” or Dalits (the oppressed), as they are called now, who were prohibited to come into contact with any of the upper castes. These groups were further subdivided in thousands of sub-castes or Jatis , with complicated internal hierarchy, eventually merged into fewer manageable categories under the British colonisation period.

The Indian constitution secures the rights of the Scheduled Castes (SC), Scheduled Tribes (ST) and Other Backward Class (OBC) through a caste-based reservation quota, by virtue of which a certain portion of higher-education admissions, public sector jobs, political or legislative representations, are reserved for them. Despite this, there is a notable earning inequality between these social categories and the rest of the population, who consists of no more than 30% to 35% of Indian population. Adopting a data-driven approach we find that, on average, SC, ST and OBC still earn less than the rest.

While unique, the caste system is not the only source of unfairness. Indeed, it accounts for less than 7% of inequality of opportunity, something that’s in itself laudable. We will need to add criteria such as gender and family background differences to explain 30% of inequality.

In a country where femicides and rapes regularly make headlines, it comes as no surprise that women from marginalised social groups are often subject to a “double disadvantage”. For some states such as Rajasthan (in the country’s northwest), Andhra Pradesh (south), Maharashtra (centre), we find even upper-caste women enjoy fewer educational opportunities than men from the marginalised SC/ST communities. Even among the graduates, while the national average employment rate for males is 70%, it is below 30% for the females.

A temporary byproduct of rising growth?

Rising inequality could be dismissed as a temporary byproduct of rapid growth on the grounds of Simon Kuznets’ famous hypothesis , according to which inequality rises with rapid growth before eventually subsiding. However, there is no guarantee of this, least of all because widening gap between rich and poor is not only limited to fast-growing countries such as India. Indeed, a 2019 study found that the growth-inequality relationship often reflects inequality of opportunity and prospects of growth are relatively dim for economies with a bumpy distribution of opportunities.

Despite sporadic evidence of converging caste or gender gaps, our research shows an intricate web of social hierarchy has been cast over every aspect of life in India. It is true that some deprived castes may withdraw from school early to explore traditional jobs available to their caste-based networks – thereby limiting their opportunities. However, are they responsible for such choices or it is the precariousness of the Indian economy that pushes them down such routes? There is no straightforward answer to these questions, even if some of the “bad choices” that individuals make can result more from pressure than choice.

Given the complicated intertwining of various forms of hierarchy in India, broad policies targeting inequality may have less success than anticipated. Dozens of factors other than caste, gender or family background feed into inequality, including home sanitation, school facilities, domestic violence, access to basic infrastructure such as electricity, water or healthcare, crime rates, political stability of the locality, environmental risks and many more.

Better data would allow researchers studying India to capture the contours of its society and also help gauge the effectiveness of policies intended to expand opportunities for the neediest.

Created in 2007 to help accelerate and share scientific knowledge on key societal issues, the AXA Research Fund has supported nearly 700 projects around the world conducted by researchers in 38 countries. To learn more, visit the site of the AXA Research Fund or follow on Twitter @AXAResearchFund.

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Gendered Impact on Unemployment: A Case Study of India during the COVID-19 Pandemic

India witnessed one of the worst coronavirus crises in the world. The pandemic induced sharp contraction in economic activity that caused unemployment to rise, upheaving the existing gender divides in the country. Using monthly data from the Centre for Monitoring Indian Economy on subnational economies of India from January 2019 to May 2021, we find that a) unemployment gender gap narrowed during the COVID-19 pandemic in comparison to the pre-pandemic era, largely driven by male unemployment dynamics, b) the recovery in the post-lockdown periods had spillover effects on the unemployment gender gap in rural regions, and c) the unemployment gender gap during the national lockdown period was narrower than the second wave.

Introduction

The coronavirus disease (COVID-19) has adversely impacted labour markets all around the world. According to the International Labour Organization, the working hours lost in 2020 were equal to 255 million full-time jobs, which translated into labour income losses worth US$3.7 trillion (International Labour Organization 2021). Due to the existing gender inequalities, women were more vulnerable to the economic impact of COVID-19 (Madgavkar et al. 2020). The sudden closure of schools and daycare centres due to the Great Lockdown exacerbated the burden of unpaid care on women (Collins et al. 2020; Power 2020; Czymara et al. 2020; Seck et al. 2021). Women also disproportionately represented the accommodation, food services, and retail and wholesale trade sectors, which were worst-hit by the COVID-19 pandemic (Alon et al. 2020; Adams-Prassl et al. 2020; Bonacini et al. 2021). In most countries, women often work in these sectors without any work protection or job guarantee (United Nations Women 2020), leading them to loose their livelihoods faster than men while also dealing with their deteriorating mental health. India is an interesting case study with one of the lowest female labour force participation rates (LFPRs) globally to analyse how the COVID-19 pandemic exacerbated the pre-existing gender disparities in unemployment. According to the World Bank data, India’s female LFPRs was approximately 21% in 2019, the lowest among the BRICS nations (Brazil, Russia, India, China, and South Africa) and 26 percentage points lower than the global average. An even more troubling fact is that women’s LFPRs has been falling since the mid-2000s (Ghai 2018; Andres et al. 2017; Sarkar et al. 2019). Since the onset of the pandemic, women in India have been increasingly dropping out of the labour force. As seen in Figure 1, the greater female labour force, which comprises unemployed females who are active and inactive job seekers, has been lower than the pre-pandemic average since April 2020. The number of unemployed women actively looking for jobs has also been lower than the pre-pandemic average barring the months of April, May, and December in 2020. On the contrary, the number of women who are unemployed but inactive in their job search has risen drastically, albeit with minor fluctuations, during this period (Figure 2). A recent survey by Deloitte (2021) identified that the burden of household chores and responsibility for childcare and family dependents increased exponentially for women worldwide and more so in India due to the pandemic. The surveyed women mentioned increase in work and caregiving responsibilities as the main reasons for considering leaving the workforce.

Figure 1 : Percent Change in Female Greater Labour Force and Unemployed Active Job Seekers Compared to the Pre-pandemic Average

Source: Centre for Monitoring Indian Economy April 2020 - May 2021

Figure 2: Percent Change in Female Unemployed and Inactive Job Seekers Compared to the Pre-pandemic Average

Figure 3: Unemployment Rate in India (Percent)

Source: Centre for Monitoring Indian Economy Jan 2020 - May 2021  

This study analyses the effect of the COVID-19 pandemic on the gender unemployment gap from its onset until the second wave using the subnational-level monthly data from the Centre for Monitoring Indian Economy (CMIE). The gender unemployment gap is defined as the difference between male and female unemployment rates  ( Albanesi and Şahin 2018 ). We assess the gender unemployment gap during the COVID-19 pandemic compared to the pre-pandemic era using a difference-in-differences (DID) model. A preliminary investigation of the gender unemployment gap based on the raw data reveals that the gap declined in the lockdown period compared to the pre-lockdown period (Figure 3). We find the gender gap to widen during the second wave, albeit smaller than the pre-pandemic level.

Although a large number of national-level studies were conducted on the impact of the COVID-19 pandemic on unemployment (Estupinan and Sharma 2020; Estupinan et al. 2020; Bhalotia et al. 2020; Chiplunkar et al. 2020; Afridi et al. 2021; Deshpande 2020; Desai et al. 2021), this study is among the very first to assess the impact of the second wave of COVID-19 on the unemployment gender gap in India. A previous study found the rise in male unemployment during the lockdown period contributing to a smaller gender gap (Zhang et al. 2021). In this study, we take one step further to assess the effect of the second COVID-19 wave on the unemployment gender gap in India.

The remainder of the article is organised as follows. In Sections 2 and 3, we present the data sources and some facts on the unemployment trend in India. The effects of first and second COVID-19 waves on unemployment disaggregated by gender are discussed in Section 4. Section 5 delves into the gendered impact on unemployment dynamics across urban and rural regions. The concluding remarks are presented in Section 6.

Data and Methodology

In this study, we use the subnational-level monthly employment data from the CMIE from the period of

January 2019 to May 2021 . Starting from January 2016, the CMIE has been conducting household surveys in India on a triennial basis, covering the periods of January to April, May to August, and September to December. This is the only nationally representative employment data in the absence of official government data (Abraham and Shrivastava 2019) and has been used by several employment studies on India (Beyer et al. 2020; Deshpande 2020; Deshpande and Ramachandran 2020).

The employment data are classified into three categories—the number of persons employed, the number of persons unemployed and actively seeking jobs, and the number of persons unemployed and not actively seeking jobs. The sum of these three categories constitutes the greater labour force. The data are also disaggregated by gender (male and female) and residence (rural and urban).[1]   For the analysis, we focus on five time periods as indicated in Table 1.

Table 1: Time Periods

For state[2] i at time t, we construct the unemployment rate as given below:

Unemployment rate = Number of persons unemployed and seeking jobs/Greater labour force                                                                                                    (1)

Stylised Facts on Unemployment

This section describes some stylised facts based on the subnational unemployment data from February 2019 to May 2021. To this end, we estimate the regression model below:

where Unemp it is the unemployment rate of state i in time t . To see the unemployment dynamics over the period of study, we use a binary variable Month s that takes the value one for month s and 0, otherwise. The model takes into consideration the impact of past unemployment rates, represented by  Unemp it −1. Additionally, the state fixed effects  δ i  are included to account for unobserved, time-invariant state-level characteristics that may potentially confound our estimates.

Figure 4: Trends in Unemployment Rate

Our coefficient of interest is β 1 s which depicts the time trend in unemployment. The results from the model estimation are shown in Figure 4, in which we can see the dynamics of aggregate unemployment in India from February 2019 to May 2021. The vertical axis pertains to coefficient β 1 s , and the horizontal axis corresponds to the respective months. In Figure 4, the aggregate unemployment rate is found to be relatively stable during the pre-pandemic era. This trend faces an overhaul during the national lockdown (April–May 2020) with a structural upward shift in the unemployment rate. The shock to the unemployment rate does not persist as economic recovery during the post-lockdown period enables unemployment to fall steadily from June 2020 onwards. The unemployment rate becomes stable from January to March 2020 as the country returned to a sense of normalcy with the continued resumption of economic activity.[3]   However, the economic impact from the onset of the second wave of the COVID-19 pandemic caused the unemployment rate to rise again in April and May 2021.

Next, we estimate Equation (3) separately for the female and male unemployment rates to assess the gender differential impacts of the COVID-19 pandemic on unemployment in India.[4]

where binary variable Quarter s  takes the value one for quarter s in the time period of our sample. The model also accounts for lagged unemployment effects through Unemp it −1.

Figure 5: Trends in Unemployment Rate by Gender

Figure 5 shows that a stark gender gap in the unemployment rate (distance between the red and blue lines) exists in the pre-pandemic era as the male unemployment rate is consistently lower than that of the female. Figure 5 also shows that the gender gap dynamics are primarily driven by male unemployment. The sharp rise in male unemployment during the national lockdown causes the gender gap to close in Q2 2020. The post-lockdown recovery (Q3–Q4 2020) is found to have a favourable impact on male unemployment, causing gender gap to revert to the pre-pandemic levels. Although both males and females lost jobs during the onset of the second wave (Q2 2021), the gender gap narrowed as males are found to lose more jobs in absolute terms.

Figure 6: Trends in Urban and Rural Unemployment Rate by Gender

Figure 6 shows the estimates of β 1 s  (see Equation [3]) for urban and rural unemployment in Panels (a) and (b), respectively. During the national lockdown, the sharp rise in male unemployment is more evident in urban areas than rural. In fact, the national lockdown period dynamics in aggregate male and female unemployment in Figure 5 largely resemble the effects seen in the urban region (see Figure 6, Panel [a]). The post-lockdown recovery suits male unemployment, both in rural and urban areas. Female unemployment remains stable in rural areas during the pandemic.

Figure 7: Trends in Regional Unemployment Rate by Gender

7 c                                                                                                                                                                         

The subsample regression estimates of β 1 s  pertaining to the north, east, west and south regions are shown in Figure 7. All regions witnessed a rise in male unemployment during the national lockdown period. On the contrary, the female unemployment dynamics differ between regions. During the national lockdown period, female unemployment rose in the west and south regions (Panels [c] and [d] in Figure 7). The north region shows an interesting anomaly (Panel [a] in Figure 7). Contrary to other regions, female unemployment dipped steeply in the north during the national lockdown period. East region alone did not 

experience any strong movements in female unemployment throughout the pandemic (Panel [b] in Figure 7).

Impact of COVID-19 on Unemployment

Section 3 discussed how the overall unemployment and unemployment gender gap witnessed structural breaks during the COVID-19 pandemic. To further investigate the gender aspect of the COVID-19 unemployment dynamics in India, we begin our empirical exercise by examining the unemployment changes during the COVID-19 pandemic compared to the pre-pandemic era. We use the following model:

where Period 1 , Period 2 , Period 3 , and Period 4  pertain to lockdown, post-lockdown, post-lockdown normalcy, and second wave time periods, respectively. Besides the overall unemployment, we also estimate Equation (4) for male and female unemployment separately. The results are shown in Table 2. We can see from Column (1) of Table 2 that the overall unemployment rate ( β 11 ) witnessed an increase of 0.066 (statistically significant at one percent level) during the lockdown period in comparison to the pre-pandemic period. This effect was primarily driven by the rise in the male unemployment that shot up by 0.082 during the lockdown period (Column [3]).

The uneven distributional effects of the post-lockdown recovery are seen from β 12 estimates. Male unemployment rose by 0.01, while female unemployment fell by 0.036 in comparison to the pre-pandemic era. The fall in female unemployment does not necessarily indicate that the overall labour conditions improved for women during this period. Equation (1) shows that the unemployment rate is driven by two components. Figure 1 validates that the female unemployment rate fell over time due to the decline in the number of unemployed females actively seeking jobs being higher than the decline in the female labour force.[5]

β 14 estimate in Column (1) indicates that the total unemployment rose by 0.019 (statistically significant at 10 percent level) during the second wave compared to the pre-pandemic period. A comparison between β 14 and β 11 estimates reveals an interesting policy highlight that the second wave’s impact on unemployment was smaller than the nationwide lockdown. Finally, the rise in unemployment during the second wave is primarily driven by male unemployment.

Table 2: Impact of COVID-19 on Unemployment

Note: *** p<0.01, ** p<0.05, and * p<0.1. The robust standard errors are in parentheses.

Unemployment Gender Gap in Urban and Rural Regions

This section delves further into the gendered impact of lockdown on the unemployment dynamics across urban and rural regions. As defined in Section 1, the unemployment gender gap measures the difference between female and male unemployment rates. To identify the effect of the first and second COVID-19 waves on the unemployment gender gap, we estimate the regression model below:

where Female is a binary variable that takes the value 1 for female unemployment and 0, otherwise.

Table 3 shows the estimation results of Equation (5). We discuss the coefficient estimates that are found to be significant. The significant β 1 coefficient reiterates that the unemployment gender gap was an existential problem in India even before the COVID-19 pandemic. The β 31 estimates reveal that the urban region dynamics drove the narrow unemployment gender gap during the lockdown period. Although the magnitude of the narrowing gap during the lockdown did not persist to the post-lockdown period ( β 32 ), rural regions experienced a narrow unemployment gender gap (marginally significant at 10%). This trend continues even in the post-lockdown normalcy period ( β 33 ) as the unemployment gender gap is narrower than the pre-pandemic level by 0.047 in the rural region. This highlights the possibility that the post-lockdown recovery process had a spillover effect on the unemployment gender gap in rural regions. Finally, β 34 estimates show that the narrowing gender gap trend persists only in the urban region during the second wave.

Table 3: Impact of COVID-19 on Unemployment across Urban and Rural Regions during the post-lockdown and post-lockdown normalcy periods.

This article analyses the impact of the COVID-19 pandemic vis-à-vis the pre-pandemic period on the gender unemployment gap. Our findings indicate that the gender gap in unemployment narrowed during the COVID-19 pandemic, primarily driven by male unemployment dynamics. Interestingly, we find that female unemployment declined during the post-lockdown period. Such a decline was likely driven by women dropping out of the labour force rather than a dip in the absolute number of unemployed persons. Further, the region-wide subsample analysis finds the unemployment gender gap in urban regions to narrow across all periods of the COVID-19 era. In contrast, the rural regions witness narrowing gender gap during the post-lockdown normalcy. This indicates that the rural regions’ unemployment gender gap witnessed spillover effects from recovery associated with the economic reopening. Finally, the narrow gender gap (compared to the pre-pandemic level) is smaller during the second wave.

There is a looming uncertainty whether the impending third wave will further narrow the gender unemployment gap at the expense of increasing male unemployment and females being pushed out of the workforce. Further research is required with a more extended period of assessment and focussed on household-level data to understand the difference in the impact of COVID-19 on the gender unemployment gap across the different parts of the country and income strata.

[1] The data are not available for Jammu and Kashmir, Andaman and Nicobar Islands, Arunachal Pradesh, Dadra and Nagar Haveli, Daman and Diu, Lakshadweep, Manipur, Mizoram, Nagaland, and Sikkim. Hence, the main analysis focuses on only 26 subnational economies.

[2] The terms “state” and “subnational economy” are used interchangeably throughout the article.

[3] According to the official data, power consumption grew by 10.2% in January 2021; the highest growth rate in three months, which was indicative of higher commercial and industrial demand (Press Trust of India 2021).

[4] In order to obtain the unemployment dynamics on a quarterly basis, Equation (2) is revised to Equation (3) with dummies pertaining to quarter instead of month.

[5] This reason is also validated by CMIE who found the female labour participation in urban regions to fall to 7.2% in October 2020, the lowest since the organisation started measuring this indicator in 2016 (Centre for Monitoring Indian Economy 2020).

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