Register with us

Latest Blogs

Gender-Based Occupational Segregation: A Barrier for Women’s Economic Empowerment

Gender-based occupational segregation refers to a situation when female and male workers are distributed differently across various occupations in a labour market, resulting in clustering of women or men around certain occupations [1]. Occupational segregation can be distinguished into two forms – horizontal and vertical. While horizontal segregation is measured by considering the differences in distribution of men and women across occupations, vertical segregation considers the distribution of men and women across hierarchies within the same occupation. Gender-based occupational segregation often creates labour market rigidities and economic inefficiencies, which leads to wastage of human capital. This also makes labour markets less flexible towards adjusting to structural changes happening nationally and globally. More specifically, it creates additional barriers for women to join the workforce by limiting the occupational choices available for them. As a result, in a highly segregated labour market, the supply of women tends to be higher for occupations where concentration of women is already high, which negatively impacts their bargaining power. A negative effect of occupational segregation is the creation of gender wage-gaps negatively biassed towards women, especially in developing countries [2]. A study exploring the interlinkages between gender-based segregation and wage differentials in India found that while a relatively large part of the rural wage gap was due to differences in educational attainment between males and females, a considerable part of the urban wage gap was explained by differences in occupational profiles across gender. At the same time, overall discrimination against women was also found to contribute to wage differences [3]. It can also create a mismatch between women’s education attainment and the type of occupation they engage in [4].

 

Contributing Factors

To a large extent, gender-based occupational segregation reflects the gendered division of labour in societies. Gendered norms are so deep-rooted in people’s minds that they often take up occupations that may align with specific roles expected by society from a particular gender. Women’s occupations are often a mirror of the common stereotypes associated with women and their supposed abilities- caring nature, greater housework skills etc. Without adequate support for care work from the State or the market, women often end up clustering around occupations that can provide them enough flexibility to manage care responsibilities at home. Again, boys tend to take into consideration future expected financial returns more than girls while choosing their educational path and occupations [3]. Moreover, gendered perceptions of employers can also lead to discriminatory hiring practices. Job roles offered to women tend to have either lower prospects of growth or pay less, as compared to those offered to men. Employers often perceive that women cannot give longer hours to jobs or cannot take up highly demanding managerial roles due to their primary responsibility as caregivers.

 

Another factor contributing to occupational segregation is gendered human capital investment by households, not only in terms of differences in levels of education attainment, but also choices of fields of education across gender. For instance, findings from All India Higher Education Survey (AIHES), 2021-22 [5] revealed that the proportion of females enrolled in technology and engineering related courses was far less than that of males. Similarly, the share of females enrolled in sociology or humanities courses, has been considerably higher than that of males. Therefore, the employability of women for jobs that require technical skills has been relatively low, which eventually contributes to segregation. Again, highly informal work conditions and lack of social security associated with jobs in India’s highly informal labour market, also hinder women’s participation in certain occupations or sectors. For instance, some manufacturing and construction sector occupations demand extensive physical labour without adequate safety standards, social protection measures, or decent work conditions in terms of work hours, basic facilities etc. Moreover, certain sectors are traditionally male-dominated, and women often find it difficult to adjust to workplace practices that may not always be gender-sensitive.

 

 

Extent of segregation in India

To capture the level of occupational segregation, a number of measurement indices can be used. While there is a lack of consensus regarding which index reflects occupational segregation better, the Duncan Dissimilarity Index [6], is one of the most widely used measures. It is interpreted as the proportion of women (or men) workers who would have to shift occupations for the occupational distribution of men and women to be the same. For the indices to be comparable over time, the occupational classifications captured in labour surveys have to be identical. India’s latest labour survey (Periodic Labour Force Survey or PLFS, 2022-23) used an updated occupational classification (National Classification of Occupation-2015 or NCO-2015), as compared to the codes used in earlier rounds between 2011-12 and 2021-22. These surveys used occupational codes as defined by NCO-2004. Even though the broad occupations at 1-digit level were comparable, the detailed occupational categories at 3-digit level captured by NCO-2004 and NCO-2015, were not exactly comparable. Again, there was great volatility in the occupational pattern of workers during 2020-21 and 2021-22 as the economy was severely hit by COVID-19 pandemic. Therefore, to understand the long-term trend in segregation during the pre-COVID decade, the surveys conducted in 2011-12 and 2019-20, were explored.

Figure 1 presents the distribution of male and female workers across broad occupations during 2019-20. Two occupations with relatively higher concentration of female workers were skilled agricultural & fishery workers, and agricultural labourers, which together constituted 58% of total female workforce in India, compared to 36% of total male workforce. Similarly, school teachers and personal services & care workers had relatively higher concentrations of female workers, although this category constituted a much smaller share of the overall workforce. Personal services & care workers include waiters in restaurants, bartenders, cooks, house-keepers, hair-dressers, beauticians, barbers, child care workers, institution-based and home-based care workers etc. Therefore, it is evident that similar to unpaid care work within the households, women’s engagement in paid care services has also been much higher than men, thereby contributing to occupational segregation.

 

Figure 1: % Distribution of Male and Female Workers (15 to 59 Years) across Broad Occupations: All India, 2019-20

 

Considering workers in the 15 to 59 years age-group, India’s overall gender-based occupational segregation in 2019-20 was 35.3%, as per Duncan Dissimilarity Index. The segregation was relatively higher in urban areas (41.7%) as compared to that in rural India (30.6%). Between 2011-12 and 2019-20, occupational segregation had risen from 31.6% to 35.3%, primarily due to increased segregation in rural areas, while that in urban areas had slightly decreased. Again, there was a steep rise in segregation among casual labourers (24.1% to 40.8%), while that among the regular-salaried (28% to 27%) or the self-employed (49% to 47%) did not change much.

 

Policy Approach towards Occupational Segregation

An integrated labour market with minimum gender-based segregation, can undoubtedly contribute to overall gender equality in a country. Two key concerns for women in a segregated labour market are limited access to work opportunities and lower average earnings compared to men. However,depending on the economic structure of a nation and formalisation of the labour market, desegregation and higher work participation of women, may not always be positively associated. Similarly, the contribution of segregation in accentuating gender wage gap, depends on a country’s wage structure characterised by setting of minimum wages, transparency of wage machinery, and coordination across firms and industries. The extent to which occupational segregation is problematic for women, depends largely on whether women are disadvantaged because of segregation in terms of poor working conditions, and lower wages, reflecting gendered hierarchies of power and discrimination [7]. Unfortunately, this is the case for many developing countries including India. Therefore, there should be a careful consideration regarding whether there should be equal policy focus on reducing gender-based occupational segregation, closing gender wage gap, and increasing female employment, or there should be trade-offs among them. The evidence that occupational segregation can boost female employment at certain stages of development, complicates such policy choices. Further, as compared to other forms of gender inequality, any reduction in occupational segregation takes much longer to achieve. This is reflected in a more even distribution of men and women across sectors in many developing countries as more women join the workforce, but into a limited number of occupations within these  sectors [8].

 

Considering India’s current situation where women’s work participation is much lower than that of men, it might be more effective to focus on policy interventions at facilitating access to decent work conditions for women, as well to provide equal opportunities for growth across all sectors and occupations that women participate in. Immediate emphasis should be to reduce vertical segregation across occupational hierarchies, which can contribute immensely in reducing gender wage gaps. At the same time, there should be a longer-term effort to reduce horizontal segregation so that women can explore a wider range of occupations. However, to achieve this, development of the care sector through public and private sector engagement, in order to make care services affordable and accessible across all economic strata, is crucial. In parallel, there should be equal focus on awareness generation through multiple channels to reduce and eliminate some of the traditional gendered norms that have impeded women’s overall empowerment and agency-building.

This blog has been authored by Mridusmita Bordoloi, Economist, IWWAGE

Why should we follow a cautious approach while interpreting the ‘usual status’ employment measures?

According to the Periodic Labour Force Survey (PLFS) rounds, the Indian economy witnessed a significant rise in female work force participation rate (FWPR) over the recent years, reaching 36% in 2022-23 from 22% in 2017-18.This rise is notably higher in rural areas, increasing from 24% to 41%, compared to the urban FWPR, which rose from 18% to 24% over the same period.However, concluding that this increase represents an unambiguous improvement in women’s labour market conditions would be misleading. This is partially due to these employment measures not informing on various other aspects of quality of employment, including the extent of underemployment. These FWPR estimates are based on identifying economic participation under the ‘usual principal and subsidiary status’ or interchangeably called the ‘usual status’ measure of employment.

The ‘usual status’ is the most widely reported statistical measure of employment across all domains. Although the recent ‘usual status’ trends indicate higher engagement of women in economic activities overall, these estimates should be interpreted with caution as these measures assign the status of being employed to  individuals with significantly different durations of economic engagements. The usual activity status of a person is determined based on both usual principal status and usual subsidiary status.  According to the definition of usual status, a person is considered employed if they meet either the principal status criterion (employed for at least six months in a year) or the subsidiary status criterion (employed for at least 30 days but less than six months in a year).  The subsidiary economic engagement is considered to define the employment status of a person only when the individual isn’t employed according to the principal status criterion. But the duration of   engagement in subsidiary activities is mostly significantly less than principal employment.  The usual status approach doesn’t differentiate between principal status and subsidiary status workers and adds them together to estimate the workforce participation rates. Consequently, the usual status measures fail to reveal the underemployment existing among subsidiary workers without any principal engagement. Therefore the drawback of a broad measure like usual status which includes the subsidiary engagement in defining employment is the inability to capture the underemployment.

We understand the risk with narrower measures like usual principal status as it undercounts the extent of activities taking place in the informal and subsistence economies, which are mostly seasonal in nature.  Thus the usual principal status measure gives us a closer picture for only those with stable employment conditions all throughout the year as it happens largely for working-age men. But it fails to measure women’s workforce participation adequately and this underestimation is significant for rural women because of their high share of engagement in short-term seasonal opportunities majorly in the agricultural sector. As the PLFS 2022-23 reveals, among the rural women solely engaged in subsidiary activities, approximately 82% are involved in agricultural activities majorly as unpaid family workers/own account workers. So, while it is important not to gloss over the subsidiary engagements where women participate significantly and capture the various activities extensively, as the broad employment measures do, we must also be mindful of the perils of interpreting the changes in these broad measures without looking into the granular details. We need to delve deeper to understand whether the change is driven by principal or subsidiary engagements. This is imperative for a better understanding of the extent of underemployment among the workers as the duration of economic engagement is one of the metrics of underemployment and it differs significantly between principal and subsidiary activities.

As we distinguish among women workers based on the principal and subsidiary engagements, we find that over the period of 2017-18 to 2022-23, the share of women solely in subsidiary engagement has risen from 10% to 23% at all-India level, with the share rising from 12% to 26% among rural women and 6% to 12% among urban women. This indicates that the increase in FWPR over the recent years, is significantly driven by an increase in subsidiary engagements. These shares are much lower for men as the shares of male workers engaged only in subsidiary activities are 3% at all-India level, 3% in rural areas, and 2% in urban areas in 2022-23. The shares reveal the higher underemployment existing among women workers, and more so in rural areas, in comparison to male  workers.

Also, when we compare women’s labour market participation across the states based on usual status estimates, we need to tread with caution. According to PLFS 2022-23 usual status measures, in case of few states with rural FWPR above national average like Karnataka, Andhra Pradesh, Maharashtra, Telangana, Tamil Nadu, and Gujarat, the shares of women with sole engagement in subsidiary activities range between 2-14%. And, in case of few other states, similarly with rural FWPR above national average like Jharkhand, Madhya Pradesh, Odisha, Uttarakhand, a very high share of rural women workers are engaged only in subsidiary activities, with the shares lying between 36-52%. Thus, the nature of women’s labour market participation is very different between these two sets of states, but it remains uncaptured if one looks at the usual status estimates alone.

In India’s context, because of the empirical realities of a developing nation like high prevalence of informal employment, seasonal activities, the broad employment measures  especially underemployment often don’t reveal the various aspects of quality of employment including underemployment. Any attempt to interpret these employment estimates and changes in these estimates should be undertaken with granular level inspection, otherwise it would be inadequate and misleading. This is particularly true for women who are majorly engaged in these ill-paid or unpaid short-term marginal activities where the increase in their participation is more often distress-driven and less in response to generation of good-quality, long-term employment opportunities. It is therefore critical that policymaking takes into account the usual status estimates in conjunction with usual principal status estimates in order to ensure a comprehensive consideration of women’s work.

This blog is written by Bidisha Mondal[1] works as a Senior Research Fellow with IWWAGE,
Aneek Choudhury[2] works as a Research Associate with IWWAGE.

Lack of census data and use of electoral roll-based sampling frame in specific studies

Selection of households and individuals is one of the most important tasks of developing sampling designs. Traditionally, in developing countries where population data is mostly available in the censuses conducted by the government, this information forms the basis of the house-listing done for the purpose of selection of households in a sample survey. In India as well, researchers mostly depend on the census data for constituting robust and representative sampling frames using a house-listing exercise to implement a particular sampling technique, unlike in the USA or other similar countries which already have readily available sampling frames. The house-listing process is a cumbersome process and often requires time and financial resources, which may, at times, deter researchers from using these probability-based sampling techniques and resort to purposive sampling which often may not be representative and may not provide unbiased information and data.

In this context, IWWAGE explored using electoral rolls as an alternative to using population census as sampling frames in the selection of household or individuals for some of our recent studies. Using electoral rolls for studies aimed at policy-making is a relatively new trend. In the absence of updated census data as well as to ensure minimised time and resource requirements, exploring electoral rolls as sampling frames may be useful, although its use for household surveys is relatively sparse in India (Vaishnav, 2021; Joshi et al. 2020). At IWWAGE, we have used electoral roll sampling frame for selection of individuals for the surveys in two of our studies on labour force participation. The data collection for one study, viz., ‘Women’s Labour Force Participation in Select States in India’, was conducted during November, 2021 and January, 2022 and the other one is an ongoing study on ‘Capturing women’s work to measure better’.

The completed study majorly aimed at unpacking the enablers and barriers of women’s labour force participation and suggesting actionable points based on the findings. For this study, approximately 5000 females and 1000 males were interviewed, from five states of India, namely Jharkhand, Karnataka, Delhi, Rajasthan, and Madhya Pradesh. The main objectives of the ongoing study are to capture women’s work comprehensively by identifying the varied, yet major, forms of paid and unpaid activities, listing activities by categories of work, and developing mechanism of estimating the simultaneity of engagement of women. Approximately 4000 females and 800 males have been surveyed from the states of Jharkhand and Karnataka for the study.

It is worth mentioning that, in a multi-stage cluster sampling context, selection of individuals (or households) from the electoral roll frame entails selection of polling booth in the previous stage of sample selection as opposed to more traditional approach of selecting villages in rural areas and census enumeration blocks (CEB) or urban frame survey (UFS) blocks in urban areas. In this note, we outline the advantages and challenges of using electoral rolls in selecting individuals based on our experience of conducting the two studies mentioned above.

Advantages of using electoral rolls in constructing the sampling frame

In addition to being time and cost efficient, there were multiple other advantages of using electoral-rolls as an alternative sampling frame, particularly in our studies. This technique provides us direct access to individual-level information like age, gender etc, that enables selection of a random sample, stratified on the basis of individual characteristics. It also allows us to minimise respondent bias by enabling enquiry from each individual rather than elicit information from only one member of the sample household who may then be the representative of the sampling unit and respond ‘on behalf’ of others, which may carry certain biases.

Also, the electoral-roll based sampling is a better alternative to the non-probabilistic sampling methods where sample selection often relied upon the ease of access to respondents and thus leads to a non-random, non-representative sample.

  1. Challenges of using electoral-rolls in constructing the sampling frame:

However, there exist a few challenges of the electoral roll-based sampling, as described below.

  1. Categorizing polling booths into rural and urban centers: In case of a few states, the rural-urban bifurcated list of polling booths is not directly available anywhere. In those cases, each polling booth has to be located in the Geographic Information System (GIS) software maps and categorized on the basis of information provided in the software. For example, in case of Karnataka, to know the rural/urban location of a polling booth, it has to be located in the GIS map and then the rural/urban location has to be decided depending on whether the polling booth is falling under a Hubli (indicating a rural area) or town (indicating an urban area).
  2. Translation from local language: In case of a few states (for example, Karnataka), where the list of polling booths and the electoral rolls are available in local languages only, translating in English and digitizing them, increase the risk of errors, and require robust monitoring and quality checks.
  3. Unavailability of voter rolls in convertible PDFs: Voter rolls are sometimes available online in standard PDF but in many cases, they are available as scanned copies of voter lists. These are difficult to convert into excel files, and hence sometimes entries of the listed individuals need to be done manually – increasing the cost and time in the digitization process. It also inbuilds a cost of manual supervision after the entries are completed in the excel file. In case of a large-scale coverage/nationally representative study, the manual process of making entries will be challenging.

 

  1. Challenges arising for electoral roll-,zbased sampling method while implementing the survey:
  2. Less frequent updating of the voter rolls: Less frequent updating of the voter rolls leads to difficulties in locating the respondents, especially in urban areas with high intra-city or inter-city out migration. Combining two of our studies, in about 20-30% instances, the respondents could not be located due to out-migration. However, as the geographical area of survey expands, this percentage comes down.
  3. Difficulty in locating respondents in dense settlements: In case of the densely populated urban areas, the houses located near the boundaries of the polling booths often get excluded from the electoral rolls corresponding to their own polling booth and get enrolled in the electoral rolls of the adjacent polling booths. This arises due to the fact that there is a cap on the number of voters in a polling booth and once the limit is reached, the remaining voters are to be enrolled in the neighbouring polling booth.
  4. Difficulty in locating women in younger age-cohort: It is also realized that locating women in the age-cohort of 18-24 years is far more difficult as compared to others. Younger women are much less likely to be listed in the voter rolls than other individuals and they also relocate more often after marriage, rendering themselves as untraceable in that particular polling booth.
  5. False entries: Sometimes the names or other information like age of the individuals does not match exactly leading to minor mismatch between the electoral roll entry and the original information of individuals. Also, the existence of false entries is found in the voter’s list.
  6. Voters not residing in the delimited area of a particular polling booth: In some cases, it is found that most of the respondents selected from the voter list of a particular booth, actually reside in a village far from the polling booth demarcated area. This is because voters in a particular area are assigned to other polling booths besides the one officially demarcated for the area.

To tackle the challenges of non-response and difficulty in locating the respondents, digitizing data of extra polling booths as buffers and preparing a list of respondents which include more numbers in addition to the required sample size for each group of respondents in each polling booth, would be a mitigating mechanism.

  1. Suggestions to facilitate a more convenient use of electoral rolls in constructing sampling frame:

Below are a few suggestions from our experience of using electoral rolls for constructing sampling frame to make the process more efficient:

  • providing the list of polling booths and electoral rolls in English;
  • indicating the rural/urban location of the polling booths in Chief electoral officer’s website;
  • making the electoral rolls available in convertible PDFs; and
  • more frequent updating of the electoral rolls.

Lastly an important limitation of using electoral rolls pertains to specific age cohorts. Since the electoral rolls include only the eligible voters, the sampling frame thus includes only those individuals who are 18 years and above. It would thus be relevant mainly for surveys that include specific age groups above a certain threshold.

 

This blog has been authored by Dr. Sona Mitra, Director- Policy and Research, IWWAGE; Dr. Bidisha Mondal, Research Fellow, IWWAGE; Prakriti Sharma, Senior Research Associate, IWWAGE; and Aneek Chowdhury, Research Associate, IWWAGE[1].

We are very thankful to Dr. Santanu Pramanick for his guidance through the process of developing a sampling frame. We are also grateful to Shri P C Mohanan for his comments in both phases of using the electoral rolls for our purpose.

Women’s control over their economic resources: Evidence from NFHS 5

Economic violence refers to any act or behavior causing economic harm to an individual and generally involves coercive control of economic resources of a person . It is one of the many interconnected forms of violence often taking place at the domestic realm in the context of intimate relationships leading to adverse consequences on mental, physical, and financial well-being as well as other development opportunities of the victims and their dependents both in the short and long-term. This blog attempts to provide estimates of the incidence of economic violence in India based on the National Family Health Survey 5, conducted during 2019-21.

Although economic violence is now legally recognized in a few of the European Union member states like Belgium, Bulgaria, Croatia, Lithuania, Hungary, Malta, Romania, Slovenia and Slovakia and it is a commonly used tactic by perpetrators for coercive control over the victims and co-occurs with other forms of violence, it is less talked about and underreported. The under-reporting arises majorly due to the general lack of awareness about what constitutes economic violence. The gap in empirical understanding of economic violence and the factors influencing the occurrence of this form of violence also leads to a vacuum in the policy-making space through prohibitive measures to support the survivors.

There are majorly three types of economic violence categorized by the European Institute of Gender Equality: economic control which includes preventing, limiting, or controlling a victim’s finances and related decision-making; economic exploitation which means using the economic resources of a victim to the abuser’s advantage; and economic sabotage which involves preventing a victim from pursuing, obtaining, or maintaining employment and/or education. However, the identified indicators from NFHS 5 allows us to explore only the extent of economic control and economic exploitation experienced by women in India.

According to NFHS 5, 49% of women, aged between 15 to 49 years, don’t have the decision-making power on how to spend their own money. The situation is relatively better for urban women as compared to their rural counterparts since the share is relatively lower at 43% for urban women and 51% for rural women. This is because urban women face less restrictive socio-cultural norms and enjoy better agency as compared to rural women. Also, there exists vast state-wise variation when it comes to women’s control over their own money. The three states with highest shares of women with decision-making power over their own money, are Himachal Pradesh, West Bengal, and Karnataka with the shares being 62%, 61%, and 59% respectively, whereas the worst performing states are Telangana, Andhra Pradesh and Assam with the shares being 32%, 29% and 28% respectively. The state-wise patterns indicate varying levels of women’s agency and the associated socio-cultural norms across the states. 

The control over one’s own money also varies among women in different age-cohorts, with the control steadily increasing with age. While only 35% women in the age-cohort of 15-19 years can decide how to spend their own money, this share rises to 59% for women in the age-cohort of 45-49 years. As women transition from young adulthood to middle age, their growing social network often make them collectively empowered, help them challenge the restrictive social norms and exercise better agency. Moreover, financial distress has been a contributing factor to the prevalence of economic violence as 54% women in the ‘poorest quintile’ reported not having the control over their own financial resources. This percentage goes down among women belonging to upper expenditure quintiles.

The partner pay gap- the difference in earnings between the partners – turns out to be a significant influencer of economic violence as women’s relative earning position tends to determine the interpersonal power dynamics within the couple. Around 65% of women who earn equal to their husbands or more than their husbands, are found to have command on how they spend their own money, and the share is 59% for those earning less than their male spouses. The findings from NFHS 5 reveal a U-shaped relationship between women’s control over their own economic resources and their education level. This implies that women at very low levels of education have better command over their economic resources as compared to women in secondary/higher-secondary levels of education; the control increases for women with graduation/post-graduation levels of education. As NFHS 5 reveals, this too can be explained by the partner pay gap. According to the data, the share of women earning more or less similar to their male spouses is high among women with lower levels of education and thus on average they enjoy better command over their economic resources. Women at secondary/higher secondary levels of education, earn much lower than their spouses on average, leading to lower agency and less control on their own economic resources, and again the ‘partner pay gap’ declines for women with tertiary level of education, leading to better agency. Additionally, as the education levels of the male spouses increases, the females are found to enjoy more decision-making power over their own earnings as educated men are supposed to conform to more gender-equal norms. Approximately 50% of women whose male spouses received no education, don’t have any command over their own money. This share goes down to 36% for women with male partners educated above the secondary level.

Another commonly found example of financial abuse is the male spouse depleting the wife’s savings without her knowledge/consent. According to NFHS 5, around 44% of women stated that they have a bank savings account of their own, but they are not in control of the money in it. This share again varies by education levels, with the share being 44% for women without any education level and the share declining to 36% for those with education level above secondary level, reflecting higher agency among educated women.

Despite the pervasiveness of low agency of women when it comes to controlling their own incomes and financial resources, the recognition of it is lower. This lack of recognition is often due to not acknowledging the exclusion as another form of discrimination and assault on women. This points to the need for generating more evidence and awareness around the various forms of exclusion both in the legal and scholarly spheres. Criminalizing economic abuse would help to send a firm message about the unacceptability of this form of violence. Allocating significant budgetary resources for training legal professionals for increasing their capacity to recognize, investigate, and prosecute economic violence would be needed to address and prevent its occurrence. Along with this, the access to the services to combat familial violence must be provided to its victims too. Lastly, we need more sophisticated surveys capturing the various dimensions of economic violence to fully comprehend the subject.

 

This blog is written by Aneek Choudhury, Research Associate and Bidisha Mondal, Research Fellow at IWWAGE.

 

Picture credit: Paula Bronstein/Getty Images/Images of Empowerment

Capturing Quality of Women’s Work: Going beyond FLFPR

The Sveriges Riksbank Prize in Economic Sciences in memory of Alfred Nobel, was awarded to Claudia Goldin, professor of economics at Harvard University, on October 9th 2023 for ‘having advanced our understanding of women’s labour market outcomes’. The recognition of Claudia Goldin’s work is expected to strengthen the discourse around gender inequalities in the Indian labour market too. Although Goldin’s work majorly focuses on high income economies, it holds important insights for the gender differences in labour market returns in India. Her work underscores the need for data collection and evidence generation on identity-based differences in labour market outcomes and critiques identity-insensitive policy-making. Using PLFS 2021-22 data, this blog explores the nature and quality of work that women in India are engaged in and how it is influenced by demographic and socio-economic factors.

In India, along with the low female workforce participation rate at 25% (PLFS 2021-22), another major concern is women’s engagement in job opportunities of poor quality in terms of wages and other benefits. A striking feature of the Indian labour market is the overwhelming presence of women engaged as unpaid family workers. According to Periodic Labour Force Survey 2021-22, 37% (all India) of total employed women are working as unpaid family workers and this percentage rises up to 43% in case of rural women. Unpaid family workers are those who are working without any pay or profit in a family operated farm or a business owned by any household member with whom the person is related by kinship/marriage/adoption etc. The unpaid family workers are considered to be part of the labour force and their contribution gets counted in national income, but their work doesn’t get remunerated and the profit belongs to the owner of the family business. The worker engages and contributes to the business considering it a part of household responsibility/obligation. Thus, in spite of being a part of the workforce, this form of engagement isn’t expected to lead to financial empowerment due to the absence of remuneration unlike the mainstream labour market activities. This non-monetized nature of the activities of unpaid family workers leads to lack of recognition of women’s work and women’s agency and often leads to underreporting of women’s work. Thus, understanding the factors influencing women’s decision to work as unpaid workers in family businesses and hindering them from entering paid work opportunities is imperative to enable informed policy-making for ensuring remunerative engagement of these women.

 

Women’s engagement as unpaid family workers is concentrated in agriculture and related activities, as 89% of them are in these farm-related activities. However, women’s participation as unpaid family workers differs by demographic variables like age-group, education level, skill training, care responsibilities and also characteristics of the households. The share of working women engaged as unpaid family helpers is much higher at 47% among those aged between 15-25 years, as compared to 34-38% among the older age-cohorts. This reflects that social norms are more restrictive for younger women when it comes to working outside the family. The education level also influences women’s working status. The share of working women engaged in unpaid family business is highest at 42% among those who are illiterate. Although, the share goes down with rise in education level, a share as high as 37% of working women with middle to higher-secondary level of education and 13% of working women with as highly qualified as graduates, post-graduates and above, are engaged as unpaid helpers in family businesses. This fact points towards the lack of paid job opportunities for those with mid to high-levels of education, along with constraining social norms. The PLFS data however indicates that those who received formal vocational training are less likely to work as unpaid family workers and tend to engage in remunerative engagements. This is indicated by the share of working women with formal vocational training engaged as unpaid family workers which is 10%,  much lower than others.

Along with these characteristics, women’s care responsibilities also influence their decision to work inside or outside their homes. The PLFS 2021-22 shows that the share of working women engaged in family businesses as unpaid helpers is 45% for those with children aged below 5 years, whereas the share is much lower at 34% for others. Additionally, as the household’s income rises, the likelihood of women being engaged as unpaid helpers in family businesses declines. According to the PLFS 2021-22, the share of working women engaged as unpaid family workers is 44% in the lowest income class and the share declines to 26% for those women belonging to the uppermost income class. This is evidently due to the inability of poorer households to hire paid workers from outside and instead have to engage household members in their family businesses.

As the factors leading to women’s engagement in these non-remunerative activities are many, including restrictive social norms, lack of job opportunities, lack of skills, care responsibilities etc, a multifaceted approach is needed to shift these women to remunerative opportunities. As the data indicate that vocational training is effective to ensure women’s remunerative engagements, raising awareness among women about these programmes, strengthening the existing programmes for higher outreach, skill training of women for the emerging non-traditional sectors, would be impactful policy measures. The availability of job opportunities for highly skilled and qualified women in the non-farm sector would also encourage women to take up these remunerative opportunities instead of working as unpaid family workers. Thus, creation of good quality job opportunities in the secondary and tertiary sectors and women-friendly work environment would be needed to address these concerns. As childcare responsibilities often act as a constraint for women to work outside their homes, state provisioning of childcare facilities would free up women’s time for commitments beyond the domestic sphere. Above all, making women aware of the implications of economic empowerment for their agency is of utmost importance for encouraging them to taking up remunerative engagements.

 

The blog is authored  by Dr. Bidisha Mondal, Research Fellow, IWWAGE

Achieving Gender Equality in STEM: Towards an Inclusive and Diverse Ecosystem

The fields of Science, Technology, Engineering and Mathematics, referred together as STEM, are crucial to a nation’s economic prosperity and global competitiveness. Prioritizing STEM education can lead to creation of new technologies and industries, sustainable solutions to climate challenges and greater participation in the global economy. As STEM fields have been historically dominated by men, promoting gender diversity holds the key to creativity, innovation, and harnessing the full potential of the human capital of an economy. This blog delves into the present trends of women’s participation in the STEM sector and how it can be improved.
According to a report by the National Association of Software and Services Companies (NASSCOM), the number of STEM jobs in India is expected to reach 100 million by 2025. This represents an increase of over 50% from the current 63 million jobs in the STEM sector. Research also suggests that women in India who take up science are more likely to be employed and earn about 28% more than women who study non-technical subjects. This makes it imperative that India focuses on achieving gender parity within STEM and creates an enabling ecosystem for more women to join STEM.
The AISHE 2020-21 reports that though the overall enrolment of women in education has increased, over the past few years, women’s enrolment rates across STEM courses at the undergraduate level has increased only marginally. Overall trends in STEM specifically, including undergraduate, postgraduate, M.Phil and PhD courses, indicate that women form about only 43.2% of the sample. B.Tech and B.E programmes have only 28.7% and 28.5% women respectively.
The promising figures of women obtaining STEM education does not get translated into the workforce. India sees the lowest participation of women in STEM globally at 26% of the STEM workforce. Indian women make up for only 13.9% of the researchers globally. Less than 5% of academic department chairs are women, who make up only 9% of fellows in the three Indian science academies (INSA, IASc, and NASI). This trend shows a huge drop off from education to joining the workforce, indicating that women face constant barriers while navigating employment in STEM.
The pipeline for women in STEM leadership roles starts wide at the time of education but narrows considerably as one moves upwards, resembling a leaky funnel that drains their talent and expertise from the system. Many factors contribute to women dropping out of the leaky pipeline of STEM. One major factor is the gendering of science and technology, which makes these fields deem suitable only for men. Boys and girls are socialised into traditional gender roles from a young age, which influences their career choices. Starting in school, children are exposed to traditionalist views on gender through curriculum design, classroom behaviour, and other interactions.
Even within STEM, the proportion of women students is not evenly distributed. Women’s enrolment in some prestigious science subjects, such as chemistry (42%), physics (38%), and engineering (32%), remains relatively low. AISHE 2020-21 shows that in the UG level there are only 6.68% women students in mechanical engineering and 23% in civil engineering. However, other fields, like life sciences (56%), microbiology (67%), and information technology/computer sciences (54%), witness higher enrolment of women, as per data from the Ministry of Education (in 2020).
These trends result in women finding themselves devoid of networking opportunities within the STEM workforce. It has often been reported that STEM workplaces and schools are often dominated by “boys’ clubs,” which are groups of men that systematically exclude women. This makes it difficult for women to feel supported within STEM fields, and many women choose not to pursue STEM careers as a result. This further leads to the persistence of a ‘glass ceiling’ perpetuated by social biases, traditionalist views of gender roles and prejudiced behaviour that exclude and discriminate against women. Encouragingly, issues like salary gaps and overt gender discrimination in India are improving, but deep-rooted social norms and biases continue to hinder progress for women especially in leadership roles.
Such an ecosystem deters women’s entry and growth in STEM fields. Overrepresentation of men prevents growth of women into leadership positions, denying early-career professionals of leaders to mentor and sponsor them. As decision-makers are mostly men, workplaces are structured to disfavour women with inflexible working hours, infrastructure, lack of childcare support, etc. Additionally, women are required to balance household responsibilities along with work responsibilities.
To address these gaps the Government of India has implemented a number of initiatives to promote women in STEM. Initiatives like the supernumerary scheme have added more seats for women in IITs. Such a scheme for private institutions can go a long way in bringing more women into STEM and creating gender parity across STEM streams. Further, the Department of Science and Technology’s Gender Advancement for Transforming Institutions charter (GATI) aims to establish gender equality practices at the institutional level through sensitisation and awareness generation in STEM institutions. The KIRAN initiative is aimed at inducting more women talent in the research & development domain through various programmes. Furthermore, the mobility Scheme of the Department of Science and Technology supports women scientists in relocation due to spouse transfers, caregiving, or children’s education in different cities.
These initiatives have been successful in increasing women’s participation in STEM, but they fall short on tackling existing biases. We need school curriculums that do not conform to traditional gender roles in labour. Additionally, schools can make an active effort to introduce gender-equity within the curriculum so that young girls are better equipped to navigate gendered ecosystems. Such early-stage initiatives should be complemented with mentoring and sponsorship initiatives at the workplace that will support women’s growth.
Another challenge for India is the lack of gender-disaggregated data on women’s participation in the sector. While the data for educational institutions and public employment in STEM is available, the private sector lags behind in reporting gender disaggregated data. Availability of such data can be beneficial in promoting women’s participation in the private sector and also enable state and union governments to promote women’s participation and education in a transparent and efficient manner.
Considering the significant impact of science and technology on economic growth, it is essential to implement more strategies that promote and retain women in STEM fields. Gender diversity in STEM has a profound impact on developing nations by driving economic growth, technological advancement, and societal well-being. Through an emphasis on investing in promoting women’s participation in STEM education, countries can capitalise on their human capital, foster innovation, and address global challenges.

The blog is authored by Sayak Sinha, Policy Manager, IWWAGE

Strengthening Capacities of Rural women through DAY-NRLM institutional Framework

Achieving gender equality is paramount for a peaceful, prosperous, and sustainable world. Women and girls represent half of the world’s population and therefore also half of its potential. But gender inequality persists everywhere, stagnating social and economic progress. In the context of India, out of the 135-crore population, 65.13 percent live in rural India and women constitute 48 percent of total rural population. These rural women who are majorly a part of unpaid work have no access to sustainable income or paid economic activities in their lives. This blog looks at some of the initiatives undertaken by the Deendayal Antyodaya Yojana-National Rural Livelihoods Mission (DAY-NRLM) aimed at empowering women. 

Launched by the Ministry of Rural Development, Swarna Gramin Swarojgar Yojana (SGSY) was introduced to provide self-employment to the Below Poverty Line (BPL) households through the formation of SHGs (Self Help Groups) to bring them out of poverty during 1999 to 2011. The programme aimed to ensure that at least one woman member from each rural poor household is brought into women SHGs and their federations within a definite time frame. Prof. R. Radhakrishna (2009) Committee reviewed the performance of SGSY and suggested changes in the design from a ‘top-down poverty alleviation’ approach to a ‘community-managed livelihood’ approach. Based on the Committee’s recommendation, SGSY was restructured into Deendayal Antyodaya Yojana-National Rural Livelihood Mission (DAY-NRLM) by the government to provide a sharper and greater focus as well as momentum for poverty elimination. DAY-NRLM was started with the mission “To reduce poverty by enabling the poor households to access gainful self-employment and skilled wage employment opportunities, resulting in appreciable improvement in their livelihoods on a sustainable basis, through building strong grassroots institutions for the poor.” 

Rural women face structural barriers in accessing their right to livelihoods, resources, and social protection, which are important factors in attaining empowerment. Realising the need of the hour, in 2016, gender mainstreaming was introduced within the NRLM program, and it was restructured as Deendayal Antyodaya Yojana- National Rural Livelihood Mission (DAY-NRLM). The approach of mainstreaming was to focus on shaping programs and policies in all verticals with a gender lens, for example- financial inclusion of women can lead to promotion of ownership of bank accounts, promotion of kitchen gardens can improve the health status of women and children, and methods for strengthening independent economic identity of women. The program also believes that mainstreaming of gender within its framework and systems is important to achieve sustainable economic, social, and political empowerment. In addition to gender mainstreaming, the focus was also on the inclusion of the most vulnerable communities- devadasis, single/widowed/divorced women, HIV+, transgender persons, elderly women, survivors of violence and trafficking.

For strengthening the approach of gender mainstreaming in all the verticals, DAY-NRLM introduced another important strategy- setting up of institutional mechanisms at different levels. The focus of setting up of these mechanisms was to establish a demand-supply relationship with other public entities like the Gram Panchayat/Village Council (specific to tribal areas), Gram Sabhas, Anganwadi Centres, Public Health Centres, Public Distribution System, banks, schools, etc and convergence with these line departments. To achieve this, a well-planned gender architecture has been placed at the community level like Gender Point Persons (GPPs), Gender Forums and Social Action Committee (SAC) at village level, Cluster Level Federation (CLF), Gender Justice Centre (GJC) and Gender Resource Centre (GRC) at block level. These institutions have been formed so that SHG members can approach them in need. The Gender Forum and the VO-SAC together prepare a Gender Action Plan to resolve critical gender issues in the village. The VO-SACs and Gender Forums also monitor progress on actions and report on them to the Cluster Level Federation (CLF), which aggregates agendas for all Village Organisations (VOs) under them. Through these collective actions, they are playing a pivotal role in uplifting women’s condition and position in society by identifying, acknowledging, and addressing issues of discrimination. 

The program has also given a platform for the capacity building for sustainability of these women federations through experienced gender experts called the National Resource Person (NRP). The NRPs train community resource persons (CRPs) at block level and help them to make Gender Operational Strategy based on the issues they are facing in their respective blocks and villages. Further, these CRPs train VOs and GPPs on gender concepts. Since the inception of gender mainstreaming in the program and as a result of these trainings, an improvement in indicators related to women empowerment has been noticed, which includes- sex ratio, participation in household decisions, having an account in the bank, having land in her name alone or jointly etc. In continuation to this, women’s autonomy and participation in grass root governance have also been seen in recent years. They have recognised their participation in Aam Sabha and Gram Sabha as well as in panchayat elections, which have been a huge milestone for this program as not only at socio-economic level, but women are heading towards political empowerment also.

Besides taking up issues related to gender discrimination, the institutional mechanisms of the program have proved its efficacy by addressing social evils. For example, the states of Jharkhand, Kerala, Maharashtra, Odisha, and Andhra Pradesh through the NRETP (National Rural Economic Transformation Project) under DAY-NRLM have successfully taken up the issue of Anti Human Trafficking and worked towards ending it with the help of community institutions. Witch hunting, which is an old social scourge practised mainly in rural India is one of the most challenging issues in states like Jharkhand, Madhya Pradesh, and Rajasthan. To curb this practice, DAY-NRLM and JSLPS (Jharkhand State Livelihood Promotion Society) has introduced Garima Project in 2020 and an institution called Garima Kendra has been established at CLF level, which aims to eradicate this practice. Another important social issue is Gender Based Violence. DAY-NRLM through its programs has been capacitating the women federations on how to deal with GBV cases with sensitivity and approach the concerned line departments for help. For this, a new federation called Gender Resource Centre (GRC) has been formed in 15 states at block and Gram Panchayat levels which would be taking issues mainly on GBV cases. In case of child marriage, DAY-NRLM has been training women federations through NRPs on how to prevent it.

DAY-NRLM is an ongoing program which aims to mobilize poor households and address gender related issues along with State Mission Units (SMUs), women’s institutions, and line ministries. It also believes in engaging men and boys as their involvement is crucial to achieving gender equality. The Mission seeks to reach out to around 10 crore rural poor households in a phased manner by 2023 and impact their livelihoods significantly. There are many stories of hope and resilience, where DAY-NRLM institutions have given voice and support to these rural women empowering them to realize their true potential.

This blog is authored by Mrs. Ankita Sharma, Senior Research Associate at IWWAGE. 

Engendering Early Childhood Development in India

Introduction

Over the past decade, there has been a growing global focus on early childhood development. Quality childcare can provide children with lifelong health, education, and social development benefits. Women have traditionally been responsible for childcare, with little help managing it alongside their work, paid or unpaid. The responsibility of unpaid care work disproportionately impacts women’s access to education, employment, leisure, health, and well-being. It also reduces the availability of opportunities for remunerative employment.  Women are frequently compelled to work in informal, unstable environments or quit entirely due to caregiving responsibilities. This unequal burden impacts women from all walks of life but disproportionately affects impoverished and underprivileged women. Policymakers in India need to address the unpaid care work women are obligated to perform. Establishing childcare centres, or creches, is a crucial policy tool for achieving this objective. This blog will look at state-sponsored creche policies and programmes and assess how well they work to help women find and retain jobs. 

In India, care policies and legislation have long been influenced by the concept of “Gendered Familialism,” which places the responsibility of care work on women based on familial relationships (Neeta and Palriwala, 2011). Unfortunately, this strategy limits the pool of potential carers and care recipients, fails to acknowledge care as a shared public responsibility, and does not take into account the fact that women frequently require assistance managing both their paid work and care obligations, particularly with regard to childcare. Over the years, many legislative and policy initiatives have sought to address this mindset by attempting to redistribute care provision to employers and the government. These include early statutory provision of childcare in the formal sector, crèches provided at worksite in the informal sector under the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA), the universalization of Integrated Child Development Services (ICDS), and the PALNA scheme, which mandates making crèches accessible for both employed and unemployed mothers (Chigateri, 2017). Although these government programmes and legal frameworks have touched on the need for childcare benefits to increase women’s labour force participation by providing daycare centres and maternity benefits, the execution of such mandates can be improved.

Tracing the History of Child Care Services 

Childcare services have been recommended for working women in many government and non – government policy documents (Chigateri, 2017).  For working mothers, ‘crèches, nurseries, and labor-saving devices’ were recommended in the 1974 report “Towards Equality” by the Committee on the Status of Women.  The “Shramshakti” report from 1988 was another significant report, which acknowledged the right of working women to have access to child care. It also suggested childcare facilities for women working in the informal sector. Childcare services for women in both the formal and informal sectors were also advised in other policy documents.  The 1988 National Perspective Plan for Women suggested that laws requiring companies to provide crèches for a certain percentage of female employees be changed to gender-neutral policies. Additionally, the 2001 National Policy for the Empowerment of Women recommended that childcare facilities be available in workplaces, educational institutions, and residences for the elderly and disabled.

Despite the strong emphasis on centre-based childcare services in several policy documents, progress towards implementing these recommendations has been slow in reality. Most legislation on the subject has only applied to women employed in the organized sector, leaving out a significant portion of the female workforce. Legislations such as the Factories Act 1948, Plantation Labour Act 1951, Mines Act 1952, Beedi and Cigar Workers’ Act 1966, Contract Labour Act 1970, Inter-state Migrant Workers Act 1980, and Building and Construction Workers Act 1996 mandate crèche facilities in the organized sector and workplaces with a relatively large number of women employees. Efforts to expand childcare options for women workers have been made in both organized and unorganized sectors through the Maternity Benefits Act (2017) and the National Rural Employment Guarantee Act (2008). The Maternity Benefits Act 1961, amended in March 2017, presents a mixed picture of state involvement in childcare provision (Chigateri, 2017)[1]. Although the Maternity Benefit Amendment Act extends the duration of wage replacement during maternity leave from 12 to 26 weeks, it also mandates establishments with 50 or more employees to provide creche facilities within a prescribed distance. The high threshold and the exclusion of women workers outside the organised sector drew criticism from women’s organisations.

In the Draft Rules on Social Security Code (SSC), which the Ministry of Labour and Employment published in November 2020, the condition of more than fifty employees in the Maternity Benefit Act (Amended), 2017, was changed to an eligibility condition of fifty “women employees.”, disregarding the needs of young children of all employees, both men and women workers (Mishra and Sachdeva, 2021)[2].

MGNREGA is the only act in the country that gives legislative support for childcare provisioning in the unorganized sector, recognizing both the work-related rights of women and their right to provide adequate nutrition and care for their infants. However, creches under MGNREGA have performed unsatisfactorily.

Another modality through which childcare provision was introduced in India was the Integrated Child Development Scheme (ICDS), launched by the Government of India in the 1970s. The programme was designed to promote early childhood development (ECD) in children under the age of six. It was the first government initiative to address young children’s nutritional, health, and early learning needs while also enhancing mothers’ capacity to meet those needs (Mishra and Sachdeva, 2021)  [3]. The program focused on six comprehensive services: supplementary nutrition and growth monitoring, immunization, health check-ups, health and nutrition education, referral services, and non-formal pre-school education. This program was to be coordinated through Anganwadi Centres (AWCs) by Anganwadi workers and helpers. Over time, the program expanded to cover all blocks in the country.  Children under the age of six now have a universal right to these services due to the Supreme Court’s order for the quality universalization of the ICDS. The ICDS has played a significant role in tackling malnutrition amongst children and mothers in the country. However, implementation of the programme has largely been reliant on mothers of children, perpetuating the notion that childcare is solely their responsibility and creating difficulties for employed women accessing services.

Furthermore, the pick-up and drop timings of AWCs frequently conflict with the mothers’ employment hours, necessitating the need for dependable childcare services. Also, the AWCs are only open for four hours, which is unhelpful for working women who put in much longer hours. In 2012, the Restructured ICDS document did recommend the conversion of 5 percent of AWCs in the country to Anganwadi-cum-crèches (AWCCs) but this has only been implemented in a limited number of AWCs.

The Scheme of Assistance Crèches for Working/Ailing Mothers was another way the government introduced childcare services for women. It was initiated in 1974 to offer creche services to the young children of female labourers living below the poverty line. The Rajiv Gandhi National Crèche Scheme (RGNCS) for Children of Working Mothers was created in 2006 as a merger of two previous crèche schemes: the aforementioned scheme and the National Crèche Fund Scheme established in 1995. The government runs the scheme in partnership with private sector and non-government organizations to target remote and underprivileged areas. It was later renamed the National Creche Scheme (NCS). Though important, this scheme restricted Creche facilities’ provision to working or ailing mothers.

Status of current schemes

As part of the recently approved Mission Shakti, the National Creche Scheme has been updated and renamed as Palna Scheme to provide creche services for children (6 months to 6 years old) of working mothers as well as to enhance the nutritional and physical well-being of kids.  The scheme will offer working women’s children a safe and secure environment for their nutritional, physical, and cognitive development and inspire women to pursue their career opportunities.  The Scheme provides Creche facilities for children of all women, whether employed or not. This denotes a progressive shift in the government’s perspective. This programme addresses the urgent need for high-quality childcare facilities. During the 15th Finance Commission, the government intends to establish an additional 17,000 Anganwadi cum creches under Palna.  Despite its carefully considered formulation, the secret to its success will be in how well it is put into practice.  The programme’s effectiveness will be ensured by increasing the network of childcare facilities and allocating sufficient financial resources in that direction. It is critical that the planning, designing, execution and monitoring of these schemes and programmes actively adopt gender intentionality in their approach to ensure that care work ceases to pose a challenge to women’s social and economic well-being.

Author: This blog is authored by Divya Singh, Research Manager at IWWAGE

[1] Palriwala, R. and Neetha, N., 2011. Stratified familialism: the care regime in India through the lens of childcare. Development and Change, 42(4), pp.1049-1078.

[2] Chigateri, S., 2017. ”Pathways to Accessible, Affordable and Gender-Responsive Childcare Provision for Children Under Six-India Case Studies.

[3] ibid

[4] Committee on the Status of Women. 1974. ‘Towards Equality’. New Delhi: Ministry of Education and Social Welfare, Government of India

[5] Government of India, 1988. Shramshakti: Report of the National Commission on Self-Employed Women and Women in the Informal Sector

[6] ibid

[7] Mishra, S and Shubhika Sachdeva in Agrawal, N., 2021. Her Right To Equality: From Promise to Power. Penguin Random House India Private Limited.

[8] ibid

Why do women depend less on informal sources for job search than men?

The latest PLFS round reveals that job search methods differ between men and women with women relying more on formal sources of job searches than men. The formal job search methods include applying to prospective employers/places, answering job advertisements, checking at factories, and work sites, registering with employment exchanges, and registering with private employment centres. In contrast, informal sources comprise personal networks, including relatives and friends. According to PLFS 2021-22, 76% of unemployed men are looking for a job through formal channels, whereas 87% of unemployed women, a much higher share, are resorting to formal sources for the job search. 20% of unemployed men are using their informal networks to find a job, and the share comes down to a much lower 12% in case of women. The rest of the unemployed are either seeking finance for starting a business or applying for a permit to start a business. This blog explores the reasons behind women’s preference for formal sources for job search over informal ones.  

Informal networks, as a social resource in job search, provide access to more valuable information which are unavailable through formal means. As a result, informal networks are often more efficient to navigate individuals into better job matches with higher job satisfaction and earnings more quickly. PLFS data corroborates this view of network efficacy as it is observed that women searching for a job through informal sources face a shorter duration of unemployment than those depending on formal sources. Among the unemployed women currently looking for a job through a formal source, more than 30% women face a spell of unemployment of more than 2 years and for 18% women, the duration of the spell of unemployment has been more than 3 years at that time of survey. On the other hand, only 15% of the unemployed women who use the informal sources for job search, had a duration of a spell of unemployment of more than two years, and only 8% of them faced a spell of unemployment of more than three years.

Despite informal networks being more effective, women depending more on formal job search methods as compared to men, have several causes and implications. Informal networks are powerful for job-hunting when they can grant access to a more heterogeneous set of people, located in various sectoral and occupational positions. With the diversity of people in network, the non-redundancy of job information and the effectiveness of one’s network rises. Also, with higher socio-economic status of one’s informal contacts, the chances of receiving information about highly paid jobs, jobs in higher social stature, increase. However, the composition of women’s informal network is often found to differ from men. With a much higher share of family responsibilities and less participation in the workforce, women have limited exposure to diverse group of contacts. Marriage further limits their informal connections due to the cultural restrictions preventing freedom of interactions with outsiders. Also, with gender homophily i.e. the preference of interactions with persons of their own gender, the informal networks are often gender-segregated with women’s network being predominantly consisting of women only. Additionally, due to the existing gender-based segregation in the labour market, women’s presence is low in high-wage, high-skill sectors and occupations. Thus, in a gender-segregated network, women get limited access to information about the high-skill, highly-paid jobs. These factors together explain why fewer women in comparison to men, find their informal network to be effective for job search and majority follows the formal search methods. However, women who had worked previously tend to depend on their informal network more than those who never worked as often due to the exposure associated with their work experience they tend to have more diverse informal contacts and an effective source of information for job opportunities.

 

 As placements through informal routes often tend to reinforce the existing gender-based occupational and industrial segregation, women with higher education depend more on formal sources in an attempt to escape the trap of female ghettoization in low-paid jobs. The PLFS data reveal that among women without any literacy, 48% depended on informal sources, with the dependence coming down to 17% for women with primary and below primary level of education, 22% for women with middle to higher-secondary level of education, and only 8% for women with graduation and post-graduation level of education. For the urban areas, women with basic and intermediate level of education depends relatively more on informal networks as compared to their rural counterparts. This indicates that for the semi-skill occupations, women’s informal network is relatively more effective in urban areas than rural areas. But again, for women with education level of graduation, post-graduation and above, the dependence is very less on their informal network in both rural and urban areas. Although for men too, the reliance on the informal network gets reduced with increase in education level, the decline is starker for women. This diminishing dependence on informal network for more educated women aspiring for better paid white-collar jobs appropriate to their education levels, points towards their gender-segregated informal network as a less effective source of information. 

However, as revealed by the PLFS data, even among the highly educated women, expectedly looking for high-skill, highly-paid jobs, those who have dependable informal network and thus explore that, face a shorter spell of unemployment as compared to those who depend on formal sources. Among women with education level of graduation, post-graduation and above, around 30% women faced a spell of unemployment of more than two years and 17% are looking for a job for more than three years, as they depended on formal sources of job-hunting. On the other hand, only 16% faced a spell of unemployment for more two years and only 5% for more than three years when these highly qualified women looked for jobs though informal sources. This indicates that informal networks when can be depended on for high-skill jobs too, can be more effective as compared to formal sources.

The findings from PLFS indicate the need of recognition of the lack of social capital for women and their exclusion from male-dominated influential informal ties and networks. Women are not a homogeneous group and there exist many other cross-cutting socio-economic factors among them determining their reach to the informal contacts instrumental to gender-balanced jobs. Even after considering these factors, women across all sections are in a disadvantageous position. This is majorly due to the gendered nature of social network and women’s poorer structural location in the jobs market ladder. With the job search method often playing a crucial role in reinforcing the existing gender-based occupational and industrial segregation by leading to women’s concentration in women-dominated jobs, few measures on part of the government and Civil Society Organisations might prove helpful. For example, developing strategies to form networking groups that will help women establish the right connections by making ‘women in powerful positions’ a part of these groups; sensitisation about the often consciously created resistance to women’s integration to the influential network, might be undertaken to address these concerns at least partially.

 

Author: Bidisha Mondal is a Research Fellow at IWWAGE. 

Need for Evidence on Skilling in India

In recent years, India’s demographic dividend has sparked scrupulous policy actions to increase its labour force participation. With India having the largest youth population in the world, the government aims to empower the youth using the ‘4E approach’ (Education, Employment, Entrepreneurship, and Excellence). The strengthened emphasis on the aforementioned pillars is inclusive of skill development and has therefore generated a renewed buzz around it. Skill development is increasingly considered a key stepping stone not just towards enhancing India’s overall labour force participation, but especially for the economic upliftment of a pertinent group of beneficiaries, women.

ILO’s Global Employment Trends (2013) rank India 120th out of 131 countries in female labour force participation. The Periodic Labour Force Survey 2020-21 reports that only 34 per cent of females within the working age group are employed. Skilling is looked upon as one of the solutions to the problem. This blog argues that good quality data is a prerequisite to assess the effectiveness and gendered outcomes of skilling programs running across the country.

If we were to google the terms “skill”, “India” and “women” today, approximately all search results would point towards and encourage the importance of skill development for women’s economic empowerment. Even though skill development programmes have existed for decades, they have found a recent push to generate and ensure improved work opportunities for the heightened employable population of the country.  Budget 2023-24 also prioritized funding for the launch of the national flagship programme on skill development: Pradhan Mantri Kaushal Vikas Yojana (PMKVY) 4.0, which, in lieu of the rising technological advancements, aims to promote skilling in new-age courses like 3D printing, robotics, AI etc.

Several skill development programmes are running across the country, which are differentiated on the basis of their funding sources, policy-making, and implementation bodies, etc. Guided by the National Policy on Skill Development (2015), various schemes are run by the state such as the aforementioned PMKVY, Deen Dayal Upadhyay Grameen Kaushal Yojana (DDUGKY), Jan Shikshan Sansthan (JSS), and National Apprenticeship Promotion Scheme (NAPS). The central body that coordinates all possible skill development efforts across the country is the Ministry of Skill Development and Entrepreneurship (MSDE), accompanied by its various facilitating bodies. The Ministry was launched in 2015 to improve the link between the demand and supply of skilled workforce and further build the vocational and technical training framework.

Among various facilitators for skilling schemes, National Skill Development Corporation (NSDC) was set up to help generate funding through Public-Private-Partnerships (PPP). Corporate Social Responsibility (CSR) funds have also driven towards skill development for women.

With such a range of policy intentions and the subsequent programmatic actions towards skilling for women, it is important to gauge how they have impacted women’s engagement in the labour market. The cardinal focus could be to understand how far the extensive skilling ecosystem has upskilled and led women towards being sustained labour force participants, what works for them within these skilling programmes, and what challenges continue to exist that require redevelopment.

According to the Skill India Reporting Hub, the administrative data on the overall implementation of PMKVY portrays that out of more than 60 lakh women enrolled for the scheme, less than one-fifth ended up getting placed. This stark difference between enrollment and placement highlights the need to understand and inspect the skilling process in India. Just like any other social development program, gender sensitivity is also pertinent to the skilling process- wherein, challenges specific to women exist, in addition to overall hurdles with respect to the existing labour supply and market demand.

Gender sensitivity in skilling programs goes on to but is not limited to, recognizing differential needs, building improved support systems, generating disaggregated information, and taking further action based on continued reflection and feedback. Setting up of 5000 new Skill Hubs all across India to further the efforts of Skill India, and “provide comprehensive vocational and skilling training” was highlighted during Budget 2023-24. However, how these hubs will undertake efforts to increase enrolment and retention of women candidates is yet to be seen.

The state-led skilling schemes do undertake measures for increasing women’s participation through reservation, running women-only Industrial Training Institutes (ITIs), and providing stipends for travel and residence. However, the statistics suggest the need to go beyond them. There is a need to reflect, regroup and renew our actions to make the continued efforts towards skilling more effective.

It is arduous to delve deeper into the challenges that surround the skilling of women in India due to limited data availability. Administrative data on state-led skilling programs is available through the following portals: Skill India Reporting Hub, NCVT MIS, PMKVY Dashboard, NRLM (on DDUGKY), MSDE dashboard, and NSDC. The data shared through these portals vary with respect to the indicators they contain, and are often not consistently updated or are sparsely filled. The most desolating fact within these available portals is that only a few provide sex-disaggregated information. Even when examined at the state level, only a  few states (Assam and Bihar) provide sex-disaggregated information on their MIS administrative portals on skilling. This is accompanied by a lack of information on process indicators – where ‘enrolment of candidates’ is the consistent measurable indicator, with information lacking on other process indicators such as completion of training, certification, placement, etc. Therefore, the need of the hour is to first build information systems that would help monitor the track we are on before we pace up our actions.

Further, the data on post-placement bifurcation, including employment type, retention rates, etc., is also publicly unavailable. Information on PPP and the role of the private sector in the skilling ecosystem are also not amalgamated within these portals. Data on efforts added by such non-state actors to skill the present population are also almost completely lacking.

The Periodic Labour Force Survey (PLFS) is one of the nationally representative surveys that collect primary data on India’s labour force participation, which also happens to include some indicators on the state of skilling in India. Apart from the sparse information obtained through PLFS on skilling, the assessment of the effectiveness of the skilling ecosystem in India is predominantly seen in micro studies. Though it is found that skilling enables women to join the labour force, many studies report challenges that vary depending on the different stages of the skilling process – from the generation of policies, and release of programs or schemes to their uptake, operation, and finally, their contribution to the existing labour force.

The literature further reports that the participation and uptake of women within these programs are deeply affected by societal norms which control their educational status, decision-making, mobility, and access to information and technology.  Importantly, these barriers also encompass how skilling programs are rolled out. For example, the introduction of courses under PMKVY for a ‘digital India’ in lieu of technological advancements would also require taking cognizance of the existing gender differential access to technology.

Therefore, robust evidence generation is pertinent for the skilling programs to identify challenges, improve and run effectively. Such an effort may help track changes in female labour force participation through skilling. However, to further help improve women’s overall well-being and standard of living, access to quality jobs with improved working conditions is necessary. It is essential therefore to track where the women tend to get employed, the sectors they are employed in, and the working conditions they are exposed to by uniting the broad skilling ecosystem in India. Developing such a system would require a holistic approach towards skilling which ensures synergy between policy-making, funding, and implementing bodies. The MSDE could act as a body that oversees these processes and puts into place an accountability mechanism.

Though skilling may prove to be an essential factor in helping more women join the Indian workforce, a meaningful policy dialogue on the subject will only be  possible with the support of enhanced quality of data. This will not only be possible through  cogent data collection, but also making existing data more accessible to development practitioners and policymakers. Such intersectional data can lead to meticulous future actions to address gender inequality and can act as an essential driver of economic growth and prosperity. But most importantly, aid in uplifting individual rights and empowerment.

Prakriti Sharma is a Senior Research Associate at IWWAGE, and has previously worked in the intersection of migration and feminist economics. She is currently engaged in visiblizing women’s work through its improved measurement.