Blogs – IWWAGE-Institute for What Works to Advance Gender Equality

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

27th September 2024

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

National Conclave on Gender Mainstreaming

18th September 2024

National Conclave on Gender Mainstreaming

The Gender Snapshot Report by the United Nations (2023) highlights slow progress towards Sustainable Development Goals (SDGs) for 2030. It projects that by 2030, over 340 million women and girls may live in extreme poverty, and close to one in four will face food insecurity. Urging immediate action, the report calls for integrated approaches, greater collaboration, sustained funding, and policy reforms to achieve gender equality and empowerment.

The G20 declaration reinforces this urgency with a focus on reducing gender gaps in labour force participation, promoting equal access to education, and increasing women’s participation in STEM and digital fields. It also emphasizes promoting access to social protection, eliminating gender-based violence, and ensuring women’s inclusion in the formal financial system.

Background

In recent years, the Gender Programme under Deendayal Antyodaya Yojana-National Rural Livelihood Mission has made significant strides, moving from policy integration to large-scale implementation. Notable achievements include the establishment of Gender Resource Centres across 15 states, and estabilishment of 44,528 Gender Point Persons collectives, 33,736 and 1,461 Block level Gender Forums respectively as platforms for dialogue and action.

The national campaign ‘Nayi Chetna,’ launched in 2022, has seen widespread engagement, fostering inter-ministerial convergence and community action to combat gender-based violence. The campaign, actively carried out in 32 states has seen close to 6 crore participation in activities over the two years advocating the need to speak up and take action against all forms of gender-based violence. Four editions of the ‘Gender Samvaad’ have further amplified advocacy efforts, drawing participation from community resource persons, practitioners, and policymakers.

Overview and objective

As the programme enters its second phase, the conclave will draw insights from practitioners, policy makers, experts and cluster level federations and explore:

Building Gender Responsive Community Institutions through stronger institutional mechanisms.
Enhancing inter-ministerial convergence to address gender issues collaboratively.
Integrating gender perspectives into NRLM’s thematic verticals to shift gender norms at the household level.
Expanding stakeholder engagement through alliances and advocacy, with a focus on engaging men and youth.

We are collating relevant information and links for your ease of access here.

Our Publications

Handbook for Institutional Mechanisms for Addressing Gender Issues

Gender Resource Centre: An Advisory

An Assessment of the National Gender Campaign for DAY-NRLM

Nayi Chetna- Coffee Table Book Year One Snapshot

SWAYAM Process Evaluation

Process Documentation Report

An Assessment of the Compiled Case Stories

Gender Modules

Workshop on Capturing Women’s Work (CWW) held at India Habitat Centre, New Delhi on July 24, 2024

13th September 2024

Workshop on Capturing Women’s Work (CWW) held at India Habitat Centre,
New Delhi on July 24, 2024

The workshop on Capturing Women’s Work (CWW) took place on July 24, 2024, at the Indian Habitat Centre, New Delhi. Hosted by IWWAGE, the event aimed to address the complexities and challenges in accurately measuring women’s work.

The inaugural session featured key insights from Radha Chellappa, Executive Director, IWWAGE, Neeta Goel, Country Lead – Measurement, Learning and Evaluation, Bill & Melinda Gates Foundation Foundation and Sona Mitra, Director – Policy and Research, IWWAGE focusing on findings from the IWWAGE study.

Led by Sona Mitra, the IWWAGE research team showcased their findings from the study titled ‘Capturing Women’s Work to Measure Better’ which aimed at developing better mechanisms for data collection by employing innovative probing techniques and sampling frames tailored to capture the nuances of women’s work. Additionally, the session emphasized on the importance of creating a robust framework for conducting women-specific surveys that could be aligned with national Labour Force Surveys (LFS). This would help in obtaining more comprehensive estimates of women’s labor force participation. The session concluded with a series of participant inquiries. The presentation of time use findings sparked discussions about how women’s time allocation evolves with age, specifically when unpaid domestic work becomes a daily routine, and the factors contributing to the transition from ‘girl’ to ‘woman’.

The second half of the presentation focused on findings around identifying and addressing the significant perception bias that often underestimates women’s economic contributions (in cases where the respondent is not the woman herself) were presented. Through these efforts, the sessions aimed to advance methodologies that more accurately reflect women’s roles in the economy.

Findings from the CWW study revealed notable gaps between self-reported data and societal perceptions, highlighting the need to include unpaid domestic work in workforce measurements for greater accuracy.

Discussions also covered the economic valuation of unpaid work, the impact of household characteristics on perceptions, and the significance of detailed recovery questions. Key points included discrepancies between the PLFS 2022-2023 and CWW survey estimates of female labor force participation rates, as well as concerns about the lack of a 180-day principal activity benchmark and the survey’s ability to accurately capture women’s work, particularly in Jharkhand.

The workshop ended with a panel discussion, moderated by Yamini Atmavilas, bringing together experts like Jeemol Unni, Madhura Swaminathan, Rosa Abraham, Neetha N, and PC Mohanan. They discussed innovations in measurement methods and the limitations of current survey instruments. Emphasis was placed on the need for regular Time Use Surveys (TUS) and refining survey tools to capture the dynamic nature of women’s work, including unpaid care and domestic activities. The panel concluded that improving measurement accuracy and recognizing the economic value of women’s work are essential for addressing historical underreporting and better informing policy decisions.

Related Resources
CWW Summary of Findings
CWW Report

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

13th August 2024

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.

karunakar

1st August 2024

Karunakar Rao

Communication Manager

Karunakar Rao is a Communication & Convenings Manager at LEAD. Previously, he worked with organisations including ACCESS Development Services, AIACA and Oxfam India.

Karunakar holds a Master’s and Bachelor’s Degree in Journalism and Mass Communication from Guru Gobind Singh Indraprastha University, Delhi.

His core experience lies in brand communications. Karunakar is passionate about strategic planning, design, content development and dabbles in photography and videography. In his free time, he likes to pamper dogs, travel, binge-watch on OTT platforms and party.

Reshaping gender roles in India: Improving women’s economic outcomes

2nd July 2024

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

31st May 2024

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.

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.

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).
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.
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.

Challenges arising for electoral roll-,zbased sampling method while implementing the survey:
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.
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.
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.
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.
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.

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.

IWWAGE at the 64th Annual Conference of the Indian Society of Labour Economics (ISLE) at Hyderabad, Telangana

17th May 2024

IWWAGE at the 64^th Annual Conference of the Indian Society of Labour Economics (ISLE) at Hyderabad, Telangana

IWWAGE participated in the 64^th Annual Conference of the Indian Society of Labour Economics held in Hyderabad, Telangana in March 2024. The ISLE engagement included organizing a panel discussion on “care,” participation in a panel on time use methods as well as paper presentations by team members.

PANEL DISCUSSIONS

Caring for the Caregivers: Pathways to Strengthen the Care Economy

29^th March 2024

IWWAGE along with the Institute for Human Development organized a panel on “Caring for the Caregivers: Pathways to Strengthen the Care Economy” which highlighted pressing issues around care based on specific contexts, advocating for better working conditions and facilities including access to key amenities like toilets and transportation. The discussion delved into the scope and environment of care work, emphasizing the need for financing, enhanced investments, and adequate legal frameworks to protect the rights of care workers. The panel was chaired by Yamini Mishra (India Director, Mac Arthur Foundation) with introductory remarks by Sona Mitra (Research & Policy Director, IWWAGE). The panellists included Ritu Dewan (Visiting Professor, IHD), A K Shivkumar (Visiting Professor, IHD), Valeria Esquivel (Employment Policies and Gender Specialist, ILO), and Prabha Kotiswaran (Professor, King’s College London) with Dipa Sinha (Assistant Professor, Ambedkar University, Delhi) joining as a discussant. The session concluded with remarks from Radha Chellappa (Executive Director, IWWAGE) encapsulating the importance of the dialogue and its implications for policy and practice.

Integrating Time Use Module with Labour Force Surveys

30^th March 2024

Organized by the Centre For Women’s Development Studies (CWDS), New Delhi, this panel delved into the possibilities and challenges of integrating time use data into labour force surveys, a crucial step towards understanding the unseen aspects of labour and productivity. The panel was chaired by TCA Anant (Adjunct Professor, Tata Institute of Social Sciences). Sona Mitra (Director – Policy and Research, IWWAGE) presented insights from a primary study that incorporated gendered activities and time-budget components. The esteemed panel was chaired by TCA Anant (Adjunct Professor, Tata Institute of Social Sciences) and also included the following experts: Padmini Swaminathan, Former Director, Madras Institute of Development Studies; G.C. Manna, (Professor, IHD India, Former Director General, CSO and NSSO) P.C. Mohanan (Chairman, Kerala State Statistical Commission), Kripa Ananthpur (Professor, Madras Institute of Development Studies) and Neetha N. (Professor, Centre for Women’s Development Studies).

PAPER PRESENTATIONS
1. Paper Title: “Informant bias’, a key factor behind underestimation of women’s work: Evidence from two IWWAGE surveys”
Authors: Sona Mitra, Bidisha Mondal, Prakriti Sharma and Aneek Choudhury
Summary: Using two primary surveys, the paper assessed the ‘informant bias’ across various economic and non-economic participation of working-age women and further investigated how it varied across the demographic and socio-economic characteristics of individuals and households.
2. Paper Title: How care responsibilities influence women’s labour force participation and the nature of their employment: Evidences from PLFS 2022-23
Author: Bidisha Mondal
Summary: Women belonging to households with childcare responsibilities are two times more likely to stay engaged in full-time domestic duties and thus stay out of the labourforce, as compared to women without childcare responsibilities. Moreover, when women with childcare responsibilities participate in the labourforce, they are more likely to be engaged in non-remunerative opportunities like unpaid family work probably due to the flexibility these types of engagement provide. Elderly care responsibilities are found to restrain women’s labourforce participation decision and remunerative engagements marginally.
3. Paper Title: “Formalising Care Economy will have Far-Reaching Implications for Women’s Employment ”
Authors: Mridusmita Bordoloi (IWWAGE), Prof. Rajshree Bedamatta, IIT Guwahati
Summary: This paper defines the care sector and the care workforce in India, based on the definition suggested by International Labour Organisation (ILO), using unit level data from PLFS, 2022-23, and explores the characteristics of the care workers. The paper argues that if the care sector can be developed further and formalised, it can have far-reaching implications. It will not only create new job opportunities in the economy for individuals across gender, but can also work as an enabler in women’s labour market participation, which is significantly low at present.

Vidhi Singh

15th May 2024

Vidhi Singh

Research Associate

Vidhi holds a Master’s degree in Public Policy and Governance from Azim Premji University, Bengaluru. She has previously interned with SEWA Bharat and PRS Legislative Research. Before joining IWWAGE as a Research Associate, she was working in the capacity of a Research Analyst in a private consulting firm based out of Lucknow. In this role, she was involved in monitoring and evaluation research studies at the intersection of gender and health. From her schooling years, she has been active in advocating for gender rights and wants to continue working in the domain. Her areas of interest primarily include intersections of gender and data. Additionally, she describes herself as an avid consumer of Hindi cinema and is very highly influenced by the actor Shah Rukh Khan.

Capturing Women’s Work Through Time Use Surveys: Implications for Policy

15th May 2024

Capturing Women’s Work Through Time Use Surveys: Implications for Policy

Dr. Ellina Samantroy, Fellow at VV Giri National Labour Institute, joined us for our seminar series on April 22nd, 2024 to discuss “Capturing Women’s Work Through Time Use Surveys and Further Implications for Policy Making. Dr. Samantroy laid the context by highlighting two alarming issues: the gender gap between men and women and the low participation of women in the job market. This is substantiated when we look at the figures in 2023, where 48.7% of women participated in the labor market as compared to 73% of men.

Women’s work participation was continuously decreasing since 2004-05 and then it started increasing after 2017-18. This increase can be attributed to the increased proportion of the self-employed workforce. The question now remains understanding the concentration of self-employed workforce across occupations and sectors. This can be clearly identified by using TUS (Time Use Survey) data.

Highlights from Dr. Samantroy’s seminar are shared below:

Background of TUS:

TUS is a quantitative summary of how individuals allocate their time over a specified time period- typically over 24 hours in a day or over the 7 days of a week on different activities and how much time they spend on each of these activities. Further, it diversifies activities into three categories: SNA activities (activities that fall within the production boundary of the UN System of National Accounts), non-SNA activities (activities which are not included in national accounts but are covered under the General Production boundary and include delegable production of services) and personal services (non-delegable services eg. sleeping, watching TV, etc.). TUS sheds light on the specific activities the individuals in the reference population are engaged in. It also talks about the time spent on doing certain activities like, average number of hours in a day spent on travelling and unpaid domestic work among other activities.

Shift from NSSO to TUS:

Women’s work has not been documented effectively in NSSO surveys as it provides generalized answers, not delving deeply into certain probing questions. NSSO data does not provide answers for restricted women’s participation based on geographical location. Also, there is a lack of occupational segregation in the survey.
TUS focuses on capturing unpaid domestic activity and other non-market activities.
Additionally it provides information on multiple and simultaneous activities and some other insights using context variables. These variables look at details of the activity, specifically looking into the location, presence of other people when the activity occurred, beneficiary perception, and monetary motivation behind the activity.
TUS gives visibility to the care economy, captures time stress, and improves workforce estimates along with throwing light on the scattered and sporadic nature of informal work. It helps in understanding the percentage of time spent on unpaid domestic and care work by sex, age group, caste, religious group, and location wise.

Highlights from National TUS 2019:

They have coded 9 activities under TUS.

Participation rates of women workers in unpaid domestic services for household members are 94.5% and 87.9% in rural and urban areas respectively. Compared to men workers, participation rates are 33.7% and 24.6% in rural and urban areas respectively.
The average time spent by women workers on unpaid domestic services for household members are 4.1 hours and 3.6 hours in rural and urban areas respectively. On the other hand, the average time spent by male workers on unpaid domestic services for household members are 1.6 hours and 1.5 hours in rural and urban areas respectively.
Under the unpaid domestic services, women are involved in care and maintenance of textiles, footwear, food and meals preparation and cleaning and maintenance of surroundings across both rural and urban areas.
The average time spent by women in unpaid domestic work is around 2.5 hours, primarily in food and meal preparation. Digging deep into unpaid caregiving services, around 20-23% of women are engaged in childcare and instruction across rural and urban areas. Additionally, the average time spent on unpaid caregiving services, specifically in childcare and instruction is around 1.7 hours across both rural and urban areas for women.

Limitations of TUS: