Reducing gender disparities in workforce participation is an important policy goal in several developing countries. India, in particular, has historically had low levels of women’s workforce participation as compared to men and as compared to peer economies. Prior research has identified both supply and demand-side explanations for low levels of women’s participation in paid work. On the supply side, social norms constraining women’s mobility and autonomy are commonly invoked as one explanation. We test the relevance of such norms in explaining heterogeneity in women’s employment using district-level data from the National Family Health Survey (NFHS) 2015 – 16 and the Sixth Economic Census (2013). Norms indices are constructed using Principal Components Analysis for 640 districts of India. The findings indicate that less restrictive norms related to decision-making, mobility, and asset ownership are positively correlated with higher levels of women’s employment.

Authors:

Subhapriya Chakraborty and Amit Basole

Unemployment is one of the key macroeconomic variables used to assess the performance of an economy. However, there is a bias towards conceptualizing unemployment solely through its predominant measure of rates. Considering that rates alone do not reflect labor market conditions, especially in developing countries, it is crucial to include unemployment duration in analyzing labor market efficacy and the larger economy. This paper utilizes longitudinal data from CMIE to understand the determinants of unemployment duration through an OLS linear regression and survival analysis. It finds that the groups that experience longer spells of unemployment are young and old individuals, the highly educated, and upper caste individuals. Nonparametric survival analysis is also employed to account for censoring through the hazard and survival function. This model also finds that duration dependence is non-monotonic with individuals experiencing high initial re-employment probabilities before experiencing a decline in their hazard rates. However, analysis of re-employmentwages and occupation indicates a positive association with unemployment duration which indicates potential benefits to extended job search.

Author:

Roshan Kannan

The cross-sectional nature of Indian employment surveys limits a true understanding of labour market dynamics. Using innovations in official national-level labour surveys that track urban individuals across four quarters, we study transitions from unemployment to employment — defined as the job-finding rate — to understand whether those seeking employment are able to find suitable work in urban India. Our analysis reveals significant weaknesses in the urban Indian economy over the period 2017 to 2023. On an average, only 17 per cent of unemployed individuals in any quarter find a job in the next quarter. Job-finding rates are the lowest for women, the young and the highly educated. Hazard-rate analyses reveals that the same cohorts take the longest time to find jobs, with a majority remaining unemployed even after four quarters of job search. We demonstrate the impact of the pandemic on urban labour markets in two ways. Not only are job-finding rates significantly lower in the post-lockdown period relative to pre-lockdown, there has also been a shift in the nature of jobs created, with casual work rising and regular wage and self-employment falling post-lockdown. Our analysis has important policy implications for understanding labour market dynamics and for the design of urban employment schemes.

Authors:

Rahul Menon & Paaritosh Nath

Employment projection, particularly at the micro or sectoral level, is considered as a useful tool for economic planners and policymakers to have a better understanding of future trends and growth, and accordingly, the policies and planning could be designed for the supply side of the labour market. 

This study finds that there is a lack of literature in the recent past on the above issue in the context of India, hence in this paper, we have tried to estimate employment numbers for seven broad economic sectors for the period 2024 – 25 to 2030 – 31. The study uses the ​“Top-down” approach to estimate and project the employment numbers by using the employment-output elasticities and forecasted values of growth rates of gross value added (GVA) at the sectoral level. 

Three broad conclusions have been drawn from the employment estimates. First, the agriculture and allied sector continued to be the dominant force in creating employment opportunities till 2030 – 31, however, a surge of employment in the sector in recent years may unlikely continue in the future. Second, the slowing down of economic activities in services sector is expected to dent high employment growth prospects in the sector. Third, a phenomenal rise of employment in industry particularly in manufacturing sector in recent years augurs well for the economy which is expected to remain buoyant in the medium term as well

Studies based on the Consumer Pyramids Household Survey (CPHS) in India have shown that the impact of the Covid-19 lockdown on household incomes was progressive in nature — richer households suffered more. But several media reports as well as purposive surveys carried out during the pandemic suggest that the poor suffered more than the rich. We use nationally representative panel data for urban India from the official Periodic Labour Force Survey (PLFS) to show that households that were relatively richer prior to the start of the pandemic suffered relatively less during the lockdown compared to households that were poorer. That is, the shock was regressive in nature. We also confirm that, as per CPHS, richer households did indeed experience higher drops in income than poorer ones. But we show that this progressivity is much less than what prevailed prior to the pandemic. Thus the pandemic either disrupted ongoing progressive income changes or was outright regressive in its impacts.

Authors:

Amit Basole, Anand Shrivastava, Jay Kulkarni and Akshit Arora

Caste and class are two major markers of social and economic stratification in India. They play a crucial role in sustaining and strengthening the process of social exclusion. It has been often expected that the process of economic growth and modernization may weaken the congruence between caste and class structures and induce social and economic mobility, thereby bringing about a change in the socio-economic environment. In this paper, we focus on the celebrated period of high economic growth in India during the previous decade to study the evolution of caste-class dynamics, to analyse the pattern of association between caste and class positions, and examine whether this association/​congruence has weakened during this period. The analysis is based on four rounds of employment-unemployment surveys of the National Sample Survey Organization covering the period 1999 – 2012. We construct a matrix of caste and class positions of repeated cross-sections of individuals that shows whether different caste groups are over- or under-represented in different class positions and how these representations have changed over time. We then use a multinomial logistic regression framework to capture the role of caste in explaining the conditional probability of an individual to belong to a particular class position, after controlling for other critical explanatory variables. We further examine how the explanatory role of caste has changed over time. Additionally, we explore the role of education, a crucial channel for socioeconomic mobility, in explaining the class positions of individuals belonging to different caste groups over time. Finally, we examine the impact of high economic growth in determining the class position of an individual in general, as well as for different caste groups over time. The analysis shows that caste has continued to remain an important factor in explaining class locations of individuals during the period of high economic growth. Further, the caste-class associations have continued to persist across different categories of education over time. While there has been a partial weakening of certain associations during the period, particularly for the Other Backward Castes and in some parts of the rural sector, the overall picture is more of continuity than change, with further strengthening and reinforcement of caste-class congruence along several axes. This calls into question the expectations about social mobility with economic growth as well as the nature of economic growth in India.

Author:

Vaishali Kohli

The last few years have seen an upheaval in practices of data collection and survey methods. Even before the pandemic, several data collection endeavors had begun the transition to digital, computer-assisted, and tablet-based surveys. India’s labor force surveys themselves had moved away from traditional paper- based surveys to computer-assisted PI techniques. The Covid-19 pandemic imposed a massive shock to these practices. Across several countries, ongoing surveys had to be prematurely terminated or put on hold in the interest of the safety of enumerators and interviewers.

Authors:

• Rosa Abraham
• Mridhula Mohan

Author:

• Vijayshree Jayaraman

In developing countries, a precise approach to measuring women’s employment remains elu- sive. Emerging evidence underscores the pivotal role of survey methodology, encompassing respondent selection and question framing, in shaping the assessment of women’s employ- ment. Drawing from two labor market experiments in rural India, this study offers insights on the influence of survey design on the measurement of women’s employment. The first ex- periment contrasts self-reported women’s and men’s employment figures with proxy-reported data from spouses. Women’s self-reported workforce participation surpasses proxy-reported estimates by six percentage points, while men’s estimates exhibit negligible differences. There are significant differences in the type of employment activities reported by self and proxy for both women and men. These divergences emanate from asymmetric measurement errors, stemming from gender-based norm disparities between spouses, and divergent interpretations of employment. Additionally, information asymmetry between spouses concerning women’s marginal activities and disparities in spousal characteristics contribute to these self-proxy differences. The second experiment investigates if framing of questions and recall period has an impact on reporting of labor market outcomes. We find that employing multiple ques- tions to capture weekly employment status yields a 10-percentage-point increase in reported women’s workforce participation, but men’s participation rate decreases by six percentage points. Furthermore, when a distinct employment query is directed at each day of the pre- ceding week as opposed to a single query for the entire week, reported women’s workforce participation increases by seven percentage points, and men’s by four percentage points.

Authors:

• Rosa Abraham
• Nishat Anjum
• Rahul Lahoti
• Hema Swaminathan

Authors:

• Zico Dasgupta
• Amit Basole

Alongside rapid economic growth, India also saw steady de-agrarianisation of its economy in terms of contribution to GDP. In terms of employment, however, the movement out of agriculture was slower, and when they did exit, it was often a withdrawal from the workforce entirely. In general, more of the workforce are in salaried employment, however, these have filtered differently by gender, caste and religion. While cross-sectional data gives us a sense of how these structural changes affect workers at any given point in time, it cannot tell us how these play out for workers over their lifetime as well as how different generations or cohorts of workers have been affected. Here, we use seven rounds of nationally representative official data to construct cohorts who are tracked over these periods to observe employment participation and the patterns over time. We find that younger generations of women systematically less likely to be in paid employment whereas for men, after a certain age, generations look similar in terms of employment rate. Similarly, when examined from the perspective of cohorts, we find that access to salaried employment has changed by gender and caste, and increase in earnings over time over their lifecycle has slowed for certain groups.

Author:

• Rosa Abraham

Small manufacturing firms are considered to be engines of growth and job creation. While most research on small firms focuses on formal sector units, in India informal sector units far outnumber the formal. This is true even for manufacturing units employing 5 to 49 workers, which constitute only 5% of all unorganised units, but in absolute numbers are nine times more numerous than organised units in the same size class. Such firms have the potential to contribute to structural transformation but their capacities vis-a-vis formal firms are not well understood. To address this, the researchers create a unit-level dataset combining Annual Survey of Industries data for organised (formal) units with the National Sample Survey data on unorganised (informal) units. They also discuss problems involved in this exercise and some ways to deal with them. They find that matching organised and unorganised units on observable characteristics reduces the labour productivity differences between them to around 25 percent. The researchers discuss some policy implications of their results.

Authors:

• Amit Basole
• Dimple Chopde
• Paaritosh Nath

Utilising data from the Periodic Labour Force Survey, the researchers estimate quarterly changes in urban labour market flow over the period 2018 to 2022 and the impact on unemployment rates for men and women. Their analysis provides non-intuitive explanations for established findings as well as points out important questions for further study. Both men’s and women’s unemployment rates have reduced in 2022 compared to 2018, showing rapid reductions following the high levels reached during the lockdown. Women’s unemployment rates have consistently been higher than men’s throughout this period. The gap between men’s and women’s unemployment rates reduced during the lockdown, but has shown signs of increasing since 2021, even as unemployment rates have fallen. For women, flows from the labour force to non-participation play a larger role in explaining changes in unemployment rates as compared to men. Flows from the labour force to non-participation, however, have reduced since the pandemic, providing an explanation as to why labour force participation rates have increased, namely, women staying for longer in the labour force rather than more women entering it. Despite rising labour force participation rates, the gender gap in unemployment rates has risen, in contrast to developed economies.

Authors:

• Paaritosh Nath
• Rahul Menon

We investigate the impact of the COVID-19 pandemic on income levels, poverty, and inequality in both the immediate aftermath and during the long uneven recovery till December 2021 using high-frequency household survey data from India. We find that the average all-India household income dropped between 30 to 38 percent during the months of the nationwide lockdown of April and May 2020. The subsequent recovery remained incomplete and was unevenly spread over the population even twenty-one months after the start of the pandemic. Households, on average, continued to make 16 to 19 percent lower cumulative income in the post-lockdown period, but have mostly recovered after the second wave in the second half of 2021. Poverty more than doubled during the lockdown and was 50 to 80 percent higher in the post-lockdown period in comparison to the pre-pandemic levels. In the post-second-wave phase, poverty was still slightly higher than in the pre-pandemic period, and any progress in poverty reduction that would have been achieved under normal circumstances over the two years was lost. Inequality too spiked during the lockdown, but returned back to the pre-pandemic levels. Using an event study model we find that the initial shock of the lockdown was more severe for the bottom of the income distribution, but the bottom also experienced a faster recovery. On the other hand, the top end of the distribution experienced smaller declines during the lockdown but they have been slow to recover. The bottom deciles in any period typically constituted households working in contact-intensive, informal, less secure occupations that were hit the hardest during the lockdown, but were quick to recover when the economy opened up. The upper end of the distribution constituted households working in less contact-intensive, formal, secure occupations that were shielded from the sudden shock but were slow to recover.

Authors:

• Mrinalini Jha
• Rahul Lahoti

This paper revisits a part of the analysis by Banerjee et al. (2020), in which they examine the consequences of the nation-wide scale up of reforms to the funds management system (e‑FMS) in India’s national workfare programme, using a two-way fixed effects specification. They report a substantial 19 percent reduction in labour expenditures. We exploit the recent literature that highlights the limitations of the TWFE estimator in the presence of staggered roll out and effect a Goodman-Bacon decomposition of the TWFE coefficient, to pinpoint sources of identifying variation. We undertake a detailed examination of subsamples of six constituent and valid DiDs based on timing of treatment that are averaged into the TWFE coefficient to identify heterogeneity in treatment effects. This disaggregated subsample analysis does not support the conclusion of any reductions in MGNREGS labour expenditures, suggesting that the TWFE coefficient based on the full sample is indeed biased.

Authors:

• Deepti Goel
• J.V. Meenakshi
• Zaeen De Souza

Drawing on results from a panel of 2778 workers interviewed during and after the 68-day hard lockdown imposed in India, the following study examines the livelihood impact of the pandemic and the extent of subsequent recovery or lack thereof. Focussing specifically on workers located in the informal economy, the study is a useful addition to the burgeoning body of work on the economic impacts of Covid-19 by providing an insight into the employment and earnings recovery of those located at the margins. These findings are spliced across socio-economic groups to showcase the differential impact of the pandemic on different demographics within the informal sector.

Authors:

• Paaritosh Nath
• Nelson Mandela S
• Aishwarya Gawali

The Covid-19 pandemic has created a need for high frequency employment and income data to gauge the nature and extent of shock and recovery from month to month. Lack of such high frequency household-level data from official sources has forced researchers to rely almost entirely on the Consumer Pyramids Household Survey (CPHS) conducted by the Centre for Monitoring the Indian Economy (CMIE). Recently, the CPHS has been criticised for missing poor and vulnerable households in its sample. In this context, it becomes important to develop a detailed understanding of how comparable CPHS estimates are to other more familiar sources. We examine the comparability of monthly labour income estimates for the pre-pandemic year (2018−19) for CPHS and the Periodic Labour Force Survey (PLFS). Across different methods and assumptions, as well as rural/​urban locations, CPHS mean monthly labour earnings are anywhere between 5 percent to 50 percent higher than corresponding PLFS estimates. In addition to the sampling concerns raised in the literature, we point to differences in the way employment and income are captured in the two surveys as possible causes of these differences. While CPHS estimates are always higher, it should also be emphasized that the two surveys agree on some stylized facts regarding the Indian workforce. An individual earning INR 50,000 per month lies in the top 5 percent of the income distribution in India as per both surveys. Second, both PLFS and CPHS show that half the Indian workforce earns below the recommended National Minimum Wage.

Authors:

• Mrinalini Jha
• Amit Basole

The Centre for Monitoring Indian Economy’s (CMIE) Consumer Pyramid Household surveys have emerged as an important source of regular labour market data for India. Given the differences in methods in data collection between the CMIE and official employment sources, it becomes exceedingly important to establish some comparability between the government and the CMIE datasets. With the release of the official labour surveys, Periodic Labour Force Surveys for 2017 – 18, we now have an overlap between the official datasets and CMIE datasets. In this paper, we examine the extent of comparability of labour force estimates from these two datasets. We find that employment estimates for men are broadly comparable. However, for women, there is a consistent divergence with CMIE estimates of women’s workforce participation lower than that of NSS-PLFS. We explore the points of divergence in the measurement of women’s work and hypothesise some potential reasons for this difference. We find that irrespective of the reference period used in the PLFS estimation of employment statuses, there is no convergence with the CMIE employment estimate for women’s employment. Moreover, the mismatch in CMIE-PLFS estimates occurs across all types of women’s employment and irrespective of what reference period of employment (in official data) is used.

Authors:

• Rosa Abraham
• Anand Shrivastava

Author:

• Zico Dasgupta

The efficacy of survey-based policy recommendations is primarily dictated by the quality of data collected in the first place. Is the survey truly representative of the population it claims to characterise? Are respondents voicing their true opinions or are they playing to the gallery? Did enumerator bias creep into the data? These are questions that most users of surveys have, but are typically brushed aside in the race to get the analyses out. While there are no foolproof measures to ensure that survey data are authentic, certain steps can be taken to improve their dependability. One such is the use of what is called ​‘para data’ (data about the process of data collection), to streamline enumerator practices, and thereby improve the reliability of the data being collected. This report details our experience of using para data to improve the quality of the India Working Survey (IWS).

Authors:

• Deepti Goel
• Rosa Abraham
• Rahul Lahoti

Using two rounds of the Periodic Labour Force Survey (PLFS) covering the periods 2017 – 18 and 2018 – 19, we construct a panel of urban Indian individuals aged 15 to 65, and analyse the dynamics of their participation – or non-participation – in the labour force. We construct transition probabilities to study the movement of individuals through three distinct statuses — employment, unemployment and non-participation – at the aggregate level and for different demographic groups. We find evidence of considerable movements from the labour force to non-participation; there exists a significant discouraged worker effect as well as a pronounced movement from employment outside the labour force, specifically for women. A majority of those unemployed in the beginning of the year remain so at the end of the year, indicating the presence of long-term unemployment. The reduction in unemployment rates from 2017 – 18 to 2018 – 19 hides significant weaknesses in Indian urban labour markets. This study represents an original contribution to the field of Indian labour economics, given the paucity of large-scale studies of the dynamics of Indian labour.

Authors:

• Rahul Menon
• Paaritosh Nath

Author:

• Kunal Mangal

Author:

• Santosh Mehrotra

This paper attempts to look at the ways informality is conceptualized in India and argues that the problems with the laws pertaining to informal labour are not simply an implementation issue, but the design of the labour laws itself exclude informal labour. While reviewing the history of labour laws in India and the social history of labour participation, the paper also examines the current change in the political approach to labour by changing the labour laws in the pretext of the pandemic. Focussing on the changes made in labour laws in Madhya Pradesh the paper argues that these changes would further informalise the workers intensifying the crisis.

Authors:

• Jenny Sulfath
• Balu Sunilraj

The Covid-19 pandemic has created unprecedented disruptions in labour markets across the world including loss of employment and decline in incomes. Using panel data from India, we investigate the differential impact of the shock on labour market outcomes for male and female workers. We find that, conditional on being in the workforce prior to the pandemic, women were seven times more likely to lose work during the nationwide lockdown, and conditional on losing work, eleven times more likely to not return to work subsequently, compared to men. Using logit regressions on a sample stratified by gender, we find that daily wage and young workers, whether men or women, were more likely to face job loss. Education shielded male workers from job loss, whereas highly educated female workers were more vulnerable to job loss. Marriage had contrasting effects for men and women, with married women less likely to return to work and married men more likely to return to work. Religion and gender intersect to exacerbate the disproportionate impact, with Muslim women more likely to not return to work, unlike Muslim men where we find religion having no significant impact. Finally, for those workers who did return to work, we find that a large share of men in the workforce moved to self-employment or daily wage work, in agriculture, trade or construction. For women, on the other hand, there is limited movement into alternate employment arrangements or industries. This suggests that typical ​‘fallback’ options for employment do not exist for women. During such a shock, women are forced to exit the workforce whereas men negotiate across industries and employment arrangements.

Authors:

• Rosa Abraham
• Amit Basole
• Surbhi Kesar

This paper makes an attempt to do an assessment of the impact of COVID-19 on employment and migration in India. The analysis is based on up-to-date facts and figures available in the public domain on economic growth, employment and migration. Using the employment elasticity approach, the study estimates employment loss during 2020 – 21 owing to the negative impact of COVID-19 on economic activities. The results of the study suggest that the country may witness job loss with the tune of 18.5 18.8 million in the current fiscal year. This in turn would shoot up the unemployment rate from 5.8% in 2018 – 19 to 8.9% in 2020 – 21, warranting a coordinated and focused approach from both the Central and State governments to uplift the confidence of the people and bring back the lost jobs, particularly the migrant workers. The study also emphasises on Central government’s urgent attention and action plan for uplifting the rural economy in order to revive India’s economy in the short run.

Authors:

• Purna Chandra Parida
• Yogesh Suri

E‑governance has changed the functioning of public programmes in India. In most cases, one technological platform is expected to perform multiple roles such as improving administrative efficiency, as an information repository for the beneficiaries and as a system for accountability. However, techno-solutionism can be incongruous to democratic principles. In this article, we highlight this by looking at some technologies, such as the Management Information System (MIS) among others, used for the implementation of the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) in India. We illustrate how such technologies have been used to subvert legal rights of workers and critically examine whether these designs incorporate democratic values. We underscore that technological interventions, with compassionate design are potentially powerful tools for transparency, accountability, and grievance redressal. However, we argue that technology alone can neither enhance participatory democracy nor reduce socio-economic inequalities.

Authors:

• Rajendran Narayanan
• Chakradhar Buddha
• Sakina Dhorajiwala

The authors examine the impact of labour law deregulations in the Indian state of Rajasthan on plant employment and performance. In 2014, after a long time, Rajasthan was the first Indian state that introduced labour reforms in the Industrial Disputes Act (1947), the Factories Act (1948), the Contract Labour (Regulation and Abolition) Act (1970), and the Apprentices Act (1961). Exploiting this unique quasi-natural experiment, the authors apply a difference-in-difference framework using the Annual Survey of Industries longitudinal data of India’s manufacturing establishments. Their results show that reforms had an unintended consequence of the decline in labour use. Also, worryingly, the flexibility resulted in a disproportionate decline in the directly employed worker. Evidence suggests that the reforms positively impact the value-added and productivity of the establishments. The strength of these effects varies depending on the underlying industry and reform structure. These findings prove robust to a set of specifications.

Authors:

• Diti Goswami
• Sourabh Paul