Social Protection Policies and Women’s Employment During COVID-19

Abstract

India imposed one of the strictest lockdowns to contain COVID-19, this brought all non-essential economic activities to a standstill. This was an unprecedented economic and health shock that affected the entire population, but the worst affected were the informal migrant workers who lived hand to mouth. Millions of them fled back to their native places seeking refuge from the economic uncertainties created by the sudden lockdown. However, this reverse migration resulted in an increased burden on rural economies in multiple ways. This chapter discusses the role played by rural social protection policies, particularly the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) and the Garib Kalyan Rojgar Abhiyaan (GKRA), in easing the burden on the labor market, with a focus on the provisions of these schemes on female labor force participation.

This chapter is part of a more detailed analysis titled “Labor market shocks, Social Protection and Women’s Work” published as the Institute of Economic Growth (IEG) Working Paper No. 453, July 2022. The views expressed here are those of the authors and not of the organizations they belong to.

7.1 Introduction

COVID-19 highlighted vulnerabilities faced by women—globally and nationally, as documented by the immediate studies following the pandemic. Women experienced an increase in their unemployment probabilities and a fall in re-employment chances along with the higher burden of unpaid care work (Deshpande, 2020; Abraham et al., 2021). Further, (Agarwal, 2021) lists the direct and indirect ways COVID-19 could multiply the hardships faced by women due to pre-existing gender inequalities and social norms. Thus, ensuing gender disparity and vulnerability have the potential to magnify the already poor labor force participation of Indian women.

India witnessed one of the strictest nationwide lockdowns in March 2020 leading to mass “reverse migration”—individuals who had come to urban areas in search of economic activities journeyed back home.¹ According to government estimates, approximately 10.4 million workers went back to their native villages (GoI, 2020), increasing the burden on the already stressed rural economies. Women being the residual workers and men enjoying the first hold over employment opportunities may result in gendered effects on the rural labor markets. Thus, in this chapter, we discuss the implications of reverse migration on women’s employment in rural India. Rural women who were already showing declined participation in paid economic activities now faced intense competition from returning workers and increased household members to be taken care of.

Fig. 7.1

Source Based on varied newspaper articles

Timeline during first wave of COVID-19.

We look at the social protection schemes like MGNREGA and GKRA (discussed in detail later) that could serve as a fallback option in the wake of economic uncertainty. While both rural men and women faced higher competition with reverse migration, the common understanding dictates that the loss could be more pronounced for rural women. With a scarcity of earning opportunities and a higher burden of household responsibilities, the male breadwinner norm at the household level may get reinforced more intensely. It may get revoked too, for instance—in case of the sudden death of the earning member due to COVID-19. In such multiple scenarios, women may want to exploit the mandated provision that guarantees 1/3rd of work generated under MGNREGA. Thus, we focus on fallback options and their implications on women’s employment amidst the pandemic, which was a huge shock to the demand and supply of labor.

Several studies note massive expansion under MGNREGA during the pandemic on account of increased demand for work (Afridi et al., 2022a). Since MGNREGA is a demand-driven, self-selection-based program it is of no surprise that this program was the ‘go-to’ option in the absence of alternative economic opportunities. However, (Narayanan & Saha, 2022) points out that this expansion was not proportionate and overall the program provided just 13.5 days per rural household. The limitation of their analysis is the exclusion of the pandemic-specific employment generation program—GKRA (Garib Kalyan Rojgar Abhiyan) which was similar to MGNREGA in design and implementation. However, unlike MGNREGA, GKRA had no mandated provision and thus, its implications for FLP could be different. Keeping in line with the central theme of our study, we explore women’s participation in MGNREGA in GKRA’s presence.

Through our analysis, we add to the bigger debate regarding women’s participation in paid economic activity and measures to retain and enhance their labor force participation. COVID-19 shock shows that any crisis having adverse labor market implications is likely to aggravate the extant problem of low and stagnant labor force participation rates (LFPR) of women in developing countries. Our paper confirms this in the context of the rural labor market and further shows that this may play out even in the historically feminized sector (such as MGNREGA). For instance, women’s share in MGNREGA person-days fell by 0.5% in post pandemic period as compared to the pre-pandemic period. However, the mandated 1/3rd provisioning in MGNREGA bounded the fall in women’s employment to some extent whereas GKRA with no special provisioning share show no such result. Thus, we advocate the need for special/targeted policies to mitigate women’s vulnerabilities and thereby overall loss in the household’s welfare.

7.2 Fall Back Options in Rural India During Pandemic

7.2.1 Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) and Women

The Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) launched in 2005, is a pan-rural India demand-based employment generation program. Under this act, each rural household has the right to manual work for 100 days (all adults per household in total) on publicly funded projects (usually for rural development).² It has been lauded as one of the largest antipoverty programs (safety net) and empirical evidence shows it to be particularly attractive to rural women. Studies underscore the role of MGNREGA in enhancing female labor force participation. Women find some of its features like- a guarantee of work near home, equal pay promise to men and women, and one-third reservation for women, quite desirable as they help in overcoming barriers to participation in paid economic activity (e.g.: preference for guaranteed work identified by Dhingra and Machin (2020), mobility restrictions identified by Afridi et al. (2020, 2022b).

We look at the disequilibrium created by the pandemic. The dependence on MGNREGA increased—more people demanded work under the scheme as other employment opportunities dried up, especially due to the mass reverse migration to rural India from urban India. For instance, nearly 133 million people demanded work in 2020–21—a 43% increase compared to the previous year. Up to 110 million people worked in the program in 2020–21, compared to an average of 78 million in four years to 2019–20. While the government increased the MGNREGA budget by INR 400,000 million for 2020–21 to address increased demand, it was considerably less than the estimated required allocation.³

7.3 Garib Kalyan Rojgar Abhiyaan (GKRA)

Another employment scheme—GKRA (Garib Kalyan Rojgar Abhiyaan), was launched with an aim to provide social protection to the “returning migrants and similarly affected rural population” in June 2020 by the Government of India. The GKRA was introduced in 116 selected districts across 6 states of Bihar, Jharkhand, Odisha, Rajasthan, Madhya Pradesh, and Uttar Pradesh. Districts with 25,000 and more returnee migrant workers in these 6 states were selected with a focus on 25 works to be coordinated by 12 different departments/ministries with a resource envelope of INR 500 billion. Panel a, Fig. 7.2 shows the distribution of the districts selected under the scheme.^{4 5}

Fig. 7.2

Source NREGA Public Data Portal (2019–2020), Census (2011) and GKRA Portal

Distribution of GKRA and women’s share in MGNREGA.

There was a significant overlap between activities under MGNREGA and GKRA with 13 (17) out of 25 activities falling under MGNREGA (Ministry of Rural Development). Moreover, one of the objectives of GKRA was to “saturate villages with public infrastructure and assets”, similar to MG-NREGA (GoI, 2021). The wages for these activities came from the allocated INR 500 billion. Thus, GKRA worked under the capacity of existing schemes and may either complement or substitute their benefits.⁶ By design, the program catered to about two-thirds of returning migrants in the allotted districts and there was no special provision for women under GKRA.⁷.

7.3.1 Rural Women Labor Force Participation

One must note that there was an intense competition not only in quantity but skill level as well. The returnee migrants were relatively more skilled which may further limit employment opportunities for women. To some extent, the provision of 1/3rd of jobs for women may act as a cushion for rural women’s employment status. Since the pre-pandemic average share of women (49% in 2019) is above the reservation, women may lose employment when the rationing of jobs becomes more intense. It is quite remarkable that the proportion of women participating in MGNREGA is more than double India’s overall FLFP. Over the years, women’s share in MGNREGA has surpassed the mandated provision in the majority of districts across India. Panel b, Fig. 7.2 shows the distribution of districts by 33% bound in the year 2019 (pre-pandemic) with most of these districts located in North India. It is based on the classification described in Sangwan and Sharma (2022) based on 2019 women’s share in MGNREGA to break the sample into districts that are (i) above bound—districts with women’s share above 33%, (ii) below bound—districts with women’s share below 33%.

Our analysis focuses on checking whether MGNREGA preserved its proven legacy of safeguarding women’s employment in the face of higher competition from men. Additionally, we examine the complementary role of the GKRA scheme in achieving this objective, even though GKRA did not have any specific provision for women.

7.4 Role of Special Provisions for Women

Similar to contemporary studies, we find an increased dependence on NREGA during the pandemic year. Figure 7.3 shows an upward trend in the number of person-days generated under MGNREGA by GKRA status. The intensity of the generation of person-days went up during the pandemic in all the districts as reflected in the higher slope post 2019. However, the figure depicts that Non-GKRA districts have relatively higher person-days generated per rural inhabitant in the pre as well as the post pandemic periods indicating historically lower reliance on MGNREGA in districts with GKRA that continues post pandemic. Interestingly, reliance on MGNREGA was not uniform and was more pronounced in the GKRA districts compared to the non-GKRA districts as reflected by the steepness of the curve. As reverse migration increased the pressure on the rural labor markets, alternative work opportunities contracted or became more competitive, one would expect a shift to the social protection program as a fallback option. And, as the stress of reverse migration was larger for GKRA districts we are seeing a greater increase in these districts relative to Non-GKRA districts.

Fig. 7.3

Source NREGS Public Data Portal (2011–2020) and GKRA Portal

Employment generation in rural India under MGNREGA (per rural inhabitant).

Since men and women might be impacted differently by labor market shocks, MGNREGA person-days may also be gendered. Figure 7.4 breaks Fig. 7.3 by gender. GKRA districts are also the ones with the lowest women’s person-days throughout the timeline considered. It follows a parallel path with respect to the men’s person-days graph and always lies below it. When we look at person-days generation by gender in Non-GKRA districts, we observe no clear pattern, in fact, women’s person-days surpass men’s person-days multiple times. In particular, from 2017 onwards women’s person-days are always more than men’s person-days. However, post pandemic both curves hint at a slight decline in person-days, unlike GKRA district's curves that show a steep increase.

Fig. 7.4

Source NREGS Public Data Portal (2011–2020) and GKRA Portal

Employment generation by gender in rural India under MGNREGA (per rural inhabitant).

We move from an absolute measure to a relative measure to examine the trends in more detail in Fig. 7.5. Despite the larger number of absolute MGNREGA person-days in Non-GKRA districts, the share of women is larger in the GKRA districts (Fig. 7.5). Notably, the overall share of women in MGNREGA is more than 50%, well above the mandated bound of 33.33%, in both pre and post-COVID-19. While women’s share in GKRA districts lies above non-GKRA districts but falls at a faster rate and starts to converge towards non-GKRA districts by the end of 2020. These trends in GKRA and non-GKRA are on expected lines as GKRA districts face greater competition from the relatively higher share of returning migrants. It is concerning that the convergence seems to be coming from the fall in women’s share- while both types of districts are witnessing a decline, GKRA districts’ fall is more rapid.

Fig. 7.5

Source NREGS Public Data Portal (2011–2020) and GKRA Portal

Women’s share in employment generation in rural India under MGNREGA (per rural inhabitant).

However, these are suggestive trends and do not control for a host of district and time trends that might be driving these patterns. A more rigorous analysis is carried out by Sangwan and Sharma (2022) that we discuss in detail here to support our discussion and conclusion. Using a first difference technique with districts fixed effects, authors find an increased dependence on MGNREGA during the pandemic. The number of person-days per person went up by a quarter of a day (6%) during the pandemic year (Panel (a), Fig. 7.6).⁸ The magnitude is larger in districts that are below the mandated provision—almost half a day (14%) but is not statistically different from above bound districts (5%). In panels (b) and (c), we report the estimated coefficients for men and women, respectively. For both the sexes, the dependence on MGNREGA increased but the magnitude of this increase is larger for men relative to women as depicted in Fig. 7.6.

Fig. 7.6

Source NREGA Public Data Portal (2019–2020) and GKRA Portal. Note The figure plots estimates for NREGA person-days (per rural inhabitant)—overall and by gender. Confidence bands with standard errors clustered at District level at 95% level of significance

Role of reservation for women in NREGA person-days.

To examine the women’s situation more closely, we study the changes in women’s share during Covid-19. The share of women in MGNREGA person-days fell from its pre-pandemic level by 0.5% as shown by Panel (a.) of Fig. 7.7. Interestingly, there exists a significant heterogeneity in the districts below and above the mandated bound. Districts where the reservation had not been reached and jobs could be claimed under MGNREGA using special provisions, saw an increase in the share of women. On the other hand, districts that had already reached the mandated provision saw a contraction in the share of women. As a result, the share of women in below bound districts went up by 2.6% while those above bound fell by 0.8%.

Fig. 7.7

Source NREGA Public Data Portal (2019–2020) and GKRA Portal. Note The figure plots the share of women in the NREGA person-days for subsamples below and above mandated reservation. All specifications have district fixed effects. Confidence bands with standard errors clustered at District level at 95% level of significance

Share of women in NREGA by GKRA and NREGA reservation.

Since the GKRA status is correlated to greater competition from the returning migrants, we look at the difference in the share of women in NREGA by the GKRA status in Panels (b) and (c) of Fig. 7.7. It is in the GKRA districts where the competition from returning migrants would be relatively higher and thereby may substitute away women if there are no special provisions to protect their livelihoods. On expected lines, the heterogeneity in the share of women by the bound is driven by GKRA districts with no change for non-GKRA districts.

In summary, women’s share is converging towards one-third bound as districts with women’s share below the bound experience a significant increase in women’s share while those above the bound observe a fall in their share. Thus, mandated provision acts as a cushion for women’s employment in the wake of increased competition for MGNREGA works even though overall the program favored men.

Sangwan and Sharma (2022) further substantiate these findings with a DID specification that exploits the average number of person-days across bordering districts as a counterfactual outcome for the GKRA districts. They find no significant difference in the number of person-days generated across the two types of districts.

Given that the number of returning migrants is publicly unavailable, the analysis relies on using a dummy for GKRA in a district. To allay concerns of sensitivity to this binary indicator, we check the robustness of the results using the person-days generated under the GKRA scheme and find qualitatively similar results.

In fact, if we restrict the sample to GKRA districts, we find a very strong correlation in the person-days generated under the two schemes of NREGA and GKRA (67% (p < 0.01)). This is expected as GKRA districts are the ones with a higher number of returning migrants, and suggests that GKRA complemented MGNREGA in reducing the stress on rural economies.

Despite the increased dependence on GKRA and NREGA, there was a significant fall in women’s share in below bound districts. This highlights the need to have special provisions for women in preserving their employment share.

The main focus of our analysis was to examine the heterogeneity in the results by the provisions under NREGA. For the same, we classified the districts on the basis of the share of women in 2019 (pre-Pandemic) into above and below mandated bound. We checked the robustness of the results using the historical share of women (2015–19) and continue to find qualitatively similar results. This confirms that our findings are not sensitive to the classification of districts on the basis of one year’s share.

7.5 Discussion

This study examines the impact of Covid-19 on women’s employment, but the insights gained are applicable beyond the pandemic period. In developing countries, women’s employment tends to be counter-cyclical, meaning that they join the workforce to support household income during economic crises. However, negative productivity shocks to different sectors may lead to a contraction in employment opportunities and thereby increase the competition for existing jobs. Faced with underlying social norms like the male breadwinner norm and the traditional roles in home production, women are likely to lose more jobs than men.

Without special provisions to protect women’s employment, these shocks can have significant welfare losses. For instance, a decrease in women’s participation in MGNREGA has direct implications for household welfare and women’s agency as suggested by the existing literature. The minimum wage set under the scheme has been shown to cause a substantial increase in private-sector casual wages for women, reducing the gender disparity. This reduced the dependence of women on men for personal savings and consumption. The ensuing economic independence enhances the say of women in household decision-making and translates into better household nutrition, and increased expenditure on child care and health services (see Sangwan and Kumar (2021), Maity (2019), Zimmermann (2012)). Additionally, a recent study by Rodriguez (2022) shows that increased participation of women in MGNREGA leads to an increase in credit demand and savings and a fall in violence against them.

While this study does not have direct data to support these findings, they suggest future research paths that could explore the relationships between women's participation in employment programs, and household welfare. Policymakers must prioritize protecting women's employment opportunities and supporting their economic independence, particularly during times of economic shock, to promote gender equality and inclusive economic growth.

7.6 Concluding Remarks: Policy Lessons

While there is an overall greater dependence on public works programs during the pandemic year as the fallback option in the rural economy, the cushioning effect on women’s employment is limited. Our analysis re-establishes vulnerabilities faced by women due to the pandemic. Using data from social safety nets—MGNREGA and GKRA, we find a positive role of one-third reservation for women. However, additional assistance under GKRA without any mandated provision for women did not help in preserving the employment status of women.

Our results echo the need for targeted special programs to help women cope with the increased competition as they tend to lose employment due to higher competition for limited jobs by men. Of course, multiple mechanisms could result in such a trend along with the societal pressure to take full responsibility for domestic chores, older family members, and children, leading to the withdrawal of women from the labor force. Our results suggest that special provisioning (as seen in MGNREGA districts where one-third reservation is binding) helps in resisting these norms to some extent.

We are able to study the impact of the first wave of COVID-19 as the period coincided with the annual data availability of work undertaken in MGNREGA. There is a need for more transparent data (also of works under GKRA) to fully understand the impact of reverse migration and the second wave to prepare ourselves for upcoming waves or any such unanticipated shocks. Reverse migration was mainly due to distress caused by economic activity shutdowns and lack of safety nets (like MGNREGA) in urban India. Thus, our analysis also supports the need for fallback options in urban India to reduce the burden on rural safety nets and thereby women’s welfare.

Appendix

See Table 7.1.

Table 7.1 Works under GKRA