Anisha Sharma

Between 2014 and 2017, seven Indian states amended their regulations to allow women to work night shifts in factories, with the condition that employers provide female-friendly amenities. This article finds that the removal of gender-discriminatory employment restrictions led to an increase in female employment, without negatively affecting male employment. However, the benefits were concentrated almost entirely among large firms. 

Do laws designed to protect women from unsafe working conditions constrain the demand for their labour? This question sits at the centre of global debates about protective legislation in labour markets. Our recent research (Gupta et al. 2025) examines what happened when Indian states lifted long-standing bans that prevented women from working night shifts in factories. Our findings offer important lessons for policymakers seeking to expand female employment, particularly considering the significant labour reforms that have been recently initiated by many state governments. 

The problem: When protection becomes restriction

For decades, Indian law prohibited women from working night shifts in manufacturing, ostensibly to protect them from unsafe working conditions and exploitation. The Factories Act of 1948 restricted women to working only between 6 AM and 7 PM in manufacturing units. Similar laws prohibited women from working night shifts in shops and other commercial establishments. While these laws were intended to safeguard women’s welfare, they inadvertently created barriers to female participation in the formal manufacturing sector. 

This “paternalistic discrimination” (Buchmann et al. 2023) reflects a global pattern. At least 20 countries still prohibit women from working at night, while 45 countries ban women from sectors deemed “unsafe” by lawmakers (World Bank, 2024). These restrictions, however well-intentioned, assume women lack agency to make their own employment choices and that employers are unable to provide safe workplaces for all workers. 

India’s experience is particularly important given its strikingly low female labour force participation rates and the potential for manufacturing to provide formal employment opportunities for women. 

The reform: A natural experiment

In the early 2000s, a series of High Court judgements held that prohibitions against women working at night were unconstitutional because they deprived women of economic opportunities. Following these judgements, between 2014 and 2017, seven Indian states – Andhra Pradesh, Assam, Haryana, Himachal Pradesh, Maharashtra, Punjab, and Uttar Pradesh – amended their regulations, either through legislative amendments to existing laws or through executive regulatory orders, to allow women to work night shifts in factories, though with certain conditions. State governments typically required employers to provide female-friendly amenities such as separate toilets, transportation facilities, mechanisms to prevent sexual harassment, and adequate rest periods between shifts. 

These staggered reforms across states offer a unique opportunity to study the impacts of removing gender-discriminatory employment restrictions. We analyse data from over 290,000 registered manufacturing establishments from the Annual Survey of Industries (ASI), in the period from 2009 to 2018, to understand how lifting these bans affects female employment. We compare changes in firms before and after the reform and use ‘dynamic estimators’ that allow for the impact of the regulatory change to vary over time. We also use ‘synthetic control estimators’ that allow for the construction of a sample of appropriate counterfactual firms. 

Key findings: Size matters

We find that removing night shift restrictions increased female employment – but the benefits were concentrated almost entirely among large firms with 250 or more employees (Figure 1). 

Figure 1. Effects of the reform at firms of different sizes

Notes: (i) These figures show the impact of state-level amendments that allowed women to work in night shifts, on firm outcomes. (ii) Share of female workers is defined as the number of female workers in the firm divided by the sum of male and female workers (panel a). (iii) The extensive margin is measured by a binary variable which equals one when the firm has at least one female worker and zero otherwise (panel d). (iv) The figure plots the estimated average effect of the night shift changes for firms of different sizes: with permanent employees of at least 50, 100, 150, 200, 250, and 300, respectively. (v) The estimation includes firm and industry-year fixed effects. (vi) The bars show the 95% confidence interval for the estimates. A confidence interval is a way of expressing uncertainty about estimated effects. A 95% confidence interval means that, if you were to repeat the experiment with new samples, 95% of the time the calculated confidence interval would contain the true effect. ————————————————————————————

In states that lifted the ban, there was a 3.5% increase in the share of female workers at large firms, a 13% increase in the number of female workers, and a 6.5% increase in the likelihood of a firm employing any female worker. 

Our results are robust to the use of synthetic control estimators that construct a comparable counterfactual group to compare with treated (subjected to intervention) firms (Figure 2). There is no evidence of any trends prior to the reform that could be driving our results. After the reform is introduced, both the share of female workers and the number of female workers steadily increase at large firms. The gradual increase in the effects of the reform over time could reflect the time taken by firms to put in place the infrastructure required to employ women at night. 

Crucially, the increase in female employment did not come at the expense of male workers. We do not find any decline in the number of male workers hired at large firms. In fact, we find an increase in the total workforce at large firms, although the estimated coefficient is not significantly different from 0. In short, large firms may have expanded their total workforce rather than substituting women for men, suggesting the reforms helped firms overcome labour constraints. 

Figure 2. Event study of the impact of the lifting of night shifts (synthetic control estimator)

Notes: (i) These figures show the dynamic impact of state-level amendments that allowed women to work in night shifts in the state on firm outcomes using the Synthetic Difference-in-Differences (SDID) estimator by Arkhangelsky et al. (2021). (ii) The regulatory change was made in the year 0. For control states (not subjected to the reform), the pre-treatment period is before 2014, when the first regulatory change is implemented. (iii) The sample comprises large firms, which are firms that employ at least 250 employees. (iv) All specifications include industry-year and firm level fixed effects. (v) The bars show the 95% confidence interval for the estimates.
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The concentration of benefits among large firms reflects the economics of compliance with the new regulations. While states lifted the outright ban, they simultaneously imposed requirements for female-friendly infrastructure and amenities. These compliance costs created a significant barrier for smaller firms.

Large firms are better positioned to absorb these fixed costs for several reasons: they can spread infrastructure investments across more workers, reducing per-worker costs, and they are more likely to already operate night shifts and employ some women (Chakraborty and Mahajan 2023).

Who responds most: Export-oriented and firms previously hiring females

We further examine which types of firms were most responsive to these regulatory changes. Firms that already employed women were much more likely to expand female hiring after the ban was lifted. This suggests that having existing female-friendly infrastructure and experience managing gender-diverse workforces positioned firms to take advantage of the new flexibility. 

Export-oriented firms showed stronger responses than those focused on domestic markets. Companies operating in competitive global markets appear more willing to hire the best available workers regardless of gender, making them more responsive to the removal of hiring constraints. Firms in high-unemployment areas were also more likely to increase female hiring, likely because they could expand their workforce without driving up wages significantly. 

Broader economic effects

Despite the increases in female employment, we find no significant changes in firm output or profits in the short term. This reflects the relatively small share of women in the overall manufacturing workforce. Even if firms want to hire women on night shifts to ease constraints in recruiting a sufficient number of productive workers, increases in female employment do not immediately translate to measurable productivity gains at the firm level. We also find a slight reduction in capital expenditure by firms: if labour was substituted for capital, then this could explain our finding that total output did not change. However, the extent of substitution is too small for us to find significant effects on profits, at least over the timeframe we are considering. 

Wage rates for both women and men also remained largely unchanged. In some specifications, female wages even decreased slightly, suggesting that the regulatory changes may have also led to an increase in female labour supply. These results are also consistent with our previous result that the biggest increases in employment for female labour took place in labour markets which previous had relatively high levels of female unemployment. 

Policy implications: Beyond simple deregulation

Our findings carry important lessons for policymakers seeking to expand female employment. In particular, while removing discriminatory laws does help increase female employment, the details of implementation matters. The concentration of benefits among large firms suggests that smaller firms need targeted support to develop female-friendly workplace infrastructure – whether through subsidies, shared facilities, or relaxing some of the compliance requirements where they may be unnecessarily onerous. Policymakers should also build on existing progress: since firms that already employ women are most likely to expand female hiring, policies encouraging even minimal initial female employment may have cascading effects. 

The experience of these seven Indian states offers a glimpse of the economic costs of gender discrimination – even discrimination that is arguably well-meaning in intention. Our research provides an example of one such discriminatory legislation that constrains firms from hiring females who are able and willing to take on productive work and suggests that removing such distortionary regulation could reduce the economic gap between less developed and more developed countries. 

This article was originally published on Ideas for India.

Over the past two decades, India’s economy has expanded steadily, with per capita income growing at about 5% per year (World Bank).1 But behind this headline growth lies a more sobering story about jobs. The pace of employment growth has lagged far behind, at just 1.6% per year. Official estimates suggest that catering to the expanding workforce would require about 8 million non-farm jobs to be created annually, on average, until 2030 (Economic Survey of India 2023-2024).2

Despite recent improvements in workforce participation — an increase of 10.5 percentage points since 2017 — there are key challenges to the creation of good-quality jobs. Agriculture and low-productivity self-employment still account for most jobs in India, even expanding their share in recent years. Indian growth has been services-led, but the segments of the sector that drive growth are not the ones that create jobs at scale. Manufacturing sector’s share of employment, as well as its contribution to growth, has remained unchanged. Average real wages have been virtually stagnant due to low labour productivity, and most workers lack job security and social protection. Further, job creation in India is unevenly distributed across regions, with southern states and urban centres accounting for most of the increase in non-agricultural employment.

This report lays out six key insights about jobs and employment trends in India today. We begin with the biggest challenge: while job creation outside of agriculture is on the rise, it is still quite limited. Moreover, even within non-agricultural jobs, real wages and work productivity have stagnated over the past decade. This suggests two things: a) that jobs are not being created in relatively more productive sectors, and b) that the supply of workers looking for jobs in the non-agricultural sector exceeds the availability of these jobs. This is especially true for young people under 25: many have more education than ever before, but still struggle to find good work, either because there aren’t enough opportunities, or they do not have the right skills. The jobs that do exist are often informal, meaning they lack basic protections like social security or health benefits. Women’s employment, although increasing, is still very low. Women are a major source of untapped talent, and bringing more of them into the workforce is essential for India’s future economic growth. Finally, growth has been highly uneven across the country. Just 13 cities have accounted for over half of India’s growth, leading to unequal job opportunities and driving large numbers of people to migrate to a few urban centres.

To navigate these challenges, we need to address crucial questions: what policy levers can best unlock job-rich growth, improve job quality, and expand access to opportunity across regions? We hope this report sparks wider debate on the most urgent and impactful solutions.

Why don’t firms invest in safer workplaces for women? Female labour force participation in developing countries like India is low and has been falling, but safer workplaces may encourage more women to participate in paid employment. In turn, attracting more women, and skilled women in particular, into the labour force can contribute to firms’ productivity and promote inclusive growth. However, according to anecdotal evidence, few firms in India comply with government regulations on workplace safety, particularly the Sexual Harassment of Women at Workplace Act (SHWA) passed in 2013 to promote a safer workplace environment for women through mandated policies.

In this project, Beaman, Sharma and Sharma provide evidence on a profit-maximizing firms’ constraints to providing a safer working environment for its female employees in an environment where implementation of the law may be weak. They analyse why firms do not invest in key amenities such as gender sensitisation programmes and training, as well as establishing an effective complaints mechanism to tackle concerns about workplace safety. They partner with the Federation of Indian Chambers of Commerce and Industry (FICCI) to survey a sample of FICCI member firms to better understand what constraints they face in hiring and retaining female employees, whether they are aware of the regulations around workplace harassment and the extent to which they comply with these laws.

In addition, they implement two interventions where they experimentally provide information to firms about job-seeker preferences over workplace amenities and job characteristics, as well as information about mandated requirements of the SHWA. Through these interventions, they will identify whether either source of information leads to an increased willingness by firms to investment in workplace safety, measured through multiple outcomes, such as attending a webinar on complying with the law hosted by Safecity, an NGO focused on reducing sexual harassment including at the workplace, and investing in workplace safety audits.

The data generated in this project will provide important insights that can inform policymakers about firms’ awareness of and compliance with the SHWA, and how this varies across different types of firms (size, industry, leadership structure). The RCT will also shed more light on the specific constraints that hold back firms from investing: whether they lack sufficient information about job-seeker preferences, information about the law, or whether they face financial constraints that prevent them from taking up these additional investments.

This project has also received funding from the Private Enterprise Development in Low-Income Countries (PEDL) coordinated by the Centre for Economic Policy and Research (CEPR).