Kanika Mahajan

India has a labour problem: youth unemployment rates of about 10 percent, farm jobs still employing at least 40 percent of the workforce, and a need to create at least 8-10 million non-farm jobs annually to absorb the growing young population (Economic Survey, 2023). At the same time, the proportion of India’s workforce in manufacturing has stagnated at about 13 percent for the last three decades. What explains this stagnation?

After liberalisation, the relative price of capital goods fell sharply following trade liberalisation and import tariff cuts, while real wages rose more moderately. This resulted in a rising wage-to-rental price of capital (w/r) ratio and capital deepening. Indian firms now tend to use less labour per unit of capital than firms in other countries at similar income levels, especially in labour-intensive industries like apparel.

Commensurately, labour’s share of value added in India’s organised manufacturing declined from 28.5 per cent in 1980–81 to 11 per cent in 2012–13. While this mirrors the global pattern of falling relative prices of capital goods and capital deepening, India stands out in having unusually low labour intensity for a low-wage economy. Firm size in India remains small, with almost 80 percent of the non-farm workforce employed in firms with fewer than 10 workers. Even among registered manufacturing firms, the median firm size is around 20 workers.
WHAT DO INDIA’S NEW LABOUR CODES CHANGE?

India has long had a labyrinthine labour law regime—over 40 central and 100 state laws dealing with different aspects of wages, industrial disputes, safety and social security. In 2002, the Second National Commission on Labour had recommended consolidation of labour laws to reduce complexity and inconsistent definitions.

Finally, India’s four new labour codes, notified between 2019 and 2020 and brought into force from 21 November 2025, replace 29 central labour laws with a consolidated framework covering wages, industrial relations, social security and occupational safety. Importantly, the new codes attempt to balance the need for worker protection with ease of doing business.

Some crucial changes which aim to enhance worker welfare: a single definition of “wages” across laws, a national floor wage set by the Centre, minimum wage coverage extended from scheduled employments to all workers, common norms on working hours, safety, welfare facilities and registration for establishments, fixed-term employees (FTE’s) to now receive parity of wages and benefits with permanent workers, and appointment letters are now made mandatory for workers making it possible to track employment histories and nudging formalization. Finally, the codes provide for the creation of a Social Security Fund for unorganised, gig and platform workers. Aggregators (ride-hailing, food delivery, e-commerce, etc.) are required to contribute 1-2 percent of their annual turnover, capped at 5 percent of the amount they pay or owe to gig and platform workers.

Major changes which have reduced compliance costs for employers include: the applicability of standing orders and the requirement for government permission for employee layoffs increasing from 100 to 300 employees, a clearer framework for negotiating with unions, with minimum worker representation, and the removal of restrictions on women working at night or in certain occupations. There has been a substantial reduction in registrations, licences and returns. For example, the Occupational Safety, Health and Working Conditions Code has reduced registrations from 6 to 1, licences from 4 to 1, and returns from 21 to 1; the Code on Wages has reduced forms from 20 to 6 and registers from 24 to 2; and the Industrial Relations Code has reduced forms from 37 to 18 and registers from 3 to 0. Though they still fall short of one registration and one return benchmark for all labour related matters.

Most importantly, there has been decriminalisation of minor offences, with fines and improvement notices replacing prosecution. Size-based regulatory thresholds (10, 20, 50, 100 workers) often triggered additional regulations and inspections and were strongly associated with bribe seeking by inspectors. The new web-based random inspections can further reduce compliance costs for firms. However, serious, repeated or critical breaches are still imprisonable offences.

WHY THESE MATTER?

Evidence over the last two decades has repeatedly underscored that India’s manufacturing growth has been stymied by its extensive labour regulations. Evidence shows that states with more flexible labour regulations have higher output, employment, investment and productivity growth in manufacturing, especially in labour intensive industries. In fact, product-market liberalisation increased productivity in states with more flexible labour laws but had little effect in rigid states, implying that labour regulation constrained firms’ ability to respond to new opportunities. Estimates show that regulations under the Factories Act increase firms’ unit labour costs by almost 35%.

More recently, our research shows that amendments that raised Industrial Disputes Act and Factories Act thresholds from 100 to 300 workers, and 10 to 20 and 20 to 40 workers, along with decriminalization of offences in some states over the last decade (also some major changes implemented in the new codes), increased plant employment and output by 5 percent in states which amended these laws relative to the others. Overall, there is sufficient evidence to show that rigid employment protection legislation and complex labour regulations have depressed firm growth and job creation in India’s organised manufacturing.
WHAT ARE THE POTENTIAL IMPACTS OF THE DEREGULATION?

First, the change that has provoked the strongest backlash from labour unions is the increase in the threshold from 100 to 300 workers for requiring government permission to lay off workers. This is due to fears of employment losses. However, notably, about 15 states, including some large ones like Rajasthan, Madhya Pradesh, Uttar Pradesh, Maharashtra, Andhra Pradesh and Gujarat, had already amended their Industrial Disputes Acts over the last decade (some spurred after the pandemic) and increased the threshold beforehand.

Thus, the effect of this change on manufacturing employment will be marginal in most states. In fact, by spurring firm growth and entry, there will be a net creation of jobs rather than job losses. When separation is costly or unpredictable, firms choose capital-intensive technologies to avoid adjustment risk, even in labour-abundant economies. By making separations more predictable and less binding at lower levels of employment, the codes can reduce the option value of staying small and capital-intensive.

Second, complex regulation and high firing costs act like a tax on labour, raising its effective price relative to capital. Relaxing these, by simplifying compliance and through decriminalization, digital registration, and unified returns, reduces the effective wage component. This makes labour relatively more attractive at the margin than capital. It also reduces harassment, transaction and compliance costs for most firms. Reduction of legal uncertainty can also increase private investment. However, the culture of corruption by officials and harassment of firms needs to change on ground for effective realization of gains. Third, requiring FTEs to receive equal pay and benefits as permanent workers, may reduce the incentive to rely excessively on third-party contractors. However, hiring contractual workers may solve a deeper problem e.g. specialization in core business tasks, training, recruitment etc than simply avoiding regulations and to that extent may have a limited effect.
ARE THESE ENOUGH?

While the above changes make important leaps, some of the provisions carried forward may still make manufacturing in India less attractive than our Asian competitors. For instance, overtime is fixed at twice the nominal wage. The standard overtime rate is typically 1.5 times the regular wage rate across most countries. The ceiling on the number of hours at 48 hours per week for a worker also makes labour more expensive, especially for industries which may experience seasonal demand. China legally sets 44 hours but often sees long hours. Similarly, Vietnam has a 48-hour limit but allows significant overtime (up to 300 hours per year) at a lower wage premium.

To bring some cheer, overtime capped at 75 hours a quarter has now been left to the discretion of states. Since 2020, some states like Haryana, Himachal Pradesh, Karnataka, Maharashtra, Odisha, Punjab, and Uttar Pradesh have increased the ceiling of overtime hours up to 144 hours per quarter. This potentially increases earnings for employees but high over time rates may still deter firms from employing labour beyond the usual 8-hours.

Second, a common national minimum wage floor in India—-generally considered a good idea for ensuring basic income security and reducing inequality—-can increase cost of labour in some states (especially the ones which already have a small non-farm sector). In India, the cost of living varies significantly between urban and rural areas, and across different states. A single, uniform national rate, even as a floor (unless taken as the minimum across the states currently) may be problematic given the large economic disparities.

Lastly, even if the new codes work as intended, manufacturing investment decisions depend on a broader package: logistics, power and infrastructure costs relative to peers, trade policy,export ecosystem, skilled labour, contract enforcement and importantly, land availability with little delays.

Comparative analyses of India’s manufacturing under-performance emphasise that while labour regulation is important, it is only one among several constraints. While the new labour codes improve India’s attractiveness for manufacturing investors at the margin, they are unlikely to be a silver bullet. Their impact will be realised only if accompanied by complementary reforms and credible implementation at the state level.

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.

Sexual harassment at workplace is one of the significant barriers women face in improving their economic outcomes. The *Me Too movement brought to light the high prevalence of this issue across the world. Several countries, including India, have already taken cognizance of this problem and promulgated legislation to prevent and punish such acts of harassment. In 1997, the Supreme Court of India passed a landmark judgment that laid down the Vishaka guidelines – a set of procedural guidelines to be followed by establishments in dealing with complaints about sexual harassment. Sexual Harassment of Women at Workplace (Prevention, Prohibition and Redressal) Act (POSH Act) went a step ahead of Vishaka Guidelines by redefining the workplace, sexual harassment, consequences of non-compliance, and a time-bound process of complaint resolution.

The POSH Act in India provides prevention and redressal mechanisms against sexual harassment complaints.1 It puts the onus of undertaking measures to prevent sexual harassment and deal with any reported incidences in a quick and fair manner on the employer. The Act was passed by both the parliamentary houses in February 2013 and came into force from December 2013. The act applies to all workplaces in India, including government, private, and non-governmental organizations. Under the POSH Act, 2013, an employer must constitute an Internal Complaints Committee that investigates all sexual harassment complaints reported within the organization. The Committee is required to be formed at each office or establishment of the company that employs 10 or more employees and is required to complete the inquiry within a time period of 90 days.

In this project, using nationally representative employment data at individual level (National employment and unemployment surveys) and panel data for manufacturing establishments in India (Annual Survey of Industries), we aim to identify the impact of the POSH Act on female employment by exploiting the discontinuity along firm size since the Act imposed larger compliance costs for firms having at least 10 workers and the time of implementation. We use a difference-in-differences design to estimate the change in relative female paid employment (vs male employment) in firms having at least 10 employees with those having less than 10 employees, after the passage of the Act. At the firm level, we again use a difference-in-difference strategy exploiting the fact that firms of size 10 or more had to bear the largest compliance cost of the POSH Act. The pre-period constitutes data from 2009-2012, and the post-period constitutes data from 2013-2016. The treatment group is any firm that hires more than 10 workers on average in the pre-period.

Policy Implication: Women are protected from discrimination under the labour laws of India. Further, laws are often enacted to with the aim to protect their rights such as the Maternity Benefits Act of 2017, the Prevention of Sexual harassment Act of 2013 and regulations that restrict their employment in the night shift due to safety concerns. While these laws are enacted with the aim to protect workers, they can backfire and undermine women’s employment if employers’ compliance cost increases with their passage. This study aims to study the impact of one such legislation that aims to protect female workers in India against workplace sexual harassment to examine whether it can lead to unintended consequences. The findings of the study can be used to design and implement public policies that aim to protect female workers without increase cost of compliance for the employers and hence resulting in adverse consequences more effectively.

Immigration and its impacts on the host country have risen to the forefront of political agendas and policy debates in the recent years. Both low skilled and high-skilled legal immigration has come under attack from policy makers. Brexit and restrictive H-1B visa regime under Trump regime in the USA are recent examples of restrictive policies in movement of high skilled labor across countries. Supporters of these policies often blame immigration for lower domestic wages and decline in employment opportunities for the natives. However, multinational companies can undertake offshoring of such jobs (hiring people in their affiliate offices abroad) when visa regimes become more restrictive, instead of increasing native employment.

In this paper, we aim to examine the impact of increase in uncertainty in costs of access to high skilled migrant workers under the Trump regime on the US and India based jobs posted by firms in India. The H-1B program in the US forms the cornerstone for high skilled immigration and Indians form 70% of the migrants under the program. In 2016 when Trump won the primary election it created a stir in the US given the high pitched political campaign against immigration, specifically the H-1B program. When he came to power, legal changes were made that increased costs of hiring under the visa program by increasing uncertainty, even though the quota remained unchanged. Such uncertainty can have impacts not only on the host country through its impacts on productivity and growth of firms that hire H-1B workers, it can also impact the labor markets in migrant sending country.

Our primary dataset comprises job postings on India’s largest online job platform between
2014 and 2019, with a market share of more than 70% in 2017. There is also information on job title, role category, functional area, location, company id, salary and educational and experience requirements along with a detailed job description. The key advantage of the vacancy data vis-a-vis the administrative datasets is its high frequency and detailed occupational classification and the possibility of tracking US based demand for labor across firms. We hypothesize that firms more impacted by the visa policy change are more likely to change hiring behaviour for India based postings after the shock. As firms exhibit heterogeneity in the number of US-related job postings, we assess the differential change in India based postings by their exposure to the policy change. We then assess whether offshoring explains the observed differential changes in jobs posted in India by firms that earlier hired for US based positions i.e., firms shift the jobs performed in the US to India.

Policy Implication: Free trade in products and people is often regarded as an important engine for creating better jobs, increasing incomes and reducing poverty in the sending country and also addressing labor and skill deficit in the receiving country. India-US trade ties are important not only for product trade but the US is also the largest market for Indian labor and for services exports from India. Hence, policies around H-1B visa access have always been a crucial fulcrum on which trade ties between the countries have rested. Indian government has often intervened on behalf of Indian industry when visa curbs have been imposed by the US (Livemint). Our study throws light on how India and US based firms cope up with curbs on hiring immigrant workers by the host country. If firms offshore jobs instead of hiring more native workers in the US, it shows that the availability of talent is indeed a binding constraint for these firms. Visa curbs or increase in uncertainty in visa policy are then unlikely to improve outcomes for native workers in the US, a usual argument for increasing visa restrictions by governments.