2. Trends, Emerging Characteristics & Current Challenges

12.1 Introduction #

This chapter encompasses an overview of employment trends and patterns in India's labour market over the past two decades, beginning from 2000. It further summarizes emerging characteristics and current challenges in the labour market. The chapter relies on unit-level data from the Employment and Unemployment Surveys and the Periodic Labour Force Surveys. The analysis focuses on three distinct periods: 2000 to 2012, 2012 to 2019, and 2019 to 2022. The fiscal, agricultural, and calendar years are interchangeably used throughout the text, with 1999–2000 as 2000, 2011–12 as 2012, 2018–19 as 2019, and 2021–22 as 2022.

22.2 Labour Force, Employment, Unemployment and Underemployment #

2.2.1 Labour force, employment and unemployment #

The labour force participation rate (LFPR) in India for individuals aged 15 years and older was 55.2 per cent in 2022, which was lower than the world average of 59.8 per cent. It consistently declined over the past two decades, from 61.6 per cent in 2000 to 50.2 per cent in 2019, before increasing to 55.2 per cent in 2022. The worker population ratio (WPR) also exhibited a similar trend, declining from 60.2 per cent in 2000 to 47.3 per cent in 2019 before increasing to 52.9 per cent in 2022. The overall open unemployment rate was quite low — a little more than 2 per cent in 2000 and 2012, which sharply increased to 5.8 per cent in 2019, followed by a significant fall to 4.1 per cent in 2022.

In absolute terms, the labour force grew by 99.2 million persons, from 396.3 million in 2000 to 495.5 million in 2019. Yet, the growth of the workforce (at 79.4 million persons) was not commensurate with the growth of the labour force, resulting in a substantial rise in open unemployment (19.8 million persons). In particular, open unemployment grew significantly (by 18.6 million persons) between 2012 and 2019, when the employment generation was virtually negligible (at 200,000 persons). A relatively greater increase in the workforce (by 78 million persons) occurred during the pandemic years, from 466.5 million in 2019 to 544.5 million in 2022, in comparison to the labour force increase (by 71.9 million persons), from 495.5 million in 2019 to 567.4 million in 2022. This dynamic resulted in a substantial reduction in unemployment (by 6.1 million persons) during this period.

The gender distribution shows that the female LFPR declined sharply (by 14.4 percentage points) when compared with the male counterparts (by 8.1 percentage points) between 2000 and 2019. But this trend reversed between 2019 and 2022, with a much greater increase in the female LFPR (by 8.3 percentage points) than in the male LFPR (by 1.7 percentage points). The female LFPR in India was 32.8 per cent in 2022, which is lower than in several middle- and upper-middle-income countries, including the Russian Federation, China, and South Africa. However, it was higher than in some neighbouring countries, such as Pakistan, Afghanistan, and Sri Lanka.

2.2.2 Underemployment #

Time-related underemployment in India was high as of 2022, at 7.5 per cent. It had fluctuated over the years, increasing from 8.1 per cent in 2012 to 9.1 per cent in 2019 before declining to 7.5 per cent in 2022. The underemployment rate was only slightly higher among men in 2022 (at 7.7 per cent) than among women (at 7.1 per cent) and more prevalent in urban areas (at 8.4 per cent) than in rural areas (at 7.2 per cent). Although underemployment was considerably higher than open unemployment, it, too, came down between 2019 and 2022, especially among women (by 2.5 percentage points).

32.3 Growth of Employment and Output #

2.3.1 Growth in employment #

Table 2.1 highlights the dynamics of employment and labour force growth across major sectors. The population (aged 15+) grew at a compound rate of 2.39 per cent between 2000 and 2012, declining to 2.07 per cent between 2012 and 2019, and further to 1.15 per cent between 2019 and 2022. The labour force grew at 1.54 per cent, 0.56 per cent, and 4.62 per cent, respectively, across these three periods. The workforce grew at 1.55 per cent, 0.01 per cent, and 5.29 per cent.

Table 2.1. Compound growth rate of the population, labour force, workforce and employment across major sectors (%) #

Compound rate of growth of	2000 to 2012	2012 to 2019	2019 to 2022
Population (aged 15+)	2.39	2.07	1.15
Labour force (aged 15+)	1.54	0.56	4.62
Workforce (aged 15+)	1.55	0.01	5.29
Agriculture	-0.39	-2.55	8.93
Manufacturing	2.89	-0.33	3.00
Construction	9.15	2.18	6.37
Services	-0.67	10.80	1.09
Total non-agriculture	3.86	2.09	2.61

Source: Computed from various years of the Employment and Unemployment Survey data and the Periodic Labour Force Survey unit-level data.

2.3.2 Sectoral changes in employment and output #

In the roughly two decades between 2000 and 2019, the Indian economy's production structure moved straight from agriculture to services-led growth without substantial expansion in the share of manufacturing. The manufacturing sector underperformed compared to the overall GVA growth. As a result, the share of manufacturing in GVA stagnated, at around 15–18 per cent, which was much lower than in developed economies and even much lower than in East and South-East Asian countries.

India experienced some modest and relatively retarded structural transformation in terms of employment during the same period, with an increase in the share of various non-farm subsectors, such as construction, manufacturing, trade, hotel and restaurants, transport, storage and communications, and finance, business and real estate services. These employment shifts occurred at a slower pace than the change in output structure.

Largely due to impacts of the COVID-19 pandemic, this trend reversed between 2019 and 2022. The share of the primary sector in total GVA increased from 14.8 per cent to 15.6 per cent, respectively, while the share of employment in agriculture experienced a significant reversal, rising from 42.4 per cent in 2019 to 46.4 per cent in 2021 and then falling marginally to 45.4 per cent in 2022. There was a corresponding decline in the share of the non-farm sector (except for construction and trade, hotels and restaurants). Importantly, manufacturing was the second-largest employer after agriculture in 2019. As of 2022, the construction sector had become the second-largest employer, followed by trade, hotels and restaurants, with manufacturing relegated to the fourth spot.

42.4 Employment Quality and Conditions #

2.4.1 Status of employment #

The structure of employment by status of employment reveals the quality of employment. In the Indian context, regular employment in the formal or organized sector is considered the best employment quality, followed by regular employment in the informal sector. Self-employment in both formal and informal sectors is the next best category, followed by casual employment. As table 2.2 shows, the share of formal employment was only 9.7 per cent in 2022, while the share of informal employment was 90.3 per cent. The share of the organized sector was 18.9 per cent, while the unorganized sector was 81.1 per cent. Regular formal employment was only 9.4 per cent of total employment. More than 61.9 per cent of regular workers did not have a written contract, and only 26.4 per cent had a long-term contract of more than three years.

Table 2.2. Status of employment (UPSS, aged 15+), 2000, 2012, 2019 and 2022 (%) #

Share in total employment	2000	2012	2019	2022
Formal employment	8.5	7.8	10.5	9.7
Informal employment	91.5	92.2	89.5	90.3
Organized sector	10.9	17.5	19.6	18.9
Unorganized sector	89.1	82.5	80.4	81.1
Regular formal employment (% of total employment)	7.6	7.5	10.2	9.4
Regular workers without written contract (% of regular employment)	59.6*	64.5	69.8	61.9
Regular workers with long-term contract (>3 years) (% of regular employment)	35.9*	29.1	21.5	26.4

Note: * = The data are for 2005.

Source: Computed from various years of the Employment and Unemployment Surveys and the Periodic Labour Force Survey unit-level data.

2.5.1 Segmentation and inequality #

There are widespread livelihood insecurities, with only a small percentage being covered with social protection measures, precisely in the non-agriculture sector, but even in the organized sector. Worse, there has been a rise in contractualization, with only a small percentage of regular workers covered by long-term contracts. The segmentation and inequalities in the labour market in terms of social groups, location (rural–urban), gender and geographical regions remain rather high. Some of these inequalities somewhat narrowed over time, but they require policy attention for generating greater employment opportunities for the relatively disadvantaged populations.

2.5.2 Poverty and employment status #

The overall improvement in the quality of employment over time is also manifested in the increase in the employment quality index and the consistent decline in the incidence of poverty among the various categories of households. However, the economic slowdown that started in the second half of the past decade, followed by the pandemic, resulted in a rise in the poor quality of employment, with declining real earnings among self-employed and regular workers and that particularly affected the earnings of women, which remains a huge concern.

2.5.3 Minimum wage compliance #

There are significant gaps in minimum wage compliance. Among regular workers, 73.9 per cent did not receive the minimum wage prescribed for unskilled workers in the agricultural sector, while 27.2 per cent of construction sector workers did not receive the minimum wage. Among casual workers, 76.2 per cent did not receive the minimum wage, with 36.5 per cent of construction sector workers not receiving the prescribed minimum wage.

2.6.1 Migration for employment #

Among all migrants in 2021, about 10.7 per cent of them migrated due to employment purposes, which included searching for employment or better employment, transfer, proximity to place of work and lack of employment opportunities in the previous place of residence. This proportion, being as low as 1.7 per cent among women, was 49.6 per cent among the men, with the states and union territories that had a corresponding larger proportion than the national average being Delhi (87.1 per cent), Karnataka (63.2 per cent) and Maharashtra (59.5 per cent).

2.7.1 Employment trends during and after the pandemic #

As evident from the analysis in the preceding sections, there was a break in the structural trends in the labour market and employment after 2019 due to the COVID-19 pandemic and subsequent lockdowns. Although India recovered rather quickly, it seems that the impacts of the lockdowns persisted even when the pandemic ended. This section analyses the impact of the pandemic on the Indian labour market, based on short-term annual and quarterly trends of the employment characteristics available in the Periodic Labour Force Survey data for 2019, 2020, 2021 and 2022.

The Indian labour market showed considerable quarterly variation during the pandemic. Two of the key labour market indicators – the LFPR and the worker population ratio – sharply declined while the unemployment rate rose in the peak pandemic quarters in 2020 and 2021. They recovered in the subsequent quarters, reaching the pre-pandemic levels and have shown continued improvement in the post-pandemic period. These changes are largely attributed to increased women's participation in the labour market in rural areas. However, other changes that show a retrogression in the structure of employment do not indicate a full recovery in the final year (2022) covered in this report.

The LFPR increased steadily over the years, from 50.2 per cent in 2019 to 55.2 per cent in 2022. Similarly, the worker population ratio also increased, from 47.3 per cent in 2019 to 52.9 per cent in 2022. In absolute terms, 63.5 million additional persons joined the labour force and 68.1 million additional persons joined the workforce between 2019 and 2021. Consequently, the unemployment rate and the number of unemployed persons declined by 1.6 percentage points and 4.6 million, respectively. The female LFPR and worker population ratio increased significantly more than what those rates did among their male counterparts between 2019 and 2020 and between 2020 and 2021, particularly in rural areas.

Between 2021 and 2022, the LFPR increased at a similar pace for men as well as women – from 77 per cent to 77.2 per cent for men and from 32.2 per cent to 32.5 per cent for women. In absolute numbers, the labour force and the workforce increased much more in rural areas (at 47 million workers and 51.3 million workers, respectively) than in urban areas (at 16.5 million and 16.8 million persons, respectively) between 2019 and 2021.

The post-pandemic recovery and the upward movement in the quarterly employment rates suggest positive trends. But these results must be moderated on the basis of the quality of employment generated and the changing structure of the workforce, which is examined in sections 2.4 and 2.6.2. The quarterly data from the Periodic Labour Force Survey show the impact of the pandemic on each quarter. The worker population ratio started declining, from nearly 48 per cent in the fourth quarter of 2019 (October–December) to 42.6 per cent in the second quarter of 2020 (April–June), which also included a nationwide lockdown period. However, the worker population ratio quickly recovered, to 49 per cent in the first quarter of 2021 (January–March), only to decline to 45.7 per cent in the second quarter of 2021, coinciding with the second COVID-19 wave and local lockdowns. This again recovered, to 48 per cent in the third quarter (July–Sept) of 2021 and showed further improvement in the subsequent quarters. During the same period, the unemployment rate also increased significantly, to 11.8 per cent in the second quarter of 2020 and then to 8.1 per cent in the second quarter of 2021, which consistently reduced to 5.1 per cent by the second quarter of 2022.

2.7.2 Impact of the pandemic on quality of employment and sectoral change #

The impact of the COVID-19 pandemic was evaluated using broad employment indicators. The analysis is based on the employment status and sectoral employment patterns.

The number of workers in the self-employment category increased consistently during the pandemic years and continued into 2022, particularly in vulnerable unpaid family work in rural areas and among women. In contrast, the number of people engaged in regular formal, informal and casual employment increased at a slower pace during the pandemic period and declined afterward, with the exception of casual employment. The number of self-employed individuals increased by 27.4 million in 2020, by 24.8 million in 2021 and by 10.8 million in 2022. Of the total additional people who joined the workforce, self-employed persons comprised more than 69 per cent in 2020, 87 per cent in 2021 and nearly all in 2022, largely consisting of unpaid family workers.

Other studies corroborate these findings: Abraham et al. (2022), Behera et al. (2021) and Deshpande (2020) pointed out that women's participation increased as they sought to supplement falling household income at the time of the pandemic-related slowdown. A large part of this increase in employment was due to rural women joining the workforce as self-employed workers in agriculture. Some studies investigating the links between the pandemic-related income shocks and the female LFPR also found that the probability of women's employment increased in households that had experienced sharp negative shocks induced by the lockdowns (see Bansal and Mahajan 2021). Women were several times more likely to lose their paid job than men and far less likely to recover work after the restrictions were lifted (APU 2021). In particular, women and youths, irrespective of the nature or industry of work, were more vulnerable to losing work and not returning to paid work (ILO 2022c; Deshpande 2020).

There was some increase in less remunerative employment during the pandemic period, which persisted to some extent into the post-pandemic years. The rise in employment in subsistence agriculture, either as own-account workers or unpaid family workers, as well as in casual workers in the construction sector, indicates that a large number of poor migrants returning to their native home and marginal workers may have been compelled to work in these sectors in rural areas for their livelihood.

The changes in real monthly wages and earnings illustrate that the negative impact of COVID-19 was felt strongly on wages during the peak pandemic years, with some recovery in 2022. Casual wages grew slowly during the first year (2020), in which the last 14 weeks were affected by a lockdown, and at a negligible rate during 2021. But the growth rate of casual wages revived during the recovery year (2022). Both the growth rate of regular and self-employed earnings remained low or negative right up to 2021 but grew during 2022. Overall, the regular wages of both female and male workers experienced a small negative growth rate between 2018 and 2022. However, female self-employed workers experienced a considerably higher negative growth rate in earnings compared with men. Additionally, women's casual wages exhibited a slightly higher growth rate than what it was for men.

The broad sectoral analysis found that the number of people engaged in construction, trade, manufacturing and information and communication services either remained stable or had a small increase between 2019 and 2022, whereas the agriculture sector had a consistent and considerable increase in employment. The number of workers in the agriculture and allied sectors increased by 30.8 million in 2020, 12.1 million in 2021 and 12.9 million in 2022. Yet, employment in the construction sector also consistently increased, by 2.4 million, 5.7 million and 3.3 million, respectively. The quarterly data indicate that people lost their jobs in manufacturing, construction, trade, hotels and restaurants and even some in the farm sector during the nationwide lockdown. Once the lockdown was lifted, employment in the agriculture and construction sectors considerably increased, confirming the annual sectoral changes in employment during the pandemic period.

The analysis found that apart from causing loss of jobs of regular salaried workers, the COVID-19 pandemic also affected the quality of employment. The disruptions put pressure on households to either start their own economic enterprise or involve other family members in unpaid work to cope with the financial strain caused by the pandemic responses. Specifically, the pandemic pushed many workers to return to their native rural home, where they primarily engaged in self-employment or casual work in agriculture or construction. Non-working family members, such as women in urban areas prior to the pandemic, were also pushed to engage in livelihood activities, resulting in a substantial increase in self-employment in agriculture during the pandemic years. It has been argued that during times of exogenous shocks, households, especially those who are poor and vulnerable, are forced to protect their livelihoods by creating some form of economic activity (Chand 2023; Kannan and Khan 2020).

The significant increase in self-employment in rural areas during the pandemic years was accounted for by the incremental workforce created by the exodus of migrant labourers from different parts of the country back to their native rural areas, which was a troubling scene to watch. The poor quality of additional employment and decline in underemployment during the pandemic and afterward was also reflected in the decrease in the average real monthly earnings of regular and self-employed categories of workers, along with only a small increase in casual wages, as discussed earlier in this section.

Note: See also COVID-19 Impact cross-chapter page for additional analysis.

2.8.1 Technological advancement and employment #

The economic disruption caused by the COVID-19 pandemic has changed work patterns and accelerated the adoption and demand for digital technologies across various industries and the services sector. This rapid integration of digital solutions offers potential for enhanced operational efficiency and productivity. But the rise of digital technologies is causing significant changes in the structure of the global labour market. Digital technologies are replacing or automating existing jobs and creating new ones, leading to job polarization and income inequalities in developed countries (Autor 2019; Jaimovich and Siu 2018; Acemoglu and Autor 2011). However, studies of those trends mostly focused on developed economies and cannot be generalized to developing countries like India. It is thus important to understand the impact of new technologies on skill demand and job polarization in the Indian labour market.

For that analysis, this section uses the National Occupational Classification (NCO) 2004 framework based on labour tasks. Labour tasks are classified into routine and non-routine, cognitive and manual tasks, and skill and no-skill categories, which are further divided into no-skill, low-skill, medium-skill and high-skill categories. To perform long-term comparative analysis, the NCO-1968 classification was converted to the NCO-2004 classification for 2000.

The share of high- and medium-skill jobs increased from 5.1 per cent in 2000 to 9.6 per cent in 2019, while low-skill jobs increased from 60.5 per cent to 65.1 per cent. Simultaneously, the share of no-skill jobs decreased from 34.4 per cent to 25.4 per cent. These trends suggest a rise in high- and medium-skill jobs and a decline in no-skill or routine-type jobs. However, the trend shifted, with a consistent increase in low-skill jobs and a decrease in high- and medium-skill jobs between 2019 and 2022. This indicates a sustained increase in the supply of low-skilled labour in the job market because many individuals were compelled to work to support their family income, as discussed in the previous section.

The manufacturing sector consistently experienced an increase in the share of high- and medium-skill (2.9–6.7 per cent) and no-skill jobs (9.7–20.4 per cent) between 2000 and 2022. However, this trend did not apply to all enterprises. In the Indian manufacturing sector, more than 90 per cent of enterprises are micro and small and informal, relying heavily on manual and unskilled labour for their operations. This trend was more prevalent in the formal, capital-intensive and modern manufacturing sectors, such as automobiles, electronics and pharmaceutical units.

In the services sector, the share of high- and medium-skill jobs in public administration, health and education (45.1 per cent) and financial, business and real estate (42.3 per cent) is much higher than in transport, storage and communication (19.7 per cent) and trade, hotels and restaurants (3 per cent). On the contrary, the share of low- and no-skill jobs are predominant in trade, hotels and restaurants (97 per cent). In particular, the share of high- and medium-skill jobs consistently increased among the transport, storage and communication category between 2000 and 2022 (from 2.7 per cent to 19.7 per cent), which includes information and communication technology-related services. The demand for high- and medium-skilled ICT workers accelerated during and after the COVID-19 pandemic.

Technological changes have increased the employment of highly skilled labour and reduced employment of low-skilled labour (often in absolute terms) in the manufacturing and services sectors over the past two decades (Ghose and Mehta 2022). Unlike in developed economies, however, the technological change has not reduced the employment of medium-skilled labour in absolute terms. In addition, technological advancement in India has led to demand for high- or medium-skilled workers in select sectors, such as large and medium-sized manufacturing enterprises and modern services, like information and, communication and software services, but at a much lower level than in developed economies. The robotization rate in India is still very low, accounting for only 0.8 per cent of the global robots, with 4,945 industrial robots in 2021, and is largely confined to capital-intensive industries and medium-sized and large services units, where it is used in few tasks with a low chance of displacing low-skilled and unskilled labour to a large extent in the near future (Ghose 2023; Mani 2022; Mehta et al. 2022). The impacts of technological changes and capital intensity on output and employment are further examined in Chapter 3.

2.8.2 Digitalization and employment #

The rapid growth of digitization in the form of advancements in internet data connectivity and the availability of high-speed computers, laptops and smartphones are reshaping the world of work, providing new opportunities for companies and individuals to hire the services of freelancers on a flexible or temporary basis. This type of short-term contractual task-based work is commonly known as the platform or gig economy and offers people with different skill sets income opportunities and work flexibility, although it also often entails poor working conditions and no social security benefits. Despite these challenges, the gig economy showed resilience even during the COVID-19 pandemic, when many services were delivered directly to people's doorsteps.

There are several estimates of the number of gig workers in India. In 2021, the Boston Consulting Group (2021) estimated gig economy jobs in India at between 8 million and 18 million, with a projection of more than 90 million in the next eight to ten years. According to a National Institution for Transforming India (NITI Aayog) study, there were 7.7 million gig workers in 2021, constituting 2.6 per cent of the total non-farm workers, or 1.5 per cent of the total workforce in India. However, the estimates of gig workers based on the Periodic Labour Force Survey data should be used cautiously because the data lack sufficient indicators to estimate gig and platform workers.

Despite the potential for rather large employment opportunities, there are growing concerns about the work offered in the gig economy. Working conditions on digital platforms are largely regulated by the terms of service agreements, which often characterize the contractual relationship between the platform owner and worker as something other than employment, making it difficult for platform workers to access workplace protections and entitlements. It has been pointed out that on-demand app-based service aggregator companies in India have poor working conditions. The lack of job security, irregular wages and uncertain employment status for workers pose significant challenges for gig or platform work (NITI Aayog 2022). This effectively reproduces or produces new forms of informality and can further deteriorate working conditions. Further, the uncertainty associated with work and income regularity also leads to increased stress and pressure for gig economy workers.

2.9.1 Methodology #

To assess the regional differences and progress in quality and conditions of employment, a composite index – the employment condition index – was constructed for 22 major states of India. The employment condition index was constructed for 2005, 2012, 2019 and 2022 using the following seven indicators:

• Percentage of workers employed in regular formal work: Represents the proportion of formal workers in the total workforce, with states that have a larger proportion receiving a better ranking.
• Worker population ratio: Represents the proportion of working individuals in total population. States with a high worker population ratio receive a better ranking.
• Proportion of casual workers: Indicates the percentage of casual workers in the total workforce. States with a small proportion receive a better ranking.
• Proportion of self-employed workers with income below the poverty line: Reflects the proportion of self-employed workers living below the poverty line. States with a small proportion receive a better ranking.
• Average monthly earnings of casual workers: Represents the average monthly wages of casual workers. States offering higher casual wages receive a better ranking.
• Unemployment rate of youths with a secondary or higher level of education: Indicates the proportion of youths who are educated above the secondary level but are unemployed. States with a low rate receive a better ranking.
• Youth not in employment, education or training: This proportion addresses a broad array of vulnerabilities among youths, touching on issues of unemployment, early school leaving and labour market discouragement. States with a smaller proportion receive a better ranking.

The employment condition index calculation employs the maximum–minimum range method, wherein the range is determined by the difference between the maximum and minimum values of each indicator. The maximum and minimum values, referred to as the goalposts, are assumed at 20 per cent higher and 20 per cent lower than the actual maximum and minimum values. The employment condition index values range between 0 and 1, with 1 denoting the highest possible score. The composite index value is derived by averaging the values of all seven indicators.

2.9.2 Findings #

The overall employment condition index value suggests a gradual but consistent improvement in employment conditions for all of India over the past 17 years, which increased from 0.40 in 2005 to 0.65 in 2022. Additionally, all 22 states showed improvement in their employment condition index value, albeit to varying extent.

Himachal Pradesh, Uttarakhand, Delhi, Telangana and Jammu and Kashmir in the northern regions consistently ranked in the top positions in the employment condition index, reflecting their robust economic and employment conditions. Specifically, the consistent top position of Himachal Pradesh, Delhi, Jammu and Kashmir and Uttarakhand in the index can be primarily attributed to the improvement in employment conditions among women.

The economically underdeveloped states of Bihar, Odisha, Jharkhand and West Bengal in the eastern region, along with Uttar Pradesh in the northern region, consistently ranked lower in the employment condition index. In particular, Haryana in the northern region ranked among the top ten states until 2019, and then experienced a significant decline in its rank in 2022. This decline was attributed to a decrease in the worker population ratio, an increase in the proportion of casual and self-employed workers living below the poverty line and a rise in the share of youths not in employment, education or training. Punjab in the north-western region, despite showing improvements between 2005 and 2012, fell into a consistent decline in its index rank thereafter. This decline was linked to a decrease in the share of regular formal employment and an increase in the proportion of casual workers and self-employed workers living below the poverty line. The decline in the index ranking in Haryana and Punjab is credited to a deterioration of employment conditions, particularly among men in these states.

The economically advanced Kerala State in the southern region demonstrated consistent improvement in its employment condition index ranking over time, landing among the top ten states in 2022. This transformation was attributed to a reduction in the share of youths not in employment, education or training and an increase in the proportion of formal regular workers, particularly among women. Similarly, both Tamil Nadu in the southern region and Gujarat in the western region consistently improved their index ranking. Tamil Nadu achieved this by increasing its worker population ratio and decreasing its share of casual workers and youth unemployment mainly among men over time. Gujarat's improvement was credited to an increase in the share of regular formal employment and a decrease in the proportion of self-employed workers living below the poverty line, a trend that was particularly pronounced among men in the state.

Some other states, such as Madhya Pradesh in the central region, experienced a decline in their employment condition index ranking due to a decrease in the share of regular formal employment and an increase in the share of youths not in employment, education or training. Rajasthan in the western region improved its index ranking, primarily due to a decrease in the share of casual workers and the proportion of youths not in employment, education or training. And Maharashtra's index ranking remained stable throughout the study period.

The analysis of main trends and patterns in the Indian labour market covering the past two decades (2000–22) in this chapter revealed interesting findings.

Since 2018, there has been an upturn in the key labour market indicators, which include labour force participation, workforce participation and the unemployment rate. This upturn constitutes a structural shift from the previous two decades. This trend continued during the COVID-19 pandemic and is all the more marked for women workers. However, analysis of this seemingly positive feature must be tempered by the nature of employment that was largely created during the recent period.

The basic long-term feature of the employment situation in India continues to be insufficient growth of the non-farm sectors and the ability of these sectors to absorb workers from agriculture. This is notwithstanding the fact that non-farm employment grew at a higher rate than farm employment over the different periods prior to 2018. After 2018, there was a structural break in several labour market indicators and it accelerated during the pandemic. These structural features were retained even during the recovery from the pandemic in 2022. The shift was accompanied by other important changes in the labour market. Contrary to the earlier period when there was a gradual shift from agriculture to non-agriculture, agriculture employment significantly increased between 2019 and 2022, with the bulk of the employment accounted for by an increase in women's self-employment in unpaid family work, which is essentially a subsistence activity. This increase may be seen as mainly a response to crises and implies a reversal of the Kuznets–Lewis process of structural change over the most recent period (2019–22) analysed in this report.

The LFPR declined between 2000 and 2019 mainly due to the decline in the female LFPR. But this, too, was completely reversed during the pandemic years due to the significant increase in women's workforce participation. This also was mainly due to the huge rise in women's self-employment activities. In a way, however, it shows that a large number of women are ready to work due to economic compulsion and if offered some remunerative opportunities. This increase in the female LFPR is an important indicator of change regarding gender equality and improving livelihoods.

Before the pandemic, the aggregate employment slowly increased mainly due to a fall in agriculture employment. Labour from agriculture was mainly absorbed by the construction and services sectors and not manufacturing, unlike the historical pattern as experienced in the now-developed countries. This led to a slow and rather stunted structural transformation in India, which is discussed in greater detail in Chapter 3.

Employment conditions remain poor, with around 90 per cent of workers being informal. However, over the years, there was overall improvement in employment conditions, as manifested by the growth in regular and organized sector workers. This is also shown by the consistent decline in the incidence of poverty among the various categories of households. The overall improvement in the quality of employment over time is also manifested in the increase in the employment quality index. At the same time, the economic slowdown that started in the second half of the past decade, followed by the pandemic, resulted in a rise in the poor quality of employment, with declining real earnings among self-employed and regular workers and that particularly affected the earnings of women, which remains a huge concern.

There are widespread livelihood insecurities, with only a small percentage being covered with social protection measures, precisely in the non-agriculture sector, but even in the organized sector. Worse, there has been a rise in contractualization, with only a small percentage of regular workers covered by long-term contracts.

The segmentation and inequalities in the labour market in terms of social groups, location (rural–urban), gender and geographical regions remain rather high. Some of these inequalities somewhat narrowed over time, but they require policy attention for generating greater employment opportunities for the relatively disadvantaged populations.

New technologies are slowly changing the labour market structure, with increases in capital intensity in various sectors. Skill composition has been gradually changing with the increase in jobs requiring high skills and the decrease in jobs requiring limited skills. This has implications for the supply and demand for skilled work, which is analysed in greater detail in the chapters that follow, but is worrisome for a country like India and its large stock of workers lacking job-related skills.

In sum, the positive trends observed in the labour market will result in positive outcomes overall if the pace and quality of jobs generated in the non-farm sectors can pick up considerably and if there is a greater match between the demand and supply of skills in the context of technological change.