Unemployment in India: definitions, forms and migration

Detail

1. What "unemployment" means: two definitions

• NSO definition (official). A person is unemployed when all three things are true:
• they are not working, because there is no work (not because they chose to stay home);
• and they seek work, through employment exchanges, middlemen, friends or relatives, or by applying to employers;

• or they are available for work at the prevailing conditions and pay (the usual wage and terms in the area).

• Economists' definition. A person is unemployed if they cannot get work for even one hour in half a day.

• Why "lack of work" matters. A student or a person who does not want a job is not unemployed. They are outside the labour force.

2. How PLFS measures unemployment

• PLFS (Periodic Labour Force Survey). It is run by the National Sample Survey Office (NSSO) under MoSPI and was launched in April 2017 [2].
• PLFS 2023-24: July 2023 to June 2024.

• It covered 1,01,920 households (55,796 rural and 46,124 urban) and 3,19,773 persons aged 15 years and above [2].

• Three key ratios [2]:

• LFPR (Labour Force Participation Rate): % of the population in the labour force (working + seeking or available for work).
• WPR (Worker Population Ratio): % of the population that is employed.

• UR (Unemployment Rate): % of persons unemployed among persons in the labour force.

• Formula:

• UR = Unemployed ÷ Labour force × 100

• Labour force = Employed + Unemployed

• Worked example:

• Take a village of 1,000 people aged 15+. 580 work, 20 are seeking work, and 400 are students, homemakers or retired people.
• Labour force = 580 + 20 = 600, so LFPR = 600/1000 = 60%.
• WPR = 580/1000 = 58%.

• UR = 20/600 = 3.3%. The denominator is the labour force, not the whole population.

• Two ways to classify a person's activity status [2]:

• Usual Status (ps+ss): looks back over the last 365 days.
  • Principal status (ps): the activity on which the person spent relatively long time (the major time criterion) in those 365 days.
  • Subsidiary status (ss): extra economic activity done for 30 days or more in those 365 days.
  • A person who is unemployed most of the year but worked 30+ days on the side is counted as employed under ps+ss.
• Current Weekly Status (CWS): looks back over the last 7 days.

• Victor's case (Class 11, Ex. 19): Victor works 2 hours a day. By CWS he counts as employed, but he is really underemployed.

• Latest data (PLFS 2023-24, age 15+) [2]:

Indicator	2017-18	2023-24
UR, usual status (ps+ss), all	6.0%	3.2%
UR ps+ss, rural / urban	5.3% / 7.7%	2.5% / 5.1%
UR ps+ss, urban female	10.8%	7.1%
UR, CWS, all	8.7%	4.9%
LFPR ps+ss, all	49.8%	60.1%
LFPR ps+ss, female	23.3%	41.7%
WPR ps+ss, all	46.8%	58.2%

• Reading the table:
• CWS UR is higher than usual-status UR (4.9% against 3.2% in 2023-24). The 7-day window catches short spells without work that the 365-day window hides.
• Urban UR is roughly double rural UR. In villages, people fall back on family farms, which hides unemployment as disguised unemployment.

3. Open unemployment

• Open unemployment is visible unemployment. The person has no work at all and is clearly looking for it.
• What it looks like:
• reading job advertisements in newspapers;
• asking friends;
• standing at labour points (labour chowks) to be hired for a day;

• registering at employment exchanges.

• Fig. 6.5 (Class 11) shows unemployed mill workers waiting for casual jobs.

• Mostly an urban and educated problem. It shows up clearly in the urban UR of 5.1% (ps+ss, 2023-24) [2].

4. Disguised unemployment

• Definition: more people are working on a task than the task needs.
• Marginal product means the extra output from adding one more worker.
• For the extra workers, the marginal product is zero.

• So withdrawing them does not reduce output.

• Why it is "hidden": everyone looks busy, but the work is shared out thinly. It is common on Indian family farms.

• Class 11 example:
• A farmer has 4 acres. The work needs 2 workers plus himself.
• He actually uses 5 workers plus his wife and children.

• The people beyond the first three are disguisedly unemployed.

• Worked example with numbers:

Workers on 4 acres	Total output (quintals)	Marginal product
3	60	—
4	60	0
5	60	0
6	60	0

• Remove workers 4, 5 and 6, and output stays at 60 quintals. Those three are disguisedly unemployed.

• Late-1950s study: about one-third of farm workers were disguisedly unemployed. Sugarcane cutters are the chapter's example (Fig. 6.6).

• Class 10, the Laxmi case:
• Laxmi's family has five members. They work 2 ha of unirrigated land, growing jowar and arhar.
• All five work all year because they have nowhere else to go.
• Their labour effort is divided, so no one is fully employed.

• Suppose two members take jobs on landlord Sukhram's land or in a factory:

  • family income rises, because of the new wages;
  • farm output does not fall, because the other three can do all the farm work.

• Urban version:

• painters, plumbers and repair workers who do not find work every day;

• cart-pushers and street sellers who "spend the whole day but earn very little".

• Cross-links:

• The zero-marginal-product mechanics are in production-and-costs.

• The Lewis model (surplus farm labour can move to industry without cutting farm output) is in growth-theories-business-cycles.

• Recent evidence of rising surplus labour on farms:

• Farm employment grew faster than agricultural gross value added (GVA) after 2019 [4].
• More workers producing only slightly more output means more disguised unemployment.

5. Underemployment

• Underemployment: the person has work, but less, or poorer, work than they could do.
• Class 10 MCQ wording: underemployment is "working less than what they are capable of doing".
• Visible underemployment: the person works fewer hours than they want.
• Victor (Class 11, Ex. 19) gets only 2 hours of work a day. He spends the rest of the day looking for work.
• Under CWS he is employed (see Section 2), but he is underemployed.

• Such people usually do casual odd jobs: loading, delivery, repairs.

• Invisible underemployment: the person works full time, but either

• productivity is low (for example, a crowded family farm), or
• the job underuses their skills (for example, a graduate working as a peon).

• The ILO-IHD India Employment Report 2024 finds many highly educated youths are overqualified for their jobs. Some even take low-skill blue-collar public-sector jobs [4].

• Evidence:

• Youth underemployment rose between 2000 and 2019 [4].
• About 62% of unskilled casual farm workers did not earn the minimum wage (2022) [4].

6. Seasonal unemployment

• Definition: farm work is seasonal, so there is no work for part of the year, mostly between harvest and the next sowing.
• The cycle:
• lean season → villagers migrate to towns for work;

• rains begin → the sowing season brings farm work again → they return home.

• Effect on data:

• Usual status may count such a person as employed, because they had 30+ days of work in the year.
• CWS may catch them in an idle week. This is one reason why rural CWS UR (4.2%) is higher than rural ps+ss UR (2.5%) in 2023-24 [2].

7. Educated unemployment

• Definition: unemployment among people with secondary or higher education.
• In India, UR rises with education.
• Youth UR in 2022 was 29.1% for graduates and 18.4% for those with secondary or higher education. It was only 3.4% for youths who cannot read and write [4].
• So graduate youth UR was about nine times the rate for illiterate youth [4].
• (NCERT scaffold: graduates' UR "around 13%". This covers all ages, is marked "verify", and was not confirmed in the sources retrieved. The youth-specific figure above is much higher.)

• Educated young women face higher UR than educated young men [4].

• Causes:

• Skill mismatch: what colleges teach does not match what employers need [4].

• Queuing: educated people wait for scarce regular or government jobs instead of taking informal work. Families who can afford it support them while they wait (see human-capital).

• The poor cannot wait. An illiterate labourer has no savings, so they take any work. This is why their UR is low (3.4%), not because they have good jobs [4].

8. Youth unemployment

• Age band: 15-29 years in Indian surveys (PLFS). 15-24 years is the international (UN/ILO) convention.
• Latest: youth UR (usual status) was 10.2% in PLFS 2023-24 [3]. For all persons aged 15+ it was 3.2% [2].
• (NCERT scaffold: "about 10%" and "3.2%". Both are confirmed.)

• The government states that this is lower than global levels [3].

• Long-run trend (ILO-IHD India Employment Report 2024):

• Youth UR rose nearly threefold, from 5.7% (2000) to 17.5% (2019).
• It then fell to 12.1% (2022) and to about 10% (2023) [4][5].

• Youth UR is higher in urban areas, and among 15-19 year-olds than among 20-29 year-olds [4].

• NEET (Not in Employment, Education or Training):

• About one in three Indian youths was NEET in 2022 [4].
• 48.4% of young women against 9.8% of young men [4].

• Women made up about 95% of all NEET youth (2022) [4].

• Share of youth among the unemployed:

• (NCERT scaffold: youth are about 83% of the unemployed, and the educated share among unemployed youth is rising.)
• The direction matches the report's findings on educated youth [4]. The 83% figure was not found in the executive summary retrieved, so treat it as scaffold-only.

9. Key point from Class 11: low UR does not mean good jobs

• The poor "cannot remain completely unemployed for very long".
• They have no savings and no unemployment allowance.

• So they take unpleasant, unclean or dangerous jobs that nobody else will do.

• Result: India's low open UR can coexist with poor job quality.

• UR was only 3.2% (2023-24) [2].

• Yet nearly 82% of the workforce is in the informal sector, and nearly 90% is informally employed (no written contract and no social security) [4].

• Exam angle: use UR together with underemployment, the informal share and wages. Never use UR alone as a measure of labour welfare.

10. Migration links

• Rural-urban migration: workers move from villages to cities.
• Push factors: unemployment and seasonal idleness in villages.
• Pull factors: jobs and development in cities.

• It is often seasonal.

• Circular migration: repeated temporary moves between home and work areas, without settling in the city.

• Examples: brick kilns, sugarcane cutting, construction.

• Construction has consistently high employment elasticity, meaning each unit of output growth creates many jobs. This makes it the main destination for such migrants [4].

• Distress migration: migration forced by crop failure, debt or disaster, not drawn by good opportunities.

• Reverse migration: migrants return from cities to their villages.
• It happened on a huge scale during the 2020 COVID lockdown, when city jobs vanished overnight.
• MGNREGA (a legal guarantee of 100 days of wage work a year to rural households) acted as a cushion.

• Agriculture's share of the workforce rose in 2019-21. This reversed structural change, the long shift of workers from farms to industry and services.

• What the data show:

• From 2000 to 2019, workers moved out of low-productivity agriculture [4].
• This shift slowed and then reversed between 2019 and 2022, with substantial growth in farm employment [4].
• The report says this happened because people returned to subsistence farming for lack of non-farm work in the pandemic slowdown [4].

• The pandemic also reversed the long-term move of youth into non-farm jobs [4].

• Chain of cause and effect:

• Lockdown → urban informal jobs lost → migrants return home.
• Back home → they join family farms, so disguised unemployment rises.

• In the data → UR looks lower, but job quality falls [4].

• Portability of welfare for migrants (ration cards, social security) is covered in Section 11.

Prelims Hooks

• UR = unemployed ÷ labour force × 100. The denominator is the labour force, not the total population [2].
• Usual status (ps+ss) uses a 365-day reference period. Subsidiary status needs 30 days or more of economic activity. CWS uses the last 7 days [2].
• PLFS was launched by NSSO (MoSPI) in April 2017 [2].
• PLFS 2023-24, age 15+: UR 3.2% (ps+ss) and 4.9% (CWS), down from 6.0% and 8.7% in 2017-18 [2].
• Youth (15-29) UR was 10.2% in 2023-24 [3].
• Disguised unemployment: the marginal product of the extra workers is zero, so removing them does not reduce output. It is hidden, and most common on family farms.
• Trap: a person working 2 hours a day is employed under CWS but underemployed (Victor, Class 11).
• Educated unemployment: in India, UR rises with education. Youth graduate UR was 29.1% against 3.4% for illiterate youth (2022) [4].
• The India Employment Report 2024 was published by the ILO with the Institute for Human Development (IHD) [4][5]. It is not a Government of India report.
• Seasonal migrants return home when the rains begin, because sowing brings farm work.

Mains Points

• Low UR, poor jobs.
• UR was 3.2% in 2023-24 [2], but about 90% of employment is informal [4].
• The poor "cannot remain unemployed", so disguised unemployment and underemployment replace open unemployment.

• Policy should target job quality (wages, contracts, social security), not just job numbers.

• Education-employment mismatch.

• Graduate youth UR was 29.1% (2022) [4], and one-third of youth are NEET, mostly women [4].

• Remedies: vocational training and apprenticeships, labour-intensive manufacturing, and more jobs to raise female LFPR.

• Stalled structural transformation.

• The shift out of farming reversed in 2019-22 [4].
• This shows that non-farm sectors cannot yet absorb workers.

• Remedies: labour-intensive manufacturing (the Lewis-model route) and higher farm productivity.

• Migration and safety nets.

• The 2020 reverse migration exposed circular migrants' lack of social protection.
• MGNREGA worked as a buffer.
• Link to portable benefits for migrants (see Section 11) and to urban employment schemes (GS-II welfare and GS-III employment).