Employment and enterprise surveys: PLFS, ASI, ASUSE and the Economic Census

Detail

1. Why these surveys exist: census vs sample

• Census: data is collected from every unit, for example every person or every shop.
• Sample survey: data is collected from a selected part of the units, and the result is scaled up to the whole country.
• The Economic Census is a complete count, so it is a census.
• PLFS, ASI (for its sampled units) and ASUSE are sample surveys.
• NSO (National Statistics Office) runs these surveys. It works under the Ministry of Statistics and Programme Implementation (MoSPI).
• Why it matters: jobs and enterprise output feed into policy, GDP estimates and employment schemes.

2. Periodic Labour Force Survey (PLFS): origin and design

• Launched by NSO in April 2017.
• Designed on the Amitabh Kundu committee's recommendations.
• What it replaced:
• the quinquennial NSS employment-unemployment rounds (held every five years; the last was in 2011-12)

• the Labour Bureau's annual Employment-Unemployment Survey (EUS)

• Goal: give labour data more often than once in five years [3].

• Original two aims (2017-2024) [3]:
• Every quarter, urban areas only, in CWS: estimate LFPR, WPR and UR.

• Every year, rural and urban areas, in both usual status and CWS: give the full set of indicators.

• Seven annual reports used the July-June cycle (the agricultural year): 2017-18, 2018-19, 2019-20, 2020-21, 2021-22, 2022-23 and 2023-24 [2].

3. Two ways of measuring activity

• Usual status (ps+ss) looks back 365 days before the survey date [3]:
• Principal status (ps): the activity on which the person spent the most time in those 365 days (the "major time criterion") [3].
• Subsidiary status (ss): any extra economic activity done for 30 days or more in the same 365 days [3].

• ps+ss counts a person as a worker if either one is "work". This gives a larger worker count.

• Current weekly status (CWS) looks back 7 days before the survey date [3].

• It catches short-term job loss and seasonal swings.
• So the CWS unemployment rate is usually higher than the usual-status rate.

• Example: 4.9% CWS against 3.2% usual status in calendar 2024 [3].

• Rotational panel: the same households are visited again on a fixed schedule. This lets NSO track changes over time.

• Up to 2024 this was done in urban areas only.
• From 2025 it covers both rural and urban areas (see section 5).

4. The three indicators, with formulas

• Labour force = people who are working + people who are seeking or available for work.
• LFPR (Labour Force Participation Rate) = (Labour force ÷ Population) × 100 [3]
• WPR (Worker Population Ratio) = (Employed persons ÷ Population) × 100 [3]
• UR (Unemployment Rate) = (Unemployed persons ÷ Labour force) × 100 [3]

• Trap: the UR is divided by the labour force, not by the population.

• Link between them: WPR = LFPR × (1 − UR/100)

• Worked example (a village with 1,000 people aged 15+):
• 600 are working or seeking work → LFPR = 600/1,000 = 60%
• 580 of them have work → WPR = 580/1,000 = 58%
• 20 are unemployed → UR = 20/600 = 3.33%

• Check: 60 × (1 − 0.0333) = 58 ✔

• Key point: a low UR can hide a weak job market.

• If many women stop looking for work, they leave the labour force.

• The LFPR falls, but the UR may not rise.

• Detailed analysis → employment-informal-sector.

5. The 2025 revamp of PLFS

• Why: to get labour data more often, with wider coverage [2].
• Monthly CWS estimates of LFPR, WPR and UR, for rural + urban, at all-India level [2].
• Quarterly estimates now cover rural and urban areas. Earlier they covered urban only [2].
• Calendar-year annual reports:
• The survey cycle moved from July-June to January-December from 2025.
• This matches the international practice of reporting labour data by calendar year [2].

• Annual Report 2025 (released 27 March 2026) is the first full calendar-year report [2].

• Rotational panel in both rural and urban areas [2]:

• Each household is visited in four consecutive months.
• 75% of the sample overlaps between one month and the next.

• 50% overlaps between one quarter and the next.

• Districts are now the basic strata (sampling groups). Earlier, NSS regions were used for most areas [2].

• Sample size:
• Up to December 2024: about 12,800 FSUs × 8 households ≈ 1.02 lakh households [2]. (An FSU, or First Stage Unit, is a village or an urban block.)
• From January 2025: 22,692 FSUs × 12 households ≈ 2.72 lakh households, about 2.65 times larger [2].
• In January-December 2025, 2,70,472 households and 11,48,634 persons were surveyed on the first visit [2].

• (NCERT scaffold: "about 2.7 lakh households a quarter". The official note describes 2.7 lakh as the first-visit sample over the full year.)

• Comparability warning: the 2025 estimates "may not be strictly comparable" with earlier PLFS reports because the sample design changed [2].

6. PLFS data: usual status (ps+ss), age 15+

Indicator	2023-24 (July-June)	Calendar 2024	Calendar 2025
UR	3.2%	3.2% [3]	3.1% [2]
LFPR	60.1%	59.6% [3]	59.3% [2]
WPR	58.2%	57.7% [3]	57.4% [2]
Female LFPR	41.7%	40.3% [3]	40.0% [2]

• Other 2025 findings [2]:
• Male LFPR was 79.1%.
• Urban UR was 4.8%. Rural UR was 2.4%.
• Youth UR (age 15-29) fell to 9.9% from 10.3% (2024). Urban youth UR was 13.6%.
• The share of regular wage/salaried workers rose to 23.6% from 22.4% (2024).
• The share of self-employed workers fell to 56.2% from 57.5% (2024).
• Agriculture's share of jobs fell to 43.0% from 44.8% (2024). Manufacturing rose to 12.1% from 11.6%.
• NEET (young people not in employment, education or training) was 21.0% for age 15-24 and 25.0% for age 15-29.

• About 61.6 crore people aged 15+ were employed in 2025: 41.6 crore men and 20.0 crore women.

• CWS, calendar 2024: LFPR 56.2%, WPR 53.5%, UR 4.9% [3].

7. Flashpoints and rival data sources

• The 2017-18 leak:
• A leaked report showed an unemployment rate of 6.1%, reported as "a 45-year high".
• Two NSC members resigned in January 2019, over the delay in releasing the report.

• NSC is the National Statistical Commission, the body that watches over the quality of official statistics.

• CMIE's CPHS (Consumer Pyramids Household Survey):

• A private survey that tracks households often.

• It uses different definitions and methods from PLFS, so its numbers often differ.

• EPFO payroll data:

• Counts new members joining the Employees' Provident Fund.
• It is used as a proxy (an indirect sign) of formal jobs.
• Weak point: it also counts workers who were already employed but only now became registered.

8. Annual Survey of Industries (ASI)

• Runs since 1960. It now works under the Collection of Statistics Act 2008.
• Coverage: factories registered under Sections 2(m)(i) and 2(m)(ii) of the Factories Act 1948:
• 10 or more workers where the unit uses power

• 20 or more workers where it does not use power

• Also covers: bidi and cigar units and some electricity undertakings.

• What it gives: data on organised (formal) manufacturing:
• GVA (Gross Value Added: the value of output minus the value of inputs used)
• employment and wages

• fixed and working capital

• ASI 2023-24 covered April 2023 to March 2024 [5]:

• Results were released on 27 August 2025.

• Results are given by NIC-2008 industry codes (National Industrial Classification) [5].

• Where the industry is: the top 5 States account for about 54% of manufacturing GVA and 55% of manufacturing employment (2023-24) [5].

9. Annual Survey of Unincorporated Sector Enterprises (ASUSE)

• What it covers: unincorporated non-agricultural enterprises.
• "Unincorporated" means the business is not registered as a company. This is the informal sector.
• It covers manufacturing, trade and other services, but excludes construction [4].

• Ownership types covered: proprietorships, partnerships (excluding LLPs), co-operatives, and societies/trusts [4].

• Annual since 2021-22.

• Earlier rounds used an October-September cycle.

• ASUSE 2025 moved to the January-December cycle [4].

• Design change in 2025 [4]:

• The sample was raised about 1.5 times.
• This allows quarterly estimates as well as annual ones.
• Districts are the basic strata, so States that take part can get district-level annual estimates.
• ASUSE 2025 surveyed 6,70,289 establishments [4].

• (NCERT scaffold: "quarterly bulletins from 2025". Confirmed as the quarterly-estimate design.)

• Key results [4][6]:

Indicator	2022-23	2023-24	2025
Establishments	6.50 crore	7.34 crore	7.92 crore
Workers	10.96 crore	12.06 crore	12.81 crore
GVA (₹ crore, current prices)	15,42,409	17,97,278	19,92,577
GVA per worker (₹)	1,41,769	1,49,742	1,56,539

• Growth in 2025 over 2023-24 [4]:
• Establishments grew by 7.97%.
• About 74.5 lakh jobs were added.
• GVA grew by 10.87%.
• Share of GVA: other services 42%, trade 37%, manufacturing 21%.
• Establishments using the internet rose to 39.4% from 26.7%.

• Women owned 27% of proprietary establishments.

• Worked example: labour productivity.

• GVA per worker = GVA ÷ workers.
• It rose from ₹1,49,742 to ₹1,56,539: (1,56,539 − 1,49,742)/1,49,742 ≈ 4.54% [4].

• This is in current prices, so part of the rise is only inflation.

• Uses of ASUSE: it feeds into the National Accounts (GDP) and helps the MSME and Textiles ministries with policy [4].

10. Economic Census

• A complete count of all establishments (farm activities are generally outside its scope).
• Rounds: the 1st was in 1977. The 7th was in 2019-21, conducted with CSC e-Governance. (CSC stands for Common Service Centres.)
• Role: it provides the list of establishments (the "sampling frame") from which ASUSE and other enterprise surveys draw their samples.

11. Labour Bureau establishment surveys

• Quarterly Employment Survey (QES):
• It is part of AQEES (All-India Quarterly Establishment-based Employment Survey).
• It tracks jobs in selected sectors, for example manufacturing, construction, trade, education, health, IT/BPO.
• It surveys establishments, not households.

12. Why this matters: the organised-unorganised gap

• ASI captures the organised sector well.
• The informal sector needs ASUSE, and ASUSE only recently became annual.
• The gap affects GDP, as a chain:
• Between surveys, informal-sector output is estimated using indicators from the formal sector.
• If informal firms are hit harder (as after a shock), GDP may be overstated.
• Annual and quarterly ASUSE data reduce this error (→ national-income-accounting).

Prelims Hooks

• PLFS was launched by NSO in April 2017, on the Amitabh Kundu committee's recommendations. It replaced the quinquennial NSS employment-unemployment rounds (last in 2011-12).
• Usual status (ps+ss) uses a 365-day reference period. Subsidiary status needs 30 days or more of economic activity. CWS uses 7 days.
• UR = unemployed ÷ labour force (NOT ÷ population). LFPR and WPR are divided by the population.
• From 2025, PLFS gives monthly CWS estimates (rural + urban). Quarterly estimates now include rural areas. Annual reports follow the calendar year (January-December).
• ASI coverage: 10+ workers with power / 20+ without power (Sections 2(m)(i)/(ii), Factories Act 1948). It is conducted under the Collection of Statistics Act 2008.
• ASUSE covers unincorporated non-agricultural enterprises in manufacturing, trade and other services. It excludes construction and LLPs.
• ASUSE 2025: about 7.92 crore establishments and 12.81 crore workers. "Other services" has the largest GVA share (42%).
• Economic Census is a complete count. The 1st was in 1977; the 7th in 2019-21 (with CSC e-Governance). ASI and ASUSE are sample surveys.
• Trap: PLFS Annual Report 2025 UR (usual status, 15+) = 3.1%. The CWS UR is higher (4.9% in calendar 2024).

Mains Points

• Data frequency vs comparability:
• The 2025 PLFS revamp gives monthly and quarterly data, which is useful for policy made in real time.
• But NSO itself warns that the 2025 figures are not strictly comparable with earlier years.

• So long-term trends need careful reading.

• Headline UR hides quality of work:

• The UR is low (about 3%).
• But youth UR is 9.9%, urban youth UR is 13.6%, and NEET (age 15-29) is 25%.
• About 56% of workers are self-employed, and agriculture still holds 43% of jobs (2025).

• This points to underemployment, not full employment.

• The informal sector is invisible in GDP:

• ASI measures the formal sector every year.
• The informal sector was measured only once in several years until ASUSE became annual (2021-22) and quarterly (2025).

• Better ASUSE data makes GDP estimates, MSME policy and credit targeting more accurate.

• Trust in statistics:

• The 2019 leak and the NSC resignations showed why data must be released on time and free from political interference.
• Checking PLFS against CMIE and EPFO data improves credibility, but each source uses different definitions.