muslimdata.in

Last updated 29 July 2026

Muslim labour force participation in India

Of people aged 15 and older, what share is in the workforce, either working or actively looking for work. The series now reaches back two decades: participation fell economy-wide from 2004 to 2017 and recovered after, with the Muslim rate trailing throughout.

55.0%working or seeking work, age 15+(2023)

higher is better

vs all communities: -5.1pp behind

Explore the interactive chart, with breakdowns by working vs looking, sex, and urban vs rural →

Latest figures by community (2023)

CommunityLatest value
Muslim55.0%
Hindu60.9%
Christian62.8%
Sikh56.1%
All communities60.1%

Working vs looking2023

CommunityIn labour forceWorking
Muslim55.0%53.2%
Christian62.8%59.9%
Hindu60.9%59.1%
Sikh56.1%52.8%
All communities60.1%58.2%

By sex2023

CommunityMaleFemale
Muslim80.6%30.2%
Sikh79.2%33.0%
Hindu78.6%43.3%
Christian76.3%50.4%
All communities78.8%41.7%

From microdata Reproduce this view. This figure is recomputed from the unit-level survey microdata, the raw NSS or PLFS records behind the linked source. Source: PLFS 2023-24 · PLFS microdata 2017-24 · PLFS microdata 2017-24 · PLFS microdata 2017-24 · PLFS microdata 2017-24 · PLFS microdata 2017-24 · PLFS microdata 2017-24 · EUS microdata 2004-12 (NSS 61st/66th/68th) · EUS microdata 2004-12 (NSS 61st/66th/68th) · EUS microdata 2004-12 (NSS 61st/66th/68th). Each value is computed from the data file · transform code; every row records its own source and method.

Urban vs rural2023

CommunityUrbanRural
Muslim49.4%58.2%
Sikh48.8%58.6%
Hindu52.5%64.4%
Christian52.9%68.6%
All communities52.0%63.7%

From microdata Reproduce this view. This figure is recomputed from the unit-level survey microdata, the raw NSS or PLFS records behind the linked source. Source: PLFS 2023-24 · PLFS microdata 2017-24 · PLFS microdata 2017-24 · PLFS microdata 2017-24 · PLFS microdata 2017-24 · PLFS microdata 2017-24 · PLFS microdata 2017-24 · EUS microdata 2004-12 (NSS 61st/66th/68th) · EUS microdata 2004-12 (NSS 61st/66th/68th) · EUS microdata 2004-12 (NSS 61st/66th/68th). Each value is computed from the data file · transform code; every row records its own source and method.

Bottom line

About 55% of Muslims aged 15 and over were working or looking for work in 2023, against 61% of Hindus, but the whole of that gap is among women. Muslim men take part at slightly higher rates than Hindu men; Muslim women, at 30%, sit far below Hindu women at 43%, and that single gap pulls the community total down.

How to read the chart

The chart tracks the share of adults in the labour force across two decades, from the older Employment surveys to the newer PLFS; the dashed break at 2017 marks the change of survey, so do not read the step there as a real fall. The By sex tab is the one to open here: it shows the gap is almost entirely about women. Working vs looking separates the employed from those still searching, and Urban vs rural splits the rate by place.

Why it matters

How many adults work or seek work sets the ceiling on a community's income. A large pool of working-age people outside the labour force, most of them women, means fewer earners in each household and less to go around.

Status

Behindgap narrowing

Muslim 55.0% vs Hindu 60.9% in 2023, 5.9pp behind. The headline gap has narrowed over twenty years, but largely because participation drifted down for everyone; the low rate among Muslim women is the part that has barely moved.

Deeper analysis

Potential drivers

  • Women's participation · The gap is almost entirely a female one: Muslim women join the workforce at very low rates, for reasons that mix social norms, safety, childcare and a shortage of suitable local work ↗ Sachar Committee Report, 2006.
  • Self-employment · Muslim men cluster in self-employment and family enterprise rather than wage work, which the surveys count but which offers thinner, less secure earnings ↗ Sachar Committee Report, 2006.
  • Education · Lower schooling keeps many out of the formal jobs that draw people into the labour force in the first place ↗ Sachar Committee Report, 2006.

Key levers

  • Enable women's work · Safe transport, childcare and nearby job creation do the most to lift the rate, since the female shortfall is where the gap lives.
  • Skilling · Vocational training through schemes like PM VIKAS and PMKVY widens the path into wage work.
  • Credit for enterprise · Affordable credit strengthens the self-employment many Muslim households already depend on.
Key stakeholders

Badges link to an independent or registered credential where the organisation publishes one (Credibility Alliance, GiveIndia, 80G, FCRA). Many smaller NGOs do not take part in these registries, so a missing badge is not a mark against an organisation.

About this measurement

Definition. Of everyone aged 15 and older, the share either working or actively looking for work.

Methodology. The 2023-24 point is PLFS 2023-24 Table 48 (pages 396-400), total residence, person-level; reference period Jul 2023 - Jun 2024 (year=2023 in the canonical row is the start of this period). The 2017-18 to 2022-23 points are computed from each PLFS round's unit-level microdata, pulled via the MoSPI NADA API: the report PDFs publish the 15+ religion split only for their own year, but the microdata carries household religion in every round. The computation reproduces each round's published all-India LFPR to 0.1 points and the 2023-24 religion table within 0.2, so the published point extends the same series.

The 2004/2009/2011 points reach back through the three quinquennial NSS Employment & Unemployment Survey rounds (61st/66th/68th), computed the same way from their unit data and reproducing the published by-religion statements of NSS Reports 568/552 cell-for-cell; the EUS and PLFS designs are not strictly comparable, so the line is dashed at the 2017 break. Two decades tell one story: participation fell economy-wide between 2004-05 and 2017-18 (Muslim 15+ LFPR 55.1% to 45.0%, all-India 63.7% to 49.8%) and recovered after, but the Muslim rate has trailed the all-India rate by 5-9 points in every round since 2004. Religion is self-reported (NSO unit-data rider: indicative, no sub-state estimates).

The "Working vs looking" tab sets this rate against the worker population ratio (share actually working, wpr-15plus.csv) from the same source; the gap between them is unemployment.

Sources. PLFS 2023-24 · PLFS microdata 2017-24 · PLFS microdata 2017-24 · PLFS microdata 2017-24 · PLFS microdata 2017-24 · PLFS microdata 2017-24 · PLFS microdata 2017-24 · EUS microdata 2004-12 (NSS 61st/66th/68th) · EUS microdata 2004-12 (NSS 61st/66th/68th) · EUS microdata 2004-12 (NSS 61st/66th/68th). Download CSV: lfpr-15plus.csv.

From microdata How to reproduce. This figure is recomputed from the unit-level survey microdata, the raw NSS or PLFS records behind the linked source.

Related indicators