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PERIODIC LABOUR FORCE SURVEY

  • Launched by: National Sample Survey Office (NSSO), Ministry of Statistics & Programme Implementation (MoSPI).
  • Year of launch: 2017.
  • Purpose: To provide timely and reliable data on:
  • Employment and Unemployment
  • Labour Force Participation
  • Nature of employment (formal/informal, self-employed, etc.)

Objectives of PLFS

  • Estimate key labour force indicators (LFPR, WPR, UR).
  • Analyze trends in employment–unemployment dynamics.
  • Provide quarterly data (for urban areas) and annual data (for rural + urban).
  • Enable evidence-based policy-making on jobs, skill training, and welfare.

Key Indicators Used

Indicator

Definition

Labour Force Participation Rate (LFPR)

% of working-age population (15+) that is either employed or seeking work.

Worker Population Ratio (WPR)

% of employed persons in the population.

Unemployment Rate (UR)

% of unemployed persons among those in the labour force.

Activity Status

Defines a person as employed/unemployed/inactive based on a reference period.

Types of Activity Status

Status Type

Reference Period

Use

Usual Status (PS+SS)

365 days (1 year)

Long-term employment trend

Current Weekly Status (CWS)

7 days

Short-term, more dynamic measure

  • PS = Principal Status, SS = Subsidiary Status

PLFS Output Frequency

Area Type

Data Frequency

Urban

Quarterly

Rural + Urban (All India)

Annually

Importance of PLFS

  • Replaced the earlier Employment-Unemployment Surveys (EUS) conducted every 5 years.
  • Supports:
    • Planning for Skill India, Make in India, Startup India, and Atmanirbhar Bharat.
    • Labour market reforms and targeting schemes like MGNREGA, PM-SVANidhi, etc.
    • Helps assess impact of economic shocks (e.g., COVID-19) on employment.

Findings from Recent PLFS (2023–24)

  • Unemployment Rate (CWS): Declined to around 6.6% in urban areas.
  • Female LFPR: Gradually increasing (positive trend).
  • Self-employment: Still dominates in rural areas.
  • Youth Unemployment: Remains a concern, especially among educated youth.

Criticisms & Limitations

Issue

Explanation

Sample Bias

Under-representation of informal & migrant workers.

Urban-Rural Discrepancies

Quarterly data is only for urban areas.

Informality Measurement

Does not fully capture gig/platform workers.

Delay in Data Release

Hampers timely policy response.

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