Q. What is the key advantage of the Periodic Labour Force Survey (PLFS) compared to earlier Employment–Unemployment Surveys (EUS)? Explain in detail.

Q. What is the key advantage of the Periodic Labour Force Survey (PLFS) compared to earlier Employment–Unemployment Surveys (EUS)? Explain in detail.

The Periodic Labour Force Survey (PLFS), launched by the National Statistical Office (NSO) in 2017, represents a major reform in India’s labour statistics system.

Earlier, the Employment–Unemployment Surveys (EUS) under the National Sample Survey (NSS) were conducted once every five years. This gave important long-term labour market trends but lacked timeliness. For policymakers, waiting five years for fresh estimates was a serious drawback, especially when the economy was undergoing rapid structural changes (automation, migration, shocks like demonetisation or COVID-19).

Key Advantages of PLFS over EUS:

1. Timeliness of Data

   • PLFS provides annual estimates for both rural and urban areas and quarterly estimates for urban areas only.

   • This is a big improvement over quinquennial surveys of EUS.

2. Labour Market Dynamics

   • PLFS captures short-term fluctuations in employment/unemployment due to seasonality, festivals, agriculture cycles, or economic shocks.

   • EUS could not capture these dynamics because of its long gap.

3. Policy Relevance

   • Quarterly results give quick insights → useful for government, RBI, economists, and labour ministries.

   • Helps in framing employment schemes, skill development, and tracking SDG indicators.

4. Flexibility in Measurement

   • PLFS reports multiple indicators: Usual Status (long-term attachment) and Current Weekly Status (short-term activity).

   • This dual reporting improves comparability across time horizons.

Thus, PLFS combines the robustness of NSS methodology with the speed of modern labour statistics, filling a critical information gap.

🔄 Cross Questions

CQ1. Why does PLFS report both Usual Status and Current Weekly Status unemployment rates?

• Answer:

  • Usual Status (reference: last 365 days) shows long-term attachment to the labour force, useful for structural analysis.

  • Current Weekly Status (reference: last 7 days) captures seasonal or temporary unemployment, showing short-term shocks.

  • Reporting both allows policymakers to distinguish between chronic unemployment vs cyclical or temporary issues.

CQ2. PLFS shows an unemployment rate of 8%, but some local field reports suggest it is around 15%. Why might this discrepancy occur?

• Answer:

  1. Sampling Error: PLFS is sample-based; local reports may reflect small-area spikes not captured in sample.

  2. Definitional Differences: PLFS has strict definitions of employment/unemployment, while field reports may rely on perception.

  3. Coverage Issues: Informal workers, gig economy, and underemployment may be under-reported.

  4. Seasonal Variations: Survey timing matters—harvest vs lean season can shift employment rates.

CQ3. (Practical Application)If you were asked to use PLFS to guide employment policy in Lucknow or Uttar Pradesh, how would you proceed?

• Answer:

  1. Use Annual PLFS Estimates: To identify long-term structural issues (e.g., high female LFPR decline).

  2. Use Quarterly Urban Data: To monitor fluctuations in manufacturing, construction, and service jobs.

  3. Supplement with State-level Data: Compare with administrative records like EPFO, ESIC, and state labour surveys.

  4. Policy Action: If high unemployment is found in youth, suggest skill development and entrepreneurship schemes.

  
  

🧩 Key Takeaway

The main strength of PLFS lies in its frequency and timeliness. It has transformed India’s labour statistics from a once-in-five-years snapshot to a continuous monitoring system, making it indispensable for real-time policy intervention.