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NSS & PLFS — Employment and Consumption Surveys

India's primary source for employment, wages, consumption expenditure, and inequality data — indispensable for economic research.

Provider
MOSPI (Ministry of Statistics & Programme Implementation)
Website
mospi.gov.in
Access Level
🟡 Free Registration for Unit-Level Data
Formats Available
CSV, Stata (.dta), SAS, Fixed-Width Text
Coverage
National → State (sample survey)
Key Surveys
NSS (periodic rounds), PLFS (annual + quarterly)

NSS vs PLFS — What's the Difference?

Feature NSS (National Sample Survey) PLFS (Periodic Labour Force Survey)
Started 1950 2017
Frequency Periodic "rounds" (every 5 yrs) Annual report + quarterly urban
Topics Employment, consumption, health, housing Employment and unemployment only
Sample size 1–2 lakh households ~1 lakh households/year
Best for Consumption poverty, specific sectors Tracking unemployment trends

Key NSS Rounds for Researchers

Round Year Topic Why Important
61st 2004–05 Employment & Unemployment Pre-reform benchmark
66th 2009–10 Employment & Unemployment Post-financial crisis
68th 2011–12 Employment & Unemployment Most cited recent round
70th 2013 Drinking Water, Sanitation Key for WASH analysis
72nd 2014–15 Social Consumption Health and education expenditure
75th 2017–18 Household Consumption Poverty measurement update
76th 2018 Drinking Water & Sanitation Post-Swachh Bharat data

PLFS Annual Reports (Free, No Login)

The PLFS annual summary reports are freely available without registration:

  1. Go to mospi.gov.in
  2. Navigate: Statistics → Labour & Employment → PLFS
  3. Download Annual Report (PDF with state-wise tables)
  4. Also available: Quarterly Bulletin (urban employment only)

Key PLFS indicators you'll find:

Indicator Definition
UPSS Unemployment Rate Persons unemployed for majority of the year
CWS Unemployment Rate Persons unemployed in reference week
LFPR Labour Force Participation Rate
WPR Worker Population Ratio
FLFPR Female Labour Force Participation Rate

How to Download Unit-Level Data 🟡

  1. Go to mospi.gov.in
  2. Navigate: Data → Unit Level Data → NSS
  3. Click "Register" → Fill academic details
  4. On approval, download the unit-level dataset for your round
  5. Data comes as fixed-width .txt files with a separate layout document

Reading Fixed-Width NSS Data in Python

NSS unit-level files use fixed-width format (not CSV). You need the layout file to know which characters correspond to which variables.

import pandas as pd

# NSS 68th Round - Employment (Schedule 10) - Household Records
# The column widths come from the layout document
col_specs = [
    (0, 2),    # State code
    (2, 4),    # District code
    (4, 6),    # Sub-round
    (6, 8),    # NSS region
    (8, 10),   # Stratum
    (10, 14),  # PSU serial number
    (14, 16),  # Household serial number
    (16, 17),  # Sector (1=Rural, 2=Urban)
    # ... add remaining columns from layout document
]

col_names = ['state', 'district', 'subround', 'nss_region', 'stratum',
             'psu', 'hh_serial', 'sector']

df = pd.read_fwf("hh_r10.txt", colspecs=col_specs, names=col_names,
                 header=None, dtype=str)

# Filter rural households
rural = df[df['sector'] == '1']
print(f"Rural households in sample: {len(rural)}")
print(f"States covered: {rural['state'].nunique()}")

✏️ Practice Exercise

Exercise 2.4 — Calculate Unemployment Rate from PLFS

Goal: Find and interpret unemployment rates from the latest PLFS report.

Time needed: 15 minutes (using published report)

  1. Download the PLFS Annual Report 2022-23 from mospi.gov.in
  2. Open the PDF → Navigate to the state-wise tables
  3. Find the table: "Unemployment Rate (UR) — Usual Principal & Subsidiary Status (UPSS)"
  4. Note the UR for your home state — separately for Rural/Urban and Male/Female

Questions: - [ ] Is the unemployment rate higher in rural or urban areas of your state? - [ ] Is female unemployment higher or lower than male unemployment? - [ ] How does your state compare to the national average UR? - [ ] Which state has the highest and lowest unemployment rate in India?

  • Census of India — Workers classification (complementary to PLFS)
  • MGNREGA — Employment scheme data
  • NDAP — Composite district indicators including employment

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