Tracking migration is crucial for public policy as over 45 crore people migrated internally in India between 2000 and 2011 (2011 Census).
Since the next Census is delayed, alternative migration measurement methods are required.
The Economic Advisory Council to the PM (EAC-PM) proposes using train travel, banking, and telecom data to estimate migration trends.
Methods to Measure Migration
1. Unreserved Train Ticket Data
Indian Railways’ unreserved ticketing system helps track low-income labor migration.
Findings:
Gujarat: 13.8% of passengers arrived from U.P. and Bihar.
Bihar: 12.4% of passengers arrived from U.P..
Tamil Nadu: 8.4% of passengers arrived from Bihar.
2. Banking Data
Banking deposits indicate savings and migrant financial behavior.
District-wise mapping shows:
Bihar and U.P. have high migration and low savings.
Maharashtra and Gujarat have higher savings, indicating inflow of migrants.
3. Telecom Data
Visitor Location Registers (VLRs) track SIM card usage to infer migration patterns.
During COVID-19 lockdowns, VLR data showed reverse migration from metro cities to rural areas.
Charts show:
Mass exodus during lockdowns from Delhi, Mumbai, and Kolkata.
Gradual return of workers post-pandemic.
Key Findings
States like U.P., Bihar, and West Bengal are major source states for migration.
Maharashtra, Delhi, Gujarat, and Tamil Nadu are major destination states.
COVID-19 caused mass reverse migration, affecting economic activity in cities.
Telecom data offers real-time migration insights, while train and banking data provide long-term trends.
Policy Implications
Urban Planning: Better migration tracking can help cities plan housing, healthcare, and transport.
Welfare Policies: Migrant workers need portable benefits (e.g., ration, healthcare, social security).
Labor Market Adjustments: Understanding migration flows helps optimize employment policies in cities and villages.
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