HomeNews ReportsIndia plans first national household income survey in 2026, MoSPI sets up expert Panel

India plans first national household income survey in 2026, MoSPI sets up expert Panel

The survey aims to generate India’s first official dataset on household income disparities, crucial for welfare schemes and tax policies by evaluating how digital adoption influences wages and household earnings.

In a landmark move to address critical data gaps, The Ministry of Statistics and Programme Implementation (MoSPI) constituted a eight member Technical Expert Group (TEG) to conduct India’s first comprehensive nationwide Household Income Survey in 2026. Dr. Surjit S. Bhalla, former Executive Director for India at the International Monetary Fund will chair the group. MoSPI announced the initiative on Monday, June 23, marking a significant step toward evidence-based policymaking.

Expert leadership and panel Composition

Apart from Dr. Bhalla, TEG team includes

•⁠ ⁠Aloke Kar, Former Professor, Indian Statistical Institute, Kolkata
•⁠ ⁠Prof. Sonalde Desai, National Council of Applied Economic Research
•⁠ Prof Praveen Jha, Jawaharlal Nehru University
•⁠ Dr. Tirthankar Patnaik⁠, Chief Economist, National Stock Exchange
•⁠ ⁠Prof. Ram Singh, Director, Delhi School of Economics
•⁠ ⁠Among other economists and statisticians .

If necessary the panel will also include special invitees. It will draw on global best practices from countries like Australia, the U.S., Canada, and South Africa to design robust methodologies. It will also guide the sample design, finalisation of survey results and their public release.

Objectives and scope

The survey aims to generate India’s first official dataset on household income disparities, crucial for welfare schemes and tax policies by evaluating how digital adoption influences wages and household earnings, reflecting India’s evolving economic structure. Past attempts (1955–1984) failed due to unreliable income data, where reported incomes were paradoxically lower than consumption and savings combined. The TEG will address these issues through advanced sampling and estimation techniques.

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