Pre-testing exercise held for new household income survey

The statistics ministry conducted a pre-testing exercise for the National Household Income Survey (NHIS), set to be launched in February 2026, to evaluate the clarity, comprehension and acceptability of the questionnaire.

Conducted in August across 15 regional offices covering six zones, including Mumbai, Delhi, Kolkata, Chennai, Bengaluru and Hyderabad, the exercise covered both urban and rural areas, representing affluent and non-affluent segments, the ministry of statistics and programme implementation said on Monday.

"It will be the first-ever pan-India survey focused on measuring household income, representing a significant step toward filling a long-standing data gap in India's socio-economic statistics system," the ministry said.


Based on the questionnaire prepared by MoSPI, the survey will capture income from salaried employment, casual labour and self-employment. It will also capture income from pensions, remittances from abroad, stipend, gratuity and income from assets and non-assets. Additionally, expenditure on food and non-food items will also be covered.

"Data from NHIS are used for rebasing consumer price index, in the preparation of national accounts and to analyse poverty and hardship in communities in countries across the world," the ministry said.

A technical expert group (TEG), chaired by Surjit S Bhalla, former executive director for India at the International Monetary Fund (IMF), has been established to oversee the survey. The ministry has invited feedback from researchers, policymakers and the public on the draft questionnaire and schedule of the survey.

Given the sensitive nature of information to be collected in the NHIS, the pre-testing report recommended awareness and confidence-building measures through wide publicity, especially in regional languages. It advised coordinating with resident welfare associations (RWAs) in urban areas, scheduling appointments at respondent's convenience, providing focused training and ensuring gender-balanced teams to facilitate collection of sensitive data related to household income.