Context:
β’ The Ministry of Statistics and Programme Implementation (MoSPI) has proposed a major revision to the Consumer Price Index (CPI) methodology, beginning February, to more accurately capture housing inflation, especially in rural India.
β’ The revamp will include monthly rent collection in both rural and urban areas, and exclude government/employer-provided housing from the housing index.
Key Highlights
- Inclusion of Rural Housing Inflation
- For the first time, rural housing inflation will be tracked monthly under CPI.
- Current system collects rent data only in urban areas, and only twice a year.
- Exclusion of Non-Market Housing
- Government and employer-provided housing will be removed from the housing index.
- Aim: reflect actual rental market transactions, not subsidised or proxy estimates.
- Weightage in Current CPI
- Housing has a weight of 21.67% in CPI-Urban and 10.07% in all-India CPI.
- Wider Sample Coverage
- New system involves monthly rental data from all selected dwellings, substantially expanding coverage.
Significance
- Why the Revision Matters
- Economists have long criticised the inclusion of government housing in CPI because rent was inferred using House Rent Allowance (HRA)βa poor proxy for real market rent.
- This change corrects a major distortion by focusing on actual market behaviour.
- Data Availability for Revision
- The Household Consumption Expenditure Survey (HCES) 2023β24 finally captured rural rental data, enabling MoSPI to build a rural housing index.
- Methodological Improvements
- IMF experts advised using a panel survey approach, converting six-month rent changes to one-month estimates to ensure consistency.
- New approach will improve statistical accuracy and reduce volatility.
- Transparency and Stakeholder Input
- MoSPI has invited feedback on the proposed changes until November 20, via email: pcdnso2020@mospi.gov.in.
- Broader Implications for Inflation Tracking
- Improved measurement will:
β’ Give a more realistic picture of rural cost-of-living trends
β’ Provide policymakers better tools for monetary policy
β’ Enhance understanding of housing stress in both regions
Mains Relevance
GS 3 β Economy
- Inflation measurement and reforms
- Data quality in economic governance
- Impact of housing inflation on consumption patterns
GS 2 β Governance
- Transparency in official statistics
- Institutional capacity for large-scale surveys
