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Comprehensive Reform of India's Statistical Ecosystem
The Ministry of Statistics and Programme Implementation (MoSPI) has initiated significant reforms to modernize India's statistical infrastructure, focusing on improving the granularity, accuracy, and timeliness of core economic indicators.
1.1. A New Framework for District Domestic Product (DDP)
MoSPI is set to overhaul the estimation of economic output at the district level to address long-standing data gaps.
• The Problem with Current Methods: At present, most DDP estimates rely on "top-down" allocation, where state-level GDP is distributed among districts based on outdated demographic indicators. This practice has been criticized for masking true inter-district economic disparities and yielding "near-identical growth rates for districts."
• The Proposed Solution: A Bottom-Up Model:
◦ Data Integration: Starting January 2025, MoSPI will integrate data from the Annual Survey of Unincorporated Sector Enterprises (ASUSE) and the Periodic Labour Force Survey (PLFS) to build a "bottom-up" DDP framework.
◦ Methodology: This approach aggregates district-level data upwards to form state and national accounts, reversing the current model. It provides a holistic measurement by combining ASUSE's data on enterprise activity in the vast unincorporated sector with PLFS's data on labor participation and earnings.
◦ Inclusion of Informal Sector: The new methodology ensures that the significant economic contributions of unincorporated enterprises and household-level activities are adequately represented.
• Significance and Objectives:
◦ An accurate DDP serves as a microeconomic counterpart to the Gross State Domestic Product (GSDP).
◦ It enables targeted policy interventions for lagging districts and supports evidence-based fiscal planning at the local level.
◦ This move aligns with India's federal structure and the government’s data-driven governance vision for Viksit Bharat @2047.
• Challenges: Implementation faces hurdles such as ensuring data reliability from the unincorporated sector, coordinating with states that have varying statistical capacities, and harmonizing datasets to avoid double-counting.
1.2. Methodological Overhaul of the CPI Housing Index
MoSPI has proposed key reforms for the housing index component of the Consumer Price Index (CPI) to make inflation measurement more accurate and representative. This is part of a broader revision of the CPI base year from 2012 to 2024.
• Current Limitations:
◦ Housing data is collected only biannually and is restricted to urban areas.
◦ The methodology includes employer-provided dwellings and uses House Rent Allowance (HRA) as a proxy, which critics argue distorts true market trends.
◦ Housing has a significant weight in the CPI basket: 10.07% at the all-India level and 21.67% for urban areas.
• Proposed Reforms:
◦ Frequency and Scope: Rent data will be collected monthly instead of every six months, with coverage expanded to include rural areas for the first time. The inclusion of rural rent data is made possible by the 2023-24 Household Consumption Expenditure Survey (HCES).
◦ Data Purity: Government and employer-provided accommodations will be excluded to ensure the index reflects only market-based transactions.
◦ Methodological Refinements: Following IMF recommendations, rent data will be collected from all selected dwellings every month, and the revised formula will ensure a "like-for-like" comparison to avoid downward bias.
• Impact: These changes are expected to align India's methodology with global best practices, enhance the accuracy of inflation assessment, and provide policymakers, including the RBI, with a more robust understanding of housing cost pressures.

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