GDP Series Revised to Enhance Accuracy

2026 Revision of India's National Accounts: Key Changes and Implications

Overview

The Central Statistical Office (CSO) is set to launch a new GDP series on February 27, 2026, aimed at addressing key challenges in estimating economic data for India's complex economy. The revision seeks to improve estimation of the unorganised sector's contribution to GDP and eliminate discrepancies between the expenditure and output sides of GDP estimates.

Changes in 2015 Revision

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The 2015 revision of the GDP series introduced significant changes, including a shift in data collection from establishments to enterprises, a change in the calculation of value added from volume to value basis, and the use of indirect taxes to measure changes in value added. These changes had wide-ranging effects in manufacturing, trade, and services, leading to an upward revision of GDP growth numbers.

Expected Changes in 2026 Revision

The 2026 revision proposes two major reforms:

1. Elimination of Discrepancies: The CSO aims to eliminate discrepancies between the expenditure and output sides of GDP estimates by expanding the source database for output and incorporating new data sets such as the frame of active companies, Management & Administration related data (MGT-7/7A), and GST data.
2. Better Estimation of Unorganised Sector's Contribution: The CSO will use the Annual Survey on Unregistered Sector Enterprises (ASUSE) data to generate estimates of the unorganised sector's contribution to GDP annually, replacing the indicator-based extrapolation approach.

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Impact of Changes

The changes are expected to result in a shrinking of the size of the informal economy from 45% to 40%. Additionally, the elimination of discrepancies between the production and expenditure approaches in final GDP estimates is expected to improve the reliability of expenditure side estimation of GDP.

No Double Deflator

The National Statistical Office (NSO) proposes to continue with the single extrapolation/volume extrapolation method, citing data intensity as a reason for not adopting double deflation. In manufacturing, double deflation will continue to be used, while in other sectors, volume extrapolation will be explored instead of double deflation.