
Strengthening GDP Estimates with GST Data

One of the most significant changes recommended in the report is the expanded use of Goods and Services Tax (GST) data. GST, being a high-frequency administrative dataset with product codes and regional markers, will now play a central role in both annual and quarterly national accounts.
Unlike the 2011–12 series, where GST was used selectively, the 2022–23 series will leverage GST data for more accurate regional allocation of Gross Value Added (GVA) of private corporations. This will improve the estimation of Gross State Domestic Product (GSDP) by using actual outward supply data rather than proxy indicators.
GST data will also help identify active private corporations and corroborate annual estimates. Product-wise GST data will support the compilation of quarterly national accounts with greater precision.
Better Coverage of the Unincorporated Sector
The report highlights extensive use of results from the Annual Survey of Unincorporated Sector Enterprises (ASUSE) and the Periodic Labour Force Survey (PLFS). With regular data flow now available, the need for extrapolating base year benchmarks a common practice in the 2011–12 series has been eliminated.
This shift ensures more reliable estimates of GVA for household enterprises and quasi-corporations. The improved methodology strengthens the representation of India’s vast informal sector in national accounts.
Reforms in Financial Sector Estimation
In the financial sector, data from the Reserve Bank of India’s Statistical Tables Relating to Banks in India (STRBI) are now being used for nationalized and private banks. A key methodological improvement concerns Private Non-Banking Financial Companies (NBFCs).
Earlier, proxy-based loan growth estimates were applied to a sample of NBFCs. The new series replaces this approach with actual financial data sourced from the Ministry of Corporate Affairs database, leading to more robust GVA estimation.
Administrative funds of EPFO, CMPFO, and SMPFO have also been included under Financial Auxiliaries, expanding institutional coverage.
Agriculture, Fisheries and Livestock Updates
For agriculture, updated productivity rates from studies such as the fodder productivity research by IGFRI, Jhansi, have been incorporated. Revised rates for marine and inland fisheries, based on studies by CMFRI and CIFRI, have also been adopted.
Livestock sector estimates now utilize findings from the ADRTC study on feed and fodder assessment, improving the calculation of animal feed consumption and GVA.
Renewable energy generation and biogas production by households have been better captured using administrative records and the Household Consumption Expenditure Survey (HCES).
Improved Consumption and Capital Formation Estimates
The 2022–23 series adopts the COICOP-2018 classification for Private Final Consumption Expenditure (PFCE). Extensive use of HCES 2022–23 data ensures more accurate benchmark estimates.
Updated rates from specialized studies have refined PFCE estimates for dairy products and transport services. Vehicle registration data from the Ministry of Road Transport and Highways (VAHAN portal) are now used in estimating road transport services consumption.
For Gross Fixed Capital Formation (GFCF), the latest ASUSE and AIDIS data have been incorporated. Funds disbursed under MPLADS are being used annually instead of fixed base-year ratios, enabling dynamic asset-wise and industry-wise capital formation estimates.
Transparent and Consultative Approach
The release of this report follows earlier publications on methodological improvements and constant price estimates.
By incorporating administrative databases, updated surveys, and improved statistical techniques, MoSPI aims to align India’s national accounts with evolving economic realities and global standards. The upcoming GDP series with base year 2022–23 is expected to offer a more accurate reflection of structural shifts in the economy.
The reforms signal a decisive move toward data-driven policymaking and stronger statistical foundations for India’s growth narrative.
