Data upgrade: How to get an accurate picture of India’s MSME sector

We have two major sources of data on unincorporated MSMEs—those not registered as a company or a limited liability partnership. The first is the Annual Survey of Unincorporated Sector Enterprises (ASUSE) conducted by the National Sample Survey Office (NSSO). It covers non-agricultural, non-construction and unincorporated establishments. Before it became an annual exercise in 2021-22, this was conducted only in 2015-16 and 2011.

 The second source includes the two main administrative databases Udyam (for MSME registration) and the Goods and Services Tax Network (GSTN), which provide a count of registered units. But there is a glaring disconnect between these sources, resulting in misleading estimates of output, employment and formalization in the sector.

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ASUSE 2023-24 estimated about 77 million non-agricultural, non-construction unincorporated establishments. Of these, 99% reported turnover below ₹1 crore and only 0.4% had Udyam registration. But the Udyam dashboard lists 66.5 million registered MSMEs, the vast majority being micro-enterprises. Similarly, 2023-24 GSTN data shows 7 million taxpayers with an annual topline below ₹1 crore. Yet, the ASUSE finds under 1.2 million such GST-registered establishments. A mismatch this big isn’t explained by ASUSE’s coverage exclusions (i.e., companies, agriculture, construction) alone.

If we take ASUSE and administrative databases at face value, India may have 140 million enterprises, employing nearly 400 million workers, which, with 250 million added in agriculture, overshoots total employment estimates of about 600 million as per the KLEMS database. Plausibly, the ASUSE is under-capturing formalized unincorporated enterprises, especially those with GST or Udyam registrations. 

This omission has three major consequences: First, it leads to an underestimation of economic contribution. Enterprises with GST or Udyam registration tend to have higher turnover, more workers and formal labour. Missing them skews averages downward, reinforcing a narrative of extreme informality and low productivity. Second, it leads to policy misalignment, as schemes designed for credit access, digitalization or skill upgrading could be mis-targeted. Third, undercounting registered MSMEs, which often participate in export-oriented supply chains, distorts the understanding of India’s export base.

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The data gap may be due to a design issue. The unit of inquiry for ASUSE is ‘Establishment’ and not ‘Enterprise.’ So, it is possible that single enterprises with multiple establishments are counted separately. But for unincorporated businesses, most have only one location. Also, the ASUSE identifies establishments by listing households, potentially missing enterprises not clearly linked to households (like shops in commercial complexes). 

Further, respondents are given a cap of only three registrations to report. There are multiple ones beyond Udyam and GST, including state and city licences. Thus, if Udyam or GST are not among their top three, they go unrecorded. Respondents may not even recognize Udyam or GST as ‘registrations’ in the same way as local trade licences or transport permits. Thus, ASUSE may not be capturing the true pace of digital formalization.

Recall that the U. K. Sinha Committee of the Reserve Bank of India had highlighted MSME data deficiencies and called for a centralized database to integrate multiple administrative sources. It also called for granular segmentation and dynamic updates. We thus need an integration of GST, Udyam, EPFO, ESIC and export promotion databases for a better picture.

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A strengthened ASUSE can: First, use GST and Udyam databases for supplementary sampling to ensure proportional representation; second, allow the recording of all, not just three registrations; third, refine establishment identification to include the listing of commercial premises and not just household-linked enterprises; fourth, update the sampling weights more frequently; fifth, collect data on more financial and digital indicators, including on digital payment adoption, e-commerce activity and supply-chain linkages; and sixth, triangulate ASUSE data with other data sources and ensure that ASUSE turnover or investment bands align with the MSME Act. 

Lastly, the NSSO must publish anonymized unit-level data for independent verification and analysis.

The ASUSE is a rich source of data and can offer a realistic picture of MSME output as well as employment; it can help identify sub-segments with high growth and export potential; optimize credit guarantee, interest subvention and technology adoption schemes; track the economy’s formalization shift; and lastly, help tailor public policy to regional needs, since MSME characteristics vary sharply across states.

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Better data will help dispel the false dichotomy of administrative databases portraying rapidly formalizing MSMEs while ASUSE data depicts a stagnant and largely informal sector. Bridging this gap is essential not just for statistical accuracy, but to make MSMEs genuine engines of productivity growth and export competitiveness.

The author are, respectively, senior fellow, Pune International Centre and senior research fellow, deAsra Foundation.