UP's bottom-up model can show the way to measuring India's true economy

India’s economy recorded 7.8 per cent gross domestic product (GDP) growth in the first quarter of FY26, outpacing expectations and reinforcing the government’s optimism about the country’s growth trajectory. The headline numbers are based on currently available, measurable data and represent the best possible estimates within the existing system.  

Yet, we align with experts who caution that these headline figures may not fully reflect reality, as the informal or unincorporated sector —  employing more than 90 per cent of India’s workforce and contributing nearly half of GDP — remains inadequately measured. This gap risks overstating or understating economic strength and misguiding policy. To fix this, India must move from a top-down model of GDP estimation to a bottom-up approach that begins at the district level, where most unorganised sector activities take place. 

A truly bottom-up exercise would ideally build GDP estimates starting from the village level, but given the enormous complexity and resource requirements of such an approach, the most feasible starting point is the smallest administrative unit with structured data systems — the district. 

Bottom-up vs top-down: India currently follows a top-down method. National gross value added (GVA) is first estimated and then apportioned to states and districts. States use local data mainly for agriculture, while manufacturing and services are allocated using central indicators that often bear little relation to actual local output. Some states compile district GDP (GDDP), but this is again done by distributing state-level numbers rather than directly measuring district-level activity. While this provides timely estimates, it fails to capture ground realities. 

A bottom-up approach would instead build GDP directly from district-level data. Agriculture can be measured from local records, manufacturing from pooled Annual Survey of Industries samples, mining from e-way bills, and organised services from Ministry of Corporate Affairs (MCA) and goods and services tax data. Public sector value added can be apportioned from balance sheets and budgets of central and state undertakings. The most critical gap is the unincorporated sector, which can only be captured through dedicated surveys: 

1. Labour force survey (LFS): A district-representative survey, capturing unemployment rate, worker population ratio, labour force participation rate, and participation in unincorporated manufacturing and services. 

2. Survey of unincorporated sector enterprises (SUSE): Estimates value added per worker in informal enterprises, offering a granular view of their contribution. 

Together, industry-wise data on workers (from LFS) and value added per worker (from SUSE) would enable precise estimates of district-level GVA. Aggregating across districts would yield more reliable GSDP and, ultimately, a GDP that reflects India’s true economic structure. 

Lessons from Uttar Pradesh: Uttar Pradesh piloted this bottom-up model in four districts — Meerut, Varanasi, Gorakhpur, and Kanpur Nagar. The contrasts with top-down estimates were striking. Manufacturing output was nearly double under the bottom-up method, while services and trade, conversely, were often lower, reflecting how top-down methods overestimate in some districts. Overall GVA was 10.3 per cent higher than top-down estimates. These divergences highlight why states need their own measurement systems: The same proxies cannot represent Varanasi’s services economy, Gorakhpur’s manufacturing, and Meerut’s trade. 

Why health and education matter: Within services, health and education are especially important, yet they remain buried under “other services.” With a large private-sector presence, their contribution must be measured accurately, as higher investment in these sectors builds a skilled, healthier workforce that boosts productivity across the economy. Their value is both immediate and long-term. District surveys in UP showed how undercounted they have been: GVA in health and education was higher than top-down estimates by 13.6 per cent in Meerut, 9.5 per cent in Varanasi, and 6.7 per cent in Kanpur Nagar. Recognising these sectors as productive human capital formation, not just social spending, is critical to capturing the true growth story. 

Using new data to measure economic activity: To strengthen bottom-up GDP, we must encourage it to systematically integrate alternative data sources into national accounts. Administrative datasets such as the corporate identification number filings with the MCA can help refine estimates for registered companies. Similarly, goods and services tax network data, which captures monthly turnover across millions of establishments (including small firms otherwise invisible to surveys) can provide dynamic measures of output. At the same time, electricity consumption data from discoms can serve as a proxy for unincorporated manufacturing and service activity, especially in districts with high informal enterprise density. Linking these datasets with labour force surveys would not only reduce reliance on extrapolation but also ensure better measurement of GVA across sectors. Together, these innovations would significantly improve the credibility and granularity of GDP compilation. 

The way forward: The pilot survey in UP has now emerged as a robust proof of concept, and the state has rolled out bottom-up  district domestic product (DDP) surveys across all 75 districts. Building on this momentum, states like Assam, Maharashtra, and Madhya Pradesh have also decided to estimate GSDP using bottom-up DDP. We are sure that other states would adopt a similar approach, ensuring that economic planning is firmly grounded in the realities of where growth and livelihoods actually take place: Small firms, local services, and unincorporated enterprises that are often undercounted in conventional data systems. If all states were to institutionalise this process, India could, for the first time, build a truly representative GDP (aggregated from bottom-up DDP) that reflects the full depth and diversity of its economy. 

 

The authors are, respectively, former director  general, MoSPI, GoI, and distinguished fellow, Pahle India Foundation