Prime Minister Narendra Modi’s call for district-level GDP estimates, made at the 11th Niti Aayog Governing Council meeting, was welcome. For too long, Indian economic policymaking has been driven by aggregates that obscure as much as they reveal.

But before enthusiasm outpaces architecture, one question must be settled: who produces these numbers, how and whose numbers count? The answer matters enormously. Getting it wrong could produce a statistical exercise that is politically convenient but economically hollow.

There are, broadly, two approaches to estimating district domestic product (DDP).

The first, and currently dominant, is top-down: start with the national or state GDP and allocate shares downward using proxy indicators like workforce size, electricity consumption or other indicators.

It is administratively straightforward, but measures nothing new—the numbers are, by construction, consistent with the national accounts from which they derive. No ground-level reality is observed.

The second is bottom-up: collect data directly from enterprises, workers and local records—surveys of unincorporated businesses and labour force data—and aggregate it upward to the district and then state total. This is harder, requiring investment in local statistical capacity and Centre-state coordination. But it actually measures something.

The distinction is significant. It determines whether district GDP tells us something true about India’s economy or merely reflects what we already assumed.

Evidence from Uttar Pradesh (UP): The most compelling argument for the bottom-up approach comes from a recent pilot study in four UP districts—Kanpur Nagar, Meerut, Varanasi and Gorakhpur—which applied a bottom-up methodology using data from the Annual Survey of Unincorporated Sector Enterprises and Labour Force Survey, and compared results against what the top-down method would have produced.

The findings are striking.

In unincorporated manufacturing alone, the top-down approach estimated combined gross value added (GVA) of ₹8.8 lakh for the four districts; the bottom-up survey found the actual figure to be ₹17.6 lakh—nearly double.

Since the pilot ran for a single month, seasonal variation could not be captured, so underestimation may be larger still. UP has since decided to extend the exercise to all 75 districts.

The findings reflect a structural failure of the top-down method to capture what is going on—particularly in the informal sectors, which accounts for nearly 50% of India’s GDP and 90% of its workforce. If half the economy is invisible to the measurement framework, we risk misleading inputs for policy formulation.

Consider India’s current statistical system. The National Statistical Office produces national GDP; state directorates of economics and statistics produce GSDP. The Centre also compiles comparable GSDP figures for inter-state benchmarking, but these stay internal, used by Niti Aayog and the Finance Commission. It is the state’s own estimate that is published.

This division is based on a sound principle: the closer the estimating agency is to economic activity, the more accurately it can observe it. DDP should follow the same logic, taking it one level further: estimates must be produced by state governments, built upward from district-level data, not downward from a national aggregate.

A concern often raised is that bottom-up district estimates may not reconcile perfectly with the state’s GSDP, which may itself diverge from the Centre’s number.

This is treated as a problem to avoid. It is not.

Several states already produce DDP estimates, largely top-down; the task is to shift progressively to a bottom-up approach that strengthens, rather than merely distributes, GSDP estimation. States and the Centre already live with divergent GSDP series without either invalidating the other; DDP should work the same way, with divergences signalling where methodologies miss ground-level activity.

District estimates that don’t add up perfectly to the GSDP should be seen as earnest, not a failure. Serious bottom-up DDP estimation requires district-level data infrastructure that most states currently lack: systematic surveys of informal enterprises, updated factory registration lists, GST-mapped location data and reliable labour force surveys.

The Centre can help fund capacity building and standardize survey methodology through the statistics ministry, but DDP should be the state’s job.

The Prime Minister’s ask is, in this sense, a prompt for a larger project: rebuilding subnational statistical capacity from the ground up—in both senses of the phrase.

District GDP, if used well, can transform how India thinks about regional development—identifying underperforming districts, flagging concentrated informality and holding states accountable for outcomes that averages conceal. The concentration is already stark: in Maharashtra, four districts account for over half the state’s GSDP; in Karnataka, Bengaluru alone contributes 38%.

Only around 100 of India’s 760-plus districts are estimated to contribute significantly to national output. Whether this is true or partly just a measurement artefact, we will not know until we measure properly.

Prime Minister Modi has asked the right question. The answer must be: let states lead, let data flow upward, and let’s resist the temptation to make district data add up to a number we already have.

The authors are, respectively, former director general, ministry of statistics, president, Centre of Data for Economic Decision-making (CoDED) and chief statistician, Pahle India Foundation (PIF); and head of CoDED and lead economist, PIF.

Prime Minister Narendra Modi’s call for district-level GDP estimates, made at the 11th Niti Aayog Governing Council meeting, was welcome. For too long, Indian economic policymaking has been driven by aggregates that obscure as much as they reveal.

But before enthusiasm outpaces architecture, one question must be settled: who produces these numbers, how and whose numbers count? The answer matters enormously. Getting it wrong could produce a statistical exercise that is politically convenient but economically hollow.

There are, broadly, two approaches to estimating district domestic product (DDP).

The first, and currently dominant, is top-down: start with the national or state GDP and allocate shares downward using proxy indicators like workforce size, electricity consumption or other indicators.

It is administratively straightforward, but measures nothing new—the numbers are, by construction, consistent with the national accounts from which they derive. No ground-level reality is observed.

The second is bottom-up: collect data directly from enterprises, workers and local records—surveys of unincorporated businesses and labour force data—and aggregate it upward to the district and then state total. This is harder, requiring investment in local statistical capacity and Centre-state coordination. But it actually measures something.

The distinction is significant. It determines whether district GDP tells us something true about India’s economy or merely reflects what we already assumed.

Evidence from Uttar Pradesh (UP): The most compelling argument for the bottom-up approach comes from a recent pilot study in four UP districts—Kanpur Nagar, Meerut, Varanasi and Gorakhpur—which applied a bottom-up methodology using data from the Annual Survey of Unincorporated Sector Enterprises and Labour Force Survey, and compared results against what the top-down method would have produced.

The findings are striking.

In unincorporated manufacturing alone, the top-down approach estimated combined gross value added (GVA) of ₹8.8 lakh for the four districts; the bottom-up survey found the actual figure to be ₹17.6 lakh—nearly double.

Since the pilot ran for a single month, seasonal variation could not be captured, so underestimation may be larger still. UP has since decided to extend the exercise to all 75 districts.

The findings reflect a structural failure of the top-down method to capture what is going on—particularly in the informal sectors, which accounts for nearly 50% of India’s GDP and 90% of its workforce. If half the economy is invisible to the measurement framework, we risk misleading inputs for policy formulation.

Consider India’s current statistical system. The National Statistical Office produces national GDP; state directorates of economics and statistics produce GSDP. The Centre also compiles comparable GSDP figures for inter-state benchmarking, but these stay internal, used by Niti Aayog and the Finance Commission. It is the state’s own estimate that is published.

This division is based on a sound principle: the closer the estimating agency is to economic activity, the more accurately it can observe it. DDP should follow the same logic, taking it one level further: estimates must be produced by state governments, built upward from district-level data, not downward from a national aggregate.

A concern often raised is that bottom-up district estimates may not reconcile perfectly with the state’s GSDP, which may itself diverge from the Centre’s number.

This is treated as a problem to avoid. It is not.

Several states already produce DDP estimates, largely top-down; the task is to shift progressively to a bottom-up approach that strengthens, rather than merely distributes, GSDP estimation. States and the Centre already live with divergent GSDP series without either invalidating the other; DDP should work the same way, with divergences signalling where methodologies miss ground-level activity.

District estimates that don’t add up perfectly to the GSDP should be seen as earnest, not a failure. Serious bottom-up DDP estimation requires district-level data infrastructure that most states currently lack: systematic surveys of informal enterprises, updated factory registration lists, GST-mapped location data and reliable labour force surveys.

The Centre can help fund capacity building and standardize survey methodology through the statistics ministry, but DDP should be the state’s job.

The Prime Minister’s ask is, in this sense, a prompt for a larger project: rebuilding subnational statistical capacity from the ground up—in both senses of the phrase.

District GDP, if used well, can transform how India thinks about regional development—identifying underperforming districts, flagging concentrated informality and holding states accountable for outcomes that averages conceal. The concentration is already stark: in Maharashtra, four districts account for over half the state’s GSDP; in Karnataka, Bengaluru alone contributes 38%.

Only around 100 of India’s 760-plus districts are estimated to contribute significantly to national output. Whether this is true or partly just a measurement artefact, we will not know until we measure properly.

Prime Minister Modi has asked the right question. The answer must be: let states lead, let data flow upward, and let’s resist the temptation to make district data add up to a number we already have.

The authors are, respectively, former director general, ministry of statistics, president, Centre of Data for Economic Decision-making (CoDED) and chief statistician, Pahle India Foundation (PIF); and head of CoDED and lead economist, PIF.