The Missing Measure in India’s Growth Story

India’s economic debate often begins with a familiar question: which states are growing fastest? Governments announce ambitious gross state domestic product (GSDP) targets, investors compare state economies, and policymakers use per-capita income to assess regional progress. Yet a more fundamental question receives less attention: how much of this growth reflects genuine improvements in productivity, and how much comes from employing more people, investing more capital or changing the composition of economic activity?

An economy can expand without becoming substantially more efficient. A state can increase output by adding workers, factories and infrastructure, while another can produce more with the same resources through better technology, skills and management. Both may report growth, but their implications for wages, competitiveness and long-term prosperity are different.

India has begun examining this distinction. The challenge now is to ensure that the data used to evaluate state economies can explain it adequately.

GSDP measures the value of economic activity within a state’s boundaries. Productivity, by contrast, asks how much output is generated from the resources used to produce it.

Labour productivity is commonly measured as output per worker or per hour worked. Total factor productivity goes further, examining how efficiently labour and capital are combined, after accounting for changes in these inputs.

Consider two hypothetical states. State A expands manufacturing output by 10 percent after increasing employment and adding machinery. State B achieves the same output growth with much smaller increases in labour and capital. Their headline growth rates are identical, but State B may have recorded a larger improvement in productive efficiency.

A working paper by the Azim Premji University titled Growth, Employment, Productivity and Demographics in Indian States separates per-capita income growth into output per employed worker, employment relative to the working-age population, and the working-age population’s share of total population. Its analysis of 1994–2023 illustrates why demographic advantages and employment absorption must be distinguished from productivity performance.

The lesson is that state growth needs to be explained through several complementary measures rather than reduced to a single ranking.

India’s state domestic product estimates are compiled by state and Union Territory Directorates of Economics and Statistics, following guidance from the National Statistical Office under the Ministry of Statistics and Programme Implementation. Common definitions and broad methodological standards help maintain consistency, but state estimates also depend on the data available locally and the methods used to fill gaps.

The government has acknowledged the need to improve this process. In its explanation of GSDP estimation, the Ministry has identified greater use of direct estimation, reduced dependence on fixed ratios and proxy indicators, better use of state-specific economic data, and stronger methodological consistency as important improvements for the revised national accounts framework.

These changes are significant because a proxy is not the same as a direct observation. Where detailed information on economic activity is unavailable, statisticians may need to estimate output using related indicators, historical relationships or information allocated from broader datasets. Such methods can be necessary, but their limitations matter when estimates are used to compare states or evaluate policy performance.

Measurement Challenges

The problem is particularly important in economies with large informal sectors, numerous small enterprises and substantial differences in industrial structure. A formal factory’s accounts may provide relatively detailed information about its production and costs. A small household enterprise may be harder to observe with the same precision.

If the underlying information differs in coverage, timeliness or quality, apparent differences in economic performance can partly reflect differences in measurement. That makes transparency about their construction essential.

Last month, the Ministry released draft guidelines for compiling GSDP from the expenditure side using the proposed 2022–23 base year framework.

Expenditure-side estimates examine economic activity through components such as private final consumption expenditure, government final consumption expenditure, gross fixed capital formation, changes in inventories and net exports. They provide a complementary perspective to production-side estimates, which measure value added across industries.

The Ministry’s announcement identified an important gap: while some states and Union Territories compile estimates of government consumption and investment, none was then compiling private final consumption expenditure estimates. The draft seeks to establish a common framework, using state-specific data where feasible and suitable allocation methods where direct information is unavailable.

This gap matters for productivity analysis, although expenditure estimates cannot measure productivity by themselves. They help explain the demand supporting production and the relationship between investment and economic activity. Combined with employment, capital-stock and sectoral output data, they can help policymakers develop a more complete account of how state economies function.

For example, rising investment may expand a state’s productive capacity, but the economic return depends on whether new assets are used effectively. Similarly, higher household consumption may reflect stronger incomes, credit-financed spending or transfers.

The new expenditure-side framework should therefore be treated as an opportunity to connect different parts of the state economy, rather than as another statistical series to publish in isolation.

A more useful approach would evaluate state economies through four linked questions.

Key Indicators

First, is output rising faster than the resources used to produce it? State governments should track output per worker, and where credible data permit, output per hour worked. Worker counts alone cannot distinguish a person employed for a few hours from someone working full-time. Changes in working hours and the intensity of work can materially affect the interpretation.

Second, are workers moving into more productive activities? A shift from low-productivity agriculture to higher-value manufacturing or services can raise aggregate productivity even if productivity within individual sectors changes little. Conversely, employment growth concentrated in low-productivity activities can weaken the gains from expansion elsewhere. State-level analysis should separate improvements within sectors from changes in the distribution of workers across them.

Third, is investment translating into additional output? Capital expenditure is an input, not an outcome. Roads, industrial parks, electricity networks and logistics facilities may improve productive capacity, but their benefits depend on utilisation, connectivity and complementary investment. Tracking investment alongside subsequent output, employment and capacity utilisation would offer a stronger assessment than spending totals alone.

Fourth, are productivity gains reaching workers and households? Higher output per worker does not automatically mean higher wages. The gains may accrue to businesses, capital owners or particular high-value sectors. Real wages, earnings by employment type, labour-force participation and the distribution of employment across formal and informal activities should therefore accompany productivity measures.

These indicators would make it harder to confuse a rise in output with a rise in efficiency.

State-level indicators also conceal differences within state borders. District-level data can help reveal these differences, but only if definitions and collection methods are sufficiently consistent. Policymakers should not interpret small differences in estimated productivity as meaningful rankings without considering uncertainty, sectoral composition and the quality of underlying data.

The same caution applies to comparisons across years. Revisions to national accounts methods, changes in survey coverage and updated base years can alter historical estimates. Productivity comparisons should use consistent real-output measures and clearly disclose methodological breaks rather than joining incompatible series without adjustment.

A practical next step would be to publish state productivity accounts alongside existing GSDP releases. These could report output per worker, employment absorption, sectoral productivity, investment and capital utilisation, and household earnings, accompanied by methodological notes explaining data gaps and revisions. Where direct estimates are unavailable, the government should identify which indicators rely on proxies and how that affects comparability.

India does not need to abandon GSDP rankings or state growth targets. It needs to ask more of them. The statistical reforms now under way provide an opportunity to bring these perspectives closer together.

The central question for India’s states is no longer only how quickly their economies are growing. It is whether they can identify the sources of that growth and use that knowledge to make the next phase more productive.

(The writer is a bio-fintech consultant and columnist. Views personal.)