Perils of statistical illusion

Santosh Kumar Mohapatra

Pic-OP

The National Statistics Office’s latest report for the July–September 2025 quarter has reignited a debate over what India’s economic data truly reveals. At first glance, the picture seems radiant. India recorded 8.2% real GDP growth— the highest in six quarters and well above the IMF’s 6.6% forecast. This comes after strong prints of 7.4% in January–March and 7.8% in April–June. Agriculture, manufacturing, services, and GST-driven consumption are all being showcased as engines of this impressive expansion. Even the drag from US retaliatory tariffs on Indian exports appears too small to scare the headline figure.

Yet underneath these glowing numbers lies a structural puzzle. Nominal GDP growth, which captures the economy’s expansion before adjusting for inflation, has been steadily eroding—from 10.7% early in 2025, to 8.8%, and further to 8.7% in the latest quarter. The shrinking gap between nominal and real GDP implies an abnormally low GDP deflator of just 0.5%. Such an unusually weak deflator inflates real GDP and makes growth appear stronger than many believe is realistic. This paradoxical coexistence of robust real growth and low nominal growth has been described as “Schrödinger’s Economics”—a term borrowed from Nobel laureate physicist Erwin Schrödinger. The term was coined by Washington Post columnist Matt O’Brien in a December 2018 article. The article used the phrase to describe the postmodern economic claims made by the Trump administration at the time, specifically the ability to deny whether something was real. In the economic context, it describes a situation or an economy in an uncertain state where contradictory indicators coexist—one indicator shows improvement, another shows deterioration.

Indian economy seems to be in a similarly contradictory state: Real GDP surges while nominal GDP slows; activity accelerates even as employment trails behind; growth looks dynamic while corporate revenues and tax collections reveal softness. The fiscal consequences are immediate. Lower nominal GDP distorts every fiscal calculation—deficits, expenditure ratios, tax projections—because nominal GDP is the denominator for all these metrics.

When the denominator weakens, the fi scal framework becomes unstable. The government’s own projections illustrate this volatility: the 2024–25 Budget projected 10.5% growth but delivered 9.7%. The 2025–26 projection of 10.1% is also set to fall short. Growth rates mean vastly different things depending on the size of the economy. One per cent rise in US GDP adds over $3051 billion; in China, $192.3 billion; in India, just $41.9 billion. India may soon be the world’s third-largest economy, but in terms of per capita income, India ranks below 135 countries. Without bridging this gap, headline growth will remain a feel-good statistic rather than a measure of widespread welfare.

What is disconcerting is that the IMF has assigned India a C-grade for its national accounts’ statistics, while awarding ing B-grade for prices, external statistics, government finances, and monetary and financial data. The C-grade indicates that although data exists, it suffers from deficiencies like an outdated 2011–12 base year used to calculate GDP and gross value added (GVA). Another major issue is India’s reliance on the Wholesale Price Index (WPI) as the GDP deflator, whereas the global standard is the Producer Price Index (PPI). More significantly, India continues to use single deflation, applying one deflator to both inputs and outputs, whereas global best practices recommend double deflation for more accurate measurement of real value-added, especially during price volatility. India also delays in publishing consolidated central and state fiscal data.

The largest blind spot lies in the informal sector, which makes up nearly half the economy. Current methods extrapolate informal sector trends from the formal sector—an approach that breaks down during disruptions such as demonetisation, GST rollout, or the pandemic, when informal activity diverges sharply.

Equally troubling are long-standing institutional delays. The population census—due in 2021—remains postponed, af fecting per-capita income, pover ty estimates, and labour market assessments. Household consumption expenditure data also remains outdated, forcing the CPI to rely on an obsolete 2011 12 consumption basket. These shortcomings somewhat hamper surveillance. A robust statistical foundation is essential not just for accurate measurement, but for credible policymaking, investor confidence, and inclusive growth.

The writer is an Odisha-based economist and columnist.

 

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