The Invisible Half of the Economy: Informality, Formalisation and the Credibility of India’s Growth Story….

Introduction: The Economy We Measure Is Not Always the Economy We Live In

India’s economic debate increasingly revolves around a paradox: the country can report relatively strong real GDP growth while a large part of the population experiences weak real wage and income growth. If the bottom half of households is seeing real wages rise by only around 1% annually, the question is not merely whether GDP is growing, but **where that growth is occurring, whom it is reaching, and how accurately the statistical system captures it**. India’s informal economy remains enormous even after years of formalisation through GST, digital payments, bank accounts, income-tax registration, social-security databases and corporate expansion. This creates a fundamental measurement problem. Formal-sector activity is easier to observe, while informal enterprises, casual workers, unpaid family labour, small traders and household businesses are inherently harder to measure. Consequently, the pace of formalisation is not simply a structural economic transformation; it also changes the statistical visibility of economic activity. A government with strong credibility, transparent methodology and confidence in independent data can make this transition more trustworthy. Conversely, when statistical revisions, base-year changes or methodological controversies coincide with political claims of exceptionally strong growth, doubts about comparability can become economically consequential.

 

The Elephant Outside the Spreadsheet

India’s informal economy cannot be treated as a small residual sector. It encompasses millions of unincorporated enterprises, agricultural workers, street vendors, household producers, construction workers, domestic workers, casual labourers and self-employed people. Employment remains substantially more informal than output measured through the organised corporate sector. This creates an important distinction between **formalisation of transactions and formalisation of livelihoods**. A small shop accepting digital payments or registering under GST has become more visible to the state, but that does not automatically mean that its workers have stable contracts, pensions, health insurance or rapidly rising real wages. Similarly, a worker receiving wages through a bank account is financially formalised without necessarily becoming economically secure. Therefore, headline indicators of formalisation can exaggerate the extent to which India's underlying employment structure has changed. Formalisation is real, but its depth must be distinguished from its administrative visibility.

 

Formalisation: Transformation or Better Visibility?

The strongest argument in favour of formalisation is that it can increase productivity, tax compliance, access to credit, digital transactions and social-security coverage. GST can bring businesses into a common tax system; digital payments can leave an electronic trail; corporate registration can improve access to finance; and payroll databases can make employment more measurable. But there is a statistical paradox: **the economy can appear to formalise partly because previously invisible transactions become visible**. If a transaction that was previously estimated indirectly is now recorded electronically, measured economic activity may increase even without an equivalent increase in physical production. That does not make the new statistics wrong; it means that comparisons across time become more complicated. The crucial question is whether measured growth represents additional production, improved measurement, a shift from informal to formal production, or some combination of all three.

 

GDP Can Grow While the Household Economy Feels Stuck

This distinction becomes particularly important when aggregate GDP growth is compared with real wages. Suppose GDP grows at 7–8% while real wages for the bottom half increase by only about 1%. The two statistics are not necessarily contradictory, because GDP measures production and income generated across the entire economy, whereas real wages measure the purchasing power of workers. Capital income, corporate profits, government expenditure, exports, high-income consumption and productivity improvements can raise aggregate GDP without generating proportionate wage growth. But persistent divergence is economically significant because households with lower incomes have a higher marginal propensity to consume. If their real purchasing power barely rises, mass consumption can become weaker even while investment, government spending or upper-income consumption supports headline GDP. The result can be an economy with impressive aggregate numbers but insufficient broad-based demand—a possible form of **demand recession beneath a GDP expansion**.

 

The Great Statistical Visibility Problem

The larger the informal economy, the greater the challenge of measuring economic performance accurately. Large corporations generate detailed accounts, tax records, financial statements and digital transactions. A tiny informal enterprise may have none of these. Statistical agencies therefore have to combine surveys, administrative information, benchmarks, assumptions and extrapolation. When the structure of the economy changes rapidly, old relationships used for estimation can become unreliable. Formalisation can consequently improve measurement while simultaneously disrupting historical comparability. A rise in recorded formal-sector activity may reflect genuine economic transformation, migration from informal to formal enterprises, improved reporting or changes in statistical coverage. The correct response is not to reject official statistics, but to demand **more transparent metadata, consistent time series, independent validation and explicit decomposition of measurement effects**.

 

Base Years, Deflators and the Politics of “Real” Growth

The problem becomes even more important when nominal GDP is converted into real GDP. Real GDP depends on price indices, weights, deflators and the structure of the base year. A change in the base year can legitimately improve measurement because consumption patterns, production structures and relative prices change. Yet it can also make comparisons with earlier estimates difficult. If the implicit GDP deflator changes substantially, the same nominal economy can produce a very different estimate of real output. Therefore, saying that India grew faster after a statistical revision requires more than comparing two headline growth rates. One must examine whether the difference arises from actual production, prices, sectoral weights, informal-sector estimation, methodological improvements or base-year effects. **Real growth is a statistical construction designed to approximate physical economic expansion; it is not a directly observed object.**

 

The Internet Revolution Changes the Meaning of Formalisation

India is entering a remarkable statistical era because digitalisation can potentially reduce the traditional invisibility of the informal economy. Unified payments, digital invoices, electronic tax records, bank transactions, corporate databases and online commerce can provide enormous quantities of economic information. In principle, India could move from periodically surveying a partly invisible economy toward continuously observing large portions of economic activity. But more data does not automatically mean better statistics. Digital transactions measure transactions, not necessarily production; bank accounts do not measure welfare; GST records do not measure every informal worker; and online activity can disproportionately represent more connected firms and households. The statistical opportunity is therefore enormous, but it requires sophisticated integration rather than simply counting digital footprints.

 

Credibility Is Itself an Economic Variable

Government credibility matters because economic statistics influence expectations. Businesses make investment decisions, households decide whether to save or consume, investors price assets, and international institutions assess economic performance using official data. If people believe that statistical institutions are technically independent, transparent and willing to publish inconvenient information, official numbers acquire greater credibility. If they believe that methodologies are being changed primarily to produce favourable narratives, even accurate statistics may be discounted. This is particularly important in an internet-driven information environment where alternative calculations, leaked datasets and competing interpretations circulate instantly. **Statistical credibility is therefore not merely an academic issue; it is part of economic policy credibility.**

 

Leadership Should Be Judged by the Questions It Encourages

The quality of economic leadership should not be assessed solely by the GDP growth rate. A credible leadership framework should ask whether productivity is rising, whether labour incomes are increasing, whether private investment is broadening, whether employment is becoming more productive, whether household savings are strengthening and whether consumption is spreading beyond affluent groups. If the bottom half of households experiences only approximately 1% real wage growth, the policy response should not simply celebrate aggregate GDP. It should investigate why productivity gains are not translating into wages. Is the problem weak labour demand, excess labour supply, inadequate skills, technological substitution, weak bargaining power, insufficient manufacturing expansion, regional inequality or high food and housing costs? The credibility of a regime ultimately depends on whether it is willing to confront these uncomfortable questions rather than allowing aggregate indicators to substitute for economic welfare.

 

From “Fast Growth” to “Broad Growth”

India's next statistical and policy challenge is therefore to distinguish **growth of the measured economy from improvement in the economic lives of citizens**. Formalisation is desirable because it can increase productivity and protection, but it should not become synonymous with development. A formal job paying stagnant real wages is not automatically better development than a rapidly growing informal livelihood, while a digitally recorded transaction is not equivalent to increased productive capacity. The ideal transformation would simultaneously increase formal employment, productivity, real wages, household financial savings, private investment and mass consumption. Such a transformation would make the economy not only easier to measure but also materially stronger.

 

Conclusion: The Test Is Not Whether GDP Is Rising, but Whether the Economy Is Becoming More Visible and More Prosperous

India's informal economy presents both a measurement challenge and a development opportunity. Formalisation can improve productivity, taxation, financial access and statistical coverage, but it can also create breaks in historical comparability because a newly visible economy is not necessarily a newly created economy. This is why GDP, real wages, employment, productivity and household consumption must be examined together. If aggregate growth remains high while real wages for the bottom half rise by only about 1%, the possibility of weak mass demand deserves serious attention even when the economy is technically expanding. In the internet age, India has an unprecedented opportunity to build a more granular, timely and transparent statistical system. But technology alone cannot create credibility. **Credibility comes when leadership allows statistics to measure reality rather than requiring reality to conform to a growth narrative.** The strongest economic regime would therefore be one that welcomes scrutiny, publishes comparable data, explains methodological changes openly and treats rising real incomes and productivity—not GDP alone—as the ultimate evidence of successful development.