Despite decades of policy focus, India's manufacturing share of GDP has remained largely stagnant. Critically examine the statistical and structural reasons behind this.

National Accounts place manufacturing gross value added at about ₹38.6 lakh crore, roughly 14.7% of GDP in 2023-24 [1] — far short of the 25% target set under Make in India [4]. The stagnation is genuine, but the measured extent of it is itself contested.

Statistical reasons

• Split measurement frames: manufacturing is estimated in two halves — the organised factory sector through the Annual Survey of Industries (units with 10+ workers with power, 20+ without) [2], and the informal sector through the Annual Survey of Unincorporated Sector Enterprises (ASUSE), launched in 2021 [3]. Blending two different sampling universes creates reconciliation gaps.
• Alternative estimates diverge: an ASI+ASUSE build-up yields a lower aggregate than the NAS figure, suggesting the official share may be overstated rather than merely flat.
• Sample versus universe data: informal-sector GVA rests on an annual sample survey with reference-period and non-response limitations [3], unlike near-census factory returns.
• Dated base year (2011-12) and unresolved back-series debates weaken comparability across decades.
• Formalisation effects: GST and EPFO-driven migration of units from unorganised to organised registers can read as growth without new output.

Structural reasons

• Services-led growth path: India skipped the labour-intensive manufacturing phase, a case of premature deindustrialisation.
• Persistent informality and small scale: manufacturing contributes only about a fifth of unincorporated-sector GVA [3], where units are tiny and low-productivity, limiting economies of scale.
• Capital-deepening without jobs: organised-sector GVA growth (11.89% in current prices, 2023-24) [2] has not translated into proportionate employment.
• Incentive design limits: PLI's ₹1.97 lakh crore outlay across 14 sectors [4] has concentrated in assembly-heavy electronics, with shallow domestic value addition.

Thus a measurement gap explains part, but not all, of the plateau. Reconciling ASI and ASUSE frames, expediting base-year revision, and simultaneously deepening domestic value chains, logistics and skilling can make both the data and the sector credible — converting statistical clarity into genuine industrial transformation.