Relevance: GS-3 (Indian Economy); Source: The Hindu

India’s recent high GDP growth (Q2FY26: 8.2%) has revived debate on whether headline numbers truly reflect quality, inclusiveness and sustainability of growth. IMF’s “C-grade” comment on India’s Data Adequacy highlights deeper structural issues.

Why GDP Alone Is Not Enough

  • Data Quality Concerns: IMF notes frictions in India’s National Accounts, especially the underestimation of the informal sector (≈90% of workforce).
  • Employment Paradox: Despite growth, formal-sector jobs remain inadequate. Only 46% of the workforce is formally engaged; sectoral job growth was just 3.5% in Q2FY26.
  • Environmental Unsustainability: India hosts 45 of the world’s 50 most polluted cities (IQAir). Delhi’s AQI > 400 implies that high GDP is coexisting with worsening air quality, water scarcity, and groundwater contamination.

Key Structural Issues Highlighted

1. Skewed Growth Pattern

  • Expansion is in informal, low-productivity sectors, not in high-skill manufacturing.
  • Lack of urban job creation pushes people back into agriculture → disguised unemployment persists.

2. Need for Better Data Infrastructure

  • IMF stresses upgrading the GDP base year and improving high-frequency indicators, especially for informal economic activity.
  • Better data also enhances policy credibility and investor confidence.

3. Green Growth Deficit

  • India’s polluted cities and degraded water systems contradict sustainability goals.
  • Clean energy, circular economy, and municipal reforms must become central to growth planning.

The Way Forward 

  • Shift from quantity to quality of growth: focus on productive formal-sector jobs, skilling, ease of doing business, and labor market reforms.
  • Environmental mainstreaming: adopt coordinated action on crop residue management, public transport, industrial emissions.
  • Fiscal priorities: Increase spending on public health, climate adaptation, and statistical capacity.
  • Institutional strengthening: independent environmental monitoring, transparent economic datasets.

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