IMF gives ‘C’ grade for India’s national accounts statistics

WHY IS THIS IN NEWS?

• IMF’s Article IV Consultation (2025) assessed India’s national accounts and gave a Grade ‘C’ for the quality of GDP data.
• Grade ‘C’ = “shortcomings that hamper surveillance” → second-lowest level.
• IMF highlighted:
  • Periodic sizeable discrepancies between production and expenditure GDP estimates.
  • Use of an outdated base year (2011–12).
  • Over-reliance on Wholesale Price Index (WPI) for deflating nominal values.
  • Need to expand expenditure-side data and informal sector coverage.
• Assessment is significant because India is expected to release Q2 FY2025–26 GDP numbers, and concerns affect global investor confidence.

Relevance

GS3 – Economy / Growth Measurement
• Quality of GDP estimation under MOSPI/NSO scrutiny.
• Discrepancies between production vs expenditure GDP.
• Outdated base year (2011–12) and need for rebasing.
• Deflator issues (WPI–CPI divergence).
• Statistical system reforms: MCA-21 data, GSTN integration.

GS2 – Governance / Institutions
• Role of IMF’s Article IV surveillance.
• Credibility of official statistics as a governance issue.
• Transparency norms and reforms in data architecture.
• Centre–State coordination for data collection (industries, services, informal sector).
• Strengthening statistical autonomy & capacity.

HOW GDP IS MEASURED ?

Three Approaches

1. Production Approach (GVA method)
   1. Sum of value added by agriculture, industry, and services.
2. Income Approach
   1. Sum of wages, profits, rents, and mixed income.
3. Expenditure Approach
   1. GDP = C + I + G + (X – M).
   2. Should converge with production-side figures.

Ideal Condition

• All three approaches should produce near-identical results.
• Persistent divergence = data quality problem, structural inconsistencies.

WHAT EXACTLY IMF FLAGGED ?

A. “Sizeable Discrepancies” Between GDP Approaches

• Large, recurrent differences between:
  • Production-side GDP (GVA-based)
  • Expenditure-side GDP (C+I+G+X−M)
• Economists flagged this over the past 5 years:
  • Private consumption growth often inconsistent with household survey indicators.
  • Investment (GFCF) estimates occasionally contradict credit data & corporate filings.
• IMF classifies this as a methodological weakness affecting reliability.

B. Base Year Too Old (2011–12)

• Structural shifts in 13 years:
  • Digitisation, GST rollout, UPI-led formalisation.
  • E-commerce, gig economy, platform work.
  • Deflation of manufacturing due to global price changes.
• Outdated base year → wrong weights → distorted GDP.

C. Over-Reliance on Wholesale Price Indices

• WPI used to deflate:
  • Manufacturing GVA,
  • Nominal capital formation,
  • Some components of GFCF and inventories.
• Issues:
  • WPI excludes services (57% of GDP).
  • Highly sensitive to commodities, making real GDP volatile and inaccurate.
  • CPI-based deflators are more reflective of consumer reality.

D. Limited Expenditure-Side Data

• India primarily uses Income Approach for GDP.
• Expenditure estimates (C, I, G, NX) rely on:
  • Sparse household surveys,
  • Small-sample enterprise surveys,
  • Rough extrapolations.
• IMF wants expenditure-side to be strengthened and independently robust.

E. Informal Sector Under-Coverage

• Informal sector = ~45–50% of employment (varies by survey).
• GDP estimation largely model-based:
  • Uses outdated NSS data.
  • Limited real-time surveys post-2011–12.
• IMF says this reduces reliability and timeliness.

IMF’s GRADING SYSTEM

Grade	Meaning
A	High-quality data; internationally comparable
B	Broadly adequate; minor weaknesses
C	Shortcomings hamper surveillance (India gets this for National Accounts)
D	Severe deficiencies

India’s Overall Score

• Overall: Grade B (across all data categories)
• National Accounts: Grade C → primary area of weakness.

IMPLICATIONS OF THE ‘C’ GRADE

A. Policy-Making Impact

• If GDP reliability is weak:
  • Monetary policy signals (RBI) become less precise.
  • Fiscal policy targeting becomes less credible.

B. Investor Confidence

• Foreign investors use GDP data for:
  • Valuation of Indian markets,
  • Assessment of macro stability,
  • Pre-investment risk modelling.
• ‘C’ grade may raise caution, particularly among sovereign funds.

C. International Comparability Issues

• Difficulty comparing India with:
  • OECD economies,
  • Asian peers (Indonesia, Vietnam, Philippines),
  • China (despite opacity).

D. Domestic Credibility

• Economists have long critiqued:
  • Back-series revisions,
  • Post-2017 manufacturing volatility,
  • Divergence between GDP and ground-level indicators (PLFS, ASI, credit data).

GOVERNMENT’S POSITION

• India argues:
  • GVA-based method is robust and widely used.
  • Discrepancies normal in developing economies with large informal sectors.
  • Revised base year planned after new household surveys (2022–23, 2023–24).
  • Transition to supply-use tables (SUTs) is ongoing.

STRUCTURAL CAUSES OF GDP DISCREPANCIES

A. Informal Sector Dominance

• Difficult to track productivity and incomes in real time.

B. Data Gaps

• Large gaps in:
  • Household consumption,
  • Unincorporated enterprises,
  • Self-employment earnings,
  • Small manufacturing units.

C. Outdated Surveys

• Key datasets:
  • NSS 2011–12 consumption survey,
  • Unincorporated enterprise surveys,
  • ASI and IIP with limited representativeness.

D. Weak Price Deflation Mechanism

• Correct deflation = accurate real GDP.
• WPI-based deflation induces errors.

REFORMS IMF EXPECTS

• Update base year to 2017–18 or 2020–21 (debate ongoing).
• Increase frequency of:
  • Household consumption surveys,
  • Enterprise surveys,
  • Service sector surveys.
• Expand use of:
  • GST data,
  • Corporate filings (MCA-21),
  • Digital payments data.
• Strengthen expenditure-side GDP with more granular monthly/quarterly data.

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