The debate over economic data

Source: The post  “The debate over economic data’’ has been created, based on “The debate over economic data” published in “BusinessLine” on 06th January 2026.

UPSC Syllabus: GS Paper-3- Indian Economy

Context: The debate over India’s GDP and employment data has intensified following methodological changes such as the 2011–12 base revision and the adoption of higher-frequency surveys. While criticisms have grown louder, many fail to account for the complexity of economic measurement in a large, diverse, and rapidly transforming economy.

Nature of Criticisms of India’s Economic Data

1. Critics of India’s national accounts fall into four broad categories based on the nature of their objections.
2. The first category resists methodological change due to concerns over loss of familiarity and historical comparability.
3. The second category selectively uses data to support preconceived narratives about economic performance.
4. The third category alleges systematic bias and imputes political motives to statistical agencies.
5. The fourth category recognises measurement challenges and offers feasible and constructive suggestions.
6. Only the fourth category of criticism contributes meaningfully to improving data quality.

Status Quo Bias and Resistance to Change

1. Resistance to methodological change often arises from professional comfort with older systems.
2. Economic evolution makes periodic updates in statistical methods unavoidable.
3. India’s shift to the UN System of National Accounts 2008 required moving from factory-based to enterprise-based measurement.
4. This involved replacing a limited RBI firm sample with the much broader MCA-21 database.
5. Although concerns were raised about dummy firms, statutory filings and data cleaning improved the database over time.
6. A small and unrepresentative sample cannot capture the realities of an economy with millions of active firms.

Changes in Employment and Consumption Measurement

1. The transition from five-yearly employment surveys to the quarterly Periodic Labour Force Survey was criticised for reducing depth.
2. However, higher-frequency labour data is essential for timely macroeconomic decision-making.
3. Over time, the PLFS has allowed more detailed analysis and proved more reliable than private estimates.
4. Similar criticism followed improvements in consumer expenditure surveys due to reduced backward comparability.
5. Repeated surveys were conducted to verify and benchmark results, improving reliability.

Selective Use of Data and Misinterpretation

1. GDP measurement is inherently complex, especially in a heterogeneous economy like India.
2. Data limitations are often highlighted selectively when growth exceeds forecasts.
3. Factors that may cause overestimation in one period can cause underestimation in another, but only the former is emphasised.
4. Forecast models cannot replace comprehensive national accounting exercises.

Technical Critiques and Their Limitations

1. The absence of double deflation was criticised for overstating growth when WPI inflation was below CPI inflation.
2. During 2021 and 2022, WPI inflation exceeded CPI inflation, implying growth was underestimated.
3. The slowdown in credit growth during the 2010s was used to question GDP estimates without accounting for rising NPAs.
4. Structural shifts from corporate to retail credit were also ignored.
5. Positive discrepancies in expenditure estimates were highlighted while negative discrepancies were overlooked.

GDP, GVA, and Deflator-Based Arguments

1. High net taxes in Q3 FY24 were cited to argue that GDP growth was inflated relative to GVA growth.
2. In subsequent quarters, net taxes declined while both GDP and GVA growth remained strong.
3. Critics later attributed high real growth to low deflators, suggesting inflation was underestimated.
4. If inflation were indeed underestimated, nominal GDP growth would have appeared weaker, which did not occur.
5. The IMF’s grading weakened overestimation claims, as inflation measurement received a higher score.

Informal Sector and Discrepancies

1. Concerns were raised that informal sector output is overstated using formal sector ratios.
2. Since 2011–12, labour skill-weighted estimates have replaced uniform productivity assumptions.
3. The production approach remains the controlling estimate, while expenditure estimates act as cross-checks.
4. Commodity flow methods capture informal sector consumption.
5. Persistent negative discrepancies indicate possible underestimation rather than overestimation of output.

Ongoing Reforms and Improvements

1. Constructive criticisms have led to ongoing reforms in data compilation.
2. These include rebasing GDP to a more recent year and expanding survey frequency.
3. Double deflation is being introduced where disaggregated price indices are available.
4. Regular ASUSE surveys will replace proxy-based estimates in services.
5. Reform proposals are communicated transparently and stakeholder feedback is encouraged.

Way Forward

1. India should ensure timely and regular rebasing of national accounts to reflect structural changes in the economy.
2. The coverage, frequency, and integration of surveys should be expanded to improve real-time economic assessment.
3. Greater use of administrative and big data sources should be made while ensuring data quality and privacy safeguards.
4. Capacity building within statistical institutions should be prioritised to handle complex estimation challenges.
5. Methodological changes and revisions should be communicated clearly to improve public understanding and trust.
6. Independent peer review mechanisms should be strengthened to enhance credibility without politicising statistics.
7. Constructive engagement with international institutions should continue while contextual challenges of emerging economies are recognised.

Conclusion

India’s economic data systems are evolving to match the scale and complexity of its economy. While methodological improvements may reduce comparability in the short term, they enhance accuracy and relevance over time. Strengthening statistical credibility requires technical refinement and institutional support, not selective criticism or politicisation.

Question: India’s GDP measurement faces challenges due to the size and heterogeneity of its economy. Analyse the measures adopted to improve accuracy and reliability.

Source: The Businessline