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Source: The post is based on the article “The debate on data” published in “The Hindu” on 1st August 2023.
Syllabus: GS3 – Indian Economy and issues relating to planning, mobilization of resources, growth development and employment.
News: The author discusses concerns over India’s statistical system and the accuracy of its data. Once admired globally, the system’s reliability has declined. There are issues with data credibility, multiple agencies providing conflicting data, and delays in publishing essential data. The author emphasizes the need for an overhaul to provide credible data for better policymaking.
What are the major issues with India’s statistical system?
Major issues with India’s statistical system:
Data Credibility:
Surveys, like household ones, face credibility questions.
Concerns about samples selected and non-response from households.
EAC-PM paper says urban data isn’t captured well.
Conflicting Data Sources:
Different agencies give different numbers for the same indicators.
Example: Manufacturing data from the Ministry of Corporate Affairs’ MCA21 portal differs from the Annual Survey of Industries.
A 2019 report found 36% of MCA21 companies, used for GDP, were not traceable or classified properly.
System Competence:
Delays in conducting and publishing surveys.
Example: Processed data of completed surveys withheld, hindering assessments of poverty.
Macroeconomic data like wholesale price series and consumer price index are overdue for revisions.
Data Non-availability:
2021 Census yet to happen.
Policymakers use thin samples, like NITI Aayog’s 2023 index based on 6 lakh households, while India has over 30 crore households.
What should be done?
Improve Data Credibility:
Use realistic samples to reflect the transforming economy.
Re-examine definitions, like ‘urban’, to ensure accuracy.
Standardize Data Sources:
Address issues like the MCA21 portal’s glitches and inaccuracies.
Reduce conflicting data from different agencies.
Enhance System Competence:
Timely conduct and publication of surveys.
Revise outdated macroeconomic data series.
Transparent Data Dissemination:
Move beyond dashboards for clear data sharing.
Review Past Recommendations:
Revisit reports, like the Rangarajan Committee Report (2001), to assess and implement past suggestions.
