Context

• Recently, a member of the PM’s Economic Advisory Council argued that national surveys are based on unsound frameworks and systematically underestimate India’s development.
• The article invited criticism but amid this debate on India’s Statistical System there are some important points that warrant attention.

 Arguments by the Member of PM’s EAM: Over Dependency on Surveys of Households

• In India, policymakers typically rely on the estimates of sample surveys of households to assess previous policies or to frame new policies.
• For example, the National Sample Survey (NSS) of households has been conducted to determine the household consumption expenditure, including services or durables, or
  • to provide estimates of persons with disabilities, or
  • to provide estimates of expenditure related to domestic tourism, or
  • to provide estimates related to drinking water, hygiene, conditions of the house, etc.
• For health, policymakers rely on the National Family Health Survey (NFHS) and the Periodic Labour Force Survey (PLFS) for questions related to employment and unemployment.
• But there is concern over non-frequent nature of some of these surveys (in particular, the household consumption expenditure survey).
• There is a constant demand for increasing frequency and size of surveys and there is practically a consensus on the robustness and the representativeness of the survey methodology.
• Along with it there have been virtually no concerns or studies on these surveys’ data quality.

Issues Highlighted by the Member of PM’s EAM

• Data quality related to NSS, NFHS, and PLFS needs a major sampling overhaul to reflect the true status of India’s real economy.
  • These surveys use outdated sampling frames and hence, are not representative. In fact, the survey mechanisms are archaic and not adapted for rapid changes.
  • As a consequence, these surveys grossly and systematically underestimate India’s progress and development and the misleading estimates from these surveys impede policy-making.
• Framing policies based on these estimates are unlikely to yield the desired results and we will continue to see a gap between ground realities and survey estimates
• Using projected population estimates, it is found that nearly all major surveys in India that were conducted post-2011 and used the Census 2011 for the sampling have overestimated the proportion of the rural population significantly.
• Overestimation is one of the several problems with data quality, but it is a critical concern and appropriately highlights the problem at hand.

Response to the Arguments Raised Member of PM’s EAM

• There are 2 main points of criticism in the member of PM’s EAM analysis of data quality.
• The first and most important is that all of them seriously overestimate the rural population of the country, and thereby underestimate the urban.
• Therefore, if the levels and the rates of progress of these various indicators are better in urban areas than in rural then the national averages will always be lower in the estimates as compared to the ground reality.
• This is true; however, it crucially rests on whether there is a systematic overestimation of the rural population by these surveys or not.
• The member’s criticism demonstrates that this is indeed the case by comparing the estimates of rural population from the surveys with those from the Census projections and showing that the discrepancy can be as high as 5 percentage points, which is substantial.
• But the point is the comparison is not being carried out among equals.

Important Points Amidst This Debate on India’s Statistical System

• Acceptance of the Existing Problems in the Statistical System
  • First, India should recognise that there is a problem in the statistical system that needs to be fixed. Defending the statistical system is no solution at all.
  • The National Statistical Office (NSO) has been collecting data primarily through administrative and sample surveys, both of which have their own strengths and challenges.
  • The data collection from administrative sources is economical and less time-consuming, but has several challenges in terms of representativeness.
  • Sample surveys are costlier, both in terms of money and time.
  • The updation of the Census used for most surveys needs to be digitised dynamically and made accessible to improve the quality of surveys and reduce bias in the estimates.
  • Geospatial technologies and crowd-sourced data platforms now permit such dynamic updation.
• Need for Expansion of Resources Base of Data
  • The national statistical system needs to expand and diversify its resource base of data — it should include new and emerging sources like Big Data leverage processing through machine learning and artificial intelligence.
  • The efforts by the NSO for developing “standards” and “methodologies” for data validation of these new datasets are going to be extremely important, so they supplement conventional data sources.
  • The UN Statistics Division has come up with guidelines for using Big Data for official purposes.
  • The NSO needs to work closely with multilateral and regional agencies for enhancing the capacity of the statistical system for the use of such data available from alternative sources.
• Enhance the Capacities of State Statistical Systems 
  • The strength of the national system is integrally dependent on the strength of the state statistical systems.
  • In this direction, the Dholakia Committee Report 2020 on sub-national accounts is crucial; it could pave the way for state governments in pursuing and adopting a bottom-up approach, thereby strengthening the data collection capacities of the state governments.
  • Several states are yet to initiate building institutional frameworks at the state and district levels.
  • The Ministry of Statistics and Programme Implementation (MoSPI) launched the India Statistical Strengthening Project with financial support from the World Bank for enhancing the capacities of state statistical systems for data collection.
• Learn from the experience of Improving Weather Predictions
  • A few decades ago, the weather forecast used to be the subject of various jokes.
  • The Ministry of Earth Sciences established the National Centre for Medium Range Weather Forecasting in 1988 and used India’s first supercomputer to develop and evolve advanced numerical models for weather forecasting.
  • The commitment to the upgradation of observation systems has made the biggest contribution in enhancing predictability, along with an improvement in the capacity of human resources for complex data collection and the development of IT infrastructure.
• Need for the Sustained Growth in the Resources Available
  • Economic growth occurs when there is a sustained expansion in the production possibility frontier and this happens when we develop better technologies; improve the quality of labour through education, on-the-job training, etc.
  • In the same analogy, there needs to be sustained growth in the resources available to the national statistical system for it to improve and this needs to be seen as an investment to ensure that India achieves the target of becoming a $5 trillion economy.

Way Forward

• Parallel Efforts on Both National and State Level
  • To enhance and institutionalise inter-agency coordination covering both national and sub-national statistical systems.
  • Madhya Pradesh has taken the lead by establishing a permanent state statistical commission for improving and integrating the statistical data flow systems.
• Finalise National Policy on Official Statistics Quickly
  • To catalyse and synergise these efforts, the National Policy on Official Statistics, announced in the Budget 2020 needs to be finalised quickly along with appropriate institutional support and resources.
  • This will ensure that we are able to track India’s progress on the Sustainable Development Goals using a bottom-up approach and also ensure that no one is left behind.
• Emphasis on Data Quality: A large part of statistical reforms should not merely focus on the availability, frequency and largeness of data, but greater emphasis should be placed on data quality.

Conclusion

• The Indian economy has been incredibly dynamic in the last 30 years with significant policy reforms and subsequent major breaks in the long-term structural growth path.
• Therefore, fast-tracking reforms and investment in the national statistical system in a mission mode is the need of the hour and cannot be delayed if India wants to play an active role once again in the international statistical fraternity.