Context

As official statistics is a public good, giving information about the state of the economy and success of governance, it needs to be independent to be impartial.

GDP calculation and its significance

• What is GDP:
  • Assigning a value to products and services: In effect, it adds apples and oranges, tractors and sickles, trade, transport, storage and communication, real estate, banking and government services through the mechanism of value.
  • GDP covers all productive activity for producing goods and services, without duplication.
  • The System of National Accounting (SNA): It is designed to measure production, consumption, and accumulation of income and wealth for assessing the performance of the economy.
• What is the significance of GDP data?
  • Influence the market: GDP data influence markets, signalling investment sentiments, the flow of funds and balance of payments.
  • The input-output relations impact productivity and allocation of resources.
  • Demand and supply influences prices, exchange rates, wage rates, employment and standard of living, affecting all walks of life.
• Issues over the present series of GDP:
  • Nominal GDP: The data on GDP are initially estimated at a current price known as nominal GDP.
  • Real GDP: Nominal GDP minus the inflation effect is real GDP.
  • Price Index: There is a way of adjusting inflation effect through an appropriate price index.
  • Pricing series issue with the service sector: The present series encountered serious problems for the price adjustment, specifically for the services sector contributing about 60% of GDP.
  • Absence of price index: There is an absence of appropriate price indices for most service sectors.
  • What the absence of series means: The deflators used in the new series could not effectively separate out price effect from the current value to arrive at a real volume estimate at a constant price.
  • Methodical issue: Replacing Annual Survey of Industries (ASI) with the Ministry of Corporate Affairs MCA21 posed serious data and methodological issues.

Need for the change in the approach of data collection

• The approach for the collection of data remains largely the same for long.
  • Price and production indices are constructed using a fixed base Laspeyres Index.
  • The yield rate for paddy is estimated by crop cutting experiments.
  • The organisation of field surveys for collection of data on employment-unemployment, consumer expenditure, industrial output, assets and liabilities continue.
• Why data collection for yields need to change?
  • Productivity and remunerative price of output are major concerns for agriculture.
  • Data collection from diverse factors: It is necessary to collect data on factors such as soil conditions, moisture, temperature, water and fertilizer use determining yield, the impact of intermediary and forward trade on farm gate price and so on.
  • Israel collects these data for analysis to support productivity.
  • Need to leverage the e-governance: The initiative under e-governance enabled the capturing of huge data, which need to be collated for their meaningful use for the production of official statistics.

Data Logistics

• Need of data from the other areas: Along with GDP, we need data to assess-
  • Inclusive growth.
  • Fourth-generation Industrial Revolution riding on the Internet of things.
  • Robotics-influencing employment and productivity.
  • Environmental protection.
  • Sustainable development and social welfare.
• How to deal with the data inconsistency
  • We need systems which have the capability to sift through a huge volume of data seamlessly to look for reliability, validity, consistency and coherence.
  • Such a system is possible through a versatile data warehouse as a component of big–data technology.
  • Rangarajan Committee recommendation: Setting up of such system has been wanting as thoughtful and well-meaning key recommendations of the Rangarajan Commission and subsequent recommendations from 2006 onwards by successive National Statistical Commissions.

Way forward

• The need for a new system: The present national accounting and analytical framework miss out on many important dimensions of the economy.
  • We need a new framework for analysis for such a complex system and evolutionary process.
  • The system needs to take into account automation, robotisation and other labour-replacing technologies affecting profitability, structural change and general welfare.
• Need to find alternative avenues for the unemployed and jobs lost: In order to inject efficiency and stability, there is a need to have detailed data on how: markets clear, prices are formed, risks build-up, institutions function and, in turn, influence the lifestyle of various sections of the people.
• Knowing market microstructure: It is also needed to know in greater detail about market microstructure and optimality therein, the role of technology and advanced research, changing demand on human skills, and enterprise and organising ability.
• Monopoly must be contained:  The loss caused to the economy through monopoly power, inefficient input-output mix, dumping, obsolete technology and product mix must be contained.
• Ensure distribution of wealth: The consensus macroeconomic framework of analysis assumes symmetric income distribution and does not get into the depth of structural issues.
  • In the changed situation of availability of microdata, there is a need to build a system to integrate the micro with the macro, maintaining distributional characteristics.

Conclusion

Data is the new oil in the modern networked economy in pursuit of socio-economic development. The economics now is deeply rooted in data, measuring and impacting competitiveness, risks, opportunities and social welfare in an integrated manner, going much beyond macroeconomics. There is a need for commitment to producing these statistics transparently.

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