Corona has put new forms of economic data into play

Context:Microdata is useful but it can’t replace the basic analytical framework we need for policy responses

Measurement of economic activity: 

• Modern governments depend heavily on large surveys as well as administrative data to track their respective economies. Such data is the bedrock of estimates on the gross domestic product, industrial production, farm output, inflation, etc.

Covid-19 shock and disruption in national statistics: 

• Suspension of forecast: Reserve Bank of India (RBI) has temporarily suspended its economic forecasts for the quarters ahead. 
• Credibility of new-age data: Government surveys of prices are now based on telephone interviews, rather than field visits to various markets.
• Change in consumption pattern: Due to lock down the relative importance of items such as food or telecom services or entertainment have perhaps increased in most family budgets.
• Use of new data sources: The high-frequency data points (Google mobility, digital payments, customs duty collections, and E-Way bills, etc.) have been used for casting economic activity in real-time rather than predicting its future value.
• Economist response:

• Economist Alberto Cavallo has built an alternative COVID consumption basket based on what the average US family is spending on during the pandemic.
• Shift in Dominance: increased importance of groceries and a decline in the importance of fuel

Challenges with online data: 

• Not holistic: Data collected from the organized private sector may not reflect what is happening in the unorganized sector. 
• Data frequency: New-age data comes at different frequencies—daily, weekly, monthly. Different seasonal patterns also complicate matters.
• Not having a clear understanding: Either the inability to go out of the house or the fear of using contaminated currency notes could have led to a spike in digital payments. 
• Cannot address the key analytical question:  policymakers need strong analytical frameworks.

Conclusion: New data can complement analytical work, but it cannot replace it.