Data Collection Could Help India Tackle its Food Inflation Problem

Context: The recent spike in Indian inflation is a reminder of how food prices are notoriously volatile.  Technology, with the use of data, can provide solutions to reduce price fluctuations.

Reason for fluctuations in supply

• Erratic weather

• Mis-calibrated expectations of Farmers:  illustrated through the Cobweb Model.

• Farmers base their expectations of future prices on what they see in the spot markets at the time of sowing

• Harvest-time price expectations based on current prices

• For, E.g. when farmers see high prices of onions, they decide to grow more of these, thus setting the stage for overproduction.

• Absence of cold-storage infrastructure.

Measures to tackle the fluctuations in supply/price of food items

• Provide farmers with better forecasts

• Gather real-time data on the area under cultivation for a few important crops, with their expected harvesting dates

• Develop a smartphone app for farmers to enter the information after sowing and give them monetary incentives for doing so.

• The app could show real-time data of sowing preferences of farmers and can help in containing oversupply

• Random audits and the monitoring of eventual sales to prevent malpractices.

• Intervention should be at the production stage rather than at the final stages.

Data forecasts can work effectively because

• Access to technology: Smartphones have already penetrated deep into the hinterlands due to the availability of cheap data.

• It will enhance the ability to diversify: Reliable forecasts well ahead in time may prompt them to diversify their crops

• Time-series forecasting and machine learning will help in improving algorithms that forecast prices.

Conclusion

• Devising a system around data can play a meaningful part in reducing the price volatility of farm produce
• It could also help governments manage the delicate balancing act between protecting the interests of food producers and consumers