India to share food price prediction tech
India is willing to offer its South Asian neighbours an artificial intelligence (AI)-based mechanism to predict prices of essential food commodities, a top official said, pointing to a technology that's helped India tame food inflation.
The first country to receive the technology may be Sri Lanka—a timely help for a country that is emerging from the throes of an economic crisis. In an interview, consumer affairs secretary Rohit Kumar Singh said the mechanism will help India’s strategic partners, including those in its neighbourhood, better plan for demand of essential commodities and plan how much needs to be imported.
India has recently exported onions and rice to strategic partners such as Bangladesh, the UAE, Mauritius, Bhutan and Bahrain.
“With the help of an algorithm-based mechanism, the government can now predict the prices of essential commodities for 30, 45, and 60 days in advance with a lot of accuracy. We used this tool to control the prices of tomatoes by selling them in the retail market at a subsidized rate,” Singh said.
Decisions based on the predictive model become key. For instance, high vegetable prices helped fuel overall inflation in July-August. In the wake of rising inflation, the government imposed a ban on rice exports, raised duties on onions and started selling tomato to consumers at a subsidized rate.
As a result, food inflation cooled to 6.56% in September against 9.94% in August on the back of softer vegetable prices. Vegetable inflation in September eased to 3.39% from 26.14% a month earlier.
In January, the government used the technology to predict onion prices for a particular date in March. Once the actual prices came that day, it was able to draw a comparison and make a note of the error.
“So, we have seen that because our system is improving, the error is reducing. This helps us taking the right decision at the right time,” Singh said. “We have showcased this tool to Sri Lankan officials. If neighbouring countries ask for it, we are ready to share the predictive pricing mechanism with them. The tool will work effectively only if the country has its own data.”
Mint on 29 October reported that the government was planning to create an AI-based real-time supply and demand prediction model for agricultural commodities that will factor in externalities like weather and trade-related measures.
The move came after a patchy monsoon disrupted kharif crops, impacting the sowing and vegetative seasons, amid a forecast by economists for farm output growth in 2023-24 to be slower.
The tool makes use of previous data, which makes it “so effective that if we want to see the price pattern of mustard oil in Hooghly for the last 10 years, it can be done in just three clicks”, Singh said.
As of now, the government collects price data for 22 commodities from 550 places and three data sources daily.
Sri Lanka may be first one to get the technology— a timely help for a country that is emerging from an economic crisis
day announced the schedule for the bi-monthly monetary policy committee meetings for the new fiscal. The first meeting will be held from 3-5 April, while the next will start on 5 June.The second bi-monthly policy review meeting will end on 7 June, RBI said, adding that this will be followed by three day meets in August, October, December and February.
New Delhi: The Commodity Participants Association of India (CPAI) on Wednesday sought timely clarification and a FAQs document from the stock exchanges on the RBI’s new rule for rupee derivatives that will come into effect on 5 April. The RBI on 5 January said the recognized stock exchanges may offer forex derivative contracts involving rupee “for the purpose of hedging contracted exposure”.