Yield21 prediction market forecasts higher UK wheat yield than DEFRA estimate
A prediction market – the first of its kind in the UK agrifood sector – predicts that there’s a 75% chance that the National wheat yield will fall between 8.0 and 8.6t/ha. This is higher than the 7.8 to 8.0t/ha provisionally estimated by DEFRA.
An innovative yield prediction contest gives a greater chance that the UK average wheat yield figure will be higher than the 7.8t/ha provisionally reported by DEFRA. The market gave a 10% chance of yields between 7.8 and 8.0t/ha compared to a 75% chance of a figure between 8 and 8.6t/ha. We now need to wait until the final figures are announced in December to see if the 7.8t/ha figure remains or changes.
Over the past eight months, 25 teams have competed in a first-of-its-kind yield prediction contest. Unlike traditional prediction competitions, where teams submit predictions, competitors are allocated credits that are used to buy yield outcomes on 0.2t/ha increments.
Outcomes can be bought and sold over the season as more information becomes available, with their price impacted by demand (just as in real-world financial and commodity markets).
The market, therefore, represents the distribution of outcomes predicted by multiple teams using multiple methods and insights. Consequently, the market prediction could be more reliable than the prediction of any one competitor and can update as new information becomes available.
In 2020, a prediction market estimating monthly COVID-19 cases in the US proved more accurate than some consensus estimates. Prediction markets have also been successfully used to predict hurricane activity.
If the prediction market proves to be reliable, then it would have broad commercial and practical applications, including providing valuable insights for crop insurers and grain traders.
How it works
Hosted on the AGORA platform, the prediction market mimics the price volatility of real-world financial and commodity markets. Each team was allocated credits, which could be used to buy yield outcomes on 0.2t/ha increments. The distribution of these outcomes was plotted on a public graph, with popularity impacting price.
As the competition progressed, teams could sell their owned outcomes and purchase new ones. This could result in either a profit or a loss for that team. The market closed on September 30th. When DEFRA announces the official yield statistics in December 2021, teams will receive additional credits for every unit of the correct outcome they hold.
The team with the highest number of credits will be declared winner and receive a cash prize.
The competition featured 25 teams with a broad range of backgrounds and techniques. These ranged from statisticians with no agricultural experience to agronomists and farming groups. Techniques included sophisticated data modelling and qualitative research, i.e. collating the personal professional views of farmers using networks and forums.
The competition started with a relatively broad range of predictions. As the season progressed, more relevant information became available, leading to an improvement in predictions. This led to a coalescing of predictions around just three outcomes (8.0-8.6).
The platform was run on Hivemind’s Agora Platform. To support predictions, Agrimetrics made data from its Agrifood Data Marketplace available to teams. This data included seasonal climate forecasts from Weather Logistics, who provide novel insights into weather perils linked to crop performance volatility.
Agrimetrics is the food and farming sector’s Data Marketplace. We enable organisations to safely share and monetise their data, whilst making it easier for data-consumers to access the information they need. Our goal is to help create a more productive and sustainable food system by enabling next-generation solutions as quickly and affordably as possible.
The four centres The Agri-Tech Centres are a unique collaboration between Government, academia and industry created to drive greater efficiency, resilience and wealth across the agrifood sector. A £90m investment from the UK’s strategic innovation agency (Innovate UK) is enabling the Centres to harness leading UK research and expertise as well as build new infrastructures and innovation. They include CHAP (Crop Health and Protection), CIEL (Centre for Innovation Excellence in Livestock), Agri-EPI (Engineering and Precision Technologies), and Agrimetrics.
About our partners
Hivemind Technologies is a data science and technology company. The Company develops software to help clients build, clean, and enrich datasets from unstructured sources such as company reports, regulatory filings, and news feeds.
Their AGORA software platform that allows you to elicit and aggregate the judgments of many individuals into consensus forecasts that are actionable and accountable and which can evolve as new information becomes available.
Weather Logistics is a ClimateTech firm. Its vision is to help re(in)insurers better price crop risk; support growers and farmers to understand and develop a climate resilience plan and diversify/ adapt their operations; and support access to sustainable finance to recover from extreme weather where its impacts are most costly.
Our farm-scale knowledge of climate risk supports multi-site operational planning:
Best-on-market performance in short-term climate prediction, using well-established climate indices and weather models from global providers to estimate basis risk/ price uncertainties through a farm-scale probabilistic ‘ensemble’
Estimate crop insurance claims within the current growing season, or for many different realisations of the current climate, rather than using outdated weather histories
Reliable insights into daily weather perils, such as air frost damage, disease outbreaks, drought, and heat stress damage, linked to agricultural losses
Specialist and rigorous approach. Currently in a brokerage for product assessment by the UK’s measurement standards agency
Agronomy partnership to support detections of crop type, field boundaries, historical yield information for each field, and estimates of maximum obtainable yield
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