Researchers and policy makers now have a powerful new tool at their disposal with the development of a cutting-edge Toolkit for efficient estimation and utilisation of state-of-the-art time-series models. This Toolkit promises to revolutionise policy analysis and forecasting by allowing for accurate predictions and informed decision-making.
One of the main challenges in analysing time series data lies in understanding the complex relationships between variables that evolve over time. Existing methods rely on extensive Monte Carlo simulations, which are time-consuming and often lead to biased forecasts. This creates a significant barrier for many users, including academics and policy analysts.
To tackle this problem, a team of experts has devised a ground breaking method that provides statistically and computationally efficient estimates for these models. The method can be easily parallelised and drastically reduces computational times by orders of magnitude. Leveraging the power of cloud computing, this approach pushes the boundaries of what was previously possible in this field.
To bring this innovation to market, the team will build an advanced prototype and collaborate closely with early adopters to fine-tune and test its capabilities. Additionally, they will conduct comprehensive business-related activities to identify the most effective route for commercialisation. The ultimate goal is to provide a user-friendly environment where researchers and decision-makers can effortlessly access accurate estimates and make informed policy decisions.
The project outcomes will include the advanced prototype, an analysis of the competitive landscape, and a well-defined strategy for bringing this technology to the broader market. With this ground breaking Toolkit, users can expect more reliable forecasts and evidence-based policy prescriptions, ultimately driving positive outcomes in various domains.
This project is funded by the UKRI under Guarantee Funding for European Research Council – Proof of Concept grants
