Structural models provide little information about the near term and, as a result. policy-making institutions spend too much time producing short-term forecasts. Here at the Fund, Machine Learning and Big Data are changing this.
By combining time-series forecasting models, we are now able to deliver forecasts for 38 countries on a weekly basis. Using several activity indicator series, including some with high frequency, we are applying various machine learning algorithms to produce promising results. The system is even smart enough to dynamically shift its machine learning algorithms to improve its performance. We explore this technology and how it will impact the work of the Fund and add value to our member countries.