Advancing Economic Forecasting and Risk Analysis Models
Economic systems that operate through a constantly expanding number of dynamic interactions have become too complex to fully represent using popular econometrics and economic modeling methods.
Research Paper, written by Nabil Abu el Ata
As the pace of innovation accelerates in the Fourth Industrial Revolution (4IR), the cause and effect of economic crisis will become nearly instantaneous. Governments and businesses can no longer afford to wait for the warning signs of an economic turmoil, before taking action. To regenerate prosperity for the betterment of humanity, economists, policymakers and financial practitioners must employ new problem-solving approaches. Eliminating the waste and managing the risk caused dynamic complexity will deliver new opportunities for growth and sustainability. But first, economic stakeholders must tame dynamic complexity and simplify decision cycles.
This paper proposes a new approach to economic forecasting and predictive analysis that allows users to uncover a wide scope of unknown risks. Armed with this knowledge, economic stakeholders will be able to quickly take action with confidence in the outcomes—before imbalances proliferate through financial markets and interdependent subsystems. The proposed approach allows users to more accurately reproduce the magnitude and direction of market behaviors, which in turn allows economists, policymakers and practitioners to predict a wider range of risks and vet which corrective actions will yield the best results.
Covid-19 Worldwide Viral Infection Model 
