Steering Economies Towards Stability in the Wake of COVID-19: Insights from a Mathematical Model

As one of the leading researchers in the field of economics and mathematics, my colleague Dr. Anna Tykhonenko and I had the privilege of presenting our latest study at the World Finance Conference. Our research sought to examine the impact of policy-maker decisions on economic convergence in a period characterized by turbulence, uncertainty, and complexity, like the COVID-19 pandemic.

Recognizing the critical need for structure and clarity in such times, we decided to employ a Markov Decision Process model in our analysis. This mathematical framework has proven invaluable for modeling complex decision-making scenarios where outcomes are partly determined by random events and partly by the actions of the decision-maker.

Our research is deeply rooted in the Bayesian approach, which is instrumental in understanding growth dynamics. We used k-means clustering to classify EU states into three categories: those catching up, those in the core, and the leaders. This categorization allowed us to analyze the performance and progression of each group more effectively.

The crux of our research is the application of a Markov Chain, a probability model that helped us estimate the probability of each group moving to a different ‘state’ economically. This assessment forms the basis of our projections and policy recommendations.

We examined three potential policy scenarios for decision-makers. The objective for these policymakers would be to select the scenario that maximizes the ‘reward function’ or the forecasted outcome of a specific policy. By utilizing backward computation, we were able to determine the best policy action and the expected reward at each point in time.

As we grapple with the fallout of the COVID-19 pandemic on the global economy, the implications of our study cannot be overstated. We found that effective decision-making is crucial for achieving economic convergence in a post-crisis world. Furthermore, our research indicated that a global and coordinated approach might offer several benefits.

Interestingly, our study suggested that the COVID-19 crisis could paradoxically provide an opportunity for poorer states to implement optimal policies they might not have been able to afford under normal circumstances.

In summary, our research offers a mathematical blueprint for policymakers, emphasizing the need for a coordinated and strategic approach to policy decision-making, particularly in times of crisis. By leveraging mathematical modeling and considering a range of potential outcomes, policymakers can better guide their economies towards stability and convergence.

Dr. Nahla Dhib
LJAD Mathematics Interactions,
University of Cote d’Azur, France and CEO of SQC