In terms of drops in real Gross Domestic Product (GDP) and private consumption, the early phase of the Covid-19 pandemic can be categorized as the worst recession period in the US and Europe since the Great Depression of 1929.

While the global economy was hugely affected in a generalized manner, the impact on different economies’ sectors and countries were uneven. An explicit example can be spotted when looking at services sectors relying on face-to-face interactions (e.g., restaurants) versus online deliveries of goods and services.

Here, the authors propose various quantitative economic models to measure how different aspects of the Covid-19 pandemic have impacted price increases between the collapse and recovery periods of the global economy, i.e. from Q4-2019 to Q4-2021. Solving these complex models requires the optimization of non-linear problems, which is carried out using Artelys Knitro.

Thanks to Artelys Knitro, the authors were able to carry out a pertinent analysis of the persistent inflation generated by Covid-19. In addition, Artelys Knitro has the ability to handle complementarity constraints, making it a valuable tool for solving economic models and applications.

At the authors’ request, we would like to point out that this study was carried out without financial support from Artelys.