1. Where we stand:

The impact that COVID-19 is having on our lives is already globally recognized as profoundly transformative and a structural change. RENASCER is a multidisciplinary team looking for economic policy instruments based on feasible and expeditious recovery trajectories. We are economists, historians, biomedical scientists, political scientists and data scientists.

Based on the historical observation of the impacts of other major epidemics, while we see that there is an urgent need to act to care and prevent, we know that the change that is taking place will be difficult to predict, we also know that other systemic shocks have profoundly transformed societies. We are in a situation of uncertainty. However, we know that it is urgent to resume the economy, return to the streets, secure jobs and ensure quality of life.

2. Deciding:

The urgent need to resume economic activities and “normal life” will be all the more successful if our return is well taken care of. Our return and the economic recovery will have to provide not only the safety of economic agents but also to be quick and effective.

3. Team:

Thus, we have assembled a multidisciplinary team that intends to find solutions for the recovery of the economy based on historical and epidemiological evidence, which allows transforming uncertainty into risk calculations.

Our team brings together big data, economics, epidemiology,biology, politics and history to study crises and recovery. We intend to look for patterns that are not obvious in the most cited studies, made for big catastrophes or large economies. Small subtle variations that are not observable when only one phenomenon is studied in a single region.

4. Process:

One of the starting points will be to resort to a systematic analysis of the crisis literature. With qualitative text analysis tools you can get a lot of information, but we can go further. That is, move from here to a database of scientific articles and a database in itself, much larger, where it is possible to scan the text or data and remove patterns. We crossed the fineness of historical analysis with statistical robustness.

These patterns that we are looking for will be translated into variables of economic forecasting models, potentially more robust to Lucas’ Critique, making this systemic shock that we are experiencing endogenous.

5. The main goal: to find feasible and expeditious recovery paths that can be used as instruments of economic policy.

We welcome computer scientists, statisticians, economists, historians, people with experience in team management, database management, knowledge of the biological as well as the economic and political aspects of society.