The first aim of the project is to provide real-time evidence of the effect of restriction policies to flatten the epidemic curve (i.e., restrictions to economic activity and mobility) on the intensity of conflict worldwide. Thanks to daily information on conflict events with specific details on the nature and the actors on both sides of the conflicts, I will be able to release frequent estimated magnitude of the impact of restriction policies. In addition, I will evaluate how the effects are evolving with the duration of the restrictions to limit the spread of coronavirus, but also during and after the loosening of restrictions and the restart of the economic activity. The second aim of the project is to estimate how the implementation and progressive lifting of restriction policies may differentially affect conflict across regions within a country. The different sources of regional heterogeneity that I will investigate are i) income; ii) trade openness; iii) natural resource production; and iv) religion. Highlight sources of regional heterogeneities within a country, may help policymakers to target regions that are more likely to face increasing violence.

Many decisions taken by rational economic agents do not involve markets, but the design of matching and voting procedures, or the use of groups and social networks. The allocation of students to schools, the choice of cases taken up by the Supreme Court or the measure of influence of social agents are all examples of issues which have recently been studied by microeconomic theorists beyond the realm of markets. Moving beyond the strict boundaries of markets and prices, economic theorists now join forces with political scientists, psychologists and computer scientists to better understand the functioning of matching, voting and network institutions. With a few exceptions, theoretical and empirical models of matching, voting and network formation are static. The objective of this project is to develop a new generation of theoretical models of dynamic matching, voting and networks by embedding static decisions in dynamic models represented by Markov processes. The project is subdivided into three sub-projects. Dynamatch is devoted to the study of dynamic matching problems, and will examine multi-stage assignment models with an initial phase of courtship, the assignment of subsidized housing to queuing agents, and of positions in high school and universities to overlapping generations of teachers. Driven by concrete applications in market design, the project involves a dialog with practitioners in social housing and teacher assignment. Dynavote focuses on dynamic voting models, and analyzes the design of multi-stage electoral rules in continuous time, models of optimal apportionment and evolutionary learning of voters over repeated elections. Dynanet is a project on dynamic formation of networks, with applications to networks of influence and networks of innovation. In addition, models of dynamic coalition formation and allocations in cooperative games will be studied in this project. Because dynamic models involve sophisticated behavior on the part of agents, we plan to test the predictions of theoretical models in the laboratory. We plan to implement a series of experiments on school choice, voting and network formation. In the long run, the objective of the project is to advance the research frontier in economic theory, to engineer matching procedures in concrete applications and to cement a community of researchers in France dedicated to matching, voting and network theories.