Title: Insights from Analytic Mean-field Games in Economics, Danial Ali Akbari, Dept. of Economics, Lund University

Abstract: This presentation has three goals. First, it sets out to show the potency of the theory of mean-field games (MFG) in producing analytic results (closed-form solutions) in economic examples. Second, it will illustrate the added-value of such specific examples (as opposed to general results) and show how economists use the insights from such analytic results to inform their analysis in more general settings. Third, and as a result, it aims to raise interest among mathematicians working on partial differential equations (PDEs) and stochastic modeling of dynamic systems to also to investigate specific examples involving mean-field games in collaboration with economists. Time-permitting, I will present three applications: skill premia under ambiguity aversion, optimal labor income taxation, and social cost of carbon under wealth inequality. I will also point out open questions in and venues for improvement for numerical methods solving the PDEs arising from MFG applications in economics.