Ellis Scharfenaker is an Associate Professor of Economics at the University of Utah. He earned his B.A. in political philosophy from The Evergreen State College and his Ph.D. in Economics from the New School for Social Research. His research develops the statistical and theoretical foundations necessary to understand how the complex interactions of heterogeneous agents, mediated by economic and social institutions, generate observable macroeconomic distributional patterns. Drawing on insights from information theory, statistical mechanics, and Bayesian inference, his work focuses on the stochastic generative dynamics of distributional outcomes in income, wealth, profit, output, and growth. His recent research includes the development of information-theoretic approaches to causal inference and structural econometric modeling. His work has appeared in leading journals across disciplines, including The American Statistician, Journal of Economic Dynamics and Control, Economics Letters, European Physical Journal, and Entropy. He also a core member of the One Utah Data Science Hub, which facilitates interdisciplinary research across the university focused on data science.

Many of his reserach interests are contained in his book manuscript, co-authored with Duncan K. Foley, Constrained Maximum Entropy Statistics: Informaiton Theory and Bayesian Statistical Inference (Forthcoming with Columbia University Press)

Also see my personal webpage.