Research and Bio
Bio
Esfandiar Maasoumi is a leading international econometrician. He has been the Editor and managing editor of Econometric Reviews since 1987. ER is one of the top 5 core journals in Econometrics with one of the most distinguished Editorial Boards in economics.
Maasoumi is a Fellow of the Royal Statistical Society (FRS), a Fellow of the American Statistical Association, a Founding Fellow of International Association for Applied Econometrics (IAAE), Inaugural Fellow of Society for Economic Measurement, Fellow of Econometric Reviews, and several others. He earned a Fellow of Journal of Econometrics since 1989 for the high frequency of his publications.
Maasoumi served as faculty at the London School of Economics, , USC, Indiana, SMU, and has been a visitor at MIT, Yale, University of California (several campuses), and many other internationally ranked institutions overseas. He has B.SC, M.SC and Ph.D degrees in Mathematical Economics, Statistics, and Econometrics (respectively) from the London School of Economics, University of London.
He has published more than 100 papers in the leading journals in economics, and numerous edited books and special issues on a wide range of topics in econometrics and economics. His publications have appeared in Econometrica, J. of Econometrics, Journal of Political Economy, Review of Econ and Stats, Review of Economic Studies, American Economic Review, Journal of Business and Economic Statistics, Journal of applied Econometric, Biometrika, Econometric Reviews, among others. He is consistently ranked in the top 50 of the “Econometrics Hall of Fame”.
Maasoumi is considered by some as an intellectual leader of the Empirical/Statistical “Income Inequality” literature, with influential works on multidimensional well-being, mobility, and poverty. His measures of aggregation, poverty and inequality in many dimensions are standards in the field, as is his leading work on stochastic dominance (with Oliver Linton and others).
He has also been a known leader and innovator in the field of Information Theory, where he is regarded as a creative force in conceptualization of econometric and economic objects with information theory criteria and techniques first developed in communication theory.
Research Areas:
His areas of research and interest range widely. They include modern Machine Learning, deep learning, automated debiased partial effects, financial econometrics, nonlinear time series models and methods, Information Theory, Aggregation, Econometric tests and estimators, finite sample distribution theory, forecasting, empirical finance, Patent infringement methods, non parametric methods, and the aforementioned areas of inequality, poverty, and mobility, especially in many dimensions. His work on program evaluation and policy analysis joins innovations in information theory, stochastic dominance testing, and treatment effect analysis.