Yacine Ait-Sahalia is the Otto A. Hack 1903 Professor of Finance and Economics at Princeton University. His research is in the area of Financial Econometrics, with a particular focus on the testing and estimation of continuous-time models and the statistical analysis of high frequency financial data. He is a Fellow of the Econometric Society, the American Statistical Association, the Institute of Mathematical Statistics and the Society for Financial Econometrics. He currently serves as Editor of the Journal of Econometrics.
Graham Elliott is a professor of Economics at the University of California, San Diego. His research focuses on a number of areas in econometrics and statistical theory. One strand of research examines how to make the best use of data in testing hypotheses when standard tests are potentially suboptimal. A second strand of research is applied to the practical problem of constructing forecasts. He served as co-editor of the International Journal of Forecasting for eight years and as associate editor of a number of other journals in the fields of economics and statistics. He co-edited the first two volumes of the Handbook of Forecasting.
Bruce Hansen is the Phipps Distinguished Chair of Economics at the University of Wisconsin-Madison. His research interests are in econometric theory and methods, with an emphasis on techniques with practical application for economists, and have included contributions in cointegration, structural breaks, nonlinear time times, threshold models, and model averaging. He is a fellow of the Econometric Society and the Journal of Econometrics.
Peter Hansen is the Henry A. Latane Distinguished Professor in Economics at the University of North Carolina, Chapel Hill. He is a leading researcher on forecasting and volatility modeling, and he has featured on the Thomson Reuters’ list of the World’s Most Influential Scientific Minds in 2014, 2015, and most recently in 2016 as one out of 70 economists worldwide. He has developed methods for comparing and selecting forecasting models, and has introduced novel estimators of volatility that draws on high-frequency financial data. He introduced the Realized GARCH framework that won the Richard Stone Prize in Applied Econometrics in 2014.
Hidehiko Ichimura is Professor of Economics at University of Tokyo. His research is in the area of econometric theory and methods, with a special emphasis on their applications to microdata. He is one of the leading pioneers in nonparametric and semiparametric models, program evaluation, matching method in economics, and bound analysis. He is a fellow of Econometric Society.
Azeem M. Shaikh is a professor in the department of economics at the University of Chicago. His academic interests lie broadly in econometric theory, including topics such as partial identification, randomization inference, the analysis of experiments and multiple testing. His research has been supported by the Alfred P. Sloan Foundation and the National Science Foundation. He currently serves as an Associate Editor for Econometrica and the Econometrics Journal.
Jeffrey M. Wooldridge is University Distinguished Professor of Economics at Michigan State University. His research spans econometric theory, panel data analysis, and the economics of education. He is the author of Introductory Econometrics: A Modern Approach (South-Western, 6e, 2016) and Econometric Analysis of Cross Section and Panel Data (MIT Press, 2e, 2010). He is a fellow of the Econometric Society and the Journal of Econometrics, and currently serves on the editorial boards of the Journal of Economic Literature and the Stata Journal.
Mark Watson is the Howard Harrison and Gabrielle Snyder Beck Professor of Economics and Public Affairs at Princeton University. His research focuses on time-series econometrics, empirical macroeconomics, and macroeconomic forecasting. He has published articles in these areas and is the author (with James Stock) of Introduction to Econometrics, a leading undergraduate textbook. He is also a fellow of the American Academy of Arts and Sciences and of the Econometric Society.