American Economic Association (AEA) Recognizes Donald Andrews as a 2026 Distinguished Fellow
The American Economic Association (AEA) has recognized Donald W. K. Andrews, the Tjalling C. Koopmans Professor of Economics, as a 2026 Distinguished Fellow.
The Distinguished Fellow awards honor the lifetime contributions of distinguished economists. Since 1965, past presidents of the AEA are recognized as Distinguished Fellows, and up to four additional individuals may be elected for the award each calendar year. Distinguished Fellows are selected by the AEA Nominating Committee and voting members of the Executive Committee, sitting together as an electoral college.
In the award citation, the AEA highlighted Professor Andrews’ many fundamental contributions to econometric theory. His work has had a lasting influence on a wide range of topics in modern econometrics, including structural change, weak identification, unit roots, instrumental variables, generalized method of moments, subsampling and bootstrap methods, semiparametric inference, and the use of empirical process methods in econometrics.
The range and quality of Andrews’ work have long been recognized by the profession. He is a Fellow of the Econometric Society, a Fellow of the American Academy of Arts and Sciences, and a Fellow of the Journal of Econometrics. He has received major recognition for his research contributions, including the Plurima Scripsit award in Econometric Theory. At Yale, his teaching has been recognized with multiple awards, and he has advised leading econometricians over decades. He was Director of the Cowles Foundation from 2011-14.
Andrews joins current faculty member Janet Currie (2025) and emeritus faculty members Robert Shiller (2017), Truman Bewley (2012), and William Brainard (2011) in receiving this honor.
This outstanding achievement will be honored at the AEA Annual Meeting in January 2027.
“We’re delighted to celebrate Don Andrews as a 2026 AEA Distinguished Fellow. Don's foundational contributions to econometric theory have forever altered how we approach complex data. This award is a testimony to Don's immense impact on economics research and practice. Don is admired by all the econometricians for his unmatched intellectual rigor, and is adored by all his colleagues, students and friends for his uplifting smiles and generosity. In addition to being a brilliant researcher, Don has mentored generations of students and visitors, and has nurtured a strong econometrics group during his 40 plus years at Yale. He is the very best of our profession.”
— Xiaohong Chen, Malcolm K. Brachman Professor of Economics
Andrews’s scholarship has repeatedly changed how econometric problems are understood, and he has pointed out where conventional methods relying on large-sample normal approximations are not appropriate. His work on structural change and parameter instability is a leading example. In settings where the timing of a break is unknown, standard methods often fail to provide a satisfactory basis for inference. Andrews developed a general framework for testing for structural change with unknown breakpoints, and that work became central to the subsequent literature. His work helped establish how to conduct inference when parameters may shift over time and when certain parameters, such as the unknown date of a structural break, are not identified under the null hypothesis of no change, so that standard asymptotic approximations for test statistics do not apply.
A second major area of contribution concerns inference under weak identification. Andrews was among the economists who did the most to clarify the consequences of weak instruments and weakly identified models for econometric practice. His work showed why conventional asymptotic approximations can be misleading in such settings and developed methods that remain valid when standard procedures do not. These contributions thus give empirical researchers stronger tools for conducting inference in models where identification is tenuous.
“We are all thrilled that the extraordinary contributions Don has made over his long career—spanning a remarkably broad range of areas including time series, nonparametrics / semiparametrics, weak identification and moment inequalities—have been recognized by this honor. His research forms the foundation of econometrics as we know it today. This is great news for us too, as Don has played a central role in the development of our econometrics group here at Yale, and he, as a researcher, teacher, and mentor, is absolutely admired by our students and colleagues alike.”
— Yuichi Kitamura, Alfred Cowles Professor of Economics
His work on generalized method of moments, bootstrap and subsampling procedures, and semiparametric econometrics was influential. Andrews has repeatedly helped determine when conventional, normal-distribution-based asymptotic approximations are reliable, when resampling methods can improve inference, and how robust procedures can be constructed in settings where parametric assumptions are too strong. His research has often provided the theoretical foundations on which later methodological work built, and upon which empirical applications have depended.
Read the full AEA award citation here.