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Tong Li

An Essay on

Xiaohong Chen’s Research Contribution

Tong Li

Gertrude Conaway Vanderbilt Professor of Economics, Vanderbilt University Overseas Dean, Institute of Economics and Business, Beihang University

First of all, I wanted to congratulate the National Economics Foundation for making the right choice for this year’s China Economics Prize by giving it to Professor Gregory Chow and Professor Xiaohong Chen. I have known Xiaohong for over twenty five years, and we have been close friends since our graduate student days at UC San Diego in early 90s. I am thrilled that Xiaohong shared the Prize this year with Professor Chow, as they two represent the best of their respective generations of Chinese economists, and fully deserve such a great honor.


While I am profoundly grateful to the Foundation for providing me with an opportunity to describe Xiaohong’s research, and it is indeed my great honor and distinct pleasure to do it, when I was going over Xiaohong’s work, despite that I had been familiar with a significant portion of her work, I was still feeling that the task I was trying to do is next to impossible to complete in a satisfactory fashion, as Xiaohong’s contribution in econometrics is so broad and deep that it is truly difficult to accurately summarize in this short essay.


Econometrics is an important integral part of modern economics along with microeconomics and macroeconomics. It concerns developing new identification strategy, estimation and inference methods to analyze economic models and economic data, which can be cross-sectional, mostly arising from microeconomic applications, or time series, mostly arising from macroeconomic applications, or panel data, a combination of both cross-section and time series, which could occur from either micro or macro applications. The breath of Xiaohong’s contribution in econometrics can be clearly seen from her work that covers both subfields in econometrics, namely, microeconometrics and macroeconometrics, and ranges over all topics in econometrics such as identification, estimating, and inference. The depth of her work, on the other hand, can be seen from her many top publications and the high impact of her work on the literature, which I will discuss briefly as follows.


. (1) Xiaohong is one of the most influential scholars in nonparametric econometrics especially in using the sieve methods. Her work in studying asymptotic properties of sieve M estimation has been published in Econometrica, the Journal of Econometrics, among others, and her chapter on sieve estimation in the Handbook of Econometrics has become a must-read for people who use the method, and is widely cited. It is not exaggerating to attribute the wide use of the sieve method in applications to Xiaohong’s Handbook chapter.


. (2)  Xiaohong has made some of the most important contributions to and is one of the leading authorities in estimation and inference on semi-nonparametric conditional moment restrictions containing unknown functions of endogenous variables, an extremely important problem in a central area in econometrics, since Lars Peter Hansen’s seminal work in 1982 on Generalized Method of Moments (GMM). She has produced an impressive body of work that has been published in some of the very best economics journals including Econometrica (multiple times), Review of Economic Studies, among others. It is also worth noting that Ai and Chen (2003) in Econometrica has become the most important work in this area, and has been widely cited; it is also one of a few theoretical econometrics papers cited in Lars Peter Hansen’s Nobel Lecture that was published in the Journal of Political Economy in 2014.


(3) She is one of the scholars who introduced the copula approach to econometrics, and her work in this area remains to be most influential to date. Her work on studying semiparametric copula models in time series won the Zellner Award for the best theoretical paper in the Journal of Econometrics in 2008. I have used the copula approach in my own research, especially in using it to model joint dependence structures in game- theoretic auction models, and I have benefited a lot from Xiaohong’s work in this area. 


Xiaohong is a top-notch theoretical econometrician and has made fundamental contributions to almost all areas in theoretical econometrics; the fact that her work was among a few theoretical econometrics papers cited in Lars Peter Hansen’s Nobel Lecture as aforementioned and that her early work on neural networks was cited in Daniel McFadden’s Nobel Lecture in 2000 is truly a testament for how important and influential her work is. She also has genuine interest in applied work, and has worked with some applied economists, and produced first rate applied work. Her paper with Richard Blundell and Denis Kristensen in Econometrica on semi-nonparametric instrumental variable estimation of shape invariant Engel curves is one of the best applied papers in using the semiparametric IV estimation method. Her paper with her applied colleague at NYU on the empirical analysis of habit based asset pricing models won the Richard Stone Prize for the best paper published in the Journal of Applied Econometrics; this shows the kind of scholar Xiaohong is---if she works on something, she will be fully involved and works hard, and any work she produces is of the very high quality.


As a fellow econometrician, I know the first-hand how important Xiaohong’s contribution to econometrics and the profession is. As a long-time friend, I also know the first-hand her struggles and sacrifices over almost a quarter century since she got PhD from UC San Diego and joined the University of Chicago as an assistant professor in 1993; her road to the podium to accept this prestigious prize has been long and challenging, and I am very happy that Xiaohong prevails and her contribution is recognized by the China Economics Prize this year. As I mentioned before, Xiaohong’s scholarship and accomplishment cannot be described accurately in such a short essay. While I cannot accurately convey her accomplishment and contribution here, I would be happy if my essay can provide a lens and offer a glimpse into Xiaohong’s tremendous contribution in econometrics and who she is as a true scholar.


◆please indicate the source if authorized: National Economics Foundation

◆photo:National Economics Foundation