Direkt zum InhaltDirekt zur SucheDirekt zur Navigation
▼ Zielgruppen ▼

Humboldt-Universität zu Berlin - High Dimensional Nonstationary Time Series

Hilda Geiringer Lecture 2019

 

Date & Time: TBD (November 2019)

Venue: Weierstraß-Institut für Angewandte Analysis und Stochastik (WIAS)
Mohrenstraße 39, 10117 Berlin
 

 

 

Lecture: Adaptive Testing in Instrumental Variables Models 

 

This paper is concerned with adaptive inference on a structural function in the semiparametric or nonparametric instrumental variables (NPIV) model.

We propose a direct test statistic for hypothesis testing based on a leave-one-out, sieve NPIV estimator. Our test is applicable to identified and partially identified models.

We analyze a class of alternative models which are separated from the null hypothesis by a \textit{rate of testing} which is sensitive to the form of identification. This rate of testing is shown to be minimax: The first type error and the second type error of our test, uniformly over the class of alternative models, cannot be improved by any other test.

We also propose an adaptive test statistic that provides a data driven choice of tuning parameters and attains the minimax optimal rate of testing within a $\log\log n$ term.

This paper concludes with a finite sample analysis of the testing procedure and empirical illustrations.

 

Speakers

 

  Xiaohong Chen 

  Yale University 

 

Xiaohong Chen is currently Malcolm K. Brachman Professor of Economics, Yale University. Previously, she has taught at the University of Chicago, London School of Economics and New York University.

Chen got her PhD in Economics in 1993 from University of California, San Diego.

She is an elected member of the American Academy of Arts and Sciences since 2019, a fellow of the Econometric Society since 2007, a fellow of Journal of Econometrics since 2012 and an international fellow of Cemmap since 2007.

 

Chen’s research field is econometrics. She is known for her research in penalized sieve estimation and inference on semiparametric and nonparametric models.

She has published peer-reviewed papers in top-ranked general-purpose journals, such as Econometrica and Review of Economic Studies in economics, and also in top-ranked field journals in statistics and econometrics (Annals of Statistics, Journal of the American Statistical Association, Journal of Econometrics, Journal of Economic Theory, IEEE Tran Information Theory, Quantitative Economic, etc.). She also published several invited review chapters. Chen is an editor of Journal of Econometrics since Jan 2019 and has been an associate editor of Econometrica, Review of Economic Studies, Quantitative Economics, and others.

In 2017, Chen won the 2017 China Economics Prize. She also won Econometric Theory Multa Scripsit Award in 2012, The Journal of Nonparametric Statistics 2010 Best Paper Award, The Richard Stone Prize in Journal of Applied Econometrics for the years 2008 and 2009, The Arnold Zellner Award for the best theory paper published in Journal of Econometrics in 2006 and 2007.

 

Registration

 

TBD

 

Schedule

 

TBD

 

Organization and Contact Information

 

Prof. Dr. Wolfgang Härdle
Dr. Ioana Ceaușu

Elena Ivanova
 

Humboldt-Universität zu Berlin
Wirtschaftswissenschaftlich Fakultät

International Research Training Group 1792
"High Dimensional Nonstationary Time Series"

Dorotheenstr. 1
10117 Berlin, Germany

 

Tel.: +49 - 30 - 2093 99593
E-Mail:

ceausuio[@]hu-berlin.de