The Department of Economics will be sponsoring a session at the 33rd New England Statistics Symposium (NESS) on May 15–17, 2019.

High Dimensional Econometrics

The technological innovations in information processing and the increased storage capability have made possible to collect very large data sets in various fields of economics and finance.

This session puts together 3 papers that present state-of-the-art techniques to deal with high dimensional issues in econometrics.

List of invited speakers:

(1) Fa Wang, Cass Business School, Fa.Wang@city.ac.uk, “Maximum Likelihood Estimation and Inference for High Dimensional Nonlinear Factor Models with Application to Factor-augmented Regressions”

(2) Yuan Liao, Rutgers Economics, yuan.liao@rutgers.edu, “Inference for Heterogeneous Effects Using Low Rank Estimation”

(3) Min Seong Kim, UConn Economics, min_seong.kim@uconn.edu, “Policy Analysis Using Panel and Multilevel Models with Group Interactive Fixed Effects”

Discussant: Jungbin Hwang, UConn Economics, jungbin.hwang@uconn.edu

Session Chair: Chihwa Kao, UConn Economics, chih-hwa.kao@uconn.edu

Information about the conference may be found online at https://symposium.nestat.org/