JSM 2012 Home

JSM 2012 Online Program

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

Online Program Home

Abstract Details

Activity Number: 472
Type: Contributed
Date/Time: Wednesday, August 1, 2012 : 8:30 AM to 10:20 AM
Sponsor: Business and Economic Statistics Section
Abstract - #305178
Title: Efficient Moment Selection from High-Dimensional Moment Conditions
Author(s): Hyunkeun Cho*+ and Annie Qu
Companies: University of Illinois at Urbana-Champaign and University of Illinois at Urbana-Champaign
Address: 101 Illini Hall, MC-374, Champaign, IL, 61820-5710, United States
Keywords: Dynamic panel data model ; Generalized method of moments ; High-dimensional moment conditions ; Moment selection ; Quadratic inference function ; Singular matrix

For high-dimensional correlated data with a large cluster size, it is feasible to generate many valid moment conditions such as in dynamic panel data models. The generalized method of moments (GMM) approach has the advantages of obtaining an efficient estimator by minimizing the weighed objective function of the moment conditions. However, the GMM estimator could be infeasible when the number of moment conditions exceeds the sample size. We propose an objective criterion which includes a set of important moment conditions in addition to selecting optimal linear combinations of the remaining moment conditions. This is in contrast to existing methods which only select a subset of the valid moment conditions. Monte Carlo simulation studies and real data example show that the proposed method performs better when important moment conditions are included in addition to linear combinations of the remaining moment conditions. It outperforms existing methods in the sense of reducing bias and improving the efficiency of the estimation.

The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2012 program

2012 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.