TY - JOUR
AU - Imbens,Guido W.
AU - Johnson,Phillip
AU - Spady,Richard H.
TI - Information Theoretic Approaches to Inference in Moment Condition Models
JF - National Bureau of Economic Research Technical Working Paper Series
VL - No. 186
PY - 1995
Y2 - October 1995
DO - 10.3386/t0186
UR - http://www.nber.org/papers/t0186
L1 - http://www.nber.org/papers/t0186.pdf
N1 - Author contact info:
Guido Imbens
Graduate School of Business
Stanford University
655 Knight Way
Stanford, CA 94305
E-Mail: Imbens@stanford.edu
AB - One-step efficient GMM estimation has been developed in the recent papers of Back and Brown (1990), Imbens (1993) and Qin and Lawless (1994). These papers emphasized methods that correspond to using Owen's (1988) method of empirical likelihood to reweight the data so that the reweighted sample obeys all the moment restrictions at the parameter estimates. In this paper we consider an alternative KLIC motivated weighting and show how it and similar discrete reweightings define a class of unconstrained optimization problems which includes GMM as a special case. Such KLIC-motivated reweightings introduce M auxiliary `tilting' parameters, where M is the number of moments; parameter and overidentification hypotheses can be recast in terms of these tilting parameters. Such tests, when appropriately conditioned on the estimates of the original parameters, are often startlingly more effective than their conventional counterparts. This is apparently due to the local ancillarity of the original parameters for the tilting parameters.
ER -