The GMM Parameter Normalization Puzzle
30 Pages Posted: 26 Oct 1999
Date Written: August 20, 1997
Abstract
A feature of GMM estimation--the use of a consistent estimate of the optimal weighting matrix rather than the joint estimation of the model parameters and the weighting matrix--can lead to the sensitivity of GMM estimation to the choice of parameter normalization. In many applications, including Euler equation estimation, a model parameter multiplies the equation error in some, but not all, normalizations. But, conventional GMM estimators that either hold the estimate of the weighting matrix fixed or allow some limited iteration on the weighting matrix fail to account for the dependence of the weighting matrix on the parameter vector implied by the multiplication of the error by the parameter. In finite samples, GMM effectively minimizes the square of the parameter times the objective function that obtains from an alternative normalization where no parameter multiplies the equation error, resulting in estimates that are smaller (in absolute value) than those from the alternative normalization. Of course, normalization is irrelevant asymptotically.
JEL Classification: C13, C51, E24, C81
Suggested Citation: Suggested Citation
Do you have a job opening that you would like to promote on SSRN?
Recommended Papers
-
By Valerie A. Ramey and Kenneth D. West
-
What Inventory Behavior Tells Us About Business Cycles
By Mark Bils and James A. Kahn
-
What Inventory Behavior Tells Us About Business Cycles
By Mark Bils and James A. Kahn
-
The Production and Inventory Behavior of the American Automobile Industry
-
Can the Production Smoothing Model of Inventory Behavior Be Saved?
-
A Variance Bounds Test of the Linear Quardractic Inventory Model
-
Inventories and the Business Cycle: An Equilibrium Analysis of (S,S) Policies
By Aubhik Khan and Julia K. Thomas