Object Reference : Object View and Procedure Reference : System
  
 
gmm
Estimation by generalized method of moments (GMM).
The system object must be specified with a list of instruments.
Syntax
system_name.gmm(options)
Options
 
m=integer
Maximum number of iterations.
c=number
Set convergence criterion. The criterion is based upon the maximum of the percentage changes in the scaled coefficients. The criterion will be set to the nearest value between 1e-24 and 0.2.
l=number
Set maximum number of iterations on the first-stage iteration to get the one-step weighting matrix.
numericderiv / ‑numericderiv
[Do / do not] use numeric derivatives only. If omitted, EViews will follow the global default.
fastderiv / ‑fastderiv
[Do / do not] use fast derivative computation. If omitted, EViews will follow the global default.
showopts / ‑showopts
[Do / do not] display the starting coefficient values and estimation options in the estimation output.
w
Use White’s diagonal weighting matrix (for cross section data).
b=arg (default=“nw”)
Specify the bandwidth: “nw” (Newey-West fixed bandwidth based on the number of observations), number (user specified bandwidth), “v” (Newey-West automatic variable bandwidth selection), “a” (Andrews automatic selection).
q
Use the quadratic kernel. Default is to use the Bartlett kernel.
n
Prewhiten by a first order VAR before estimation.
i
Iterate simultaneously over the weighting matrix and the coefficient vector.
s
Iterate sequentially over the weighting matrix and coefficient vector.
o (default)
Iterate only on the coefficient vector with one step of the weighting matrix.
c
One step (iteration) of the coefficient vector following one step of the weighting matrix.
e
TSLS estimates with GMM standard errors.
prompt
Force the dialog to appear from within a program.
p
Print results.
Note that some options are only available for a subset of specifications.
Examples
For system estimation, the command:
sys1.gmm(b=a, q, i)
estimates the system SYS1 by GMM with a quadratic kernel, Andrews automatic bandwidth selection, and iterates simultaneously over the weight and coefficient vectors until convergence.
Cross-references
See “Additional Regression Tools” and “System Estimation” for discussion of the various GMM estimation techniques.