Invalid name

[Dapeng Cheng]

Hi! I tried to replicate an example on the tutorials. https://www.stata.com/manuals13/rgmm.pdf (Example 12).
The code is

I copied this program and then run the code below.

use http://www.stata-press.com/data/r13/poisson2
gmm gmm_poiend, nequations(1) vce(cluster id) onestep > parameters(y:x1 y:x2 y:x3) instruments(x1 x2 L2.x3, noconstant)

but it showed that ‘mu’ invalid name.

Can anyone tell me why this happened? Thanks.

[Carlo Lazzaro]

Dapeng:
it works for me with Stata 16 (please note that I have only replaced 13 with 16 as far as -version- is concerned; no missing observations, though):

. program gmm_poiend
  1.
. version 16
  2.
. syntax varlist if, at(name)
  3.
. quietly {
  4.
. tempvar mu
  5.
. matrix score double `mu' = `at' `if', eq(#1)
  6.
. replace `mu' = exp(`mu')
  7.
. local mylhs : coleq `at'
  8.
. local mylhs : word 1 of `mylhs'
  9.
. replace `varlist' = `mylhs'/`mu' - L.`mylhs'/L.`mu' `if'
 10.
. }
 11.
. end

. use http://www.stata-press.com/data/r16/poisson2

. gmm gmm_poiend, nequations(1) vce(cluster id) onestep parameters(y:x1 y:x2 y:x3) instruments(x1 x2 L2.x3, noconstant)
note: 500 missing values returned for equation 1 at initial values

Step 1
Iteration 0:   GMM criterion Q(b) =  61.832288 
Iteration 1:   GMM criterion Q(b) =  .03402584 
Iteration 2:   GMM criterion Q(b) =  .01101288 
Iteration 3:   GMM criterion Q(b) =  6.339e-06 
Iteration 4:   GMM criterion Q(b) =  1.620e-12 
Iteration 5:   GMM criterion Q(b) =  1.312e-25 

note: model is exactly identified

GMM estimation

Number of parameters =   3
Number of moments    =   3
Initial weight matrix: Unadjusted                 Number of obs   =      3,766

                                   (Std. Err. adjusted for 500 clusters in id)
------------------------------------------------------------------------------
             |               Robust
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
          x1 |     1.8141   .2688318     6.75   0.000       1.2872    2.341001
          x2 |  -2.982671   .1086666   -27.45   0.000    -3.195653   -2.769688
          x3 |   4.126518   6.369334     0.65   0.517    -8.357147    16.61018
------------------------------------------------------------------------------
Instruments for equation 1: x1 x2 L2.x3

.

Caveat emptor: I've not delved into model (correct) specification, I've simply given it a try and check possible Stata gaspings along the way.

[Nick Cox]

See also #3 in https://www.statalist.org/forums/for...s-in-intervals by William Lisowski .

[Dapeng Cheng]

See also #3 in https://www.statalist.org/forums/for...s-in-intervals by William Lisowski .

Thanks, Nick! It is useful!

[Dapeng Cheng]

Dapeng:
it works for me with Stata 16 (please note that I have only replaced 13 with 16 as far as -version- is concerned; no missing observations, though):

. program gmm_poiend
1.
. version 16
2.
. syntax varlist if, at(name)
3.
. quietly {
4.
. tempvar mu
5.
. matrix score double `mu' = `at' `if', eq(#1)
6.
. replace `mu' = exp(`mu')
7.
. local mylhs : coleq `at'
8.
. local mylhs : word 1 of `mylhs'
9.
. replace `varlist' = `mylhs'/`mu' - L.`mylhs'/L.`mu' `if'
10.
. }
11.
. end

. use http://www.stata-press.com/data/r16/poisson2

. gmm gmm_poiend, nequations(1) vce(cluster id) onestep parameters(y:x1 y:x2 y:x3) instruments(x1 x2 L2.x3, noconstant)
note: 500 missing values returned for equation 1 at initial values

Step 1
Iteration 0: GMM criterion Q(b) = 61.832288
Iteration 1: GMM criterion Q(b) = .03402584
Iteration 2: GMM criterion Q(b) = .01101288
Iteration 3: GMM criterion Q(b) = 6.339e-06
Iteration 4: GMM criterion Q(b) = 1.620e-12
Iteration 5: GMM criterion Q(b) = 1.312e-25

note: model is exactly identified

GMM estimation

Number of parameters = 3
Number of moments = 3
Initial weight matrix: Unadjusted Number of obs = 3,766

(Std. Err. adjusted for 500 clusters in id)
------------------------------------------------------------------------------
| Robust
| Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
x1 | 1.8141 .2688318 6.75 0.000 1.2872 2.341001
x2 | -2.982671 .1086666 -27.45 0.000 -3.195653 -2.769688
x3 | 4.126518 6.369334 0.65 0.517 -8.357147 16.61018
------------------------------------------------------------------------------
Instruments for equation 1: x1 x2 L2.x3

.

Caveat emptor: I've not delved into model (correct) specification, I've simply given it a try and check possible Stata gaspings along the way.

Thanks, Carlo!