Hi there,

I have estimated a dynamic linear panel regression with new command "xtdpdgmm" following the slides provided by
PHP Code:
Sebastian Kripfganz 
However, I am receiving warnings or signals in the output as
* asymptotically invalid if the one-step weighting matrix is not optimal
.

Code:
xtdpdgmm L(0/1).Y X1 X2, model(fodev) gmm(X1 X2, lag(0 2)) vce(r)

Code:
Generalized method of moments estimation

Fitting full model:
Step 1         f(b) =  .00862567

Group variable: id                           Number of obs         =      3877
Time variable: year                          Number of groups      =       138

Moment conditions:     linear =     277      Obs per group:    min =         1
                    nonlinear =       0                        avg =   28.0942
                        total =     277                        max =        47

                                   (Std. Err. adjusted for 138 clusters in id)
------------------------------------------------------------------------------
             |               Robust
        Y   |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        Y  |
         L1. |   .2349892    .055445     4.24   0.000     .1263189    .3436594
             |
      X1|   .0199681   .0091513     2.18   0.029      .002032    .0379043
    X2|  -.0052541   .0016753    -3.14   0.002    -.0085377   -.0019705
       _cons |   .0029555   .0078291     0.38   0.706    -.0123893    .0183003
------------------------------------------------------------------------------
Instruments corresponding to the linear moment conditions:
1, omitted for space
 2, model(level):
   _cons

. estat serial, ar(1/3)

Arellano-Bond test for autocorrelation of the first-differenced residuals
H0: no autocorrelation of order 1:     z =   -1.8644   Prob > |z|  =    0.0623
H0: no autocorrelation of order 2:     z =    0.6648   Prob > |z|  =    0.5062
H0: no autocorrelation of order 3:     z =    2.2343   Prob > |z|  =    0.0255

. estat overid

Sargan-Hansen test of the overidentifying restrictions
H0: overidentifying restrictions are valid

1-step moment functions, 1-step weighting matrix       chi2(273)   =  616.0026
note: *                                                Prob > chi2 =    0.0000

1-step moment functions, 2-step weighting matrix       chi2(273)   =  130.9023
note: *                                                Prob > chi2 =    1.0000

* asymptotically invalid if the one-step weighting matrix is not optimal
Please let me know what should I do to correct the warnings and to make 1-step moment functions, 1-step weighting matrix insignificant (the p value is 0.000)