我想可能是版本的问题，你可以下载一个最新的xtabond2命令。命令为：

ssc install xtabond2, replace

至于nomata选项，它的作用是不采用mata进行运算（mata的运算速度较快，但要求stata9.0以上版本），我当时在制作视频时之所以加入该选项，是为了防止部分学员的stata版本过低导致mata运算不可行。如果你使用的是stata10，可以去掉该选项。

连老师我重新下载了xtabond2命令，问题已经解决谢谢。但是发现运行该命令附加nomata和不附加nomata两个结果中的hansen检验P值不同，所运用的工具变量个数也不同，不知道是何原因？另外请教老师，Sargan 检验和Hansen检验出现矛盾时我们该如何判断和抉择谢谢！

. do "C:\DOCUME~1\ADMINI~1\LOCALS~1\Temp\STD03000000.tmp"

. xtabond2 contribution lcontribution lcontribution2 ldiffcontribution1 ldiffcontribution2,gmm(l
> contribution lcontribution2 ldiffcontribution1 ldiffcontribution2) nomata twostep robust small
Building GMM instruments.....
57 instrument(s) dropped because of collinearity.
Estimating.
Warning: Two-step estimated covariance matrix of moment conditions is singular.
Number of instruments may be large relative to number of groups.
Using a generalized inverse to calculate optimal weighting matrix for two-step estimation.
Computing Windmeijer finite-sample correction...................................................
> ..............................................................................................
> ....................
Performing specification tests.

Dynamic panel-data estimation, two-step system GMM
------------------------------------------------------------------------------
Group variable: subject                         Number of obs      =      1312
Time variable : period                          Number of groups   =       164
Number of instruments = 108                     Obs per group: min =         8
F(3, 163)     =     72.64                                      avg =      8.00
Prob > F      =     0.000                                      max =         8
------------------------------------------------------------------------------
             |              Corrected
contribution |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
lcontribut~n |   .8988869   .1153642     7.79   0.000     .6710859    1.126688
lcontribut~2 |   .1973221   .0441006     4.47   0.000     .1102399    .2844043
ldiffcontr~1 |  -.3376674   .1352491    -2.50   0.014    -.6047337   -.0706012
ldiffcontr~2 |  -.3964245   .1431313    -2.77   0.006    -.6790551   -.1137939
       _cons |  -1.292562   .7001243    -1.85   0.067    -2.675045    .0899204
------------------------------------------------------------------------------
Instruments for first differences equation
  GMM-type (missing=0, separate instruments for each period unless collapsed)
    L(1/.).(lcontribution lcontribution2 ldiffcontribution1
    ldiffcontribution2)
Instruments for levels equation
  Standard
    _cons
  GMM-type (missing=0, separate instruments for each period unless collapsed)
    D.(lcontribution lcontribution2 ldiffcontribution1 ldiffcontribution2)
------------------------------------------------------------------------------
Arellano-Bond test for AR(1) in first differences: z =  -5.68  Pr > z =  0.000
Arellano-Bond test for AR(2) in first differences: z =  -1.48  Pr > z =  0.140
------------------------------------------------------------------------------
Sargan test of overid. restrictions: chi2(103)  = 170.07  Prob > chi2 =  0.000
  (Not robust, but not weakened by many instruments.)
Hansen test of overid. restrictions: chi2(103)  = 120.55  Prob > chi2 =  0.114
  (Robust, but can be weakened by many instruments.)

.
end of do-file

. do "C:\DOCUME~1\ADMINI~1\LOCALS~1\Temp\STD03000000.tmp"

. xtabond2 contribution lcontribution lcontribution2 ldiffcontribution1 ldiffcontribution2,gmm(l
> contribution lcontribution2 ldiffcontribution1 ldiffcontribution2) twostep robust small
Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm.
Warning: Two-step estimated covariance matrix of moments is singular.
  Using a generalized inverse to calculate optimal weighting matrix for two-step estimation.
  Difference-in-Sargan/Hansen statistics may be negative.

Dynamic panel-data estimation, two-step system GMM
------------------------------------------------------------------------------
Group variable: subject                         Number of obs      =      1312
Time variable : period                          Number of groups   =       164
Number of instruments = 94                      Obs per group: min =         8
F(4, 163)     =     72.64                                      avg =      8.00
Prob > F      =     0.000                                      max =         8
------------------------------------------------------------------------------
             |              Corrected
contribution |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
lcontribut~n |   .8988869   .1153642     7.79   0.000     .6710859    1.126688
lcontribut~2 |   .1973221   .0441006     4.47   0.000     .1102399    .2844043
ldiffcontr~1 |  -.3376674   .1352491    -2.50   0.014    -.6047337   -.0706012
ldiffcontr~2 |  -.3964245   .1431313    -2.77   0.006    -.6790551   -.1137939
       _cons |  -1.292562   .7001243    -1.85   0.067    -2.675045    .0899204
------------------------------------------------------------------------------
Instruments for first differences equation
  GMM-type (missing=0, separate instruments for each period unless collapsed)
    L(1/.).(lcontribution lcontribution2 ldiffcontribution1
    ldiffcontribution2)
Instruments for levels equation
  Standard
    _cons
  GMM-type (missing=0, separate instruments for each period unless collapsed)
    D.(lcontribution lcontribution2 ldiffcontribution1 ldiffcontribution2)
------------------------------------------------------------------------------
Arellano-Bond test for AR(1) in first differences: z =  -5.68  Pr > z =  0.000
Arellano-Bond test for AR(2) in first differences: z =  -1.48  Pr > z =  0.140
------------------------------------------------------------------------------
Sargan test of overid. restrictions: chi2(89)   = 170.07  Prob > chi2 =  0.000
  (Not robust, but not weakened by many instruments.)
Hansen test of overid. restrictions: chi2(89)   = 120.55  Prob > chi2 =  0.015
  (Robust, but can be weakened by many instruments.)

Difference-in-Hansen tests of exogeneity of instrument subsets:
  GMM instruments for levels
    Hansen test excluding group:     chi2(73)   =  97.47  Prob > chi2 =  0.029
    Difference (null H = exogenous): chi2(16)   =  23.08  Prob > chi2 =  0.112

.
end of do-file

我此前并未注意到nomata选项会导致不同的结果。你可以看一下如下这篇文章，Roodman详细介绍了xtabond2这个命令，或许探讨了nomata选项。

Roodman, D., 2009, How to do Xtabond2: An Introduction to Difference and System GMM in Stata, The Stata Journal, 9 (1): 86-136.

Sargan和Hansen检验的区别在完成xtabond2估计后有提示：

Sargan test of overid. restrictions: chi2(89)   = 170.07  Prob > chi2 =  0.000
  (Not robust, but not weakened by many instruments.)
Hansen test of overid. restrictions: chi2(89)   = 120.55  Prob > chi2 =  0.015
  (Robust, but can be weakened by many instruments.)

二者的抉择问题，多少有点主观的因素在里面，所以不好判断。不过，就文献中的应用来看，多数学者都是报告Sargan检验值。就你的例子来看，工具变量数目较多，建议采用Sargan检验。

连老师以我的例子为例，报告Sargan检验值的话是否意味着我的模型设置不恰当需要重新选择工具变量？该如何选择比较好呢？麻烦了！

是的，从你的例子来看，sargan统计量拒绝了原假设，意味着模型设定存在问题。

不过，在使用xtabond2命令进行分析时，sargan检验在多数情况下都会拒绝原假设，这个问题我也很困惑，我猜测该检验在sys-GMM中可能存在过度拒绝的问题。

建议你使用FD-GMM做一下，看看sargan检验是否能通过。或者重新设定一下模型，新增一些控制变量或增加某些变量的滞后项，以便弱化序列相关问题。