Basically , the qustion is: why sargan test statistic changes a lot by including and excluding one variable in gmmstyle option.
In my regression, tobin_q in the main explanatory variable, and could be influenced by past dependent variable. So, it should be included in the gmmstyle option, right? However, I find the results are very different by including and excluding it in the gmmstyle option. I do not know why?
I checked Roodman's paper, but I did not find a clear cut answer. On page 38 of Roodman (2008) paper, I find "As a result, most regressors appear twice in a command line, once before the comma for inclusion in X, once after as a source of IV- or GMM-style instruments."
Does this mean it is okay to leave tobin_q out of the gmmstyle option?
Thank you very much.
1. excluding the tobin_q from the gmm option
xi: xtabond2 ownershipratiosum l.ownershipratiosum l2.ownershipratiosum ///
L(0/2).(tobin_q logsales sigma divratio) ///
logfirmage i.calyear , ///
gmm(ownershipratiosum logsales sigma divratio, lag(3 .) collapse ) iv(i.calyear logfirmage ) ///
ar(5) twostep robust small
results:
Arellano-Bond test for AR(1) in first differences: z = -3.54 Pr > z = 0.000
Arellano-Bond test for AR(2) in first differences: z = -0.03 Pr > z = 0.979
Arellano-Bond test for AR(3) in first differences: z = -0.13 Pr > z = 0.900
Arellano-Bond test for AR(4) in first differences: z = 1.27 Pr > z = 0.203
Arellano-Bond test for AR(5) in first differences: z = -0.84 Pr > z = 0.402
------------------------------------------------------------------------------
Sargan test of overid. restrictions: chi2(54) = 66.72 Prob > chi2 = 0.115
(Not robust, but not weakened by many instruments.)
Hansen test of overid. restrictions: chi2(54) = 62.80 Prob > chi2 = 0.193
(Robust, but can be weakened by many instruments.)
2. including the tobin_q in the gmmoption
xi: xtabond2 ownershipratiosum l.ownershipratiosum l2.ownershipratiosum ///
L(0/2).(tobin_q logsales sigma divratio) ///
logfirmage i.calyear , ///
gmm(ownershipratiosum tobin_q logsales sigma divratio, lag(3 .) collapse ) iv(i.calyear logfirmage ) ///
ar(5) twostep robust small
results:
Arellano-Bond test for AR(1) in first differences: z = -4.35 Pr > z = 0.000
Arellano-Bond test for AR(2) in first differences: z = 0.93 Pr > z = 0.353
Arellano-Bond test for AR(3) in first differences: z = -1.28 Pr > z = 0.201
Arellano-Bond test for AR(4) in first differences: z = 1.45 Pr > z = 0.146
Arellano-Bond test for AR(5) in first differences: z = -1.17 Pr > z = 0.242
------------------------------------------------------------------------------
Sargan test of overid. restrictions: chi2(71) = 135.92 Prob > chi2 = 0.000
(Not robust, but not weakened by many instruments.)
Hansen test of overid. restrictions: chi2(71) = 98.38 Prob > chi2 = 0.017
(Robust, but can be weakened by many instruments.)
In my regression, tobin_q in the main explanatory variable, and could be influenced by past dependent variable. So, it should be included in the gmmstyle option, right? However, I find the results are very different by including and excluding it in the gmmstyle option. I do not know why?
I checked Roodman's paper, but I did not find a clear cut answer. On page 38 of Roodman (2008) paper, I find "As a result, most regressors appear twice in a command line, once before the comma for inclusion in X, once after as a source of IV- or GMM-style instruments."
Does this mean it is okay to leave tobin_q out of the gmmstyle option?
Thank you very much.
1. excluding the tobin_q from the gmm option
xi: xtabond2 ownershipratiosum l.ownershipratiosum l2.ownershipratiosum ///
L(0/2).(tobin_q logsales sigma divratio) ///
logfirmage i.calyear , ///
gmm(ownershipratiosum logsales sigma divratio, lag(3 .) collapse ) iv(i.calyear logfirmage ) ///
ar(5) twostep robust small
results:
Arellano-Bond test for AR(1) in first differences: z = -3.54 Pr > z = 0.000
Arellano-Bond test for AR(2) in first differences: z = -0.03 Pr > z = 0.979
Arellano-Bond test for AR(3) in first differences: z = -0.13 Pr > z = 0.900
Arellano-Bond test for AR(4) in first differences: z = 1.27 Pr > z = 0.203
Arellano-Bond test for AR(5) in first differences: z = -0.84 Pr > z = 0.402
------------------------------------------------------------------------------
Sargan test of overid. restrictions: chi2(54) = 66.72 Prob > chi2 = 0.115
(Not robust, but not weakened by many instruments.)
Hansen test of overid. restrictions: chi2(54) = 62.80 Prob > chi2 = 0.193
(Robust, but can be weakened by many instruments.)
2. including the tobin_q in the gmmoption
xi: xtabond2 ownershipratiosum l.ownershipratiosum l2.ownershipratiosum ///
L(0/2).(tobin_q logsales sigma divratio) ///
logfirmage i.calyear , ///
gmm(ownershipratiosum tobin_q logsales sigma divratio, lag(3 .) collapse ) iv(i.calyear logfirmage ) ///
ar(5) twostep robust small
results:
Arellano-Bond test for AR(1) in first differences: z = -4.35 Pr > z = 0.000
Arellano-Bond test for AR(2) in first differences: z = 0.93 Pr > z = 0.353
Arellano-Bond test for AR(3) in first differences: z = -1.28 Pr > z = 0.201
Arellano-Bond test for AR(4) in first differences: z = 1.45 Pr > z = 0.146
Arellano-Bond test for AR(5) in first differences: z = -1.17 Pr > z = 0.242
------------------------------------------------------------------------------
Sargan test of overid. restrictions: chi2(71) = 135.92 Prob > chi2 = 0.000
(Not robust, but not weakened by many instruments.)
Hansen test of overid. restrictions: chi2(71) = 98.38 Prob > chi2 = 0.017
(Robust, but can be weakened by many instruments.)
Comment