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st: xtdpd two-step robust estimates
From
Daniel Borowczyk Martins <[email protected]>
To
[email protected]
Subject
st: xtdpd two-step robust estimates
Date
Thu, 29 Jul 2010 11:54:11 +0100
Dear Stata users,
I am experiencing a problem with xtdpd. Maybe you're familiar with
this problem and can help me solve it.
Basically, I cannot mimic some of the estimations I do using xtabond2.
In particular, xtdpd reports an error (estimates post: matrix has
missing values) when I choose options robust standard errors,
twostep, or both.
1. I start by implemeting a one-step difference GMM procedure using
both commands. The results are almost the same.
xtdpd md_jfr md_omg, dg(md_omg, l(2 6)) nocons
Dynamic panel-data estimation Number of obs = 12854
Group variable: i Number of groups = 275
Time variable: t
Obs per group: min = 19
avg = 46.74182
max = 47
Number of instruments = 220 Wald chi2(1) = 32.94
Prob > chi2 = 0.0000
One-step results
md_jfr Coef. Std. Err. z P>z [95% Conf. Interval]
md_omg .0342955 .0059756 5.74 0.000 .0225835 .0460075
Instruments for differenced equation
GMM-type: L(2/6).md_omg
xtabond2 md_jfr omg_md, gmm(md_omg, l(2 6)) noleveleq
Dynamic panel-data estimation, one-step difference GMM
Group variable: i Number of obs = 12852
Time variable : t Number of groups = 275
Number of instruments = 220 Obs per group: min = 19
Wald chi2(1) = 32.50 avg = 46.73
Prob > chi2 = 0.000 max = 47
md_jfr Coef. Std. Err. z P>z [95% Conf. Interval]
md_omg .0340472 .0059719 5.70 0.000 .0223424 .0457519
Instruments for first differences equation
GMM-type (missing=0, separate instruments for each period unless collapsed)
L(2/6).md_omg
Arellano-Bond test for AR(1) in first differences: z = -40.63 Pr > z = 0.000
Arellano-Bond test for AR(2) in first differences: z = -1.86 Pr > z = 0.062
Sargan test of overid. restrictions: chi2(219) =1084.45 Prob > chi2 = 0.000
(Not robust, but not weakened by many instruments.)
2. Now if I ask for robust standard errors, xtabond2 completes the
task with no problem, but xtdpd reports the error above.
xtabond2 md_jfr omg_md, gmm(md_omg, l(2 6)) noleveleq robust
Favoring space over speed. To switch, type or click on mata: mata set
matafavor speed, perm.
Dynamic panel-data estimation, one-step difference GMM
Group variable: i Number of obs = 12852
Time variable : t Number of groups = 275
Number of instruments = 220 Obs per group: min = 19
Wald chi2(1) = 5.27 avg = 46.73
Prob > chi2 = 0.022 max = 47
Robust
md_jfr Coef. Std. Err. z P>z [95% Conf. Interval]
md_omg .0340472 .014833 2.30 0.022 .004975 .0631193
Instruments for first differences equation
GMM-type (missing=0, separate instruments for each period unless collapsed)
L(2/6).md_omg
Arellano-Bond test for AR(1) in first differences: z = -6.52 Pr > z = 0.000
Arellano-Bond test for AR(2) in first differences: z = -0.98 Pr > z = 0.329
Sargan test of overid. restrictions: chi2(219) =1084.45 Prob > chi2 = 0.000
(Not robust, but not weakened by many instruments.)
Hansen test of overid. restrictions: chi2(219) = 242.76 Prob > chi2 = 0.130
(Robust, but can be weakened by many instruments.)
xtdpd md_jfr md_omg, dg(md_omg, l(2 6)) nocons vce(robust)
estimates post: matrix has missing values
r(504);
3. The same problem occurs if I ask xtdpd for twostep and twostep and
robust standard errors.
4. I tried to assess whether the error might be related with the
number of instruments and/or the covariance matrix of moments being
singular. This because when that is the case, xtabond2 uses a
generalized inverse to calculate optimal weighting matrix for two-step
estimation. My analysis suggests this is not where the problem lies.
Do you have an idea of what's going on and how I can implement twostep
and robust ses options using xtdpd?
Cheers,
Daniel
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