Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.
| From | Daniel Borowczyk Martins <stata.danielbm@gmail.com> |
| To | statalist@hsphsun2.harvard.edu |
| 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 * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/