I'm running etregress in Stata 14. It gives me a "convergence not achieved" message but that occurs before the iteration log. It also says "missing standard errors indicate some of the parameters are not identified" but there are no missing standard errors.
I can't provide a data example due to size, but the output is below. Should I be worrying about the convergence message before the iterations? Suggestions please.
Phil
etregress FmtbAve1_3 L1mtb L1ind_mtb F1ind_mtb L1roa L1ind_roa F1ind_roa L1at L1revt Lboardsize LNcaucasian1 LNmen LNoutsidebd ///
> if use==1, treat(Null= Ldatadate L1ind_at L1ind_ebit L1ind_roa L1mkt_value L1revt L1roa L2bkvlps L2ebit L2ind_at L2ind_ebit L2ind_mtb LAllWhite Lap Laqc ) ///
> vce(robust)
convergence not achieved
The Gauss-Newton stopping criterion has been met but missing standard errors indicate some of the parameters are not identified.
Iteration 0: log pseudolikelihood = -8607.2694
Iteration 1: log pseudolikelihood = -8533.9854
Iteration 2: log pseudolikelihood = -8531.806
Iteration 3: log pseudolikelihood = -8531.7975
Iteration 4: log pseudolikelihood = -8531.7975
Linear regression with endogenous treatment Number of obs = 3,344
Estimator: maximum likelihood Wald chi2(13) = 696.40
Log pseudolikelihood = -8531.7975 Prob > chi2 = 0.0000
------------------------------------------------------------------------------
| Robust
| Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
FmtbAve1_3 |
L1mtb | .6173737 .0476638 12.95 0.000 .5239544 .710793
L1ind_mtb | -.00173 .0017342 -1.00 0.318 -.0051289 .0016689
F1ind_mtb | .6458511 .1032618 6.25 0.000 .4434616 .8482406
L1roa | .0329101 .0094866 3.47 0.001 .0143168 .0515035
L1ind_roa | -6.416385 1.877586 -3.42 0.001 -10.09638 -2.736385
F1ind_roa | -1.36676 3.651841 -0.37 0.708 -8.524237 5.790718
L1at | -.1263021 .1593853 -0.79 0.428 -.4386915 .1860873
L1revt | .7646522 1.074971 0.71 0.477 -1.342251 2.871556
Lboardsize | .1418719 .0378133 3.75 0.000 .0677592 .2159846
LNcaucasian1 | -.0554023 .024755 -2.24 0.025 -.1039212 -.0068833
LNmen | -.1094744 .0323472 -3.38 0.001 -.1728736 -.0460751
LNoutsidebd | .0012599 .0052522 0.24 0.810 -.0090342 .011554
1.Null | -2.059116 .4950943 -4.16 0.000 -3.029483 -1.088749
_cons | .4653399 .1935304 2.40 0.016 .0860273 .8446525
-------------+----------------------------------------------------------------
Null |
Ldatadate | -.0002607 .0000541 -4.82 0.000 -.0003667 -.0001546
L1ind_at | -6.06e-08 2.79e-08 -2.17 0.030 -1.15e-07 -5.95e-09
L1ind_ebit | 2.17e-07 3.31e-07 0.65 0.513 -4.32e-07 8.65e-07
L1ind_roa | -1.172686 .9978161 -1.18 0.240 -3.12837 .7829973
L1mkt_value | -1.24e-06 1.58e-06 -0.79 0.432 -4.33e-06 1.85e-06
L1revt | -.6133746 1.521015 -0.40 0.687 -3.59451 2.367761
L1roa | -.0019713 .0039945 -0.49 0.622 -.0098003 .0058577
L2bkvlps | .0010208 .0007754 1.32 0.188 -.000499 .0025406
L2ebit | -5.08e-06 3.90e-06 -1.30 0.193 -.0000127 2.57e-06
L2ind_at | 5.90e-08 2.75e-08 2.14 0.032 5.00e-09 1.13e-07
L2ind_ebit | 1.79e-07 3.09e-07 0.58 0.561 -4.26e-07 7.85e-07
L2ind_mtb | -.0041626 .0441417 -0.09 0.925 -.0906788 .0823535
LAllWhite | .1284362 .0474345 2.71 0.007 .0354663 .221406
Lap | 1.02e-06 3.37e-07 3.02 0.003 3.57e-07 1.68e-06
Laqc | .0000155 9.89e-06 1.57 0.117 -3.89e-06 .0000349
_cons | 4.174541 1.029673 4.05 0.000 2.156419 6.192662
-------------+----------------------------------------------------------------
/athrho | .7655414 .1885081 4.06 0.000 .3960722 1.135011
/lnsigma | .7015973 .1008839 6.95 0.000 .5038685 .899326
-------------+----------------------------------------------------------------
rho | .6443294 .110247 .3765832 .8127272
sigma | 2.016972 .2034799 1.655112 2.457946
lambda | 1.299594 .3400837 .6330424 1.966146
------------------------------------------------------------------------------
Wald test of indep. eqns. (rho = 0): chi2(1) = 16.49 Prob > chi2 = 0.0000
I can't provide a data example due to size, but the output is below. Should I be worrying about the convergence message before the iterations? Suggestions please.
Phil
etregress FmtbAve1_3 L1mtb L1ind_mtb F1ind_mtb L1roa L1ind_roa F1ind_roa L1at L1revt Lboardsize LNcaucasian1 LNmen LNoutsidebd ///
> if use==1, treat(Null= Ldatadate L1ind_at L1ind_ebit L1ind_roa L1mkt_value L1revt L1roa L2bkvlps L2ebit L2ind_at L2ind_ebit L2ind_mtb LAllWhite Lap Laqc ) ///
> vce(robust)
convergence not achieved
The Gauss-Newton stopping criterion has been met but missing standard errors indicate some of the parameters are not identified.
Iteration 0: log pseudolikelihood = -8607.2694
Iteration 1: log pseudolikelihood = -8533.9854
Iteration 2: log pseudolikelihood = -8531.806
Iteration 3: log pseudolikelihood = -8531.7975
Iteration 4: log pseudolikelihood = -8531.7975
Linear regression with endogenous treatment Number of obs = 3,344
Estimator: maximum likelihood Wald chi2(13) = 696.40
Log pseudolikelihood = -8531.7975 Prob > chi2 = 0.0000
------------------------------------------------------------------------------
| Robust
| Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
FmtbAve1_3 |
L1mtb | .6173737 .0476638 12.95 0.000 .5239544 .710793
L1ind_mtb | -.00173 .0017342 -1.00 0.318 -.0051289 .0016689
F1ind_mtb | .6458511 .1032618 6.25 0.000 .4434616 .8482406
L1roa | .0329101 .0094866 3.47 0.001 .0143168 .0515035
L1ind_roa | -6.416385 1.877586 -3.42 0.001 -10.09638 -2.736385
F1ind_roa | -1.36676 3.651841 -0.37 0.708 -8.524237 5.790718
L1at | -.1263021 .1593853 -0.79 0.428 -.4386915 .1860873
L1revt | .7646522 1.074971 0.71 0.477 -1.342251 2.871556
Lboardsize | .1418719 .0378133 3.75 0.000 .0677592 .2159846
LNcaucasian1 | -.0554023 .024755 -2.24 0.025 -.1039212 -.0068833
LNmen | -.1094744 .0323472 -3.38 0.001 -.1728736 -.0460751
LNoutsidebd | .0012599 .0052522 0.24 0.810 -.0090342 .011554
1.Null | -2.059116 .4950943 -4.16 0.000 -3.029483 -1.088749
_cons | .4653399 .1935304 2.40 0.016 .0860273 .8446525
-------------+----------------------------------------------------------------
Null |
Ldatadate | -.0002607 .0000541 -4.82 0.000 -.0003667 -.0001546
L1ind_at | -6.06e-08 2.79e-08 -2.17 0.030 -1.15e-07 -5.95e-09
L1ind_ebit | 2.17e-07 3.31e-07 0.65 0.513 -4.32e-07 8.65e-07
L1ind_roa | -1.172686 .9978161 -1.18 0.240 -3.12837 .7829973
L1mkt_value | -1.24e-06 1.58e-06 -0.79 0.432 -4.33e-06 1.85e-06
L1revt | -.6133746 1.521015 -0.40 0.687 -3.59451 2.367761
L1roa | -.0019713 .0039945 -0.49 0.622 -.0098003 .0058577
L2bkvlps | .0010208 .0007754 1.32 0.188 -.000499 .0025406
L2ebit | -5.08e-06 3.90e-06 -1.30 0.193 -.0000127 2.57e-06
L2ind_at | 5.90e-08 2.75e-08 2.14 0.032 5.00e-09 1.13e-07
L2ind_ebit | 1.79e-07 3.09e-07 0.58 0.561 -4.26e-07 7.85e-07
L2ind_mtb | -.0041626 .0441417 -0.09 0.925 -.0906788 .0823535
LAllWhite | .1284362 .0474345 2.71 0.007 .0354663 .221406
Lap | 1.02e-06 3.37e-07 3.02 0.003 3.57e-07 1.68e-06
Laqc | .0000155 9.89e-06 1.57 0.117 -3.89e-06 .0000349
_cons | 4.174541 1.029673 4.05 0.000 2.156419 6.192662
-------------+----------------------------------------------------------------
/athrho | .7655414 .1885081 4.06 0.000 .3960722 1.135011
/lnsigma | .7015973 .1008839 6.95 0.000 .5038685 .899326
-------------+----------------------------------------------------------------
rho | .6443294 .110247 .3765832 .8127272
sigma | 2.016972 .2034799 1.655112 2.457946
lambda | 1.299594 .3400837 .6330424 1.966146
------------------------------------------------------------------------------
Wald test of indep. eqns. (rho = 0): chi2(1) = 16.49 Prob > chi2 = 0.0000
Comment