ordered probit IV using cmp

[Adeola Kolade]

Dear all,
I am using the cmp command for instrumental variable in my ordered probit model. I got this result but I don't know how to interpret it. I don't know how to tell if my independent variable is endogenous from this result, which is 1st or 2nd stage, what tells me if the instrument is weak, how do I get the f statistics? many thanks.

isced1997_r

=independent variable,

sl_hs045d2= dependent variable, dn033_1=instrument

This is the command and the result.

cmp (isced1997_r = sl_hs045d2) (sl_hs045d2 = dn033_1), ind($cmp_oprobit $cmp_probit)nolr

Fitting individual models as starting point for full model fit.
Note: For programming reasons, these initial estimates may deviate from your specification.
For exact fits of each equation alone, run cmp separately on each.

Iteration 0: log likelihood = -11462.671
Iteration 1: log likelihood = -11454.183
Iteration 2: log likelihood = -11454.183

Ordered probit regression Number of obs = 7,794
LR chi2(1) = 16.98
Prob > chi2 = 0.0000
Log likelihood = -11454.183 Pseudo R2 = 0.0007

------------------------------------------------------------------------------
_cmp_y1 | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
sl_hs045d2 | -.1862259 .0452082 -4.12 0.000 -.2748323 -.0976195
-------------+----------------------------------------------------------------
/cut1 | -1.078698 .0179396 -1.113859 -1.043537
/cut2 | -.4399117 .015115 -.4695365 -.4102868
/cut3 | .4644665 .0151765 .4347211 .494212
/cut4 | .5817112 .0155064 .5513192 .6121031
/cut5 | 2.601518 .0577342 2.488361 2.714675
------------------------------------------------------------------------------

Iteration 0: log likelihood = -536.06062
Iteration 1: log likelihood = -536.03597
Iteration 2: log likelihood = -536.03597

Probit regression Number of obs = 2,010
LR chi2(1) = 0.05
Prob > chi2 = 0.8243
Log likelihood = -536.03597 Pseudo R2 = 0.0000

------------------------------------------------------------------------------
sl_hs045d2 | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
dn033_1 | -.0081992 .0369023 -0.22 0.824 -.0805264 .064128
_cons | -1.410154 .1346613 -10.47 0.000 -1.674086 -1.146223
------------------------------------------------------------------------------

Fitting full model.

Iteration 0: log likelihood = -11990.235
Iteration 1: log likelihood = -11990.216
Iteration 2: log likelihood = -11990.216

Mixed-process regression Number of obs = 7,794
Wald chi2(2) = 11.69
Log likelihood = -11990.216 Prob > chi2 = 0.0029

------------------------------------------------------------------------------
| Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
isced1997_r |
sl_hs045d2 | -.1840948 .0539897 -3.41 0.001 -.2899128 -.0782769
-------------+----------------------------------------------------------------
sl_hs045d2 |
dn033_1 | -.0082522 .0369107 -0.22 0.823 -.0805959 .0640915
_cons | -1.409138 .1354056 -10.41 0.000 -1.674528 -1.143748
-------------+----------------------------------------------------------------
/cut_1_1 | -1.078535 .0180819 -59.65 0.000 -1.113975 -1.043096
/cut_1_2 | -.4397479 .0152849 -28.77 0.000 -.4697058 -.4097899
/cut_1_3 | .4646277 .0153394 30.29 0.000 .4345631 .4946923
/cut_1_4 | .5818718 .0156645 37.15 0.000 .5511699 .6125736
/cut_1_5 | 2.601698 .0577884 45.02 0.000 2.488435 2.714962
/atanhrho_12 | -.0041086 .0569038 -0.07 0.942 -.115638 .1074208
-------------+----------------------------------------------------------------
rho_12 | -.0041086 .0569028 -.1151253 .1070095
------------------------------------------------------------------------------

[Phil Bromiley]

You didn't get a quick answer. cmp is user written although widely used. You may need to contact the author to answer questions.

[Adeola Kolade]

Many thanks.