An Analysis on Danish Micro Data - School of Economics and ...
An Analysis on Danish Micro Data - School of Economics and ...
An Analysis on Danish Micro Data - School of Economics and ...
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.<br />
. /*Panel probit same as Galarraga - with proxy*/<br />
. xtprobit emp ad_dummy mtx wageinc age ab02 ab36 ab79 ab1014 single iel<strong>and</strong>1 ie<br />
> l<strong>and</strong>2 short higher agesq use<strong>of</strong>medicin u<br />
Fitting comparis<strong>on</strong> model:<br />
Iterati<strong>on</strong> 0: log likelihood = -2397.2264<br />
Iterati<strong>on</strong> 1: log likelihood = -1170.2482<br />
Iterati<strong>on</strong> 2: log likelihood = -906.5375<br />
Iterati<strong>on</strong> 3: log likelihood = -849.72244<br />
Iterati<strong>on</strong> 4: log likelihood = -842.85539<br />
Iterati<strong>on</strong> 5: log likelihood = -842.71697<br />
Iterati<strong>on</strong> 6: log likelihood = -842.7169<br />
Fitting full model:<br />
rho = 0.0 log likelihood = -842.71689<br />
rho = 0.1 log likelihood = -776.54617<br />
rho = 0.2 log likelihood = -740.88172<br />
rho = 0.3 log likelihood = -720.72813<br />
rho = 0.4 log likelihood = -711.35509<br />
rho = 0.5 log likelihood = -711.37265<br />
Iterati<strong>on</strong> 0: log likelihood = -711.35511<br />
Iterati<strong>on</strong> 1: log likelihood = -653.0012<br />
Iterati<strong>on</strong> 2: log likelihood = -631.34757<br />
Iterati<strong>on</strong> 3: log likelihood = -624.6963<br />
Iterati<strong>on</strong> 4: log likelihood = -623.697<br />
Iterati<strong>on</strong> 5: log likelihood = -623.67158<br />
Iterati<strong>on</strong> 6: log likelihood = -623.67156<br />
R<strong>and</strong>om-effects probit regressi<strong>on</strong> Number <strong>of</strong> obs = 3508<br />
Group variable (i): udtrnr Number <strong>of</strong> groups = 1202<br />
R<strong>and</strong>om effects u_i ~ Gaussian Obs per group: min = 1<br />
avg = 2.9<br />
max = 9<br />
Wald chi2(16) = 243.28<br />
Log likelihood = -623.67156 Prob > chi2 = 0.0000<br />
------------------------------------------------------------------------------<br />
emp | Coef. Std. Err. z P>|z| [95% C<strong>on</strong>f. Interval]<br />
-------------+----------------------------------------------------------------<br />
ad_dummy | -.3334316 .2447323 -1.36 0.173 -.8130981 .146235<br />
mtx | -.0005216 .0007189 -0.73 0.468 -.0019305 .0008874<br />
wageinc | .0000341 2.26e-06 15.05 0.000 .0000297 .0000385<br />
age | .0399983 .0584284 0.68 0.494 -.0745193 .1545158<br />
ab02 | -.272244 .4634026 -0.59 0.557 -1.180496 .6360084<br />
ab36 | -.6195473 .3603268 -1.72 0.086 -1.325775 .0866802<br />
ab79 | -.2887016 .3451986 -0.84 0.403 -.9652785 .3878753<br />
ab1014 | -.583789 .2515078 -2.32 0.020 -1.076735 -.0908427<br />
single | -.7538968 .2069677 -3.64 0.000 -1.159546 -.3482476<br />
iel<strong>and</strong>1 | .8326754 .8543805 0.97 0.330 -.8418796 2.50723<br />
iel<strong>and</strong>2 | 1.475047 .942306 1.57 0.117 -.3718391 3.321932<br />
short | .6950118 .2112231 3.29 0.001 .2810222 1.109001<br />
higher | -.0771721 .2840773 -0.27 0.786 -.6339533 .4796092<br />
agesq | -.0012727 .0006447 -1.97 0.048 -.0025363 -9.08e-06<br />
use<strong>of</strong>medicin | -.0004527 .0001139 -3.97 0.000 -.0006761 -.0002294<br />
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