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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higher | .0160771 .2154333 0.07 0.941 -.4061645 .4383187<br />
agesq | .0003125 .0005689 0.55 0.583 -.0008025 .0014276<br />
use<strong>of</strong>medicin | -.0001419 .000106 -1.34 0.181 -.0003497 .0000659<br />
u | -.1076506 .0671388 -1.60 0.109 -.2392401 .023939<br />
_c<strong>on</strong>s | .317934 1.272168 0.25 0.803 -2.17547 2.811338<br />
------------------------------------------------------------------------------<br />
note: 0 failures <strong>and</strong> 14 successes completely determined.<br />
.<br />
. mfx<br />
Marginal effects after probit<br />
y = Pr(emp) (predict)<br />
= .77301569<br />
------------------------------------------------------------------------------<br />
variable | dy/dx Std. Err. z P>|z| [ 95% C.I. ] X<br />
---------+--------------------------------------------------------------------<br />
c<strong>on</strong>s_a~p | -.0000136 .00005 -0.28 0.782 -.00011 .000083 86.6774<br />
mtx | .0001923 .00027 0.72 0.469 -.000328 .000712 220.258<br />
wageinc | 5.60e-06 .00000 14.40 0.000 4.8e-06 6.4e-06 115135<br />
age | -.0142939 .01515 -0.94 0.346 -.043997 .015409 49.9776<br />
ab02*| .1381092 .07496 1.84 0.065 -.008808 .285026 .031034<br />
ab36*| -.0311281 .11184 -0.28 0.781 -.250334 .188078 .063793<br />
ab79*| .0713519 .07532 0.95 0.343 -.076263 .218967 .067241<br />
ab1014*| .0322971 .07371 0.44 0.661 -.112163 .176757 .136207<br />
single*| -.0177156 .06511 -0.27 0.786 -.145335 .109904 .255172<br />
iel<strong>and</strong>1*| .1274478 .16647 0.77 0.444 -.19883 .453726 .960345<br />
iel<strong>and</strong>2*| .1795652 .08688 2.07 0.039 .009283 .349847 .018966<br />
short*| .05426 .06214 0.87 0.383 -.067541 .176061 .4<br />
higher*| .0048267 .06455 0.07 0.940 -.121681 .131335 .174138<br />
agesq | .0000942 .00017 0.55 0.580 -.00024 .000428 2610.34<br />
use<strong>of</strong>m~n | -.0000428 .00003 -1.27 0.206 -.000109 .000023 866.898<br />
u | -.0324464 .02085 -1.56 0.120 -.073308 .008416 6.07914<br />
------------------------------------------------------------------------------<br />
(*) dy/dx is for discrete change <strong>of</strong> dummy variable from 0 to 1<br />
Pooled probit – Table 9:<br />
. use /akf/702517/ycb2517/Initial/finaldata3.dta<br />
. /*Including the variable indicating the doses <strong>of</strong> antidep taken last 5 years,<br />
> pooled probit*/<br />
. quietly reg c<strong>on</strong>s_antidep mtx wageinc age ab02 ab36 ab79 ab1014 single iel<strong>and</strong>1<br />
> iel<strong>and</strong>2 short higher agesq use<strong>of</strong>medicin u y96 y97 y98 y99 y00 y01 y02 y03<br />
.<br />
. predict ohat, resid<br />
.<br />
. probit emp c<strong>on</strong>s_antidep mtx wageinc age ab02 ab36 ab79 ab1014 single iel<strong>and</strong>1<br />
> iel<strong>and</strong>2 short higher agesq use<strong>of</strong>medicin u ohat y96 y97 y98 y99 y00 y01 y02 y0<br />
> 3, robust<br />
note: ab36 dropped due to collinearity<br />
note: y96 dropped due to collinearity<br />
note: y97 dropped due to collinearity<br />
note: y98 dropped due to collinearity<br />
note: y03 dropped due to collinearity<br />
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