Dear Statalist,
I have question about estimating probit model for each year and plot probability of predicted value for "au" (dependent variable) for two groups (au=1 and au=0) as below:
This is my data
I have some questions as below:
Q1: How can I estimate probit model for each year in a quickly way? Because now I write command and run manually for each year and compute the predicted value for "au" as following:
The following years are done similarly by only changing the year. But if doing like this, I have to repeat the command for the whole period.
Q2. Is this Likelihood ratio index as Pseudo R2 from results of probit model?
Q3. I need to plot the predicted value (or prob of "au" hat) in each year for 2 groups of firms ( firms have "au"=1 and firms have "au"=2) like an image below. In particular, I need to split the range into 20 intervals. And the percentage of each firms in each interval is plotted against the mid-value of the interval for both groups. So, it likes a discrete approximation.
Q4. How can obtain the value of cut-off point of two line in this graph?
Thank you so much for your consideration.
I am really appreciated to receive your help.
I have question about estimating probit model for each year and plot probability of predicted value for "au" (dependent variable) for two groups (au=1 and au=0) as below:
This is my data
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input long gvkey double year float(au size roa mtb aqe exf) 1004 2009 1 7.313915 .029731346 1.0414093 .033695575 .006125473 1004 2010 1 7.440574 .04098427 1.255999 0 -.001381535 1004 2013 1 7.695985 .033143897 .9617889 .001764136 -.008624665 1004 2014 1 7.323171 .006732673 1.2381912 .00013460762 -.0834298 1004 2015 1 7.273856 .033076763 .9731014 0 -.004971087 1004 2016 1 7.31595 .03756399 1.3129827 .0021213768 -.0014934492 1013 2005 1 7.336286 .07211726 2.6268575 .02922615 .0022948938 1013 2006 1 7.384859 .040772 1.9200138 0 .001525553 1013 2007 1 7.475793 .06023346 2.1825328 .0014365263 .0007108584 1034 2007 0 7.160974 -.010542904 1.206971 .0015534413 .06981232 1050 2007 0 4.5699058 .0653131 3.967728 .03116333 .02306806 1050 2011 0 4.3738055 .10425358 1.8740126 0 -.002851378 1050 2012 0 4.5444007 .11529797 2.721909 .011530767 -.0005995999 1072 2004 1 7.432335 .032982413 1.4720843 -.0004835262 -.0012897506 1072 2005 1 7.423693 .0488011 2.104968 0 -.00149675 1072 2006 1 7.549365 .08100136 1.5957184 0 -.0014539503 1072 2008 1 7.535045 .04317477 .9265363 .0008384805 -.0009911828 1072 2009 1 7.626323 .06963615 1.3409446 8.027479e-06 -.0004590954 1072 2010 1 7.749099 .1051972 1.2438934 0 -.000021391113 1072 2011 1 7.811168 .0619142 1.0604296 0 -.0007725336 1072 2012 1 7.864034 -.02471642 1.0171332 .007850877 -.0010281052 1072 2013 1 7.776949 .05326526 1.0827607 .0001604176 -.0006092862 1072 2014 1 7.807516 .09185426 1.1257565 0 -.00015286943 1072 2015 1 7.787307 .04213387 .9670519 0 -.000973231 1072 2016 1 7.81497 .05077272 1.2410194 0 .0005406946 1072 2017 1 7.890869 .0018370482 1.2425467 .028181544 -.0015216947 1072 2018 1 7.942106 .0966179 1.2278615 .0011225757 .00003928149 1078 2003 1 10.192993 .10305812 5.577196 .004883957 -.004811323 1078 2004 1 10.267 .1124829 5.08001 .02097785 .004158493 1078 2013 1 10.667862 .05997253 2.357419 .002631867 .002640942 1084 2008 0 -1.7487 -4.5632186 -2.961447 0 .4625 1084 2009 0 -5.521461 -181.75 -1.249938 0 .502809 1084 2010 0 -.9113032 -1.482587 -3.474963 0 .6699507 1084 2011 0 -1.2765435 -6.075269 -2.843761 0 .23788546 1084 2012 0 -1.439695 -7.021097 -4.854805 0 .45348835 1084 2013 0 -1.1147417 -12.585366 -3.493628 0 .9097345 1084 2014 0 -3.575551 -35.107143 -3.050291 0 .14044943 1084 2015 0 -3.649659 -155.26923 -.6544932 0 4.435185 1084 2016 0 -2.3751557 -12.182796 -1.1653346 0 3.142857 1084 2017 0 -1.6928195 -14.929348 -2.1432517 0 .5758123 1084 2018 0 1.3470336 .4560582 -20.052353 0 .1085608 1094 2003 1 4.816395 .06148852 2.253776 0 -.001789133 1094 2004 1 5.008613 .08728966 2.816428 .00847681 -.000611238 1094 2005 1 5.004134 .067202136 1.687143 0 .0009574023 1094 2006 0 5.115548 .05544684 1.4602293 0 -.0007239719 1094 2007 0 5.238981 .05418139 1.8029152 0 .0003407779 1094 2008 0 5.403771 .06062283 1.330167 0 .00007547703 1094 2009 0 5.325271 .04199763 1.1670898 0 .0006078928 1094 2010 0 5.446095 .02838461 1.0428514 .0009981364 .002588523 1109 2003 0 1.6823165 -.097434 3.4589114 0 .019037424 1109 2004 0 2.0700223 -.008580442 3.401972 .07889198 .09433962 1109 2005 0 2.1475673 -.002452125 1.7976558 .0006974346 .013129965 1109 2006 0 1.9095426 -.4022222 1.9219157 0 .007640068 1111 2004 1 7.175461 .10584462 2.704997 .00469773 .015962439 1111 2005 1 7.257183 .02838065 3.124528 .001264119 .008272366 1111 2006 1 7.492174 .04782026 3.80148 .004754527 .002950624 1111 2007 1 7.836241 .13628113 4.1310906 .007954109 .005551008 1117 2005 0 3.437722 .3307623 3.451609 0 -.006180007 1117 2006 0 3.564053 .09706566 2.4783134 0 .0017238265 1117 2007 0 3.406019 .06123735 1.5182197 0 .0009396342 1117 2008 0 3.4217186 -.05309908 .3781489 0 .012440963 1117 2009 0 3.4474764 .07520448 1.4697592 0 -.01208839 1117 2010 0 3.5493875 -.01896988 .8565058 0 .015759746 1117 2011 0 3.460943 -.015480265 .529798 0 -.015006227 1117 2012 0 3.5251834 .06080683 .7538961 0 .00017475344 1117 2013 0 3.527037 .03356553 1.457509 0 .00038244855 1117 2014 0 3.6105394 .04388147 1.973701 0 .001013956 1117 2015 0 3.675009 .0263885 1.5537088 0 .0006018186 1117 2016 0 3.750539 .06320515 1.822378 0 -.0008049468 1117 2017 0 3.7565615 -.08471765 1.5141876 0 -.002724237 1117 2018 0 3.668447 -.004975632 1.7345374 0 -.02001415 1121 2003 1 5.34835 .014753093 1.3533316 0 0 1121 2004 1 5.475852 .036038753 1.5008677 0 0 1121 2005 1 5.745123 .05642195 1.4673315 0 0 1121 2006 1 5.667419 .03623737 1.7077773 0 -.007039633 1121 2007 1 5.877946 .04776588 1.2119876 0 -.002320681 1121 2008 1 5.351507 -.02641685 .8770196 0 0 1121 2009 1 5.519062 .01663586 1.1098543 0 0 1121 2010 1 5.708123 .02864539 1.1376506 0 0 1121 2011 1 5.937114 .06052951 1.1093962 0 0 1121 2012 1 6.039066 .066247754 1.0888226 0 0 1121 2013 1 6.104976 .04822778 1.86788 0 0 1121 2014 1 5.831337 .01913947 1.337734 0 0 1121 2015 1 5.493946 -.005242276 1.0620366 0 0 1121 2016 1 5.50887 .010179364 1.1052904 0 0 1161 2003 1 8.867053 -.03869138 2.1403224 .00024639114 -.0022868165 1161 2017 1 8.171882 .012146893 16.269657 0 -.0014575134 1165 2004 0 2.0192933 -.12677552 -.003211403 0 -.005392768 1165 2005 0 2.0090191 -.15008047 -.003057106 0 -.004903596 1165 2006 0 2.1525757 .05611711 -.004956734 0 -.02916641 1166 2003 1 6.74158 -.04361092 3.7424004 0 .037149664 1166 2004 1 7.016884 .029179435 2.481453 .003076133 .033667497 1166 2005 1 6.868947 -.04950958 3.1341565 .0003138779 -.022232614 1166 2006 1 7.001594 .0412525 3.088033 .0003720301 .002980852 1166 2007 1 7.11244 .07256315 2.766611 .00008815233 -.010363704 1166 2008 1 6.974196 .02397871 1.0165823 .00005335747 -.023687014 1166 2009 1 7.107144 -.12511551 3.8524864 .00001572496 .035828665 1166 2010 1 7.384618 .0911272 3.394258 0 -.015197933 1166 2014 1 7.701097 .07515746 1.3044246 0 -.003420236 1166 2015 1 7.720596 .07576045 1.1082753 0 -.00823872 end
Q1: How can I estimate probit model for each year in a quickly way? Because now I write command and run manually for each year and compute the predicted value for "au" as following:
Code:
probit au size roa mtb aqe exf if year==2003, vce(robust) predict pprobit2003, pr replace pprobit2003=. if year>2003
Q2. Is this Likelihood ratio index as Pseudo R2 from results of probit model?
Q3. I need to plot the predicted value (or prob of "au" hat) in each year for 2 groups of firms ( firms have "au"=1 and firms have "au"=2) like an image below. In particular, I need to split the range into 20 intervals. And the percentage of each firms in each interval is plotted against the mid-value of the interval for both groups. So, it likes a discrete approximation.
Q4. How can obtain the value of cut-off point of two line in this graph?
Thank you so much for your consideration.
I am really appreciated to receive your help.
Comment