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# st: marginal effects in the censored ordered probit

 From Marina Mastrorillo <[email protected]> To <[email protected]> Subject st: marginal effects in the censored ordered probit Date Mon, 29 Aug 2011 11:36:55 +0100

```Hello,

I'm Marina. I used the do.file written by Edoardo (found online) to
estimate the impact of migration on education using a censored ordered
probit. Many thanks to Edoardo!

Now I should estimate the marginal effects. Could please anyone help me,
or give me any suggestion? Thanks a lot.

Best regards,
Marina

PS: Below there are the exact commands I used.

/*define school attainment dependent variable*/
gen school0 =schooling==0
gen school1 =schooling==1
gen school2 =schooling==2

gen school3 =schooling==3
gen school4 =schooling==4
gen school5 =schooling==5

gen unc=enrol==0
//define uncensored observation: children not attending school

program define maxcens
args lnf1 theta1 cut1 cut2 cut3 cut4 cut5
qui replace `lnf1' = unc* (ln((\$ML_y1*normprob(`cut1'-`theta1'))+(\$ML_y2*
(normprob(`cut2'-`theta1')-normprob(`cut1'-`theta1')))+(\$ML_y3*
(normprob(`cut3'-`theta1')-normprob(`cut2'-`theta1')))+(\$ML_y4*
(normprob(`cut4'-`theta1')-normprob(`cut3'-`theta1')))+(\$ML_y5*
(normprob(`cut5'-`theta1')-normprob(`cut4'-`theta1')))+(\$ML_y6*
(1-normprob(`cut5' -`theta1')))))+ enrol* (ln((\$ML_y1)+(\$ML_y2*
(1-normprob(`cut1'-`theta1')))+(\$ML_y3*
(1-normprob(`cut2'-`theta1')))+(\$ML_y4*
(1-normprob(`cut3'-`theta1')))+(\$ML_y5*
(1-normprob(`cut4'-`theta1')))+(\$ML_y6*(1-normprob(`cut5'-`theta1')))))
end

ml model lf maxcens (school0 school1 school2 school3 school4 school5 =
years_1013
years_1417 years_1822 male_mig_hh female_mig_hh school_mighh hh_greece
hh_italy sch_head costal central mountain soc_cap dist_ind m07_q05 reshat,
nocons) /cut1 /cut2 /cut3 /cut4 /cut5

ml search, repeat(100)
ml maximize, difficult

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```