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st: Graphing Marginal Effects after -xtprobit-
From
"Pavlos C. Symeou" <[email protected]>
To
"[email protected]" <[email protected]>
Subject
st: Graphing Marginal Effects after -xtprobit-
Date
Fri, 15 Jul 2011 12:06:09 +0300
Dear Statalisters,
I am attempting to graph the marginal effects of an interaction
term whose coefficient is estimated with the -xtprobit- command,
inspired by the Stata code which can be found here
http://homepages.nyu.edu/~mrg217/interaction.html. The original
code is based on a -probit- model. Stata interrupts my do file in
line 4 and gives me the following error:
. drawnorm MG_b1-MG_b6, n(10000) means(e(b)) cov(e(V)) clear;
6 variables specified but specified means(e(b)) is 1 x 7
expected a 6-vector
r(503);
I speculate the missing variable is the unobserved error term
encountered in panel models. How do I account for this? Apparently,
I will need to address this in lines 13, 14, and 15 where I give
values to my variables (including the constant).
Could you suggest a solution to this problem?
Pavlos
**********Code_Follows**************************************************************************
1. #delimit ;
2. xtprobit str_logit dev_log_ch_lag1 pr_lag1
dev_log_ch_pr_lag1 log_emp roa, re;
3. preserve;
4. drawnorm MG_b1-MG_b6, n(10000) means(e(b)) cov(e(V)) clear;
5. postutil clear;
6. postfile mypost prob_hat0 lo0 hi0 prob_hat1 lo1 hi1 diff_hat
diff_lo diff_hi
using sim , replace;
noisily display "start";
7. local a=0 ;
8. while `a' <= 2 { ; /*a here represents the range of values that
pr takes 0,1,2*/
9 {;
10. scalar h_dev_log_ch_lag1=0.00000000173;
11. scalar h_log_emp=1.243789;
12. scalar h_roa=0.0228954;
13. scalar h_constant=1;
14. generate x_betahat0 = MG_b1*h_dev_log_ch_lag1
+ MG_b2*(`a')
+ MG_b3*h_dev_log_ch_lag1*(`a')
+ MG_b4*h_log_emp
+ MG_b5*h_roa
+ MG_b6*h_constant;
15. generate x_betahat1 = MG_b1*(h_dev_log_ch_lag1+1.75814)
/*1.75814 is the SD of dev_log_ch_lag1*/
+ MG_b2*`a'
+ MG_b3*(h_dev_log_ch_lag1+1.75814)*(`a')
+ MG_b4*h_log_emp
+ MG_b5*h_roa
+ MG_b6*h_constant;
16. gen prob0=norm(x_betahat0);
gen prob1=norm(x_betahat1);
gen diff=prob1-prob0;
egen probhat0=mean(prob0);
egen probhat1=mean(prob1);
egen diffhat=mean(diff);
tempname prob_hat0 lo0 hi0 prob_hat1 lo1 hi1 diff_hat diff_lo
diff_hi ;
_pctile prob0, p(2.5,97.5) ;
scalar `lo0' = r(r1);
scalar `hi0' = r(r2);
_pctile prob1, p(2.5,97.5);
scalar `lo1'= r(r1);
scalar `hi1'= r(r2);
_pctile diff, p(2.5,97.5);
scalar `diff_lo'= r(r1);
scalar `diff_hi'= r(r2);
scalar `prob_hat0'=probhat0;
scalar `prob_hat1'=probhat1;
scalar `diff_hat'=diffhat;
post mypost (`prob_hat0') (`lo0') (`hi0') (`prob_hat1')
(`lo1') (`hi1')
(`diff_hat') (`diff_lo') (`diff_hi') ;
};
drop x_betahat0 x_betahat1 prob0 prob1 diff probhat0 probhat1
diffhat ;
local a=`a'+ 1 ; /*A unit increase in pr_lag1. It can be
whatever I think it makes sense*/
display "." _c;
} ;
display "";
postclose mypost;
use sim, clear;
gen MV = _n-1;
graph twoway line diff_hat MV, clwidth(medium) clcolor(blue)
clcolor(black)
|| line diff_lo MV, clpattern(dash) clwidth(thin)
clcolor(black)
|| line diff_hi MV, clpattern(dash) clwidth(thin)
clcolor(black)
|| ,
xlabel(0 1 2, labsize(3)) /*I think these should be
the values of the modifying variable*/
ylabel(-.1 0 0.1 0.2, labsize(3))
yscale(noline)
xscale(noline)
yline(0)
legend(off)
title("Marginal Effect of Log_Ch on Env_Performance As
Pressure Changes", size(4))
subtitle(" " "Dependent Variable:
Environmental_Performance" " ", size(3))
xtitle(pr_lag1, size(3.5) )
ytitle("Marginal Effect of Log_Ch", size(3.5))
xsca(titlegap(2))
ysca(titlegap(2))
scheme(s2mono) graphregion(fcolor(white));
graph export h:\figure1.eps, replace;
translate @Graph h:\figure1.wmf;
exit;
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