Dear all,
I have two questions:
1) I am trying to estimate the marginal effects using gsem, with probit as the option, do you know which command shall I use?
2) I also want to control for year and country fixed effects, but directly putting in the country or year dummies in a nonlinear model will cause inconsistency, is there any way to deal with this?
My detailed problem is as follows:
I want to know whether international media shaming has effects on improving political rights, and whether government increase terror to offset the improving in political rights, so I specified my models below:
PIRI_2_increase is an indicator for whether terror has increased, Media_ai_tot is the level of international media shaming, polrt_decline is an indicator for whether political rights has improved (higher scores of PIRI and polirt mean worse cases)
The first equation is to estimate the effects of media shaming on terror (probit model), the second is to estimate the effects of media shaming on political rights (probit model), the third is to estimate the effects of political rights on terror (probit model), the fourth is to estimate the effects of previous political rights on the amount of shaming (OLS), and the fifth is to estimate the effects of terror on political rights (probit). I am particularly interested in knowing the marginal effects of media shaming in equation 1 and 2, but I don't know how to get them.
I would appreciate for any help you could offer.
Best,
Yuqing
I have two questions:
1) I am trying to estimate the marginal effects using gsem, with probit as the option, do you know which command shall I use?
2) I also want to control for year and country fixed effects, but directly putting in the country or year dummies in a nonlinear model will cause inconsistency, is there any way to deal with this?
My detailed problem is as follows:
I want to know whether international media shaming has effects on improving political rights, and whether government increase terror to offset the improving in political rights, so I specified my models below:
:
global X = "l.cat_rat l.ccpr_rat l.democratic l.C_lgdppc l.C_lpop l.Civilwar2 l.War" gsem (PIRI_2_increase <- l.Media_ai_tot l(1/3).PIRI_2 $X i.year i.idcode, family(binomial) link(probit))(polrt_decline <- l(2).Media_ai_tot l.polrt $X i.year i.idcode, family(binomial) link(probit)) (PIRI_2_increase <- l.polrt l(1/3).PIRI_2 $X i.year i.idcode, family(binomial) link(probit)) (Media_ai_tot <- l.polrt i.year i.idcode, regress) (polrt_decline <- l(1/3).PIRI_2 l.polrt $X i.year i.idcode, family(binomial) link(probit)), nocaps
The first equation is to estimate the effects of media shaming on terror (probit model), the second is to estimate the effects of media shaming on political rights (probit model), the third is to estimate the effects of political rights on terror (probit model), the fourth is to estimate the effects of previous political rights on the amount of shaming (OLS), and the fifth is to estimate the effects of terror on political rights (probit). I am particularly interested in knowing the marginal effects of media shaming in equation 1 and 2, but I don't know how to get them.
I would appreciate for any help you could offer.
Best,
Yuqing