Question for result intepretation following Marginal Effect in Ordered probit

[Jean Dewals]

Dear colleagues,

I'm currently working on an ordered probit model. This model aims to measure the influence of several explanatory variables on the frequency of consumption of FAPs, which are divided into three classes.

My first command is as follows:

 oprobit frq_conso age genre enfant deplittoral revenumid revenusup prix_crit_dom obj pref_mode_prod pref_methode_prod pref_frais pref_env_sauv pref_env_elev pref_france pref_sanit sante faccuisin tasty expens [pweight=weight]

After that, to obtain my marginal effect, i use :

mfx, predict (outcome(1))
mfx, predict (outcome(2))
mfx, predict (outcome(3))

For exemple, i obtaine the following results for my outcome 1:

To interpret the result, can we say that consumers who perceived FAPs as expensive (last variable of the table) have a 6.9% increased probability of being in the Outcome 1 category?

Thanks again for your help, and i remain available if youy needed more information!

Best regards,

Jean-François DEWALS

[Erik Ruzek]

That is generally correct, but you can be more precise by indicating whether expens is continuous or categorical. That said, mfx has been superceded by margins. If you haven't before, I'd strongly suggest you read Richard Williams incredibly helpful course notes on using margins and other commands after ologit to get useful quantities of interest.

[Richard Williams]

About the only time you would use mfx is if you are condemned to using some horribly antiquated version of Stata, e.g. version 9. Even then, I would probably download and use the user written commands mfx2 and margeff. But if you've got Stata 11 or higher, use margins and/or the user-written commands in spost13.