Dear all,

I'm having troubles with a simple ordered probit model. Indeed, I am doing a research to know if the risk aversion ratio (varies between 3.5 and 0.9) is perfectly correlated with the investor profile. So I have the following data: Profile type (conservative, moderate, balanced, dynamic, aggressive (all are dummys)), Age (> 39 or <39) dummy, Sex (dummy), respondent has a partner (dummy), and the LossRatio (3.5, 3.3 , 2.5, 2, 1.53, 1.25, 1.1, 1, 0.9) a category of 9 possible values.

When I run the code (I'm not sure it is correct), I get a result for each type of investor profile, except for raggresive, it puts me "omitted"

oprobit LossRatio rconservative rmoderate rbalanced rdynamic ragressive Age_category_39 rpart Nationality_ rfemale c.Age##c.Age , vce(robust)
estimate store Oprobit1

estimates restore Oprobit1
margins, dydx(rconservative rmoderate rbalanced rdynamic ragressive ) predict(pr) post


| Delta-method
| dy/dx Std. Err. z P>|z| [95% Conf. Interval]
--------------+----------------------------------------------------------------
rconservative | -.0454679 .043117 -1.05 0.292 -.1299757 .0390398
rmoderate | -.0377651 .0346429 -1.09 0.276 -.1056638 .0301337
rbalanced | -.0157885 .0148816 -1.06 0.289 -.0449558 .0133788
rdynamic | -.0127741 .014752 -0.87 0.387 -.0416875 .0161393
ragressive | 0 (omitted)

Would anyone have an explanation for this? A big thank you in advance,

Best,