I have a question about how to interpret the marginal effects in a probit model that I hope someone can help me with. Take a model that looks at school dropout (dependent variable =1 if dropped out, 0 otherwise) and household asset loss (independent variable ranging from 0 to 1, indicating the proportion of assets lost in the past year due to earthquake).

Code:
 . probit dropout assetloss

dropout       Coef.   Std. Err.      z    P>z     [95% Conf.    Interval]
        
assetloss     .491884   .0888692     5.53    0.000     .3177036    .6660644
_cons   -1.493199   .0399956   -37.33    0.000    -1.571589    -1.414809
Code:
margins, dydx(assetloss) predict(pr) post 

Average marginal effects    Number of obs     =    2,879
Model VCE    : OIM

Expression   : Pr(enrolled), predict(pr)
dy/dx w.r.t. : assetloss

        
Delta-method
dy/dx   Std. Err.      z    P>z     [95% Conf.    Interval]      
assetloss    .0736991   .0134485     5.48    0.000     .0473406    .1000576
Is it correct to interpret the marginal effects as follows: As asset losses increased by 100 per cent, the average marginal effect on the probability of dropping out of school increased by 0.073 percentage points?