可以自己根据公式计算。

probit y x1-xn
predict gw, xb
g lambda=normalden(gw,0,1)/normal(gw) if y==1
replace lambda=-normalden(gw,0,1)/normal(-gw) if y==0

*y是0-1变量，x1-xn是解释变量，lambda即IMR

3Q

predict y_hat, xb
gen imr = normalden(y_hat)/normal(y_hat)
可以比较
heckman y ... mills(lambda)

这么算吧：
predict p1, xb
Above calculate predicted value from regression (equivalent to Ziγ )
replace p1=-p1
Above calculates -Ziγ
generate phi = (1/sqrt(2*_pi))*exp(-(p1^2/2))
This is the normal distribution density function: phi is equivalent to φ(- Ziγ)
generate capphi = normal(p1)
This is the cumulative debsity function: capphi is equivalent to Φ(- Ziγ )
generate invmills1 = phi/(1-capphi)
This calculates Inverse Mills ratio λi(-Ziγ)