Average Marginal Effects interpretation

I ran a regression where the dependent variable is winning (1=win)
Given that my regression is probit I want to understand the coefficient.
I’ve done margins, dydx() for my independent variable (average marginal effects). This yielded a result of -.41.

What does this mean? Does it mean that the probability of winning goes down by .41 percentage points? and if so, when does it go down by that much?

I just want a lay person’s way to explain this .41 value.


The average marginal effect gives you an effect on the probability, i.e. a number between 0 and 1. It is the average change in probability when x increases by one unit. Since a probit is a non-linear model, that effect will differ from individual to individual. What the average marginal effect does is compute it for each individual and than compute the average. To get the effect on the percentage you need to multiply by a 100, so the chance of winning decreases by 41 percentage points.

Source : Link , Question Author : Katie , Answer Author : Maarten Buis

Leave a Comment