Step 2 – identifying the estimand(s)

This short section is all about finding estimands with DoWhy. We’ll start with a brief overview of estimands supported by the library and then jump straight into practice!

DoWhy offers three ways to find estimands:

• Back-door
• Front-door
• Instrumental variable

We know all of them from the previous chapter. To see a quick practical introduction to all three methods, check out my blog post Causal Python — 3 Simple Techniques to Jump-Start Your Causal Inference Journey Today (Molak, 2022; https://bit.ly/DoWhySimpleBlog).

Let’s see how to use DoWhy in order to find a correct estimand for our model.

It turns out it is very easy! Just see for yourself:

estimand = model.identify_effect()

Yes, that’s all!

We just call the .identify_effect() method of our CausalModel object and we’re done!

Let’s print out our estimand to see what we can learn:

print(estimand)

...