Hi and welcome to the A16Z podcast. I'm Hannah. Good data, bad data. There's maybe no other area where

understanding what the evidence actually tells us is harder than in health and parenting.

In this episode, economics professor Emily Oster, author of Expecting Better and the recently

released crib sheet, a data-driven guide to better, more relaxed parenting, does just

that, looking at the science and the data behind the studies we hear about and make decisions

based on in those worlds, from whether to breastfeed your child to screen time to sleep

training. We talk about what it means to make data-based decisions in these settings, in diet

and in health and in life, like whether chia seeds are actually

good for you and how we can tell what's real and what's not. We also talk about how guidelines and

advice like this gets formalized and accepted for better or for worse and how they can or can't be

changed. And finally, how the course of science itself can be changed by how these studies are done.

You describe yourself as teasing out causality in health economics.

Can you give us a little primer on what exactly that means and how you start going about doing that?

So there are a lot of settings in health.

And in all of those settings, we have to figure out what does the evidence say?

And I think about some of them in this context of parenting, but you can think about even

questions like, you know, is it a good idea to eat eggs or is it a good idea to take vitamins,

other kinds of health decisions?

And you can sort of think about there being kind of two types of data you could bring to that.

One would be randomized data.

So you could run a randomized trial in which half of the people got

eggs and half of the people didn't and you followed them for 50 years and you saw which of them

...