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Hi, I'm one of the paper authors here. Happy to answer questions. Here's how I think about our methodology. Car seat laws generate an unusually sharp predictio

Hi, I'm one of the paper authors here. Happy to answer questions. Here's how I think about our methodology. Car seat laws generate an unusually sharp prediction for births that can be distinguished from a lot of competing effects (not perfectly, of course, but compared with a lot of other demographic effects) We're not testing whether the state and years with more stringent car seat laws have lower birth rates. That could be due to tons of stuff going on in those states. We're not even testing whether the states and years with more stringent car seat laws have lower birth rates just for third child births. That could be relatively fewer things, but still a lot. Rather, we're testing whether states and years with more stringent car seat laws have lower third child birth rates specifically for families whose first two children are below the mandate for their state and year. And this mandate is itself changing over time for both states and years, so we're talking about different ages of children in question depending on which state and year it is. This clearly doesn't rule out everything. But the set of candidate explanations for what else could be going on for those specific families in those years is a lot smaller than the broad demographic effects we started with.

stanfordkid 6y ago
It seems like low birth rates are pretty correlated with wealth. It also seems like liberal states, which are generally wealthier, have much more stringent regulatory policies -- such as mandatory car seats. How deeply do you understand these very clear confounding variables?
- davidsolomon 6y ago
  In terms of the general effects that some counties are richer than others, and some years people are richer than others, this will be captured by our fixed effects that control for overall birth rates for each combination of county, year, and number of children. So all effects are measured relative to other two child families in the same county and year. This captures the large majority of other regulatory and social changes that might be happening in that county and year. Next, we also add income by year and income by county fixed effects. So if richer people in a given county have more children relative to the average of all two child families in that county and year, we'll also control for that. If richer people in a given year have more children compared to the average of all two child families in that county and year, we'll capture that too. The point isn't that you need to add every one of these complicated fixed effects to find our result. It shows up in simpler tests too. It's just that you can control for a lot of potential confounding effects, and it still seems to be there.
  - uzbit 6y ago
    Cool analysis! Two questions. 1) Will you share the software you used for this analysis? I briefly scanned the article Methodology, but didn't see names dropped. Forgive me if you mentioned it there. 2) Are you hoping to win an Ig-Nobel prize with this? :D

stanfordkid 6y ago

It seems like low birth rates are pretty correlated with wealth. It also seems like liberal states, which are generally wealthier, have much more stringent regulatory policies -- such as mandatory car seats. How deeply do you understand these very clear confounding variables?

davidsolomon 6y ago
In terms of the general effects that some counties are richer than others, and some years people are richer than others, this will be captured by our fixed effects that control for overall birth rates for each combination of county, year, and number of children. So all effects are measured relative to other two child families in the same county and year. This captures the large majority of other regulatory and social changes that might be happening in that county and year. Next, we also add income by year and income by county fixed effects. So if richer people in a given county have more children relative to the average of all two child families in that county and year, we'll also control for that. If richer people in a given year have more children compared to the average of all two child families in that county and year, we'll capture that too. The point isn't that you need to add every one of these complicated fixed effects to find our result. It shows up in simpler tests too. It's just that you can control for a lot of potential confounding effects, and it still seems to be there.
- uzbit 6y ago
  Cool analysis! Two questions. 1) Will you share the software you used for this analysis? I briefly scanned the article Methodology, but didn't see names dropped. Forgive me if you mentioned it there. 2) Are you hoping to win an Ig-Nobel prize with this? :D