It might go that way"?

So, so I think in 80, 80 to 90% of the cases it was absolutely crystal clear.

There are some borderline cases, and we ended up, you know, uh, in multiple rounds of refereeing, doing all sorts of checks, um, a- including some of these borderline cases, uh, like Ronald Reagan.

You know, there are some cases that, that they use, they, they, they- They use some populist rhetoric, but it's not the core strategy they, they pursue, right? So, um, in-- we can include or exclude those people in the analysis.

W- again, we, we decided to exclude them as a baseline because we want to impose this high bar.

We also have parts of the analysis where we just use existing data sets of political scientists who have coded this using textual analysis of speeches, right? That's another approach that people have used.

Or expert coding, right? So there's various approaches to how you can go about identifying populists.

Uh, what about redistribution, for example, income inequality? Um, did, did you look at other macroeconomic, uh, variables or things that people might care about, and, uh, what did you find?

How, in that case, do you define a boom, unfortunate name in this context, in military spending?

We use the credit booms literature.

This was our inspiration.

You know, the last big crisis we had was financial, and there was all this research trying to understand the consequences of these credit booms.

So we used this kind of methodology and identify booms by strong increases in military spending to GDP.

Specifically, if a country has a six point five percent increase in military spending to GDP over two consecutive years, that is considered a boom onset, according to our algorithm.

And then the boom ends once the growth rate goes below zero, so when basically there's no more growth in military spending.

Mm-hmm.