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Comment by JacobAGeller on Book Review: Why Are The Prices So Damn High? · 2019-11-21T03:42:52.924Z · LW · GW

I'm confused about some of the data in Tabarrok's book.

Take physicians per capita (PPC) . Big increase since 1960, yet many other countries have the same or (many) more PPC than the US. Many have also had large increases. Germans for example had as many PPC in the 90s as Americans do now, and today Germany has twice as many, yet somehow they spend half of what we do on health care. How are they affording that? There is a pile of other similar countries... Why are so many countries' health care systems seemingly immune to Baumol cost disease? Are German doctors really getting that much less education (25% as much)? Or what?

I understand that Tabarrok's data is overwhelmingly longitudinal, which is fine if he's asking why costs have increased over time, but there are cross-sectional mysteries like this one, all over the place.

Another data oddity, this one is from K-12 education: pupils per teacher (PPT) in public schools fell from about 22 in 1970 to about 15 in 2008... Yet the average class size is still somehow about 22. Um, what? These data come from the NCES, same as in Tabarrok's book. Very weird.

I casually checked some data sources like the NCES while reading the book, and my inner Seinfeld "What's, the deal, with that?" kept ringing in my head.

When I read a data-driven answer to an empirical question, I like to come away from the experience feeling like I really understand the data, but this book just didn't do that for me. It was interesting, and I feel like I understand the theory (Baumol) better, but I'm still confused about a lot of facts as they actually exist on the ground. It's a free, 90-page "book" (hardly more than a big white paper), so it's fine I guess, but if Tabarrok ever expands it into a more conventional print-length book, I'd like to see him deal more directly with how weird America is relative to other countries (more cross-sectional data), and really help readers better understand the data (over and above the theory) in general.