Oh, it’s a very curious one - book on networks (social) by an economics professor (Matthew O. Jackson) based on various specialised research on networks for many years + publishing publicly (MOOCs) on the topic. (Goodreads)

Not too hard, but also not really a light primer on economics coupled with some Game Theory excerpts, field-research and all kinds of engaging examples.

Saying outright - I’d recommend it as reading to broaden perspectives on quite a few economics topics: ranging from banking policy, education, disease control (it was published right-right before Covid, timing miss on that one), to globalisation outlook. But not to get deep into network theories or even basic methods. Now to think of it - maybe it’s a little bit like supercharged ‘Freakonomics’, just a bit though.

However, my expectations were a bit pre-formed and I did find some structure lacking.

Diverse baggage of research - author’ own, and overall reads great and ‘clicks’ on quite a few issues for me personally, highlighting not exactly obvious topics.

But it might be a bit too much, from a small pop-sci format we do get a bit of popular cases treatment - simple, clear, well-researched and articulated. At the same time, each of the themes - Financial social networks / Healthcare / Education / Trade / Relationships / Inequality / and many more - worth a library on its own, not a chapter.

And the tech/method side while so powerful and elegant, meaning representing economies/cases as networks, which they’re, gives much more nuanced view and also adds predictive power, but alas, represented quite minimally and most of the topics would be more conventional, maybe more related to ‘surrounding theory’, rather than network.

Quite curious excerpt (mentioned in the book), but sourced from the article (2013).

Great Gatsby Curve - quite a nice addition to Gini index (making it more convincing in my opinion), which shows ‘correlation’ of parent/child income and from lower end I’d interpret as ‘availability of opportunity’, on the higher - ‘security of position’.

Well, at the end of the day we read books among many reasons to learn something new and help us think a bit differently through an author’s eyes for a few hours.

And I’m not unhappy that I’ve added that set of mini-lectures to my neural net.