placed a hold request for the #PlanetMoney book.

The planet money podcast is doing a series on publishing a book. This episode is on bookstore economics. It’s in my queue to listen to, but I listen to planet money podcast fairly regularly and they’re mostly good.

#Books #BookPublishing #PlanetMoney #Podcast #Economics

Me: aw, come on fellas, don’t make fun of me, I’m a cool guy

Also me: Hooray! My pre-ordered copy of “Planet Money: A Guide to the Economic Forces that Shape Your Life” by Alex Mayyasi and the Hosts of #NPR’s Planet Money just got in!!!!

🤓

#planetMoney #bookstodon

#BookReview for "Planet Money: A Guide to the Economic Forces That Shape Your Life" by the team behind #NPR 's #PlanetMoney podcast.
Recommended
Common economic concepts (cost disease, compound interest, cartels and more) presented in a lively way.
The book is clearly made for print first and audio second. It lacks the conversational back-and-forth of the podcast. The first chapter in particular is jarring - presumably made of many small tidbits of information presented in a visually interesting way, but lacking smooth transitions in an audio medium.
Still, the team does a good job of keeping the discussion lively, using real world examples and a light tone as they make the concepts approachable for a wide audience.
I just listened to this Planet Money episode about NBA teams taking to get better draft picks: https://www.npr.org/2026/03/06/nx-s1-5739178/nba-draft-tanking
Here's my plan for solving the problem. Tell me what's wrong with it!
Rank the teams based on their whole-season performance, BUT rather than considering all the games for the entire season, use a random subsample of games (like, say, ¼), with the random selection algorithm weighted to choose more games near the start of the season.
#PlanetMoney #NBA #NBADraft (1/3)

Planet Money: "Don't hate the replicator, hate the game"

A solution to the "replication crisis" in some fields, maybe.

https://www.npr.org/2026/02/27/nx-s1-5720653/replication-crisis-games-abel-brodeur

#science #economics #PlanetMoney #podcastEpisode

When Trump decided to collect #tariffs some companies thought this was illegal, and they sued to get their money back. No one knew what the #SupremeCourt would decide. Companies that wanted money now, sold their rights to any future refund for 20% of its value. Hedge funds paid them for this right. When the Court ruled tariffs illegal, a company could now get 40% from a hedge fund for quick cash. If a company wanted the full 100%, it would have to pay for a lawyer. Source: #PlanetMoney podcast.

BOARD GAMES 1: We're making a game
#PlanetMoney

We want to make a board game. It must, of course, teach the world about economics. It must be fun. It'd be nice if it sold lots of copies! How hard could that be!? (Monopoly and Catan are hugely popular and basically little economy simulators, after all.)

Well, turns out, it's quite hard!

In the first episode of our new series, Planet Money sets forth on an epic quest to beat the odds.

https://www.npr.org/2025/10/01/nx-s1-5558425/planet-money-board-game-episode-1

@drahardja There's apparently (thanks, #PlanetMoney!) A good amount of solid research that says when your central bank becomes non-independent, the economy suffers. These folks surely know this.

Planet Money gets AI wrong (again)

Planet Money‘s coverage of generative AI has been consistently facile and far too reluctant to challenge or examine critically the claims of AI proponents. Their most recent episode about this, “So are we in an AI bubble? Here are clues to look for,” was so bad that I felt compelled to send them this email about it:

To: [email protected]
Subject: What you missed about the AI bubble

I just finished listening to https://www.npr.org/2026/01/09/nx-s1-5672643/market-ai-what-is-a-bubble. It was hugely problematic.

First of all, you failed to acknowledge or mention or even hint at in any way the fact that bubbles are very often driven by at best smoke and mirrors and at worst outright cheating and fraud.

I don’t have to tell you about all the fraud that caused the housing bubble, because you reported on it extensively and in great detail.

As for the dot com bubble, I was there, working for a company whose IPO paid for the down-payment for the house I still live in 29 years later, and I can tell you first-hand that all of us engineers working for that company knew that senior management was delusional and our IPO was driven by lies. Not to mention all the jokes that were being told during that bubble, of which you surely must be aware, about how all any startup had to do to to get a huge pile of investor cash was put the word “internet” in their pitch somewhere.

There is every reason to believe this same thing is going on with AI. There have been plenty of news articles explaining why—much of it straight economics reporting your team should surely be aware of—and plenty of rock-star experts in the field calling it out on a regular basis.

You failed to acknowledge any of this. Instead, you begged the question by assuming that the market efficiency hypothesis (i.e., Fama) is correct, and then the rest of what you said for the entire episode was predicated on that assumption. Markets where investment is being driven by lying, cheating, and fraud are not efficient, they are rigged. Rigged markets cannot be sustained forever; this is why bubbles pop.

Second, the bit at the end about “maybe all these data centers we’re building will be useful for something else even if the bubble pops” entirely missed the point—which, again, is no secret, it’s mentioned frequently in news coverage—that these data centers are being built specifically for AI with hardware which is only good for AI and which becomes obsolete and has to be replaced at gargantuan expense every few years. This is nothing like the fiber optics you mentioned as a supposedly comparable example. Fiber-optic cables can be used to carry any data for any purpose. AI data centers can’t be repurposed for other things without ripping out all the hardware inside them and replacing it, at huge financial and environmental cost.

There are plenty of experts who could have discussed both of these issues intelligently. It’s journalistic malpractice that you didn’t seek them out and include any of what they have to say for this episode.

Jonathan Kamens

#AI #bubbles #economics #NPR #PlanetMoney