EconLog

Joy on Severance and Wild Problems           

Joy BuchananLeave a comment

For EconLog, I wrote a reflective piece on Season 2 of Severance and how it relates to the book Wild Problems by Russ Roberts.

You Cannot Outsource Life: Severance and Wild Problems (EconLog link)

The essay is about pain and a meaningful life.

Rather than accepting that work, grief, and love may transform us, Lumon divides experience from identity.  An adult who is primarily asking, “Who do I want to become?” likely would reject the Lumon…

Read more at the link above. Remember that the first words spoken in Season 1 were “Who are you?” Maybe Russ Roberts should do a whole podcast on this show.

During a rare slower week in the summer (thanks to my sister) I was able to binge Season 2. The genre could be described as Science Fiction. S2 does answer some of the questions raised in S1 but ends with a new cliffhanger to bring you back for Season 3. If you want to enjoy the show, the trick for me was not to take it too seriously. Ben Stiller is a producer and you can see traces of what feels like Zoolander humor to me.

I think the dialog is great. The sibling relationship and marital disputes and office inside jokes feel realistic.

As I said about Season 1, this show could be, among other things, a meditation on AI alignment. When you think enough about AI alignment, I guess you start seeing it in your TV shows. I wrote about that previously in: Artificial Intelligence in the Basement of Lumon Industries

Other previous posts on Severance, based on Season 1:

Lumon Industries and Drudgery (Joy)

Perks in Severance (Joy)

Severance and the Disutility of Work (Mike)

Most Published Research Findings Are Directionally Correct

James BaileyLeave a comment

As a new quick rule of thumb inspired by the Nature papers, you could do worse than “cut estimated effect sizes in half”. If a published paper says that a college degree raises wages 100%, then chances are the degree really does raise wages, but more like 40–50%. In 2005, John Ioannidis said that “most published research findings are false”. By 2026, we seem to have improved to “most published research findings are exaggerated.”

That’s the conclusion of my piece out today at Econlog: “Is Economics Finally Becoming Trustworthy?“

There’s plenty of both good and bad news for economics and the social sciences in both my piece and the Nature special issue it describes. It’s kind of like the Our World in Data motto:

In short, our attempt to replicate hundreds of papers showed that published social science results shouldn’t be trusted precisely today, but they seem to be getting more reliable over time, and they are much more reliable than chance. Economics and political science look the best, though we are still very far from perfect:

You can read the full piece here.

Commodity Sports

James BaileyLeave a comment

I’m trying to coin “Commodity Sports” as the term to refer to sports betting that takes place on exchanges regulated by the US Commodity Futures Trading Commission, as opposed to sports betting that takes place through casinos regulated by state gaming commissions. So far it seems to be working alright, I haven’t convinced Gemini but have got the top spot in traditional Google search:

That article- Will Commodity Sports Last?– is my first at EconLog. I’m happy to get a piece onto one of the oldest economics blogs, one where I was reading Arnold Kling’s takes on the Great Recession in real time, where I was introduced to Bryan Caplan’s writing before I read his books, and where Scott Sumner wrote for many years (though I started reading him at The Money Illusion before that).

The key idea of the piece, other than the legal oddity of sports betting sharing a legal category with corn futures, is that the Commodity Sports category is being pioneered by prediction markets like Kalshi. As readers here will know, I like prediction markets:

I love that CFTC-regulated exchanges like Kalshi and Polymarket are bringing prediction markets to the mainstream. The true value of prediction markets is to aggregate information dispersed across the world into a single number that represents the most accurate forecast of the future.

But I’m not so excited to see them expanding into sports:

Although I see huge value in prediction markets when they are offering more accurate forecasts on important issues that help policymakers, businesses, and individuals make more informed plans for our future (e.g., Which world leaders will leave office this year?, or Which countries will have a recession?)… I see much less value in having a more accurate forecast of how many receptions Jaxon Smith-Njigba will have.

Like Robin Hanson, I worry that the legal battles against Commodity Sports and the brewing cultural backlash against sports betting risk taking the most informative prediction markets down along with it.

The full piece is here.