Something I have been insisting on: right now, the rich are having more kids, not fewer, than the poor, reversing a long-standing demographic pattern. The ultimate status symbol for a finance bro? Three kids and a Rivian.

Use AI more than me: ugh, you have no taste, total cognitive surrender Use AI less than me: what a waste of time, boomer mindset

OpenAI and Anthropic compete at the cheap end of the market, not just at the frontier.

What should an open scientific paper look like in the AI age? We made a demonstration project out of our paper on the childhood socioeconomic circumstances of the Nobel Laureates. Please check it out and share. Details in 🧵 1/

With math essentially being delegated to OpenAI, here's what I predict for economics and the social sciences more generally: ✅The top tier of research will just become better and it will be normal human-led research where AI is used for scale (e.g. conducting qualitative interviews with relevant populations, running behavioral interventions in the field, analyzing massive text data, etc.) ✅ Field experiments will rise in value and generally making "connections" with firms and being able to run stuff (potentially testing AI pipelines) will be in high demand ✅ Research with administrative data will become even more valuable, but the benefits might be concentrated among some prolific authors who are allowed by the government agencies to use local models to analyze the data at scale. PhD students can probably forget about it ✅Economic history will have a very exciting boom and there will be an enormous race and big rewards for digitizing archives as a source to both identify new research strategies and document new descriptive facts. ✅Review and verification systems will become massively improved with AI assistance and it will become standard practice to do a 360 review of the paper + code + data at the *submission* stage. ⚠️Research that in principle can already be almost completely outsourced to the AI (download and analyze public data, run simple survey experiments, write theory models) is in for a big shock. This would be very bad from the perspective of researchers who depend on this "bread and butter" research, but I think this type of work will just be outsourced to public agencies who can answer their own questions without the need for "peer-reviewed" research.

New post with the excellent @FutureEconJacob examining the evidence (so far) on the impact of AI on the labor market. We reviewed 20+ papers and datasets and attempted to synthesize the evidence. Our take: 1) There is no strong signal that AI has had a negative or positive impact on employment in the aggregate. 2) When looking at specific sectors and demographics, the evidence is fairly mixed. While some have argued for negative impact on AI-exposed, early career hiring, others have identified moderators such as remote work or macroeconomic trends. There is also some evidence of positive impacts as well. So has AI hit the labor market yet? When looking at the employment statistics--not really. But that does not mean that jobs are not changing significantly, and that there aren't substantial changes in what skills are becoming less relevant versus in greater demand. That's a topic for another post! Link: aleximas.substack.com/p/has-…

🚨New paper with @mireiagine and @javiersanzespin. After rising for decades, and stabilizing in the 2010s, the college wage premium has been dropping every year since 2022. It's already back to the level it was in the mid-1990s. Link to paper: papers.ssrn.com/sol3/papers.… #EconTwitter

Given concerns over impacts of #COVID19 disruption on women, we looked at data on 1st submissions to @JEEA_News using same time period comparison as @RFisman @restatjournal & @profesk @EJ_RES Share of women submitters falls: 28 to 16% Breakdown by gender comp of papers below: