ECON OF WORK - Private feed for review
Season 1
by Cole Wagner
Five years after the pandemic reshaped where and how we work, where have we actually landed? In this episode, Ben sits down with Nick Bloom, professor of economics at Stanford and the world's leading researcher on remote and hybrid work. Drawing on surveys of hundreds of thousands of workers across many countries,Nick unpacks what the data actually shows about productivity, innovation, and the future of the office. Topics covered: Where work-from-home rates have settled since the pandemic peak Why culture, not technology, explains why some countries went back to the office while others didn't The "personal trainer effect": why being in the same room still matters for concentration and collaboration Why forcing people back five days a week drives up attrition by a third and costs firms more than they save The U-shaped relationship between age and office preference, and what it means for how companies should design their policies What good management actually looks like, and why so much bad management persists even when better practices are well understood The "donut effect": how hybrid work is reshaping cities and suburbs About Nick Bloom: Nick Bloom is the William D. Eberle Professor of Economics at Stanford University and co-founder of WFH Research. He is one of the most cited economists in the world on the subjects of management practices, and the future of work, and is the author of the upcoming book The Triple Win. Follow Nick on LinkedIn and on X Follow us on LinkedIn Follow Ben on LinkedIn Sign up for our Newsletter Visit our website for more information Get in touch with us at info@reveliolabs.com
What makes a transaction repugnant? And why does society allow some controversial markets to flourish while banning others that seem far less harmful? In this episode, Ben sits down with Al Roth, Nobel laureate and professor of economics at Stanford, to explore the hidden moral architecture beneath the markets we take for granted, and the ones we don't allow at all. Drawing on his new book Moral Economics, Al makes the case that good policy can't be built on moral intuition alone. Topics covered: What "repugnant" actually means in relation to transactions Surrogacy, gene editing, and AI companions: where the line between protection and paternalism blurs The coercion vs. exploitation distinction: is banning a market for poor people's benefit sometimes just denying them an opportunity? How public opinion and legislation diverge Why labor markets are fundamentally different from commodity markets How the internet (and now AI) has flooded job markets with applications and destroyed the information value of applying What the economics job market's "signaling" system can teach LinkedIn, dating apps, and corporate hiring alike Al Roth is a Professor of Economics at Stanford University and a recipient of the Nobel Memorial Prize in Economic Sciences. He is the author of Who Gets What — and Why and Moral Economics, and is one of the world's leading researchers in market design and matching theory. Follow us on LinkedIn Follow Ben on LinkedIn Sign up for our Newsletter Visit our website for more information Get in touch with us at info@reveliolabs.com
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Official labor statistics are the backbone of economic policymaking, and they were mostly designed in the 1950s. The man who ran BLS through the pandemic has a lot to say about what needs to change. Topics covered: Why BLS was built for a world of probability sampling that no longer works How the design of a survey encodes a worldview How Indigenous Americans had a 37% unemployment rate at the peak of the pandemic What happened when the BLS commissioner was fired How private data and official statistics compliment each other Why the longitudinal survey of the Covid generation just got defunded About Bill Beach: Bill Beach served as the 15th Commissioner of the Bureau of Labor Statistics, overseeing the agency through the Covid pandemic under two administrations. He now leads the Fiscal Lab at the American Enterprise Institute, focusing on labor market data, economic measurement, and federal statistical policy. Follow Ben on LinkedIn Follow us on LinkedIn Sign up for our Newsletter Visit our website for more information Get in touch with us at info@reveliolabs.com
The AI and work debate has been dominated by economists with exposure scores and tech CEOs with predictions. What's been missing is the ground-level view of how work is changing for the people actually living it now. Topics covered: Why the biggest effects of AI on work are showing up in quality, not quantity Why job losses are happening first in the gig economy Why some innovations are an augmentation for one worker and automation for another Why worker voice matters more than any particular policy Why the current labor market freeze is less about satisfaction than about fear Check out We Are Not Machines here: https://a.co/d/07COglMk Read Sarah's work at the Financial Times here: https://www.ft.com/sarah-o-connor About Sarah O'Connor: Sarah O'Connor is a columnist and associate editor at the Financial Times, where she covers work, employment, and the labor market. She is the author of We Are Not Machines: The Fight for the Future of Work. Follow Ben on LinkedIn Follow us on LinkedIn Sign up for our Newsletter Visit our website for more information Get in touch with us at info@reveliolabs.com
Productivity growth in the US has jumped by about a percentage point since 2023. That's a big deal. Whether AI is the cause, or just the context, is a much harder question to answer than most commentary assumes. Topics covered: Why labor productivity and total factor productivity are telling completely different stories right now Why quality-adjusting a data center over months is nearly as hard as comparing a 1790 warship to an Aegis cruiser How AI displacement tends to happen: not gradually, but in sudden drops during recessions when firms rebuild with newer technology The travel agent case: why the survivors of automation end up paid more, and why that doesn't make the disruption less real Why controlling for population aging, the US employment rate is near a non-WWII high — and what that implies about long-run fears New business formation as a productivity engine, and whether AI-era solopreneurs will hire up the way small businesses historically have Research mentioned: San Francisco Fed Total Factor Productivity measure — SF Fed Check out Stripe Economics here: https://stripe.com/research Follow Ernie on Substack here: https://ernietedeschi.substack.com/ About Ernie Tedeschi: Ernie Tedeschi is chief economist at Stripe and former chief economist at the Council of Economic Advisers. He previously led economics at the Yale Budget Lab. His research spans labor markets, fiscal policy, and the macroeconomics of technological change. Follow Ben on LinkedIn Follow us on LinkedIn Sign up for our Newsletter Visit our website for more information Get in touch with us at info@reveliolabs.com
If AI agents can represent us in negotiations, handle our hiring, shop on our behalf, and coordinate across firms without friction, a lot of what economists call market failures start to look solvable. That used to just be a thought experiment, but it might be getting closer and closer to reality. Topics covered: Why the entire economy right now is essentially a bet on AI yielding large productivity gains The cosine singularity: what markets look like when agents negotiate on our behalf and transaction costs collapse Why AI could potentially make the labor market more like professional sports, where performance is always being observed The best workers are often purposely not doing what their job description says, and why a panopticon would miss that Why intelligence has diminishing returns, and why the returns are probably highest where it's currently scarcest Why the paper circuit is a waste of time right now, and what economists should be doing instead Research mentioned: Fradkin et al., "The Coasean Singularity? Demand, Supply, and Market Design with AI Agents" — NBER Check out the Justified Posteriors podcast here: https://www.justifiedposteriors.com/ Check out Andrey's website here: https://www.andreyfradkin.com/ About Andrey Fradkin: Andrey Fradkin is an assistant professor of economics at Boston University and co-host of the Justified Posteriors podcast. His research focuses on market design, platform economics, and the economics of AI. Follow Ben on LinkedIn Follow us on LinkedIn Sign up for our Newsletter Visit our website for more information Get in touch with us at info@reveliolabs.com
When two people have a conversation in person, their brains synchronize. Over Zoom, they lose 90% of that neural synchrony. That's the starting point for understanding what remote work has actually cost us. Topics covered: Why in-person work drives creativity How remote work reduced written code feedback by 20% even between people on the same campus Why remote work hurts junior workers twice: separated from mentors and now from the entry-level tasks AI is taking Why managers are 40% off in estimating how much workers value remote work The difference between a return-to-office mandate and a return to meaningful in-person interaction Check out Natalia's book here: https://a.co/d/0fe5GEHr About Natalia Emanuel: Natalia Emanuel is a research economist at the Federal Reserve Bank of New York. Her research focuses on the economics of remote work, mentorship, and workplace productivity. She is the author of In Person: How Working Together Fuels Creativity, Productivity, and Growth. Follow Ben on LinkedIn Follow us on LinkedIn Sign up for our Newsletter Visit our website for more information Get in touch with us at info@reveliolabs.com
There are three distinct communities doing economics of AI research, and they don't always agree. Seth Benzell sits at the intersection of all of them and has views about where each one goes wrong. Topics covered: The three factions of AI economics: digitization, macro labor, and growth Why "directing technical change" toward pro-worker outcomes is probably less controllable than the optimists think Diminishing returns to intelligence Capital accumulation as an underrated story Why human task data is a factor of production Why priors in economics shift more from being weakly held than from unusually strong evidence Check out the Justified Posteriors podcast here: https://www.justifiedposteriors.com/ Check out Seth's website here: https://www.sethgbenzell.com/ Research mentioned: Acemoglu & Restrepo, "The Race Between Man and Machine" — NBER Sutton's Bitter Lesson — http://www.incompleteideas.net/IncIdeas/BitterLesson.html Kevin Bryan on RCTs and economic dentistry — A Fine Theorem About Seth Benzell: Seth Benzell is an assistant professor of economics at Chapman University and co-host of the Justified Posteriors podcast. His research focuses on the macroeconomics of automation, capital accumulation, and AI's long-run effects on growth and labor markets. Follow Ben on LinkedIn Follow us on LinkedIn Sign up for our Newsletter Visit our website for more information Get in touch with us at info@reveliolabs.com