Podcast Summary
Podcast: The Brainy Business – Understanding the Psychology of Why People Buy
Host: Melina Palmer
Episode: 543. The Winner’s Curse
Date: October 23, 2025
Guests: Dr. Richard Thaler (Nobel Laureate, Pioneer of Behavioral Economics), Dr. Alex Emas (Behavioral Economist, University of Chicago)
Episode Overview
In this milestone episode, Melina Palmer welcomes Nobel Prize-winning economist Dr. Richard Thaler and co-author Dr. Alex Emas to discuss the newly reimagined book The Winner’s Curse. The discussion navigates the evolution of behavioral economics—from its roots in anomaly-spotting to today’s robust, data-driven field engaging with real-world markets and the rise of AI. The conversation offers practical insights for anyone seeking to understand why smart people make predictably irrational decisions, the importance of noticing anomalies, and how behavioral economics is deployed in business.
Core Themes & Discussion Points
1. Evolution and Definition of Behavioral Economics
[03:06–09:06]
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Richard Thaler reflects on “messing with economists for 40 or 50 years,” introducing psychology into rigid economic models. He credits the shift to ideas from Daniel Kahneman and Amos Tversky, highlighting the importance of descriptive accuracy in economic models:
“I got the idea that I could use their concept of systematic bias to create another way of doing economics that would have better descriptive models. So more accurate descriptions of what people do.”
— Richard Thaler, [07:15] -
Alex Emas elaborates the distinction between behavioral economics and psychology: Behavioral economics compares real-world “anomalies” to idealized, rational behavior in traditional economic models, especially in market contexts:
“Behavioral economics is kind of defined relative to standard economics, where you have the standard model and show how there are anomalies… But where behavioral economics departs from psychology is that it’s really rooted about economic questions.”
— Alex Emas, [08:11]
2. Anomaly-Spotting: The Genesis of The Winner’s Curse
[09:06–14:53]
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Thaler’s interest in anomalies originated from questioning models that didn’t match observed behavior.
“I would see these models and my reaction was really, is that what people are doing?”
— Richard Thaler, [10:01] -
The Winner’s Curse began as a quarterly “Anomalies” column for the Journal of Economic Perspectives in 1987, later bound into the original book.
3. Why a New Edition? What’s Different Now?
[14:53–18:55]
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Alex explains the new edition is “essentially a new book”—two-thirds new material—and each anomaly is now followed by a robust, data-rich update on its relevance today. They showcase the real-world, global endurance of these findings.
“It’s not just lab subjects at UBC, it’s also professional golfers. It’s also traders on some of the biggest exchanges in the world… So that’s something we really wanted to emphasize... there’s no replication crisis in behavioral economics.”
— Alex Emas, [17:02]
4. Empirical Developments: From Lab to Real World
[18:55–22:42]
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Thaler highlights the leap from survey data to massive consumer data sets. Example: During the 2008 crisis, gas prices fell and “people started buying more premium gas,” a clear case of mental accounting (using “saved” money for luxury, even in a recession).
“From anecdotes and experiments… to data with real people, real consumers. There are lots of others with traders and so forth.”
— Richard Thaler, [20:54] -
Alex points to the endowment effect—first in mugs and pens, now visible in the housing market—showcasing the growing breadth and impact.
“Sellers who own their own house set very different prices… because essentially sellers are endowed with their house. They set too high of a price and then they don’t move it as fast.”
— Alex Emas, [21:26]
5. Favorite Chapters & Signature Anomalies
[22:42–36:10]
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Thaler’s Favorite: The finance chapter on “law of one price” is full of “smoking gun anomalies” with funny examples like the CUBA fund, which skyrocketed due to investor confusion over the name:
“It was the day that President Obama announced his intention to relax relationships with [Cuba]… although the fund cannot invest in Cuban securities, and there aren’t any Cuban securities.”
— Richard Thaler, [25:56] -
Alex’s Favorite: The titular “Winner’s Curse,” where winning an auction means you likely overpaid. Even sophisticated bidders fall prey because they fail to adjust for the fact that winning means their estimate is the highest (thus, likely too high):
“You could literally go to a bar down the street, put down a jar of pennies, and make some money because you’re going to get the winner’s curse.” — Alex Emas, [30:39]
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Loser’s Curse/NFL Draft: Thaler’s research with Cade Massey shows NFL teams systematically overpay for top draft picks, even though the probability of a higher pick beating the next is just 53%—almost a coin toss.
“You shouldn’t give away the house for the right to pick the first one… there’s only a 53% chance that he’s really better than the next one.” — Richard Thaler, [32:41]
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Preference Reversals: Melina’s favorite concept, showing that even small changes in how options are presented can reverse choices.
“Just getting started into this idea… how you frame something will impact the choice someone is going to make.”
— Melina Palmer, [34:43]
6. Reflections on Co-authors and the Evolution of Behavioral Economics
[34:44–36:10]
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Thaler reflects on the importance of working with Amos Tversky and preserving collaborators’ voices in the new edition:
“He was a genius and very meticulous thinker and, and also funny. So there’s a chapter there with Amos. There are two chapters that were Dania was a co author… We leave their names there because they’re important.”
— Richard Thaler, [35:14]
7. Technology, AI, and the Behavioral Economics of the Future
[37:52–44:20]
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Alex: Integration of AI will make behavioral economics even more relevant. AI personalizes choice architectures, supercharges A/B testing, and could exploit—or support—consumer decision-making depending on ethical use.
“Everything is going to be kind of customized to every user… AI could potentially kind of supercharge it… much more relevant for business than it used to be just because of the scale at which it could be deployed… for good and for bad.”
— Alex Emas, [38:08] -
Thaler: Urges long-term customer trust over short-term gains. Illustrates with the Home Depot hurricane example—behavioral insights can help build brand loyalty rather than exploiting customers.
“You can… take advantage of them and you can make money that way. It’s not the way I would choose to run a firm. I would prefer to run a firm that people come back to because they think they can trust us.”
— Richard Thaler, [43:00]
8. Advice and Takeaways for Listeners and Future Behavioral Economists
[44:20–48:27]
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Thaler: “Understand the way the people you interact with think. So they're your customers, your employees, your competitors, and it's a long game with all of them. Don't try to win every exchange. Take the long view.”
— [45:24] -
Alex: Watch out for status quo bias. Embrace change, especially with new technology—avoid clinging to familiar methods at the expense of progress.
“One of the lessons from behavioral economics is that you should just be absorbing the information that you have and don’t put any extra weight on things that you’re endowed with… process information as it’s coming in…”
— Alex Emas, [46:40]
9. Open Research Questions & The Nature of Difficulty in Choice
[50:00–51:36]
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Thaler highlights an unsolved question: How do we define and measure what makes a decision difficult? Different problems (e.g., tic-tac-toe vs. chess) require different models, yet economics often applies a “one-size-fits-all” optimization model.
“We don’t have a metric for what makes something hard. And we think there ought to be more research on that though we say it’s a hard problem.”
— Richard Thaler, [51:07]
Notable Quotes & Moments
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On anomaly-spotting:
- “So often… we’re trained to look for patterns… But sometimes the most powerful signals are the ones that don’t fit neatly into the story.”
— Melina Palmer, [53:03]
- “So often… we’re trained to look for patterns… But sometimes the most powerful signals are the ones that don’t fit neatly into the story.”
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On replication and robustness:
- “There’s no replication crisis in behavioral economics”
— Alex Emas, [17:24]
- “There’s no replication crisis in behavioral economics”
-
On endowment effect in housing:
- “If you’re shopping for a house, don’t bother to negotiate with somebody who paid more for it than what it’s worth now. It’s not worth your time.”
— Richard Thaler, [22:16]
- “If you’re shopping for a house, don’t bother to negotiate with somebody who paid more for it than what it’s worth now. It’s not worth your time.”
Timestamps for Key Topics
- [03:06–09:06] — Defining behavioral economics (Thaler & Emas)
- [09:06–14:53] — The genesis of The Winner’s Curse and anomaly columns
- [14:53–18:55] — Why and how the new edition is different (Evolving research)
- [18:55–22:42] — From anecdote to big data: the maturation of the field
- [22:42–36:10] — Favorite chapters/anomalies; example stories (CUBA fund, Winner's & Loser's Curse)
- [37:52–44:20] — Impact of AI and technology; business implications
- [44:20–48:27] — Advice for the future: long-view, status quo bias, embracing change
- [50:00–51:36] — Open research question: What makes a choice difficult?
Final Thoughts from the Host
Melina reflects on the power of curiosity about anomalies—a mindset at the core of behavioral economics. She encourages listeners to look for what doesn’t fit, suggesting those “quiet outliers might just hold the key to something remarkable.”
Where to Learn More
- Thaler and Emas are both active on Twitter.
- Check the episode show notes for links to The Winner’s Curse (new edition) and additional behavioral economics resources.
This summary collects and organizes the rich ideas from the conversation, preserving the warmth, humor, and clarity of the original speakers. It’s ideal for those wanting a deep yet digestible briefing on a landmark episode in behavioral economics, business, and decision science.
