Overview of Why you overpaid at that online auction
This NPR episode (The Indicator) explains the “winner’s curse”: why the highest bidder in auctions often overpays. Using a classroom jar-of-coins experiment, interviews with Nobel laureate Richard Thaler (co‑founder of behavioral economics), historical examples, and corporate case studies, the episode describes where the phenomenon comes from, why it matters in business (M&A, drafts, corporate deals), and how to guard against it — with a look at whether the current AI arms race might be susceptible.
Key points and main takeaways
- Definition: The winner’s curse occurs when the winning bidder systematically overpays because their estimate was an outlier — they were the most optimistic about the item’s value.
- Origins: First noticed by oil companies in the 1970s bidding for Gulf of Mexico drilling rights; winners repeatedly got less oil than expected.
- Statistical intuition: The auctions you win are not a random sample — they’re the ones where your estimate was unusually high compared to others. The more bidders, the greater the chance the highest bid is an overestimate.
- Empirical support: Studies and examples show highest bidders in competitive takeovers tended to be less profitable after the deal; Thaler also found evidence in the NFL draft and many corporate mergers.
- Practical implication: When many bidders compete, bid more cautiously or seek ways to avoid open competition.
Examples from the episode
- Classroom experiment: A jar of coins worth $8 drew bids; the winner paid $9.25 — a small, relatable instance of the winner’s curse.
- Oil drilling: Gulf of Mexico leases — winning bids correlated with worse-than-expected oil yields, revealing the phenomenon.
- Corporate M&A study: Analysis of 56 takeovers (mid‑80s to 2012) found the highest bidders often became significantly less profitable than losing bidders.
- Personal anecdote: Thaler’s boardroom rule — insist on exclusivity when acquiring companies to avoid competitive bidding that creates winner’s‑curse risk.
- Wine-auction anecdote: Making many low bids reduced curse risk; they won cheaply when turnout dropped.
Why it matters now — AI and tech competition
- The episode raises the question: could the AI talent/compute arms race produce a winner’s curse? Firms paying huge sums for top talent or compute capacity risk overestimating future returns if incremental AI gains don’t justify massive investment.
- Thaler: It’s plausible; incumbent tech/products (search, Wikipedia, existing tools) may already be good enough that enormous incremental investments won’t pay off.
How to reduce the risk of the winner’s curse (practical steps)
- Avoid open auctions when possible: secure exclusivity or negotiated deals.
- Bid more conservatively if many bidders are expected; adjust downward for competition-driven optimism.
- Use strategies that reduce exposure to being the most optimistic (e.g., many small low bids so you only win when prices are genuinely low).
- Incorporate independent valuation checks and scenario analysis (what if quality/benefit is lower than my estimate?).
- Consider strategic alternatives (partnerships, staged investments) rather than an all-in one-time purchase.
Notable quotes & pithy lines
- “The auctions you win are not a random sample of the ones you bid. They’re the ones you bid high.”
- “If there were 100 bidders, you should be pretty worried.”
Further reading / resources
- Richard Thaler, The Winner’s Curse: Behavioral Economics Anomalies, Then and Now (co‑authored book mentioned in the episode).
- The Indicator (NPR) — episode production credits: produced by Julia Ritchie; edited by Kate Concanon.
Bottom line
Winning an auction feels good — but if many people competed, winning can be a warning sign you overestimated value. Businesses and individuals should adjust bidding strategies, seek exclusivity when possible, and account for optimism and competition when valuing targets (from companies to AI talent and compute).