New Zealand, 1990. The government hires consulting firm NERA, which recommends a sealed second-price (Vickrey) auction — a format whose theoretical foundations would earn a Nobel Prize six years later. Expected revenue: NZ$250 million. Actual revenue: NZ$36 million. One bidder offered NZ$100,000 and paid NZ$6. Another bid NZ$7 million and paid NZ$5,000.

One wrong choice of auction format cost the treasury NZ$214 million.

In 2019, Google changed the auction format for the $48 billion programmatic advertising market. In 2021, the FCC raised $81 billion in a C-band spectrum auction — a world record that still stands. The EU ETS has generated over €250 billion from auctioning the right to pollute since 2013. In every case, it wasn’t the good that determined the price — the auction rules determined the price.

Four Basic Auctions

Every auction in the world is a combination of two variables: open or sealed bids, and whether the winner pays their own price or someone else’s.

First-Price (pay your bid)

Dutch (open, descending)Price falls from ceiling. First to say "stop" wins and pays current price. Strategy: wait longer = cheaper, but risk losing.
Sealed first-price (closed)Tenders, government procurement, programmatic ads since 2019. All submit bids in sealed envelopes. Highest wins. Strategy: bid shading — bid below true value.

Second-Price (pay 2nd bid)

English (open, ascending)Christie's, Sotheby's. Price rises. Last bidder standing wins and pays just above second-highest. Strategy: bid up to your true valuation, no higher.
Vickrey (sealed second-price)Foundation of the 1996 Nobel Prize. Highest bid wins, but pays second price. eBay's proxy bidding. Dominant strategy: bid exactly your true valuation.
Strategic equivalence: Dutch ≡ sealed first-price — strategically identical regardless of how bidders value the good (same information, same strategy, different pacing). English ≈ Vickrey only under independent private values: both make the winner pay ≈ the second valuation. With correlated values the English auction leaks information as rivals drop out, and the equivalence breaks.

How It Works: One Item, Three Prices

Three bidders value a painting at $100, $80, and $50. What happens under different rules?

First-Price Sealed

Optimal bid with n=3: b(v) = v × ⅔
  • Bidder A: values $100, bids $67 — wins
  • Bidder B: values $80, bids $53
  • Bidder C: values $50, bids $33
  • Seller receives: $67

Vickrey (Second-Price)

Dominant strategy: bid your true value
  • Bidder A: values $100, bids $100 — wins
  • Bidder B: values $80, bids $80
  • Bidder C: values $50, bids $50
  • Seller receives: $80 (second bid)

English (Open Ascending)

Price rises until one bidder remains
  • C drops out at $50
  • B drops out at $80
  • A wins, pays $81 (one step above B)
  • Seller receives: ≈$80

Bidding Formulas

Second-Price (Vickrey)

b(v) = v. Bid your true value. Always. Dominant strategy — independent of number of participants and their behavior.

b(v) = v

First-Price (Sealed)

b(v) = v × (n−1)/n. With 2 bidders: shade 50%. With 10: shade 10%. More competition → more aggressive bids.

b = v·(n−1)/n

Bid shading by number of participants (value = $100, first-price):

n = 2
$50
$50
n = 3
$67
$67
n = 5
$80
$80
n = 10
$90
$90
n = 20
$95
$95
n = 100
$99
$99

Revenue Equivalence Theorem

E[RevenueFP] = E[RevenueSP] = (n−1)/(n+1) With n bidders drawing values from U[0,1], the expected seller revenue is identical across all four formats. The key word is expected: in any single auction prices differ, but across many they converge. Proved for two bidders by Vickrey (1961); generalised independently by Myerson (1981) and Riley & Samuelson (1981). Vickrey's broader work on auctions earned the 1996 Nobel Prize.

Conditions: independent private values, risk neutrality, symmetric bidders, no collusion. In reality, every condition is violated — making format choice a critical decision.

Independent private values

If holds: all formats equal
  • If violated: English yields more (less winner's curse)
  • Example: oil exploration — correlated values

Risk neutrality

If holds: RE works
  • If violated: first-price yields more (risk-averse bidders shade less)
  • Example: government contracts

Symmetric bidders

If holds: RE works
  • If violated: strong bidder shades more; weak overbids
  • Example: NZ 1990 — incumbent vs newcomer

No collusion

If holds: RE works
  • If violated: second-price → floor manipulation; English → ring bidding
  • Example: header bidding SSPs

The New Zealand Disaster

NZ$250M
expected revenue
NZ$36M
actual revenue
86%
revenue lost

Specific lots:

Lot Bid Paid Discount
Radio frequency license NZ$100,000 NZ$6 99.994%
Radio frequency license NZ$7,000,000 NZ$5,000 99.93%
National cellular license NZ$101,000,000 NZ$11,000,000 89.1%
Sky Network TV, Lot 1 NZ$2,371,000 NZ$401,000 83.1%
Three design errors: (1) No minimum price (reserve price) — you could bid $6. (2) Sold identical licenses through separate Vickrey auctions instead of a unified uniform-price auction. (3) Asymmetric participants (incumbents vs newcomers) — revenue equivalence breaks down.

Comprehensive Format Comparison

English (ascending)

Christie'seBayFCC SMRA
  • Strategy: bid up to true value
  • Pays: ≈ 2nd valuation
  • Info: high — see other bids
  • Speed: slow (minutes–hours)
  • Collusion resistance: low
  • Winner's curse: less dangerous

Dutch (descending)

Aalsmeer flowersGoogle IPOTreasury
  • Strategy: bid shading
  • Pays: own bid
  • Info: low — one price
  • Speed: very fast
  • Collusion resistance: high
  • Winner's curse: dangerous

First-Price (sealed)

ProcurementTendersProgrammatic 2019+
  • Strategy: bid shading
  • Pays: own bid
  • Info: zero
  • Speed: one round
  • Collusion resistance: high
  • Winner's curse: most dangerous

Vickrey (second-price)

eBay proxyRTB 2007–2017
  • Strategy: b(v) = v (dominant)
  • Pays: 2nd bid
  • Info: medium — 2 prices
  • Speed: one round
  • Collusion resistance: medium
  • Winner's curse: absent

Ad Auctions: 100 Milliseconds and $500 Billion

Advertising auctions are the most massive in history: trillions of auctions per day. Their 12-year evolution recapitulated the path auction theory traveled over 50 years.

2007
RTB and second-price auctions
Birth of programmatic: SSPs run real-time Vickrey auctions. Highest bidder wins and pays second price + $0.01. Truthful bidding — everyone bids their true value.
~2012
Waterfall: cascade of inefficiency
Publishers call ad networks sequentially: Google first, then rest. An $8 bid from the third SSP never beats the $5 price from the first — it's never seen. Loss: 20–40% of revenue.
2014–15
Header bidding: simultaneous auctions
Revolution. All SSPs receive bid requests simultaneously. Prebid.js (2015, open source, AppNexus-led) becomes the de facto standard wrapper. Publisher RPM gains commonly 20–40%. Sequential → simultaneous auction.
2017
Exchanges switch to first-price
OpenX, Rubicon Project and others drop second-price. Reason: in header bidding, second-price enables SSP floor-price manipulation. First-price is simpler and more transparent.
2019
Google Ad Manager → unified first-price
Google — the last major exchange. Eliminates "last look" privilege. Unified auction = one first price for all. Bid shading becomes mandatory. The $48B market shifts overnight.
2021
AdSense → first-price. Full circle.
Display AdSense (Content/Video/Games) drops second-price. Theory said second-price → truthful. Practice: first-price + bid shading. Search ads (Google Search, AdSense for Search) stay on the GSP auction — still second-price-flavoured, but never truthful (see below).
Summary: Ad industry traveled from Vickrey (2007) to first-price (2019) in 12 years — for the same reasons Vickrey described in 1961: when values correlate, bidders are asymmetric, and intermediaries exist, second-price creates manipulation opportunities. The theory wasn't wrong — the conditions of application were.
The GSP trap — why "second-price" search ads aren't truthful: Google's search-ad auction is the Generalized Second-Price (GSP) auction: rank advertisers by bid, give the top slot to the highest, and charge each winner the bid just below them. With one slot, GSP is exactly Vickrey — bid your value, dominant strategy. With multiple slots it is not: truth-telling stops being an equilibrium, and bidders gain by shading. Edelman, Ostrovsky & Schwarz (2007) and Varian (2007) proved this — and noted that Google's own marketing once invoked Vickrey's "Nobel Prize-winning" truthfulness for a mechanism that does not, in general, have it. GSP is not a misimplemented Vickrey; it is a different auction that merely borrows the name.

Auctions in Finance

Financial markets are auctions with different names. Treasury, IPO, buyback — the same mechanisms everywhere.

US Treasury Bills

Dutch / uniform-price auction
$23T+ debt
  • Fed NY sells government bonds via Dutch auction
  • Primary dealers bid with desired yield
  • All winners pay a single price

Google IPO, 2004

Modified Dutch auction
$1.67B raised
  • Investors specified price and volume
  • Final price $85 — uniform for all
  • First day: +18%. Goal: minimize underpricing

Stock Exchanges

Continuous double auction
~$120T/year
  • NYSE, NASDAQ — buyers and sellers bid simultaneously
  • Trade on bid/ask intersection
  • Billions of trades daily

EU ETS Carbon Market

Sealed uniform-price
€250B+ since 2013€38.8B in 2024 alone
  • Weekly auctions on EEX exchange
  • Average 2024 price: €65/tCO₂ (peak 2023: €100+)
  • 599M allowances sold in 2024

Energy Markets

Uniform-price merit order
€60–300/MWh
  • EPEX SPOT (Europe), PJM (US): hourly bids
  • Cheapest sources (solar, wind) first, then expensive (gas)
  • Marginal price = last generator activated

FCC Spectrum Auctions

SMRA (Milgrom-Wilson design)
$81B record

Auctions in Technology

AWS Spot Instances

Up to 90% discount on idle EC2 capacity
  • Since 2009: auction for unused compute
  • In 2017 switched from pure auction to smoothed pricing
  • Interruption: 30 sec – 2 min notice

Ethereum Gas (EIP-1559)

First-price → hybrid mechanism
  • Pre-2021: pure first-price auction for block space
  • Post-EIP-1559: base fee (algorithmic) + priority tip
  • Significant reduction in fee volatility and waiting times

Domain Auctions

English auction + reserve price
  • GoDaddy, NameJet, DropCatch for expired domains
  • voice.com sold for $30M (2019)
  • Premium domains via sealed-bid on Sedo/Afternic
Pattern: The same evolution repeats everywhere. Start with a pure auction (AWS Spot 2009, Ethereum pre-1559, programmatic 2007). Over time, transition to a hybrid: auction mechanism + algorithmic pricing. Pure auctions are too volatile for production systems. Stability beats theoretical optimality.

Where Auctions Are Heading

AI Bidding Agents

Now → 2027
  • ML algorithms already do bid shading (Google, TTD)
  • Next: autonomous agents trading without humans
  • Risk: algorithmic collusion without explicit agreement

Privacy-Preserving Auctions

Now → 2028
  • Apple ATT, Privacy Sandbox, EU DSA — user data disappearing
  • On-device bidding, federated auctions, contextual signals

Combinatorial Auctions

2025+
  • FCC Incentive Auction (2017) — first major two-sided example
  • Station-repacking is NP-hard; recast as SAT and solved by SATFC
  • Next: 5G/6G shared spectrum, multi-cloud procurement

Dynamic Mechanism Design

2026+
  • Classical theory covers one-shot auctions
  • Reality: billions of repeated auctions with learning participants

Real-Time Energy Markets

2025+
  • P2P electricity auctions between households
  • Pilots: Power Ledger (Australia), Sonnen (Germany)

Auctions → Automatic Markets

Long-term
  • AWS Spot is no longer an auction — it's algorithmic pricing
  • Pure auctions dissolve into dynamic pricing
  • The foundation — auction theory — remains

Evolution: From Gavel to Algorithm

Pre-20th century
English, Dutch — minutes to hours
People in a room. Christie's (1766), Aalsmeer flower auction (1911).
1960–1990
Sealed-bid, Vickrey — days to weeks
Companies + governments. NZ Spectrum 1990, US Treasury auctions.
1994–2010
SMRA, combinatorial — weeks to months
Telecoms + regulators. FCC Auctions designed by Milgrom & Wilson (Nobel 2020).
2007–2019
RTB second → first-price — 100ms
DSP/SSP algorithms. Programmatic advertising, header bidding revolution.
2020+
ML bid agents + hybrid — microseconds
AI vs AI. Auto-bidding, Spot pricing, EIP-1559. Auction theory as invisible OS.

One Lesson

Rules determine behavior. Behavior determines price. Whoever designs the rules owns the market.

The same radio waves cost between $0.001 and $0.875 per MHz/pop — an 875× difference. The same ad generates 30–40% more or less revenue depending on the auction format. The same carbon costs €5 or €100 — depending on cap-and-trade rules.

An auction is not a gavel at Christie’s. It’s a model of any market with competition for a scarce resource.

AI Disclosure: Research conducted with Claude (Anthropic). Human editorial direction and domain expertise.