Participation, Not Prices

How a Consumer Resale Market Absorbs Scheduled News

Information-Perishable Goods and the Missing Margin of Dynamic Pricing

Evidence from 178M observations of the FIFA World Cup 2026
Final resale order book · June 12 – July 19, 2026

Draft v9 · July 2026

The puzzle in one slide

July 15, 2026, 21:05 UTC. England–Argentina ends. The second finalist is public, worldwide, instantly.
  • A Final ticket's value just jumped for Argentina's fans and collapsed for England's — for everyone, at the same instant.
  • Thirty years of dynamic-pricing theory (Gallego & van Ryzin 1994 → state-dependent p(x,t,s)) predict: sellers reprice immediately.
  • Sweeting (2012, JPE): even household sellers reprice along the calendar — 40%+ declines approaching the event.
Our measurement at 5-minute resolution: median continuing seller's price change at the whistle = exactly 0.0% — at every resolution, in 26 of 29 testable cells.

The asset class: information-perishable goods

Time-perishable (the canon)

  • Value decays along the calendar toward a deadline
  • Airline seats, hotel rooms, event tickets
  • Seller's problem: when to discount
  • Validated empirically (Sweeting 2012)

Information-perishable (this paper)

  • Value jumps or collapses at scheduled public epochs
  • Tournament tickets, playoff-conditional products
  • Seller's problem: how to reprice on a resolution tree
  • Measured here for the first time
The puzzle: the same households who optimize over the calendar do nothing over the state tree. Yet the market clears. How?

The benchmark: what theory says sellers should do

ModelPolicyPrediction at a public shock
Gallego & van Ryzin (1994, MS)p(x,t)Decline toward expiry; continuous adjustment
Talluri & van Ryzin (2004)target pathShortfall ⇒ cut; scarcity ⇒ raise
Su (2007); Levin–McGill–Nediakstrategic customersFlatter paths, but never zero response
Aviv & Pazgal (2008, MSOM)two-periodShock = structural break; re-solve the game
den Boer (2015); Feng & Xiao (2012)p(x,t,s)State change ⇒ immediate policy change
One line: for thirty years, in every variant, the optimal policy responds immediately when demand-relevant information becomes public. Our sellers: 0.0%.

Contributions

  1. A precise zero (fact). Median reprice 0.0% at state resolutions — 26/29 cells across the entire 30-match knockout bracket; degenerate CIs. RM capability is dimension-specific.
  2. A measurement warning (export). Every index move decomposes into composition or a repricing minority — never the median seller. Price-index event studies read participation as repricing.
  3. A dose-graded participation response (mechanism). Quantities respond monotone in state resolved (R32 −0.3% → SF −12.2%); demand strikes at certainty, not surprise.
  4. Design & policy pricing (so-what). The measured gaps price the fixes — platform tools, organizer instruments, and a regulatory redirect (US FIFA subpoenas; China's sha-shou rules).

Data: the full resale order book

SourceContentCoverage
FIFA official resale (households)Every seat: block/row/seat, category, USD price5-min, Jun 24–Jul 19; 167.0M seat-obs, 52 matches
TickPick (brokers/API)Event listing count, min/mean/max15-min, Jun 13–Jul 19, continuous
Vivid, TicketNetworkEvent stats + full listings15-min + ~4×/day (complete)
Gametime; StubHub/ViagogoEvent stats / page totals15-min / top-grid; common ownership
  • Deduplicated: 178.2M → 178.0M rows; three panel generations unioned.
  • Cross-platform: FIFA↔broker inventories ≈99% disjoint; Vivid↔TicketNetwork ~33% shared.
  • One consolidated DuckDB database (19 base tables + analysis views).

The shocks: every knockout match, not a selected subset

RoundEventsState resolved (dose)Window
Round of 32161 of 32 teamsJun 28 – Jul 3
Round of 1681 of 16Jul 3 – 7
Quarter-finals41 of 8Jul 9 – 12
Semi-finals21 of 4 (finalist)Jul 14 – 15
Why credible: pre-scheduled timing (no endogeneity), content unknowable in advance, globally public at one instant, 30 repetitions on one asset family.

Result 1 — The intensive margin is exactly zero

Event (FT, UTC)Continuing seatsRepricedMedian reprice
QF Morocco (Jul 9)68020%0.0%
QF Belgium (Jul 10)7371%0.0%
QF Norway (Jul 11)8011%0.0%
QF Switzerland (Jul 12)8011%0.0%
SF France (Jul 14)8372%0.0%
SF England (Jul 15)87013%0.0%
  • Same at 20 further R32/R16 resolutions: 26/29 clean cells (3 excluded: documented feed rescale).
  • Full asset matrix: 27 asset×event cells (7 ticket assets × QF/SF whistles) — median 0.0% in 27/27; repriced shares 0.3–49.6% within cells.
  • 95% bootstrap CI for the median is degenerate at zero.
  • Not a platform lock: off-epoch hazard 0.2%/hr; the 1–20% minority moves up +42% at the two largest events.

Tier A — precisely estimated causal null

Result 2 — Dose gradient across the full bracket

RoundCellsMedian Δ listings (TickPick)Regime tail p
R328−0.3%inside pool
R168−0.6%inside pool
QF4−1.0%0.01–0.14
SF2−12.2%0.012–0.014
  • SF cells: −10.7%, −13.8% within 1h; ~3× the largest same-day non-whistle movement (±4.3%); day-block bootstrap p < 10⁻⁴.
  • Placebo assets (3rd-place tickets at QF whistles): flat, −0.0% to −1.6%.
  • Monotone in dose — and in calendar proximity (collinear; disclosed).
  • No cherry-picking: every knockout match is in the table.

Tier A (timing) / B (magnitude — dose collinear with days-to-expiry)

Result 3 — Index moves misattribute the mechanism

EventTotal ΔWithinExitEntrantAttribution
Morocco+8.9%+8.9%0.0−0.1repricing minority (20%)
Belgium+1.1%−0.2%+1.1%+0.2composition
Norway, Switz., France0.0%0.0%0.0%0.0%
England+3.4%+0.0%+3.4%0.0composition (cheap exits)
The warning: a naive index study reports "sellers raised prices" (England), "the median seller repriced" (Morocco), or "nothing happened" (France, while 10.7% of the market changed hands). Decomposition is not optional at information epochs.

Tier A — accounting decomposition (mechanical, given the data)

Result 4 — Supply fire sales, demand at certainty

Supply: wealth-graded, hours late

  • Post-elimination entrants vs same-day median: Morocco −28%, Switzerland −23%, England −22%, France −13% (Norway +10%, Belgium +56% also shown)
  • Entry begins ~3h after the whistle
  • Exits are the cheap tail (13–49% below market)

Tier B (entry timing) / C (level) / D (wealth gradient, n=4)

Demand: certainty, not surprise

  • All four QF winners were favorites — flows still wait for the whistle
  • Decided match: flat in-play series for 2h, step at FT
  • Contested match: −7% in-play bleed, still −22% in 45 min post-FT
  • Hypothesis (pending odds): irreversible complements require p = 1

Tier D+ — hypothesis, strong circumstantial support

Result 5 — Lifecycle: consumed vs flipped (with DiC)

Platform / EventFlip ΔContinuing ΔDiC gap
Vivid / SF France−1.2%+1.6%−2.8pp
Vivid / SF England−17.2%+1.8%−19.0pp
TicketNetwork / SF England−20.6%+0.0%−20.6pp
  • Whistle changes the rate of exit (40% vs ~30% baseline), not the type (whistle exits reappear more than baseline).
  • No instant-arb markups (flips return 0 to −18%): pickoff is speed + continued downward discovery.
  • Rent-transfer number ($1,500–2,000/ticket) not supported by flip evidence — cut, flagged for matched-counterfactual design.

Tier B (DiC: −19 to −21pp gap at England SF, within-window comparison)

Contrast panel — the calendar channel, at scale

  • 30 knockout matches' own markets terminate at pre-kickoff sales cutoffs.
  • Listings collapse 47–89% in the final hours — gradual (absorption, not cutoff mechanics).
  • Prices drift +2.5% median (IQR −8.3 to +14.3): cheap inventory absorbed first — composition again.
One market, one margin: calendar deadlines and state resolutions are absorbed by the same margin — participation. Sweeting's discounting channel is invisible in indices in both regimes.

Tier B — timing clear; purchase-vs-delist split not measured

Interpretation: who manages the tree?

  • Brokers (κ ≈ 0): approximate the state-contingent policy — reposition within minutes.
  • Households (κ large): fixed policy between epochs — never reprice.
  • Strategic-looking aggregates without strategic sellers: structural work estimates 5–19% strategic buyers (Li, Granados & Netessine 2014); our aggregates look strategic and decompose into a 0.0% median + composition + a ≤20% minority.
The reverse error — assuming repricing where none exists — is what we measure. No prior paper has quantified it.

Why it matters: design, priced by our measurements

Measured factAgentInstrument
Households never repricePlatformsReprice-on-outcome tools
Demand strikes at p=1Organizer (FIFA)State-conditional tickets (prices the tree)
Fire sales 3–6h late, −28%Organizer / platformEpoch buyback windows
Exit wave timed to the minutePlatformResolution-synchronized release; trading halts

Playoff-conditional tickets exist in practice with zero formal analysis — the literature gap is confirmed.

Why it matters: consumer protection runs the wrong direction

United States (2025–26, live)

  • NY + NJ AGs: subpoenas to FIFA (May 2026) — seat misrepresentation, artificial scarcity; covers MetLife incl. the Final
  • German court injunction vs FIFA resale (Jul 2026); Texas AG vs StubHub
  • NY Algorithmic Pricing Disclosure Act (Nov 2025); FTC probe; RealPage settlement

China

  • "Sha shou" (big-data price discrimination): PIPL ban; SAMR+CAC rules (Jan 2026); Ctrip victory
  • Ticket crackdown: mandatory real-name ticketing; 85% public-sale rule
Our redirect: both frameworks target algorithmic pricing — platforms repricing too well. The harm we measure runs the opposite direction: households can't reprice at all, and speed beats price. No current complaint names this channel.

Limitations (stated plainly)

  • Certainty mechanism is a hypothesis until in-play odds are merged (Betfair planned).
  • Sale vs withdrawal: exit rate is whistle-timed; exit type matches ordinary days.
  • One event-correlated coverage collapse (post-England-SF); FIFA panel is a third-party aggregator with flicker.
  • Dose collinear with days-to-expiry; disclosed, not fully separable.
  • One tournament, one Final; asking prices, not transactions.

Conclusion

At every scheduled resolution in a complete knockout bracket, a deep consumer market absorbed the news through participation: the median seller never repriced (26/29 cells), quantities responded in proportion to the state at stake (R32 → SF dose gradient), and price indices moved only through composition or a repricing minority.
  • Revenue management prices time-perishable capacity. We measure information-perishable goods — and the canonical margin is missing.
  • Where sellers don't manage the state tree, the market does it for them — through who shows up.

Participation, not prices.

Key references

  • Dynamic pricing: Gallego & van Ryzin (1994) MS; Talluri & van Ryzin (2004); Su (2007) MS; Aviv & Pazgal (2008) MSOM; den Boer (2015); Feng & Xiao (2012) OR.
  • Empirical: Sweeting (2012) JPE; Li, Granados & Netessine (2014) MS; Hendel & Nevo (2006) Econometrica; Williams (2022) Econometrica.
  • Tickets/resale: Leslie & Sorensen (2014) ReStud; Courty (2003) JLE; Courty & Li (2000) REStud.
  • Indices/stickiness: Nakamura & Steinsson (2008, 2012); Bils & Klenow (2004); Cavallo (2018); Brogaard, Hendershott & Riordan (2019) JF.
  • Regulatory: NY/NJ AG FIFA investigation (May 2026); NY Algorithmic Pricing Disclosure Act (2025); RealPage DOJ (2025); PIPL (China 2021); SAMR+CAC (2026).

Draft v9 · claims tiered per CLAIMS_REGISTRY.md · artifacts in analysis/