What kind of company bids on 97 government contracts and never wins a single one?
Not an unlucky one.
The World We're In
🏛
Governments buy stuff
📈
Firms compete
💰
Lowest bid wins
👍
Taxpayers save
Every year, governments spend trillions buying everything from pencils to highways. The system is elegant: companies compete, lowest price wins, taxpayers get a good deal. That's the theory.
The Crime Nobody Sees
🤝
Secret handshake
🔄
Take turns
💸
Inflate prices
🧾
Taxpayers bleed
Enter the cartel. Companies secretly agree who wins each contract. They rotate. They inflate. And the public — foots the bill without a clue. Half a century after Posner documented it, most cartels remain undetected.
The Frustrating Part
🚫
Scarce investigators
📊
Most tools need bid amounts
🌎
Most countries don't have them
The best detection tools — Imhof screens, variance tests, kurtosis — require granular bid amounts. But most procurement systems, especially in developing countries, only record who showed up and who won. That's it. Dead end? Not quite.
Something Weird in the Data
São Paulo, Brazil. 41,000 firms bid on government contracts between 2009 and 2019. Among them, 16,843 never won. Not once. And within those eternal losers, 2,735 bid with an intensity that defies economic rationality. One company entered 97 tenders over a decade. Won zero. Every bid costs money. Zero wins means negative expected profit. So why do they keep coming back?
Meet the Cover Bidders
★ Winner (cartel pick)
Genuine bidders
✗ Cover bidders (FL)
Brazilian law requires at least 3 bidders for sealed-bid contracts. Cartels need bodies to fill the room. Cover bidders show up, submit comically high bids, lose by design, and collect a side payment. They're not competitors. They're extras in a rigged play. And here's the key: they must participate. That footprint is all we need.
A Beautifully Simple Filter
👥 41,000 firms in BEC (2009–2019)
▼
❌ 16,843 never won a tender (always-losers)
▼
🚨 2,735 bid too often to be rational
Win rate = zero. Participation count above the IQR outlier threshold. That's it. Needs only who bid and who won. Any procurement agency can run it with a spreadsheet.
Follow the Money
baseline
Without FL
+3.6–7.7%
With FL
Same product. Same year. Same purchasing unit. When a frequent loser appears, prices run 3.6 to 7.7 percent higher. Cross-fit, OLS, matching, IV — four different estimation approaches, same story. That's not noise. That's a premium somebody is paying.
Tested Against Real Cartels
0.00
AUC Score
3.5×
Co-participation vs expected
3
Convicted firms are themselves FL
2.2×
Survives exact count matching
Brazil’s competition authority, CADE, has convicted 65 procurement cartels. Against that ground truth: AUC = 0.94 — though volume contributes substantially (within participation-count bands, AUC drops to 0.54). The screen’s detection power comes from identifying the high-participation tail of always-losers. A count-matched permutation test (2.2×) confirms the FL classification adds signal beyond volume alone.
The Dispersion Paradox
FL Bids
CV 0.57
Lower dispersion
vs
Non-FL Bids
CV 1.65
Higher dispersion
Here's the twist that makes the paper click. FL bids are less dispersed than genuine bids. They cluster tightly above the winner. This is coordinated cover bidding — and it means variance-based screens lose power exactly when coordination is strongest. A participation-based screen sidesteps this completely. It doesn't care how they bid. It cares that they showed up at all.
The Telltale Asymmetry
Convite (Sealed bid)
+3.8%
Law requires 3 bidders. Some FL presence is just compliance noise.
Pregão (E-auction)
+9.3%
No minimum-bidder rule. Every FL appearance is voluntary.
The premium is almost three times larger where cover bidding is purely strategic. When no law forces you to show up and you show up anyway — and lose, every time — that's not compliance. That's strategy. And when we interact FL with a constraint-binding indicator, the entire effect comes from voluntary participation: a 7.6% premium.
Five Clues, One Pattern
👥
No crowding out
+0.19 firms
🎯
Price anchoring
−4%
🔗
Dyadic links
4,696 pairs
📈
Lower exit
HR = 0.60
FL firms don’t displace genuine bidders — they add to participation. Winners bid closer to reference prices. FL–winner pairs recur far beyond chance. And firms in FL-exposed markets exit less, not more. Each fact alone has benign readings. Together? Hard to square with anything but coordinated cover bidding.
Two Lenses, One Problem
FL Screen
AUC 0.94
Participation only
(0.54 within bands)
correlation 0.06
Imhof Screen
AUC 0.90
Bid-level data
The FL screen and bid-level tools capture almost entirely different information. Correlation of just 0.06. In a horse-race regression, the FL coefficient actually rises when you add the Imhof flag. They're complementary. The paper proposes using them sequentially: FL first to triage, then bid-level forensics on the flagged subset.
Where It Bites Hardest
21.4%
Smallest PBUs (Q1)
9.8%
Q2
4.5%
Q3
1.7%
Largest PBUs (Q4)
A 12.5× gradient across purchasing-unit size. Where oversight is weakest, the screen signal is strongest. This matches the framework's prediction: cover bidding is most profitable where detection probability is lowest. The screen bites hardest where it's needed most.
The Three-Stage Pathway
1
Screen
Apply the FL filter to participation records. A SQL query. Minutes.
2
Triage
Prioritize by network metrics and oversight capacity. Focus on competitive markets.
3
Investigate
Deploy bid-level forensics only where the signal is strongest.
Not a conviction machine — a flashlight in a dark room. From 41,000 firms to 2,735 flags. From millions of tenders to the ones that matter. It tells investigators exactly where to start looking.
What We Don't Claim
✗ This is not causal identification. It's a conditional association.
✗ The screen flags environments, not guilty firms.
✗ Diagnostics are consistent with cover bidding but don't prove it.
✗ The staggered DiD yields a null result — insufficient power and pre-trends preclude causal interpretation.
✓ An omitted confounder would need to explain 17.5% of residual variation in both FL presence and prices to nullify the result.
The diagnostics don't prove the mechanism. They make the case for deploying the screen.
“Firms that lose too often may be losing on purpose. And this pattern — detectable with nothing more than participation records — reveals where cartels are most likely hiding.”
Genicolo-Martins & Furquim de Azevedo
INSPER • São Paulo, Brazil • 2026
Sometimes the best clue isn’t who wins. It’s who keeps losing.