This presentation by Robert Porter (Professor of Economics, Northwestern University, US) was made during a workshop on “Cartel screening in the digital era” held by the OECD in Paris on 30 January 2018. More papers and presentations on the topic can be found out at oe.cd/wcsde.

1. Detection of Collusion
Robert Porter
Northwestern University
OECD
Workshop on Cartel Screens
Paris
30 January 2018

2. 2
Introduction
Pro-active cartel detection methods can complement reactive
amnesty or leniency programs.
The two approaches are not necessarily substitutes.
Screens identify markets in which industry structure is conducive to
collusion, behavior is suspicious, or where the complaints of
customers or rivals warrant closer scrutiny.
Screens can provide evidence to justify an investigation.
In a procurement setting, the appropriate remedies may include re-
design of the procurement process, as opposed to antitrust
enforcement alone.

3. 3
Introduction
My purpose today is to:
• Review the factors that facilitate cartel formation.
• Provide an overview of the cartel screening approaches.
Structural vs. behavioral screens
• Discuss some of the challenges in screen design and
implementation.
• Describe some recent developments in screening techniques.
• Discuss how the wealth of data now available offers the prospect
of more extensive investigations, but how it can also facilitate
collusive practices.

4. 4
Cartel Formation and Governance Issues
A collusive scheme must:
1. Enlist conspirators
- problematic if potential participants are asymmetric
2. Come to an agreement
- prices
- market shares or market division
- product features
3. Enforce agreement
- detection and deterrence of cheating
4. Protect gains from entry or expansion by non-participants
5. Avoid detection
6. Respond to new circumstances

5. 5
Structural Screens
A typical approach considers a set of industries or markets.
Regress a measure of cartel incidence or of the degree of collusion
on various industry characteristics that may facilitate collusion:
– Number or concentration of sellers
– Degree of product differentiation
– Excess capacity
– Entry barriers
– Demand stability
– Pricing transparency
Caution: The extent to which these factors facilitate collusion
depend on individual industry circumstances.
Also, 3 or 4 digit SIC codes may be too aggregate.

6. 6
Structural Screens
Dependent variable:
1. Measure of profits
Problems of interpretation (Schmalensee, HIO 1987)
E.g., Demsetz critique – under competition, high market
shares and profits accrue to firms with better products or
lower costs
2. Indicator of cartel existence, or number of discovered cartels
Does not account for undetected cartels, absent strong
assumptions about rates of cartel formation and dissolution
(e.g., Hyytinen, Steen & Toivanen 2017 study of legal
cartels in Finland)
Results help to indicate of markets of potential concern, but offer a
crude measure.

7. 7
Behavioral Screens
Many collusive agreements encounter operational problems,
associated with formation and governance issues.
The manner in which a conspiracy deals with these problems can
facilitate detection.
However, there is no general detective prescription. Individual
circumstances suggest the line of inquiry. Case studies are
inevitable.
Behavioral screens determine whether suspicious behavior is
consistent with competition or collusion.
In some cases, collusive behavior would be difficult to achieve
without communication.

8. 8
Behavioral Screens
It isn’t possible to study all markets of potential concern.
Instead, behavioral screens are more likely to be useful when
investigating a complaint by customers or rival firms, or arising
from studies of individual markets (e.g., Nasdaq).
If behavior is deemed suspicious by the screen, then a more detailed
investigation may be warranted.
Firms could be asked to rationalize the suspicious behavior, and
offered leniency should they confess to collusion.
In this sense, using screens can complement leniency programs.

9. 9
Behavioral Screens - Implementation
I’ll describe a number of potential screens.
They are designed to detect anomalous behavior and test whether it
is consistent with competition.
They are tailored to the circumstances of the individual market.
I’ll also describe some potential challenges of implementation and
interpretation.

10. 10
Structural Breaks: Price Patterns
Many agreements are short lived.
Price changes at time of cartel formation and demise can be useful
markers.
Formation: Often witness gradual increase, not associated with cost
increases, as cartel experiments with the price that the market
can bear.
Demise: The ends of cartel agreements are rarely managed,
resulting in sudden price collapses.
Vitamin C: Bernheim 2002, 2008, Igami & Sugaya 2017
Variance screen: When a cartel is active, prices can be less
responsive to costs, and less variable more generally.
Frozen perch: Abrantes-Metz, Froeb, Geweke & Taylor 2006

11. 11
Structural Breaks: Price Patterns
If firms interact repeatedly, can sustain agreement by threatening
defections with future punishment.
Requires rapid, sure and severe responses to suspected cheating.
May nevertheless witness, or suspect, deviations.
Punishment?
Legal cartels can use fines.
Corn syrup: compensate rivals for foregone market share at
agreed-upon cartel price.
If no recourse to fines, a ring can punish non-compliance by
singling out the deviator from the ring, or by dissolving the ring.
LA trash haulers used local price wars to target punishment.
Temporary price wars may also be employed.
Joint Executive Committee railway cartel (Porter 1983, Ellison
1994): price wars triggered by departures from allotted market
shares

12. 12
Pricing to Avoid Detection
A procurement auction bidding ring may submit phony, or
complementary, bids, that by design are higher than the serious
bid submitted by the ring, to create the appearance of
competition.
Example: Long Island highway contracts (Porter & Zona 1993)
Ring met prior to the auction to assign low bid privileges.
Other conspirators often submitted complementary bids.
How does this behavior manifest itself?
Exploit non-inclusiveness of cartel, plus presence of phony bids.
Split data along two dimensions:
(1) Cartel vs. non-cartel (those not present at meetings).
(2) Low bid within group vs. higher bids.

13. 13
Pricing to Avoid Detection
Test whether the low bidder for a given group is determined by the
same process as the ranking of higher bids.
Accept for non-cartel firms, do not accept for cartel.
The order of the bids submitted by non-conspirators is related to cost
measures (capacity, utilization rate).
The low or serious conspirator bid likely to be submitted by the firm
with the lowest cost.
The ranking of higher cartel bids is unrelated to the cost measures.
Bajari & Yi 2003 adapt method to identify cartel participants.
Caution: A sophisticated cartel could pass this test, by inflating all
bids (serious and phony) by the same amount, preserving the
ranking of bids based on costs.
Then have to compare cartel and non-cartel bid levels.

14. 14
Pricing to Avoid Detection
Example: Japanese construction project auctions (Kawai &
Nakabayashi 2015)
Suspicious patterns of bids across re-auctioned projects; focus on
rank reversals.
Sealed bid auction where low bid wins, but only if it is below the
secret reserve price (maximum bid).
If not, re-auction item shortly thereafter.
Examine auctions which went to a second round, where the
difference between the lowest and second lowest bids is less
than 1% of the reserve price.
The low bidder in the first round is almost always the low bidder in
the second round.
Not true of the second and third bidders, when their bids are close.

15. 15
Pricing to Avoid Detection
Figures plot the percentage difference between the second round
bids of the lowest and second lowest bidders in the first round,
Δ12, and the analogous difference for the second and third
lowest bidders, Δ23.
Patterns indicative of a ring designating one serious bidder.

16. 16
Partial Agreements
If a cartel is not all inclusive, then the behavior of outsiders can serve
as a standard of comparison.
Example: Ohio school milk auctions (Porter & Zona 1999)
Plant locations matter, as processed milk is costly to ship.
The three Cincinnati dairies bid both near their plants and well
beyond their local territories.
Their more distant bids tended to be lower.
Other dairies’ bids increase with distance from their closest plant to a
given school district.
The Cincinnati dairies’ bidding is consistent with territorial allocation
of nearby school districts, where they were the lowest cost
potential competitors, and more competitive bidding in distant
districts.
An “inverted price umbrella,” consistent with a local monopoly
constrained only by distant rivals.

17. 17
Anomalous Price Patterns
Other price patterns are also inconsistent with competition.
Example: Japanese paving auctions (Ortner & Chassang 2017)
Cities announce reserve price, maximum bid based on engineer’s
estimate of upper bound on costs (not binding).
Some also have adopted minimum bids, so as not to compromise
quality; relatively low.
Find that in some cities, winning bids are lower after a minimum bid
is adopted, in comparison with control cities.
Consistent with collusion, if a minimum bid limits the punishments
associated with a price war following suspected cheating.

18. 18
Excess Entry in Average Bid Auctions
Average bid auctions are frequently used to award procurement
contracts.
Low and high bids are discarded according to a pre-specified rule,
and the winner’s bid is the closest to the average of the
remaining bids.
Incentive for a ring to submit many bids, to manipulate the average
bid, and to increase the chance of being the winner.
Example: Italian roadworks (Decarolis & Conley 2016)
Many more bids submitted than in comparable first price auctions
(50 vs. 7 on average).
Devise test for presence and membership of ring, validated on
sample where collusion was uncovered.
Apply to sample where collusion suspected.

19. 19
Market Allocation
Many cartels have internal political problems, arising from
differences in costs, capital, customer bases, discount rates, etc.
Examples: OPEC, US agricultural marketing agreements.
Cartel problem is to allocate shares and divide the spoils.
An imperfect solution is a territorial assignment:
- by region,
- by point in time (GE/Westinghouse electrical conspiracy in the
1950s used phases of the moon),
- by incumbency (NY trash hauling),
- by pure randomization (e.g., identical bids).
Caution: geographic specialization, bid rotation, and low client
turnover are not inconsistent with competition.
But lack of competition can be symptomatic of collusion.
Example: Offshore oil lease bidding (Aradillas-Lopez, Haile,
Hendricks & Porter 2017)

20. 20
Market Share Patterns
Another imperfect solution is to act to keep market shares stable.
Market shares are unpredictable, and may need to compensate for
excess shares after the fact.
Quebec gas: staggered price changes to meet market share targets
(Clark & Houde 2013, 2014).
School milk auctions: strong vs. weak cartels (Pesendorfer 2000)
Strong cartel distinguished by ability to make side payments.
Allegations of side payments in Florida ring, not Texas.
Market shares will be more stable in a weak cartel, to maintain
internal discipline.
Assign low bidding privileges based on relative market share.
Market shares were more volatile in Florida (especially revenue
shares).
Akin to a variance screen test for market shares.

21. 21
Increasing Data Availability
The wealth of data now available offers the prospect of more
extensive investigations, but it can also facilitate collusion.
In particular, more readily available pricing data speeds the detection
of deviations from agreed upon prices, dampening the incentives
to cheat, especially if rivals respond more quickly than
customers to price cuts.
Example: Price transparency rules
Danish concrete: “Government Assisted Oligopoly
Coordination,” Albaek, Mollgaard & Overgaard 1997
Example: Airline Tariff Publishing Company case (Borenstein 2004)
Airlines could communicate with advance price announcements,
without having to sell tickets at those prices.

22. 22
Price Comparison Websites
It was thought that the internet would lower the costs of consumer
search, spurring price and quality competition.
Firms can dampen these effects by shrouding attributes of their
products (Ellison & Ellison 2009, 2017).
But there is evidence that, even absent shrouding, price comparison
sites can lead to higher prices.
Luco 2017 studies a Chilean program that mandated that gas
stations post their prices on a government website.
After the program began, prices increased 10 percent, and more in
poor neighborhoods. In high income neighborhoods, where
people were more likely to visit the website, prices increased
less, or fell.

23. 23
Corruption of Bidding Processes
In some auctions, corruption of the process is a concern.
E.g., in a sealed bid procurement auction, a bidder could bribe the
buyer’s agent to learn their rivals’ bids, to maximize their payment
when they win.
Andreyanov, Davidson & Korovkin 2017 study 4.3 million Russian
procurement auctions.
Their test uses the time when sealed bids are submitted.
Preferred bidders wait until the end of the auction to decide whether to
submit, and if so bids just enough to win.
Their tests suggest that more than 10 percent of winning bids were in
auctions with “bid leakage” (e.g., winning bid more likely to be late).
Contract prices are higher than under an equal playing field:
- direct effect: higher bid by preferred bidders
- indirect effect: others bid more aggressively, but less likely to bid

24. 24
Corruption of Bidding Processes
Auctions where bids have multiple dimensions (multiple items, or price
and quality) are especially vulnerable (Burguet & Che 2004).
If the auctioneer has discretion in choosing the winner, for example by
favoring some bidders on the basis of perceived quality, then the
process can also be corrupted.
The auctioneer can inflate the quality of the preferred bidders, or give
more weight to dimensions in which they are stronger.
Bidders with insider status need not bid as aggressively on price to win
the contract.
There is a role for rules that limit the selling agent’s discretion, or
otherwise create an open process.
Lewis-Faupel, Neggers, Olken & Pande 2016: adoption of e-
procurement in India and Indonesia resulted in entry of non-local
bidders and quality improvement (e.g., contract more likely to
completed on schedule), but not lower prices.

25. 25
Corruption of Bidding Processes
If there are contract renegotiation possibilities, then a competitive
bidding process may be compromised by corruption of the
renegotiation process.
E.g., bidders who have a relationship with the auctioneer (or the person
responsible for renegotiation) may bid aggressively to win the
contract, knowing that profits will be more than recouped in the
renegotiation process.
Also concern about corruption of contract implementation.
Example: Land auctions in China (Cai, Henderson & Zhang 2013).
Properties were sold with zoning restrictions on development.
Two stage process: indicative bidding, followed by bid adjustments.
Preferred bidders signaled presence by submitting indicative bids
immediately after first round bidding opened.
Others stayed out, knowing that only insiders would obtain relaxed
zoning restrictions (e.g., permitted building height).

26. Summary: Potential Screens for Collusion
1. Structural breaks in prices
- Level changes associated with birth or death
- Variance screens
Caution: ensure not associated with cost or demand changes
2. Suspicious losing bids (indicative of complementary bidding)
3. Indications of punishment of defections
- Permanent or temporary collapse of agreement
- Targeted punishment
4. Comparisons with firms outside the ring
5. Comparisons across markets
Associated with differences in:
- the extent of competition from outside the cartel
- the strength or cohesiveness of the cartel
26

27. Summary: Potential Screens for Collusion
6. Market share patterns inconsistent with competition
- Geographic specialization
- Bid rotation
- Low client turnover
- Too stable
Caution: not necessarily indicative of collusion
7. Suspicious bid timing
- Low pre-emptive bids
- Late winning sealed bids
8. Suspicious patterns in contract renegotiations
27