Public Policy in Private
Markets
Collusion
Announcements

HW:


HW 1, graded – can pick up at the end of class
HW 2, due 3/1; HW 3 due 3/6

3/6: first debate – group presenters: video
is due to me by 3/2 (this Friday)

3/8: midterm #1 (review sheet posted) –
material will be reviewed on 3/1
Collusive Restraints of Trade

Practices covered by Section 1:

Direct Agreements


To fix price
To Allocate markets



Geographically
By type of customer
Other Collusive restraints


Gray area (circumstantial evidence)
Conscious parallelism, trade associations,
non-profit organizations
Industrial Organization
Weak Case of Price Fixing: School
Milk
Ohio v. Trauth




Schools: Bid solicitation for annual
supply of milk (sealed bid auction)
> 600 school districts
Solicitation: menu of milk types,
sometimes with other requirements
such as napkins, coolers.
Local diaries supplied milk


Costs similar across diaries
Distance is the key factor
Market concentration
Ohio v. Trauth








Homogeneous product
Similar technology across processors
Costly transportation (competition is localized)
High barrier to entry (no one builds a plant solely
for selling milk to schools)
Inelastic demand
Infrequent demand
Information available (schools posted info)
Easy allocation of markets
Ohio v. Trauth


Methods involved bid rotation &
complementary bidding: artificially raised the
price for schools
Case where direct evidence was not enough:


Additional economic (statistical) evidence was
needed
Would a “control” group behave the way
defendants behaved?



Closeness should increase probability of submitting bid
Conditional on submitting a bid, bid level should
increase with distance
Are bids correlated? (complementary bidding)
Ohio v. Trauth
Control group behavior
Accused firms behavior
Ohio v. Trauth
Accused firms behavior
Ohio v. Trauth

Aftermath:




Settled out of court in 1996 (even though
statistical evidence was strong).
Problem: DOJ lost a federal case in 1995
(due to unreliable confessions)
Collusion is frequent in school milk
auctions
130+ criminal cases filed
Industrial Organization
Collusion and Non-Profits: MIT & Ivy
League schools case
MIT Financial Aid (DOJ, 1991)


MIT, Brown, Columbia, Princeton, U Penn, Yale,
Dartmouth, Cornell, Harvard
The controversial activity:





“Overlapping” student athletes (1950’s)
No aid beyond financial needs (agreement)
It then extends to non-athletes
Aid package + family contribution (fixed across schools)
Important elements in case:


Do antitrust laws apply to not-for-profit organizations? (what
do they maximize?)
Per se vs. rule of reason approach
MIT Financial Aid

Example: Family contribution = $10,000
across all schools
MIT Financial Aid

Government:

Tuition is commercial activity (section 1
applies)




Recall NCAA case re broadcasting of games
Practice aimed at increasing tuition and
revenue
Some consumers harmed: wealthy and
smart
Per se rule: no room for justifications
MIT Financial Aid

MIT:






No trade or commerce (outside of section
1)
Tuition < cost
Court did not have experience with not-forprofit organizations (hence rule of reason)
Not-for-profits maximize something else
Agreements helped the needy (in line with
government’s objectives)
No evidence of increased revenue
MIT Financial Aid

Statistical analysis



How does tuition in Ivy league schools
compare to similar schools?
Regress tuition/student on many variables,
including indicator of whether school is Ivy
league
Further studies:

Look at whether tuition increased after Overlap
group practices were eliminated
Merger Law
The Trial





8 Ivy League schools signed consent decrees
MIT refused and went to trial
Sept ‘92: MIT found guilty of violating Section
1 of Sherman Act (under rule of reason)
Court of Appeals upheld the District Court’s
ruling but disagreed on several points
Case ended in a Settlement in 1993: MIT
could participate in overlap practices, but only
in general, not on specific students
Statistical analyses in antitrust

Bottom line in statistical analyses is to
compare behavior of suspect firms:


With control group (Ohio, MIT)
During conspiracy v. outside conspiracy
(ADM, MIT)