Spring 2024 Alumni Newsletter

Your coauthor In-Koo Cho
DA:
visited our department and
recently
a paper the two of you
presented
apparently been working on for
have
The title of the paper was
years.
Outcomes Without
"Collusive
Algorithmic Pricing in a
Collusion:
Model." I recall feeling
Duopoly
and perhaps even a little
surprised
by the results he
astonished
I thought it'd be interesting
reported.
follow up on In-Koo's presentation
to
ask you to provide your take on
and
paper. Let me begin by asking
the
Thanks for the question. First,
NW:
bit of context. There is a long
a
in economics looking the
literature
of collusion be firms in
possibility
where they have some
markets
power. Most obvious, and
pricing
illegal, is for firms to enter
clearly
an agreement to set prices
into
than they would in a
higher
setting.
competitive
driving up prices, firms can earn
By
profits. But there is an incentive
more
any one firm to undercut its
for
– cut prices just a bit,
competitors
earn profits on each item sold,
still
capture more of the market and
but
increase total profits. So any
so
agreement must have a
collusive
of punishment to prevent a firm
form
defecting on this collusion.
from
I mentioned that explicit
Now,
agreements are illegal, but
collusive
are myriad ways that firms
there
potentially collude implicitly.
could
example, suppose you and you
For
I are the only suppliers in a
and
and we’ll both be around for
market,
long time as the only suppliers.
a
you move first and set your
Suppose
at a high level. Then while I
price
be tempted to undercut you, I
would
know that in response you’ll
may
me by dropping your price
undercut
below what I set. My
substantially
gain is offset by future
short-term
and so I may rather decide to
losses,
your high price. Even though
match
have not explicitly agreed to
we
the threat of punishment
anything,
mean that collusion can arise as
may
these basic issues have been
While
for a long time, they’ve gained
around
prominence in modern, datarich
new
markets, where an increasing
of firms have turned to
number
pricing algorithms. These
automated
observe market conditions
algorithms
can quite rapidly adjust prices in
and
to the outcomes that they
response
An important question
observe.
both economists, regulators,
facing
policymakers is whether these
and
can learn to collude, and if
algorithms
what should be done about it.
so,
particular background which
The
our paper – although as you
sparked
we’d been working on
mentioned,
ideas for a long time – was a
related
of papers finding that collusive
series
of higher prices could
outcomes
from the interaction of
emerge
algorithms. This work, which
pricing
based on simulations, provided
was
intuitive explanation suggesting
some
the algorithms had ``learned to
that
In-Koo and I wanted to
collude.’’
this in more detail, to
explore
the forces at play in the
understand
of pricing algorithms, and
interaction
characterize precisely and
to
what we could expect in
theoretically
settings.
such
Alright then. Well, it seems to
DA:
that, in the environment you
me
That was our intention. In
NW:
to study the possibility of the
order
of collusive outcomes,
emergence
studied an extreme
we
Dr. Noah Williams on the
Collusion Illusion
Interviewed by David Andolfatto
what this paper is about.
an outcome.
it should be close to
study,
for collusion or collusive-
impossible
like behavior to emerge, no?
where we intentionally
environment
down all of the known
shut
that would facilitate
avenues
collusion.