For macroeconomists
Karl Whelan recently tweeted: “Read Cochrane and Woodford on
neo-Fisherism today. Cochrane - clear and thought provoking. Woodford
- unclear and rambling.” I agree about the clarity of John
Cochrane’s writing, both in absolute terms and relative to Michael
Woodford. But on this occasion I think Woodford has a more realistic
approach. So here is my attempt to explain the issue that both are
addressing, and Woodford’s version of learning. The two papers Karl
is referring to can be found here
and here.
The ‘problem’ that both address is that in the standard New
Keynesian model a fixed interest rate policy involves an infinite
number of rational expectations equilibrium paths. Another way of saying the
same thing is that the initial jump in prices is not tied down, but
if you choose to select a starting point the subsequent path would
preserve rational expectations. This multiple equilibrium result
typically means that macroeconomists would regard this monetary
policy regime as problematic, but Cochrane says that there is no
logical reason to reject these paths, and Woodford agrees. However
Woodford argues that this policy is problematic, because if you
choose some particular way of selecting a particular equilibrium (and
Cochrane does suggest one), it will not be learnable in the sense
Woodford describes. (The idea that indeterminate rational
expectations solutions are not learnable is not new, as I note
below.)
What is Woodford’s reflexive approach to learning? For me the most
intuitive way to describe it is that it is very similar to Fair and
Taylor’s method of finding the solution to a dynamic economic model
involving rational expectations, although it may be that this just
reflects my background. (Woodford’s discussion of how his idea
relates to the literature, which opens with this analogy, is very
readable and can be found in section 2.4.) The method starts by
assuming some arbitrary values for expectations variables in the
model, and solves it. This gives a solution to the model conditional
on those arbitrary expectations. Now take that solution, and
recompute using these solution values as expectations. Iterate until
the solution hardly changes, and take that solution as the rational
expectations equilibrium. The logic is that if some set of
expectations (almost) reproduce themselves in this way, they are
(almost) model consistent.
Woodford’s reflexive learning is very similar, although he would
impose some arbitrary, and small, cut off for the number of
iterations (=n). This has various interpretations, but the one I like
is that each period a proportion of the population fully recomputes
their expectations assuming rationality (or iterates a large number
of times), while others stick to their previous expectations. Another
interpretation (which could also have diversity) is to appeal to
‘level k thinking’, which has been observed in experiments. The
reflexive learning idea is based on work by Evans and Ramey, and is
closely related to the E-stability concept developed by Evans and
Honkapohja: Woodford explains why he prefers his approach. Evans and
Honkapohja have also applied their learning technique to this very
issue, with similar results: see George Evans here
for example.
Woodford shows, both analytically and with numerical examples, how
the reflexive equilibrium converges to the rational expectations
equilibrium as the number of iterations n increases if monetary
policy is described by a Taylor rule that obeys the Taylor principle,
but does not for a fixed nominal interest rate policy. To quote:
“It is true that under the assumption of a permanent interest-rate peg, the only forward-stable PFE are ones that converge asymptotically to an inflation rate determined by the Fisher equation and the interest-rate target (and thus, lower by one percentage point for every one percent reduction in the interest rate). But for most possible initial conjectures (as starting points for the process of belief revision proposed above), none of these perfect foresight equilibria correspond, even approximately, to reflective equilibria — even to reflective equilibria for some very high degree of reflection n.”
There is much more in the paper, but on the issue of reflective
equilibrium a natural conjecture (mine not Woodford) is whether all
indeterminate solution paths fail to be a reflexive equilibrium. In
other words is this a rationale for ignoring indeterminate solutions,
or perhaps more appropriately, designing policy to avoid them? Using
the analogy with the Fair-Taylor algorithm, it may depend on the
relationship between iterative stability and dynamic stability. When
there was much more use of iterative methods for model solution I
think there was a literature on this (and it may still be alive), and
I seem to remember both similarities but also differences, but beyond
that I have no idea.
I am not qualified
to address the extent to which Woodford’s idea of a reflexive
equilibrium adds to the learning literature, but it is now beginning
to look as if the result that a fixed interest rate policy is not
stable under learning is robust. As James Bullard says in a recent
presentation (HT ‘acorn’ in comments), this may be “a sort of
“victory” for the learning literature”.
Postscript (31/12) See this note from Evans and McGough (in a Mark Thoma post) which I think is consistent with what I say here.
Postscript (31/12) See this note from Evans and McGough (in a Mark Thoma post) which I think is consistent with what I say here.