824 The Econometrics of Monetary Policy
as a consequence of developments in macroeconomic theory and empirical mod-
eling. On the theory side, the realization of the importance of price stickiness and
of slow adjustment to the forward-looking rational expectations equilibria led to
the “renaissance” of the role of monetary policy in understanding macroeconomic
fluctuations. At the same time a new role was attributed to empirical analysis of
providing evidence on the stylized facts to include in the theoretical model adopted
for policy analysis and deciding between competing general equilibrium monetary
models. This new role emerged with the realization that the solution of a dynamic
stochastic general equilibrium (DSGE) model can be well approximated by a vec-
tor autoregressive (VAR) model, and VARs have become the natural tool for model
evaluation.
The use of VARs led to the establishment of a number of facts and features to be
included in models for monetary policy evaluation, well described by Christiano,
Eichenbaum and Evans (2005) and Sims (2007).
- Since VAR models are not estimated to yield advice on the best policy but rather
to provide empirical evidence on the response of macroeconomic variables to
policy impulses in order to discriminate between alternative theoretical models
of the economy, it then becomes crucial to identify policy actions using restric-
tions independent from the theoretical models of the transmission mechanism
under empirical investigation, taking into account the potential endogeneity of
policy instruments. - Most of the monetary actions are systematic responses to the state of the econ-
omy, so there is very little in the way of random fluctuations in policy to produce
business cycles. - Money supply is close to a random walk and monetary aggregate shocks do
not look like monetary policy shocks in their effect. The foundation of the way
people think about monetary policy is based on interest rate adjustments.
The main results of the VAR-based evaluation model is that, in order to match
fluctuations in the data, any model must feature some attrition that causes tem-
porary but rather persistent deviations from the long-run equilibrium defined by
a frictionless neoclassical economy.
Adding frictions implies increasing the number of parameters, especially along
the dimension of parameters little related to theory. As a consequence, calibration
became impractical for attributing numerical values to the DSGE parameters and
estimation came back into fashion. However, estimating DSGE models by clas-
sical maximum likelihood methods proved to be very hard, as the convergence
of the estimates to values that ensure a unique stable solution turned out to be
practically impossible to achieve when implementing unconstrained maximum
likelihood estimation. Note that three types of solution are possible for a DSGE
model, depending on its parameterization: no stable rational expectations solu-
tion exists, the stable solution is unique (determinacy), or there are multiple stable
solutions (indeterminacy). Determinacy is a prerequisite in order to use a model to
simulate the effects of economic policy.^2