Smets-Wouters (2003) Model
Recent developments in the construction, simulation and estimation of dynamic stochastic general
equilibrium (DSGE) models have made it possible to combine a rigorous microeconomic derivation of
the behavioural equations of macro models with an empirically plausible calibration or estimation
which fits the main features of the macroeconomic time series.
The main difference between empirical DSGE models and the more traditional macroeconometric models
(such as the AWM) is that both the parameters and the shocks to the structural equations are related
to deeper structural parameters describing household preferences and technological and institutional
constraints.
These micro foundations have three advantages:
- They provide a theoretical discipline on the structure of the model that is being
estimated, which may be particularly helpful in those cases where the data themselves are not
very informative, for example regarding the long-run behaviour of the economy or because there
has been a regime change.
- Being able to relate the reduced-form parameters to deeper structural parameters makes the
use of the model for policy analysis more appropriate, i.e. less subject to the Lucas critique,
as those structural parameters are less likely to change in response to changes in policy
regime.
- Micro-founded models may provide a more suitable framework for analysing the optimality of
various policy strategies as the utility of the agents in the economy can be taken as a measure
of welfare.
For these reasons, staff at the ECB and the Eurosystem have started to develop empirical DSGE models
for monetary policy analysis. The Smets-Wouters (2003) Model is an example of such a medium-sized
DSGE model, which has been estimated on the basis of quarterly euro area macro data. The model
features three types of economic agents: households, firms and the central bank. Households decide
how much to consume, how much to invest and how much to work and at what wage. Firms employ workers
and capital and decide how much to produce and at what price to sell their products.
In addition to a number of real frictions such as habit formation in consumption and adjustment costs
in investment, the model features nominal price and wage rigidities. The model is estimated using
seven euro area macroeconomic series (real GDP, consumption, investment, employment, real wages,
inflation and the nominal short-term interest rate). Using Bayesian estimation and validation
techniques, it is shown that the estimated model is able to compete with more standard, unrestricted
time series models, such as vector auto regressions (VARs), in out-of-sample forecasting.
back to top
