This chapter provides an overview of solution and estimation techniques for dynamic stochastic general equilibrium models. We cover the foundations of numerical approximation techniques as well as statistical inference and survey the latest developments in the field.

Macroeconomic researchers use a variety of estimators to parameterise their models empirically. One such is FIML; another is a form of indirect inference we term "informal" under which data features are "targeted" by the model -i.e. parameters are chosen so that model-simulated features...

We propose a new type of test. Its aim is to test subsets of the structural equations of a DSGE model. The test draws on the statistical inference for limited information models and the use of indirect inference to test DSGE models. Using Monte Carlo experiments on two subsets of equations of...

In this paper we analyze the small sample properties of full information and limited information estimators in a potentially misspecified DSGE model. Therefore, we conduct a simulation study based on a standard New Keynesian model including price and wage rigidities. We then study the effects of...

One of the leading methods of estimating the structural parameters of DSGE models is the VAR-based impulse response matching estimator. The existing asymptotic theory for this estimator does not cover situations in which the number of impulse response parameters exceeds the number of VAR model...