This chapter provides an overview of and user's guide to dynamic factor models (DFMs), their estimation, and their uses in empirical macroeconomics. It also surveys recent developments in methods for identifying and estimating SVARs, an area that has seen important developments over the past 15...

We show that when a model has more shocks than observed variables the estimated filtered and smoothed shocks will be correlated. This is despite no correlation being present in the data generating process. Additionally the estimated shock innovations may be autocorrelated. These correlations...

In conventional structural vector autoregressive (VAR) models it is assumed that there are at most as many structural shocks as there are variables in the model. It is pointed out that heteroskedasticity can be used to identify more shocks than variables. However, even if there is...

Structural vector autoregressive analysis aims to trace the contemporaneous linkages among (macroeconomic) variables back to underlying orthogonal structural shocks. In homoskedastic Gaussian models the identification of these linkages deserves external and typically notdata-based information....

Most macroeconomic models, both fully structural models as well as SVAR models, view economic outcomes as the product of a combination of endogenous and exogenous dynamic forces. In particular, the exogenous forces are generally modeled as a set of linearly independent dynamics processes. In...