In a number of time times models there are I(1) variables that appear in data sets in differenced from. This note shows that an emerging practice of assuming that observed data relates to model variables through the use of "measurement error shocks" when estimating these models can imply that...

The paper provides a short account of the major complete macroeconometric models that have been constructed in Australia. Initially these were by academics but later both the Treasury and Reserve Bank of Australia developed these for policy analysis and forecasting, so that the history focuses a...

Representative models of the macroeconomy (RMs), such as DSGE models, frequently contain unobserved variables. A finite-order VAR representation in the observed variables may not exist, and therefore the impulse responses of the RMs and SVAR models may differ. We demonstrate this divergence...

Pesaran and Smith (2011) concluded that DSGE models were sometimes a straitjacket which hampered the ability to match certain features of the data. In this paper we look at how one might assess the fit of these models using a variety of measures, rather than what seems to be an increasingly...

Standard solution methods for linearised models with rational expectations take the structural parameters to be constant. These solutions are fundamental for likelihood-based estimation of such models. Regime changes, such as those associated with either changed rules for economic policy,...

We describe methods for assessing estimated Dynamic Stochastic General Equilibrium (DSGE) models. One involves the computation of alternative impulse responses from models constrained to have an identical likelihood and the same contemporaneous signs as responses in the DSGE model. Others ask...

When sign restrictions are used in SVARs impulse responses are only set identified. If sign restrictions are just given for a single shock the shocks may not be separated, and so the resulting structural equations can be unacceptable. Thus, in a supply demand model, if only signs are given for...

The early history of cycles research involved locating turning points in the data. Later, the development of methods such as spectral analysis led to a focus on oscillations. A distinction between cycles and oscillations is needed - both imply turning points, but turning points do not...

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...