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 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...

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...

In this paper it is argued that describing seasonal patterns as an evolving seasonals model in which the coefficients attached to seasonal trigonometric terms follow simple autoregressive processes can be very useful when one is faced with the task of extending well known results obtained for...

NOTE: This is a description of the paper and not the actual abstract. In this paper it is argued that describing seasonal patterns as an evolving seasonals model in which the coefficients attached to seasonal trigonometric terms follow simple autoregressive processes can be very useful when one...