Recently, interest in the methodology of constructing coincident economic indicators
has been revived by the work of Stock and Watson (1989b). They adopt the framework
of the state space form and Kalman filter in which to construct an optimal estimate
of an unobserved component. This is interpreted as corresponding to underlying economic
activity derived from a set of observed indicator variables. In this paper we apply
the Stock and Watson approach to the UK where the observed indicator variables are
those that make up the Central Statistical Office (CSO) coincident indicator. The
time series properties of the indicator variables are examined and three of the five
variables are first difference stationary and are cointegrated, the remaining two
are stationary in levels. We then construct two alternative measures of economic
activity, each of which deals with the different orders of stationarity of the variables.
The first uses the levels of the observed component variables that allows for the
cointegrating relationship. The second imposes stationarity on the I(1) variables
before the estimation by taking first differences. The levels index is viewed as
the preferred specification as it allows for the long-run relationships between the
variables and has a superior statistical fit.