ABSTRACT
A standard assumption in spatial models such as (16.1)
and in time series models such as (16.2)
is that β and β are invariant over space and time, i.e. over i and t. This is a very restrictive assumption which may be quite unwarranted. There is now a great deal of evidence to show that the process (es) embodied in equations (16.1) and (16. 2) do indeed vary over space and time. A number of methods exist for discerning the presence of variable parameters and for building this fact into models such as those above. In this paper the method of cubic splines is proposed to generate models in which the parameters follow complex spatial or temporal paths. Details of the method are given in a later section. An illustration of the approach is provided using a time series model of regional unemployment.
