Abstract
Cointegration in multivariate time series'. The aim of this paper is to establish a forecast equation with three non-stationary time series variables. An attempt will be made to show the effect of the size of a community and the level of atmospheric pollution on the number of admissions with chest illnesses to the emergency department of a hospital. Various regression systems are put to the test: regression with variables without transformation, with differentiated variables and through a Box-Jenkins transfer function, all of which show problem in fitting the data. It is found that the three variables are cointegrated and that a regression equation with an error correction mechanism which correctly adjusts the variables actually exists. The advantages of the cointegration and the error correction mechanism over other regression systems are shown.
