FORECASTING AND TESTING IN CO-INTEGRATED SYSTEMS

Article Abstract:

This paper examines the behavior of forecasts made from a co-integrated system as introduced by Granger (1981), and Weiss (1983) and Engle and Granger (1987). It is established that a multi-step forecast will satisfy the co-integrating relation exactly and that this particular linear combination of forecasts will have a finite limiting forecast error variance. A simulation study compares the multi-step forecast accuracy of unrestricted vector autoregression with the two-step estimation of the vector autoregression imposing the co-integration restriction. To test whether a system exhibits co-integration, the procedures introduced in Engle and Granger (1987) are extended to allow different sample sizes and numbers of variables.

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Bayesian econometrics and forecasting

Article Abstract:

Contemporary Bayesian forecasting methods draw on foundations in subjective probability and preferences laid down in the mid-twenties century, and utilize numerical methods developed since that time in their implementation. These methods unify the tasks of forecasting and model evaluation. They also provide tractable solutions for problems that prove difficult when approached using non-Bayesian methods. These advantages arise from the fact that the conditioning in Bayesian probability forecasting is the same as the conditioning in the underlying decision problems. [C] 2001 Elsevier Science S.A. All rights reserved.

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