LONG-RUN FORECASTING IN MULTI- AND POLYNOMIALLY COINTEGRATED SYSTEMS

Boriss SILIVERSTOVS (German Institute for Economic Research)

In this paper long-run forecasting in multi- and polynomially cointegrated models is investigated. It is shown that the result of Christoffersen and Diebold (1998) derived for I( 1) cointegrated models generalizes to multi- and polynomially cointegrated systems. That is, in terms of the trace mean squared forecast error criterion, imposing the multi- and polynomially cointegrating restrictions does not lead to improved long-run horizon forecast accuracy when compared to forecasts generated from the univariate representations of the system variables. However, when one employs a loss function derived from the triangular representations of the (polynomially-) cointegrating systems, gains in forecastability are achieved for system forecasts as opposed to the univariate forecasts. The paper highlights the importance of carefully selecting loss functions in forecast evaluation of cointegrated systems.