Abstract
Forecasting by implementation of a dynamic model is an important tool in econometric control-system design. Applications can address both planning and the utilization of resources. A recursive forecaster is developed based on the bootstrap Kalman filtering algorithm. The performance of the proposed algorithm is compared with that of the conventional method used for forecasting econometric models. A dynamic model of agricultural gross domestic product in Saudi Arabia is used to illustrate the procedure.