This project brings the power of the vector processor (supercomputer) to bear on solving large models of the U.S. economy. The supercomputer is playing a more and more fundamental role in economic analysis. In the past, models which were built for analytical tractability often incorporated unrealistic behavioral assumptions. The supercomputer, due to its speed, has decreased the need for such a high degree of tractability and allowed for more realistic models. However, a cost is being paid by researchers trying to use the supercomputer. The programming code used to solve models on a standard mainframe is not readily transportable to the vector processor, and typically does not make full use of the computational speed. At present some economic analysts are doing pioneering work on developing algorithms and codes for the vector processor to solve economic problems. This project is part of that work. Technically, Professor Ando compares the computational power of the CYBOR 205 and the IBM 3090 supercomputers for solving large macroeconomic models. He has shown in past work that the CYBOR 205 is disappointingly slow in carrying out the necessary computations. There is evidence that the IBM 3090 is much faster and requires less modification of code to carry out the same computations. This project compares the speed and analytical accuracy of the two machines by estimating stochastic nonlinear equations of a very large model of the U. S. economy. If such differences in computational speed, set up costs, and coding transportability are inherent in the machines themselves, this work will provide very useful information to other researchers doing economic analysis.
