The goal of incorporating, into a computable general equilibrium model, an econometric model of agricul tural production that maintains flexibility and global convexity for a large number of inputs and outputs leads to a computationally complex estimation prob lem. We have developed and implemented an iterative least squares procedure to estimate the parameters of this nonlinear production system subject to nonlinear constraints imposed by the underlying economic the ory. The large computer memory of the Cornell Na tional Supercomputer Facility allows the estimation of this large, globally convex, flexible agricultural produc tion system.
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