Estimating input allocation for farm supply models

When building an economic model for supply analysis the aim is to model a decision makingprocess of one or more agents which fits the observed practice as good as possible. Hereby themodeller is often confronted with incomplete information about the production process; particularcrop specific input data are rarely available. The problem of defining activity related technologyinputs coefficients is not new. A good deal of literature comes from the mathematicalprogramming perspective, where input coefficients were estimated using a standard linear regressionfunction to fully represent the mathematical program. However this approach is a puretechnical device and may result in an inconsistent model.The author of the paper wants to investigate whether it is possible, employing proper estimationtechniques, to simultaneously estimate all unknown coefficients of a mathematical farm supplymodel. This includes the estimation of parameters of the non linear cost function, used to calibrateand catch the simulation behaviour and the crop specific input coefficients. It is shownthat a simultaneous estimation of all parameters improves the goodness of fit of the estimatedparameters and that such an approach is technically feasible.