Least squares estimation of joint production functions by the differential evolution method of global optimization

Most of the studies relating to estimation of joint production functions have noted two difficulties: first that allocation of inputs to different outputs is not known, and the second that a method of estimation cannot have more than one dependent variable, which necessitates construction of a composite output transformation function. This study has conducted some simulation experiments on joint estimation of the CES, the Transcendental and the Nerlove-Ringstad functions. Allocation parameters of inputs across the products have been introduced. Estimation has been done jointly, but without constructing a composite macro production function or an output transformation function. We use nonlinear least squares based on the Differential Evolution method of global optimization that permits fitting multiple production functions simultaneously.