On Bayesian and non-Bayesian estimation of a two-level CES production function for the Dutch manufacturing sector

Abstract

In this paper maximum-likelihood estimates of the parameters of the two-level CES function, obtained by direct estimation of this function, are given. In addition the authors propose to show how a Bayesian analysis may help to find a solution to the difficulties related with, but not specific to, this particular estimation problem. It is shown that numerical integration of the posterior distribution may give an indication as to which parameter has to be pinpointed and at which value when multi-collinearity precludes unconditional maximization of the likelihood. It is suspected that this approach has a wider field of application.