Stochastic Frontier Approach of Measuring Agricultural Productivity and

It has been recognized that modeling agricultural productivity growth and inefficiency is a challenging task since there exists many methodologies and each one has its own merits and drawbacks. The main purpose and motivation of this paper is to offer some new modeling approaches to overcome the heterogeneity problem in measuring productivity and efficiency using stochastic frontier modeling. As an extension, the paper also shows how to incorporate endogeneity of the input in the production process by mean of auxiliary information. Regarding the estimation, the paper proposed various procedures that are fairly easy to implement, given the current existing computing power and readily automated software packages. Finally, the paper suggests a way to decompose the TFP growth and efficiency measurements for policy formulation purposes