Stochastic Frontier Model and Factors Influencing Seed Cotton Production Cost

Author: Dr. Eddy Hope Kabasele Bambe   We estimated a model of stochastic cost frontier functions to better measure inefficiency. To ...

Author: Dr. Eddy Hope Kabasele Bambe

 We estimated a model of stochastic cost frontier functions to better measure inefficiency. To identify a more reliable estimation of empirical cost efficiencies, we elaborated a framework with a stochastic frontier trans-logarithmic cost function for cross-sectional data that captures the effects of exogeneity and endogeneity on both inefficiency estimation and the random noise term. The main contribution of this study is that we are the first to successfully apply a stochastic frontier cost function model to cross-sectional data in the agricultural sector while considering the effects of exogeneity and endogeneity. Previous studies, with the exception of Wang (2002), have ignored this aspect. Key to addressing this is recognizing the relevance of including in the main stochastic frontier model the exogenous variables in both components of the error term, i.e., inefficiency and noise representing the idiosyncratic error term. The analysis was illustrated using data on 1253 Chinese seed cotton producers in three main locations. The objective was to acquire a better understanding of both cost inefficiency and its determinants for Chinese seed cotton farms despite the serious issue of economic theory. Our results indicate that the assumption that cost minimization based on input prices orienting cost inefficiency may be inappropriate for the data considered in this study. We also obtained a nearly zero inefficiency score among our Chinese seed cotton producers. Surprisingly, we obtained homogenous cost inefficiency estimates in different locations, which indicates consistent integration of the cotton production sector in China. Our results, however, suggested significant differences in both input prices and other variables. Finally, the main result of this study was that having the proper climate conditions has a beneficial effect for producers. Thus, our main conclusion was to support of a policy of relocating cotton production to the appropriate areas.

Eddy Hope Kabasele Bambe is a Ph.D. researcher at the Institute of Agricultural Information at the Chinese Academy of Agricultural Sciences. His research interests are in the fields of agricultural information analysis, ranging from theory to model formulation, particularly time series, productivity, and efficiency measurement, and spatial econometrics. He also works on agricultural monitoring and early warning research.

He is currently working on a project focused on the assessment of the productivity and profitability of countries’ seed cotton production. 

 

Paper link: https://journalspress.com/LJRS_Volume19/628_Stochastic-Frontier-Model-and-Factors-Influencing-Seed-Cotton-Production-Cost.pdf