A Slack Based Enhanced DEA Model with Undesirable Outputs for Rice Growing Farmers Efficiency Measurement

Abstract

Agricultural production process typically produces two types of outputs which are economic desirable as well as environmentally undesirable outputs (such as greenhouse gas emission, nitrate leaching, effects to human and organisms and water pollution). In efficiency analysis, these undesirable outputs cannot be ignored and need to be included in order to obtain the actual estimation of firm’s efficiency. There are several approaches that has been proposed in DEA literature to account for undesirable outputs. Many researchers have pointed that directional distance function (DDF) approach is the best as it allows for simultaneous increase in desirable outputs and reduction of undesirable outputs. Additionally, slack based DEA approaches considers the output shortfalls and input excess in determining efficiency. The proposed model uses an enhanced DEA model which is based on DDF approach and incorporates slack based measure to determine efficiency in the presence of undesirable factors. Later the proposed increase in desirable outputs and reduction in undesirable outputs can be found for inefficient farmers. The developed model is used to determine rice farmers efficiency form Kepala Batas, Kedah. The study found 13 out of 30 farmers are CRS efficient and 17 out of 30 farmers are VRS efficient. From the basic DEA model, higher number of efficient farmers are identified due to the fact that the effect of undesirable outputs is not included in the model. Generally, DEA models which considers the effects of undesirable outputs produces more robust results.