Environmental Efficiency Analysis with one Detrimental Input Variable through A Stochastic Frontier Analysis Approach (A Case Study of Shallot Farming System)
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Date
2016-12-26
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Sekretariat Badan Penelitian dan Pengembangan Pertanian
Abstract
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Sustainable agriculture having high complexity, especially related to the choice of using inputs that could potentially harm the environment or often called a detrimental input. In order to realize sustainable agriculture, the level of efficiency of the use of these inputs must be able to measure, especially from the aspect of environmental efficiency. The objective of this research in to analyze the environmental efficiency (EEnv) with a detrimental input variable namely the Nitrogen surplus in shallot farming through approach Stochastic Frontier Analysis (SFA). At the initial stage has been built translog stochastic frontier regression model consisting of the response variable namely the production of onion, five independent variables, namely land, seed, Phospor fertilizer, Kalium fertilizer, labor and pesticides, as well as one independent variable is a surplus of nitrogen as a detrimental input. Stochastic frontier translog regression models were built to explain some of the interactions between several independent variables affect the production of shallot. Some interactions are significant, namely seeds and pesticides, fertilizer P with a surplus of nitrogen, and the interaction between K fertilizer with nitrogen surplus. From the regression model can also be calculated value of elasticity, where the elasticity of independent variables namely seed is the highest, equal to 0.1687. Furthermore stochastic frontier translog model can be calculated value EEnv, the results show the value of EEnv still low at only at 0.2765. This may imply inefficient shallot farmers from the aspects of the environment, especially if associated with the use of nitrogen fertilizer. Although technically shallot farmers have achieved a level of technical efficiency (ET), which is indicated on the ET value of 0.9475.