Risk efficiency in data envelopment analysis and stochastic metafrontier
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Date
2014
Authors
Ferdushi, Kanis Fatama
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Abstract
Research on technical inefficiency of agricultural production in developing countries has extensively been done. It has contributed in identifying its cause and problems. However, only a few studies have attempted to search the reason of inefficiency of rice farms in Bangladesh. Therefore, this thesis does employ a cross-sectional Stochastic Frontier Analysis (SFA) on the rain-fed low land TRANSPLANTED AMAN (T. AMAN) rice farms data during the year 2011. The technical efficiency has been compared in view of small scale rice farms of different regions, taking into consideration the inefficiency effects model in SFA. The hypothesis of inefficiency effects empirically proved that inefficiency existed in the Dhaka (DHR), Chittagong (CHR), Rajshahi (RAJR), Khulna (KHR), Barisal (BAR), Sylhet (SYR) and Rangpur (RANGR) regional farms in Bangladesh. The inefficiency index ranges from 20% to 35% in seven different regions. Following the estimated results of efficiency, the hypothesis recommended to imply Metafrontier Production Function (MP) which accommodates differences in technology. The estimated MTRs indicate that the RAJR, BAR, and RANGR rice farms were close to the frontier. The problems of technical inefficiency have been significantly elaborated in studies of farms performance in risky production environments. The rain-fed low land T. AMAN farming systems are embodied along with such risky environments. Based on the findings, production risk was examined. The heterogeneity test results imply that farms in different regions were exposed to production risk. The partial derivative of the production risk function shows whether input variables are risk increasing or not. In Feasible Generalized Least Square method, output variance elasticities in DHR,
CHR, BAR, SYR, and RANGR imply that the variance function contributed to diminishing variability as the scale of the farm increases. It is of a great concern whether farm can minimize risk or not. The novelty of this study is to develop the Risk Efficiency model. The results show that KHR farms were stochastically dominating the others.