Evaluation of Palm Groves Technical Efficiency Using Bootstrap Data Envelopment Analysis: A Case Study of Roodkhanehbar Area, Iran
الموضوعات :غلامرضا زمانیان 1 , مصطفی خواجه حسنی 2
1 - استادیار دانشکده مدیریت و اقتصاد دانشگاه سیستان و بلوچستان، زاهدان، ایران
2 - دانشجوی دکتری اقتصاد کشاورزی دانشگاه سیستان و بلوچستان، زاهدان، ایران
الکلمات المفتاحية: Data envelopment analysis, Technical efficiency, Hormozgan province, Bootstrap, Keriteh date, Roodkhanehbar,
ملخص المقالة :
Roodkhnehbar area, having approximately 111 thousands of Keriteh palm trees, is one of the most important areas of date production in the Rudan County[1]and the source of peoples’ income in this area, directly or indirectly. As a result, its production efficiency has a critical importance to the orchardists in this region. This study aims to evaluate technical efficiency of palm groves in this area using input-oriented bootstrap data envelopment analysis and sampling 50 palm groves of Keriteh date producers of Roodkhanehbar area in 2013. The results suggested that 64% of date producers operate with less than 50% efficiency and only 14% of them operate efficiently. The study, then, carries the implication that it is recommended to train the orchardists, providing a chance for successful orchardists to share their experiences with others in an attempt to optimize allocation of inputs. [1]Rudan County is a county in Hormozgan Province in Iran
Bahadori, Alireza, Hosseini Nahad, Saeed, & Habibinia, Ghasem. (2013). Use of Bootstrap simulation process for estimating non parametric efficient frontier “Investigating problems existing in the process provided in Saeed Ebadi’s paper. Research in Operation And Its Applications, 37(2), 113-135.
Balcombe, Kelvin, Fraser, Iain, Latruffe, Laure, Rahman, Mizanur, & Smith, Laurence. (2008). An application of the DEA double bootstrap to examine sources of efficiency in Bangladesh rice farming. Applied Economics, 40(15), 1919-1925.
Barlett, James E, Kotrlik, Joe W., & Higgins, Chadwick C. (2001). Organizational research: Determining appropriate sample size in survey research. Information Technology, Learning, and Performance Journal, 19(1), 43-50.
Brümmer, Bernhard. (2001). Estimating confidence intervals for technical efficiency: the case of private farms in Slovenia. European review of agricultural economics, 28(3), 285-306.
Cooper, William W, Seiford, Lawrence M, & Tone, Kaoru. (2006). Introduction to data envelopment analysis and its uses: with DEA-solver software and references: Springer Science & Business Media.
Dong, Fengxia, & Featherstone, Allen M. (2006). Technical and scale efficiencies for chinese rural credit cooperatives: a bootstrapping approach in data envelopment analysis. Journal of Chinese Economic and Business Studies, 4(1), 57-75.
Ebadi, Saeed. (2011). A method for ranking efficiency scores using Bootstrap. Research in operation and its applications, 29(2), 29-44.
Efron, Bradley, & Tibshirani, Robert J. (1993). An Introduction to the Bootstrap, Monographs on Statistics and Applied Probability, Vol. 57. New York and London: Chapman and Hall/CRC, 321-335.
FAO, STAT. (2012). FAOSTAT-Statistical Database, 2012.
Färe, Rolf, & Grosskopf, Shawna. (2006). New directions: efficiency and productivity (Vol. 3): Springer Science & Business Media.
Farrell, Michael James. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society. Series A (General), 120(3), 253-290.
Gocht, Alexander, & Balcombe, Kelvin. (2006). Ranking efficiency units in DEA using bootstrapping an applied analysis for Slovenian farm data. Agricultural Economics, 35(2), 223-229.
Lothgren, M. (1998). How to bootstrap DEA estimators: a Monte Carlo comparison. WP in Economics and Finance(223).
Lothgren, Mickael, & Tambour, Magnus. (1999). Testing scale efficiency in DEA models: a bootstrapping approach. Applied Economics, 31(10), 1231-1237.
Löthgren, Mickael, & Tambour, Magnus. (1996). Scale Efficiency and Scale Elasticity in DEA-models: A Bootstrapping Approach: Economic Research Inst.
Odeck, James. (2009). Statistical precision of DEA and Malmquist indices: a bootstrap application to Norwegian grain producers. Omega, 37(5), 1007-1017.
Schmidt, Shelton S. (2008). The measurement of productive efficiency and productivity growth:Oxford: Oxford University Press.
Shephard, RW. (1970). The theory of cost and production functions, Princeton. New Jersey: Princeton Univ. Press (1st edition, 1953).
Silverman, Bernard W. (1986). Density estimation for statistics and data analysis (Vol. 26): CRC press.
Simar, Leopold. (1996). Aspects of statistical analysis in DEA-type frontier models. Journal of Productivity Analysis, 7(2-3), 177-185.
Simar, Leopold, & Wilson, Paul W. (1998). Sensitivity analysis of efficiency scores: How to bootstrap in nonparametric frontier models. Management science, 44(1), 49-61.
Simar, Leopold, & Wilson, Paul W. (2000). A general methodology for bootstrapping in non-parametric frontier models. Journal of applied statistics, 27(6), 779-802.
