Regional Simulation of Bootstrap Efficiency of Broiler Production in Peninsular Malaysia

Authors
Institute of Agricultural and Food Policy Studies, University of Putra, Malaysia.
Abstract
Bootstrapping the DEA is one of the current methods of measuring robust efficiency by constructing a confidence interval and measuring the noise (bias) in production. In this study, two estimators: the conventional Data Envelopment Analysis (DEA) and bootstrap simulation with 2,000 bootstrap iterations were applied on a cross sectional data of 296 broiler farms in Peninsular Malaysia. The objective of the study was to measure the robust technical efficiency, production bias and factors motivating technical efficiency in the Northern, Southern, and East-central regions of Peninsular Malaysia. As a regional approach, the study found the existence of both inefficiency and noise in broiler farms across regions of Peninsular Malaysia. Findings show disease infestation and unfavorable temperature as components of noise or exogenous factors or factors beyond farmers’ control in broiler production. The study identified age (+), education (+), experience (+), production system (-), number of poultry farms owned (-), business status (+) and land tenure status (-) as statistically significant in ameliorating efficiency in broiler production. Result also show that strong statistically significant differences exist in the magnitude of technical efficiency scores between the two estimators across the regions. The study advocate for increase in scale of production as majority of the farmers produce at increasing returns to scale.

Keywords


1. Akhter, S. and Rashid, M. H. A. 2008. Comparative Efficiency Analysis of Broiler Farming under AFTAB Bahumukhi Farm Limited Supervision and Farmers’ Own Management. Progress Agric., 19(2): 195-204.
2. Alabi, R. A. and Aruna, M. B. 2005. Technical Efficiency of Family Poultry Production in Niger-Delta. J. Central Eur. Agric., 6(4): 531-538.
3. Ali, S., Ali, S. and Riaz, B. 2014. Estimation of Technical Efficiency of Open Shed Broiler Farmers in Punjab, Pakistan: A Stochastic Frontier Analysis. J. Econ. Sust. Dev., 5(7): 79-88.
4. Alrwis, K. N. and Francis, E. 2013. Technical Efficiency of Broiler Farms in the Central Regions of Saudi Arabia: Stochastic Frontier Approach. Agric. Res. Cent., 116(1): 5-34.
5. Ariffin, A. S., Mohtar, S. and Baluch, N. 2014. Broiler Industry with Emphasis on Short Supply Chain in Malaysia. Proceeding of International Conference on Technology and Operations Management, 34-46.
6. Banker, R. D., Charnes, A. and Cooper, W. W. 1984. Some Models for Estimating Technical and Scale Efficiencies in Data Envelopment Analysis. Manag. Sci., 30(9): 1078-1092.
7. Begum, I. A. Buysse, J., Alam, M. J. and Van Huylenbroeck, G. 2010. Technical, Allocative and Economic Efficiency of Commercial Poultry Farms in Bangladesh. World Poult. Sci. J., 66(1): 465-476.
8. Chang, H. S. 2007. Overview of the World Broiler Industry: Implications for the Philippines. Asian J. Agric. Dev., 4(2): 67-82.
9. Charnes, A., Cooper, W. W. and Rhodes, E. 1978. Measuring the Efficiency of Decision Making Units. Eur. J. Oper. Res., 2(6): 429-444.
10. Charnes, A., Cooper, W. W. and Rhodes, E. 1979. Short Communication: Measuring the Efficiency of Decision Making Units. Eur. J. Oper. Res., 3(4): 339-352.
11. Corzo, A. C., Fritts, A., Kidd, M. T. and Kerr, B. J. 2005. Response of Broiler Chicks to Essential and Non-essential Amino Acid Supplementation of Low Crude Protein Diets. Anim. Feed. Sci. Tech., 118: 319-327.
12. Darsi, E., Shivazad, M., Zaghari, M., Namroud, N. F. and Mohammadi, R. 2012. Effects of Reduced Dietary Crude Protein Levels on Growth Performance, Plasma Uric Acid and Electrolyte Concentration of Male Broiler Chicks. J. Agri. Sci. Tech.,14: 789-797.
13. DVS. 2012. Department of Veterinary Services Malaysia: Statistics. http://www.dvs.gov.my/ststistik.
14. DVS. 2013. Department of Veterinary Services Malaysia: End of Year Statistics and Report. Kuala Lumpur, Malaysia, http://www.dvs.gov.my/ststistik.
15. Gocht, A. and Balcombe, K. 2006. Ranking Efficiency Units in DEA Using Bootstrapping: An Applied Analysis for Slovenian Farm Data. J. Agric. Econ., 35(2): 223-229.
16. Heidari, M. D., Omid, M. and Akram, A. 2011. Using Non-parametric Analysis (DEA) for Measuring Technical Efficiency in Poultry Farms. Brazilian J. Poult. Sci., 13(4): 271-277.
17. Mahjoor, A. A. 2013. Technical, Allocative and Economic Efficiency of Broiler Farms in Fars Province, Iran: A Data Envelopment Analysis (DEA) Approach. World Appl. Sci. J., 21(10): 1427-1435.
18. Nguyen, T. D. N., Nguyen, T. T. H. and Phung, G. H. 2011. Enhancing Coordination in Chicken Production in Yen the District, Bac Giang Province, Vietnam. J. ISSAAS, 17(2): 104-116.
19. Simar, L. and Wilson, P.W. 1998. Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Non-Parametric Frontier Models. Manag. Sci., 44(1): 49-61.
20. Todsadee, A., Kameyama, H., Ngamsomsuk, K. and Yamauchi, K. 2012. Production Efficiency of Broiler Farming in Thailand: A Stochastic Frontier Approach. J. Agric. Sci., 4(12): 221-231.
21. Yamane, T. 1967. Statistics: An Introductory Analysis. Harp. Row Pub., 1: 1-919.
22. Yusef S.A. and Malomo, O. 2007. Technical Efficiency of Poultry Egg Production in Ogun State: A Data Envelopment Analysis (DEA) Approach. Inter. J. Poul. Sci., 6(9): 622-629.
23. Zaghari, M. 2009. Evaluation of Using Phytase Nutrient Equivalency Values for Layer Hens and Broiler Chickens. J. Agri. Sci. Tech., 11: 57-66.