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Journal of Integrative Agriculture  2015, Vol. 14 Issue (6): 1069-1080    DOI: 10.1016/S2095-3119(14)60990-4
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Technical and environmental efficiency of hog production in China -A stochastic frontier production function analysis
 ZHOU Ying-heng, ZHANG Xiao-heng, TIAN Xu, GENG Xian-hui, ZHANG Peng, YAN Bin-jian
1、College of Economics and Management, Nanjing Agricultural University, Nanjing 210095, P.R.China
2、China Center for Food Security Studies, Nanjing Agricultural University, Nanjing 210095, P.R.China
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摘要  This article analyses the technical and environmental efficiency of hog production in China using data from the China Agricultural Product Cost-Benefit Compilation (NDRC 2005–2013) and the First National Census of Pollution: Manual of Discharge Coefficient of Livestock and Poultry Industry (IEDA and NIES 2009). The empirical results show a great variation in environmental efficiency, ranging from 0.344 to 0.973 with a mean value of 0.672 that declines over time. Southwest China is found to be the most environmentally efficient region, while the Northeast and the Northwest are the least efficient. Another finding is that technical and environmental efficiencies are highly correlated in hog production; the most environmentally efficient regions are usually found to have high technical efficiency, and vice versa. In addition, we computed the output elasticities with respect to each factor input. The results show that feed is the most efficient input, with an output elasticity of approximately 0.551, which is much higher than the elasticity of the nitrogen surplus, other capital or labour. The output elasticity with respect to the nitrogen surplus is 0.287 on average. Finally, the scale elasticity in hog production is slightly higher than 1.

Abstract  This article analyses the technical and environmental efficiency of hog production in China using data from the China Agricultural Product Cost-Benefit Compilation (NDRC 2005–2013) and the First National Census of Pollution: Manual of Discharge Coefficient of Livestock and Poultry Industry (IEDA and NIES 2009). The empirical results show a great variation in environmental efficiency, ranging from 0.344 to 0.973 with a mean value of 0.672 that declines over time. Southwest China is found to be the most environmentally efficient region, while the Northeast and the Northwest are the least efficient. Another finding is that technical and environmental efficiencies are highly correlated in hog production; the most environmentally efficient regions are usually found to have high technical efficiency, and vice versa. In addition, we computed the output elasticities with respect to each factor input. The results show that feed is the most efficient input, with an output elasticity of approximately 0.551, which is much higher than the elasticity of the nitrogen surplus, other capital or labour. The output elasticity with respect to the nitrogen surplus is 0.287 on average. Finally, the scale elasticity in hog production is slightly higher than 1.
Keywords:  environmental efficiency       technical efficiency       hog production       China       stochastic frontier production function  
Received: 05 January 2014   Accepted:
Fund: 

The study was sponsored by the National Natural Science Foundation of China (71473123, 71333008), and A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions, China (PAPD).

Corresponding Authors:  GENG Xian-hui, Tel/Fax: +86-25-84399653,Mobile: +86-13951962095, E-mail: gengxh@njau.edu.cn     E-mail:  gengxh@njau.edu.cn
About author:  ZHOU Ying-heng, E-mail: zhouyh@njau.edu.cn;

Cite this article: 

ZHOU Ying-heng, ZHANG Xiao-heng, TIAN Xu, GENG Xian-hui, ZHANG Peng, YAN Bin-jian. 2015. Technical and environmental efficiency of hog production in China -A stochastic frontier production function analysis. Journal of Integrative Agriculture, 14(6): 1069-1080.

Baker A. 2002. Fluorescence properties of some farm wastes:Implications for water quality monitoring. Water Research, 36, 189-195

Baltussen W H M, Hoste R, Daatselaar C H G, Janssens S RM 1992. Differences in Mineral Surpluses between Farmsin the Livestock Sector and in the Arable Sector, LEI-DLOonderzoekverslag 101, The Hague. (in Dutch)

Battese G E, Coelli T L. 1995. A model for technical inefficiencyeffects in a stochastic frontier production function for paneldata. Empirical Economics, 20, 325-332

Boggs R L. 1997. Hazardous waste treatment facilities:Modeling production with pollution as both an input and anoutput. Ph D thesis, University of North Carolina, Chapel Hill.

Coelli T L. 1995. Estimators and hypothesis tests for a stochasticfrontier function: A Monte Carlo analysis. Journal ofProductivity Analysis, 6, 247-268

Cropper M L, Oates W E. 1992. Environmental economics: Asurvey. Journal of Economic Literature, 30, 675-740

NDRC (National Development and Reform Commission,China). 2005-2013 China Agricultural Product Cost-BenefitCompilation. China’s Statistical Press, Beijing. (in Chinese)

FAO (Food and Agriculture Organization of the United Nations).2014. FAOSTAT. [2014-4-20]. http://faostat3.fao.org/download/Q/QA/E

Färe R, Grosskopf S, Lovell C A K, Pasurka C. 1989.Multilateral productivity comparisons when some outputsare undesirable: A nonparametric approach. The Reviewof Economics and Statistics, 71, 90-98

Färe R, Grosskopf S, Lovell C A K, Yaisawarng S. 1993.Derivation of shadow prices for undesirable outputs: Adistance function approach. The Review of Economics andStatistics, 75, 374-380

Farrell M J. 1957. The measurement of productive efficiency.Journal of the Royal Statistical Society (Series A, General),120, 253-281

Galanopoulos K, Aggelopoulos S, Kamenidou I, Mattas K.2006. Assessing the effects of managerial and productionpractices on the efficiency of commercial pig farming.Agricultrual Systems, 88, 125-141

Hantschel R E, Beese F. 1997. Site-oriented ecosystermmanagement: Precondition to reducing the contaminationof waters and the atmosphere. In: Modern Agriculture andthe Environment. Springer, The Netherlands. pp. 135-145

Haynes K E, Ratick S, Bowen W M, Cummings-Saxton J.1993. Environmental decision models: U.S. experience anda new approach to pollution management. EnvironmentInternational, 19, 261-275

Haynes K E, Ratick S, Cummings-Saxton J. 1994. Toward apollution abatement monitoring policy: Measurements, modelmechanics, and data requirements. The EnvironmentalProfessional, 16, 292-303

IEDA (Insititue of Environment and Sustainable Eevelopmentin Agriculture, Chinese Academy of Agricultural Sciences),NIES (Nanjing Institute of Environmental Science, Ministryof Environmental Protection of China). 2009. The FirstCensus of Pollution: Manual of Discharge Coefficient ofLivestock and Poultry Industry. Unpublished.

Kautsky N, Ronnback P, Tedengren M, Troell M. 2000.Ecosystem perspectives on management of disease inshrimp pond farming. Aquaculture, 191,145-161

Kopp R J. 1981. The measurement of productive efficiency:A reconsideration. The Quarterly Journal of Economics,96, 477-503

Lansink A O, Reinhard S. 2004. Investigating technicalefficiency and potential technological change in Dutch pigfarming. Agricultural Systems, 79, 353-467

Li P J. 2009. Exponential growth, animal welfare, environmentaland food safety impact: The case of China’s livestockproduction. Journal of Agricultural and EnvironmentalEthics, 22, 217-240

Ma H Y, Hu Q L, Li W, Rae A N, Guo S M, Tang H C, Ren XJ. 2011. Hog production in China: Technological bias andfactor demand. Agricultural Sciences in China, 10, 468-479

McCulloch R B, Stephen Few G, Murray Jr. G C, Aneja VP. 1998. Analysis of ammonia, ammonium aerosols andacid gases in the atmosphere at a commercial hog farmin eastern North Carolina, USA. Environmental Pollution,102, 263-268

NBSC (National Bureau of Statistics of China). 2005-2013China Statistical Yearbooks. China’s Statistical Press,Beijing, China. (in Chinese)

Pittman R W. 1981. Issues in pollution control: Interplant costdifferences and economies of scale. Land Economics, 57,1-17

Pittman R W. 1983. Multilateral productivity comparisons withundesirable outputs. Economic Journal, 372, 883-891

Rae A N, Ma H, Huang J, Rozelle S. 2006. Livestock in China:Commodity-specific total factor productivity decompositionusing new panel data. American Journal of AgriculturalEconomics, 88, 680-695

Reinhard S, Lovell C A K, Thijssen G J. 1999. Econometricestimation of technical and environmental efficiency: Anapplication to Dutch Dairy farms. American Journal ofAgricultural Economics, 81, 44-60

Reinhard S, Lovell C A K, Thijssen G J. 2000. Environmentalefficiency with multiple environmentally detrimentalvariables: estimated with SPF and DEA. European Journalof Operational Research, 121, 287-303

Schofield K, Seager J, Merriman R P. 1990. The impact ofintensive dairy farming activities on river quality: TheEastern Cleddau catchment study. Water and EnvironmentJournal, 4, 176-186

Sharma K R, Leung P, Zaleski H M. 1997. Productive efficiencyof the swine industry in Hawaii: Stochastic frontier vs. dataenvelopment analysis. Journal of Productivity Analysis, 8,447-459

Shephard R W, Färe R. 1974. The Law of Diminishing Returns.Springer, Heidelberg, Berlin. pp. 287-318

Shortall O K, Barnes A P. 2013. Greenhouse gas emissionsand the technical efficiency of dairy farmers. EcologicalIndicators, 29, 478-488

Weiss R A, McMichael A J. 2004. Social and environmental risk factors in the emergence of infectious disease. NatureMedicine, 10, s70-s76.Wu Y R. 2011. Chemical fertilizer use efficiency and itsdeterminants in China’s farming sector. China AgriculturalEconomic Review, 3, 117-130

Xiao H, Wang J, Oxley L, Ma H. 2012. The evolution of hogproduction and potential source for future growth in China.Food Policy, 37, 366-377

Yang C C. 2009. Productive efficiency, environmental efficiencyand their determinants in farrow-to-finish pig farming inTaiwan. Livestock Science, 126, 195-205

Yang C C, Hsiao C K, Yu M M. 2008. Technical efficiency andimpact of environmental regulations in farrow-to-finish swineproduction in Taiwan. Agricultural Economics, 39, 51-61

Zhang T, Xue B D. 2005. Environmental efficiency analysisof China’s vegetable production. Biomedical andEnvironmental Science, 18, 21-30
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