我国原料奶生产演变和全要素生产率研究
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摘要
奶业是一个节粮、高效、产业关联度较高的产业,与世界发达国家奶牛饲养相比,我国奶牛饲养的技术水平、生产规模和生产力都比较低。因此,探索和构建我国原料奶生产的全要素生产率模型,客观地估计我国原料奶生产的全要素生产率,找出制约我国原料奶生产全要素生产率的主要影响因素,能够为我国原料奶生产发展提供有益的参考。本文基于2004-2008年省级层面微观统计数据,使用多产出的随机边界距离函数方法,估计我国原料奶生产的全要素生产率发展趋势和增长方式,为评价不同地区原料奶生产能力和潜力提供一种新的方法,也获得一些有意义的结论和政策建议。
首先,从我国原料奶的生产历史出发,分析原料奶生产的区域分布、饲养方式变迁和成本收益状况,并运用扩展型Nerlovian模型研究了原料奶供给反应机制。研究发现,东北地区、华北地区和西北地区“三足鼎立”的区域生产布局形成,其中内蒙、新疆、河北和黑龙江四省原料奶产量合计约占全国58.1%;利润低下的农户散养仍然是我国奶牛饲养主体,大规模饲养方式处于辅助形式;产量滞后一期对原料奶供给影响最大,而原料奶供给总量对价格的反应较为迟钝,不利于我国原料奶生产的稳定。
第二,采用随机边界距离函数测算了原料奶生产全要素生产率,结果发现:全要素生产率增长缓慢,年均增长率为1.15%;技术效率决定全要素生产率增长强度,技术进步的变化影响了全要素生产率的提升;全要素生产率在产出增长中贡献率低,原料奶生产过度依赖要素投入,整个产业的发展方式较为“粗放”。
第三,研究原料奶生产技术效率变动特征,分析影响技术效率提升的关键因素。结果发现:全国原料奶生产平均技术效率为78.3%,且地区间技术效率差异逐渐缩小;饲料投入结构、消费需求、饲养收益、饲养方式、牛奶收购价格等因素对技术效率的影响显著。
最后,研究原料奶生产的要素产出弹性和规模报酬状况,结果发现:精饲料产出弹性最大,是提高原料奶生产的首要生产要素;劳动力投入的数量和质量均有待提高,是制约生产率提高的因素之一;我国奶牛饲养处于规模报酬递增阶段,应当鼓励适当地扩大养殖规模。
Dairy farming is a grain-saving, high efficiency and high industrial linkage sector. Compared with developed countries in the world dairy, China's dairy farming technology, farm size and productivity are lower. In order to measure total factor productivity on China’s dairy farms and identify its major determinats, it is necessary to find and define a specific model for those dairy farms in a trasition economy, like China. Using the 2004-2008 microscopic provincial dairy farm production cost survey data and employing a stochastic frontier distance function model, this thesis estimates the growth trends and patterns of total factor productivity on China’s dairy farms, and evaluates the ability and the potential of fresh milk over various producing areas, and finally the thesis has drawn some important conclusions and provided some policy recommendations based on the estimated results as follow:
First, after reviewing the fresh milk production, the thesis investigates the regional distribution, production evolution and cost-feeding features on China’s dairy farms over time. Then, an extended Nerlovian model is used to study the response mechanism of fresh milk supply for China. The results show that‘three pillars’production setting has been formed for the past two decades. The three core producing areas are Northeast China, North China and Northwest China, respectively, among which, output of fresh milk from Inner Mongolia, Xinjiang, Hebei and Heilongjiang accounts for nearly 60% of national total fresh milk production. In addition, backyard farming system still accounts for a large part of dairy cattle, while large size farming system is the second form in term of fresh milk production. The estimated parameters show that the lagged production has the maximum positive effect on fresh milk supply, and the price variable of fresh milk is lack of flexibility, which will interfere with the stability of raw milk production
Second, the thesis uses a stochastic frontier distance function to estimate the total factor productivity of fresh milk production. It is found that total factor productivity grows slowly, with average annual growth rates of 1.15%. It is important to find that technical efficiency is the most important factor that drives total factor productivity growth, while technological change actually deteriorates total factor productivity. The TFP contribution is low to output growth, and fresh milk production is excessively dependent on investment increase on China’s dairy farm sector.
Third, we study the changes of the technical efficiency of fresh milk production and identify the key factors affecting technical efficiency. The results show that the average technical efficiency of fresh milk production is 78.3% and the regional differences of technical efficiency are gradually reduced over the study period. Feed input composition, consumer demand, consolidated revenue, dairy farm size, farmgate fresh milk price and other factors all significantly play a role in the improvement of technical efficiency on fresh milk production in China.
Finally, the output elasticity of production factors and the returns to scale are also researched. The results show that concentrated feed has the maximum output elasticity, and therefore, it is the primary way to improving the level of fresh milk production. Both quantity and quality of the labor force need to be improved, they are the factors restricting productivity. Dairy farming sector in China is in the stage of its increasing returns to scale, and therefore it should be encouraged to expand to its current dairy farm size.
首先,从我国原料奶的生产历史出发,分析原料奶生产的区域分布、饲养方式变迁和成本收益状况,并运用扩展型Nerlovian模型研究了原料奶供给反应机制。研究发现,东北地区、华北地区和西北地区“三足鼎立”的区域生产布局形成,其中内蒙、新疆、河北和黑龙江四省原料奶产量合计约占全国58.1%;利润低下的农户散养仍然是我国奶牛饲养主体,大规模饲养方式处于辅助形式;产量滞后一期对原料奶供给影响最大,而原料奶供给总量对价格的反应较为迟钝,不利于我国原料奶生产的稳定。
第二,采用随机边界距离函数测算了原料奶生产全要素生产率,结果发现:全要素生产率增长缓慢,年均增长率为1.15%;技术效率决定全要素生产率增长强度,技术进步的变化影响了全要素生产率的提升;全要素生产率在产出增长中贡献率低,原料奶生产过度依赖要素投入,整个产业的发展方式较为“粗放”。
第三,研究原料奶生产技术效率变动特征,分析影响技术效率提升的关键因素。结果发现:全国原料奶生产平均技术效率为78.3%,且地区间技术效率差异逐渐缩小;饲料投入结构、消费需求、饲养收益、饲养方式、牛奶收购价格等因素对技术效率的影响显著。
最后,研究原料奶生产的要素产出弹性和规模报酬状况,结果发现:精饲料产出弹性最大,是提高原料奶生产的首要生产要素;劳动力投入的数量和质量均有待提高,是制约生产率提高的因素之一;我国奶牛饲养处于规模报酬递增阶段,应当鼓励适当地扩大养殖规模。
Dairy farming is a grain-saving, high efficiency and high industrial linkage sector. Compared with developed countries in the world dairy, China's dairy farming technology, farm size and productivity are lower. In order to measure total factor productivity on China’s dairy farms and identify its major determinats, it is necessary to find and define a specific model for those dairy farms in a trasition economy, like China. Using the 2004-2008 microscopic provincial dairy farm production cost survey data and employing a stochastic frontier distance function model, this thesis estimates the growth trends and patterns of total factor productivity on China’s dairy farms, and evaluates the ability and the potential of fresh milk over various producing areas, and finally the thesis has drawn some important conclusions and provided some policy recommendations based on the estimated results as follow:
First, after reviewing the fresh milk production, the thesis investigates the regional distribution, production evolution and cost-feeding features on China’s dairy farms over time. Then, an extended Nerlovian model is used to study the response mechanism of fresh milk supply for China. The results show that‘three pillars’production setting has been formed for the past two decades. The three core producing areas are Northeast China, North China and Northwest China, respectively, among which, output of fresh milk from Inner Mongolia, Xinjiang, Hebei and Heilongjiang accounts for nearly 60% of national total fresh milk production. In addition, backyard farming system still accounts for a large part of dairy cattle, while large size farming system is the second form in term of fresh milk production. The estimated parameters show that the lagged production has the maximum positive effect on fresh milk supply, and the price variable of fresh milk is lack of flexibility, which will interfere with the stability of raw milk production
Second, the thesis uses a stochastic frontier distance function to estimate the total factor productivity of fresh milk production. It is found that total factor productivity grows slowly, with average annual growth rates of 1.15%. It is important to find that technical efficiency is the most important factor that drives total factor productivity growth, while technological change actually deteriorates total factor productivity. The TFP contribution is low to output growth, and fresh milk production is excessively dependent on investment increase on China’s dairy farm sector.
Third, we study the changes of the technical efficiency of fresh milk production and identify the key factors affecting technical efficiency. The results show that the average technical efficiency of fresh milk production is 78.3% and the regional differences of technical efficiency are gradually reduced over the study period. Feed input composition, consumer demand, consolidated revenue, dairy farm size, farmgate fresh milk price and other factors all significantly play a role in the improvement of technical efficiency on fresh milk production in China.
Finally, the output elasticity of production factors and the returns to scale are also researched. The results show that concentrated feed has the maximum output elasticity, and therefore, it is the primary way to improving the level of fresh milk production. Both quantity and quality of the labor force need to be improved, they are the factors restricting productivity. Dairy farming sector in China is in the stage of its increasing returns to scale, and therefore it should be encouraged to expand to its current dairy farm size.
引文
[1] Ahmed M., Bravo-Ureta B. An econometric decomposition of dairy output growth [J]. American Journal of Agricultural Economics, 1995, 77: 914-921.
[2] Aigner J., Lovell K., Schmidt P. Formulation and estimation of stochastic frontier production function models [J]. Journal of Econometric, 1977, 6: 21-37.
[3] Alvarez A., Arias C. Technical efficiency and farm size: a conditional analysis [M]. Agricultural Economics, 2004, 30: 241-250.
[4] Andrés J. Picazo-Tadeo, JoséA. Gómez-Limón, Ernest Reig-Martínez. Assessing farming eco-efficiency: a data envelopment analysis approach [J]. Journal of Environmental Management, 2011,92(4): 1154-1164.
[5] Armagan G., Nizam S. Productivity and efficiency scores of dairy farms: the case of Turkey [J]. Springer Science+ Business Media B. V. 2010.
[6] Atkinson S. E., Primont D. Stochastic estimation of firm technology, infficiency, and productivity growth using shadow cost and distance functions [J]. Journal of Econometrics, 2002 (108):203-225.
[7] Barnes P. Does multi-functionality affect technical efficiency? A non-parametric analysis of the Scottish dairy industry [J]. Journal of Environmental Management, 2006, 80(4): 287-294.
[8] Battese G. E., Coelli T. J. A model for technical inefficiency effects in a stochastic frontier production function for panel data [J]. Empirical Economics, 1995 (2): 325-332.
[9] Bohrnstedt G. W., Knoke D. Statistics for social data analysis [M]. Ithaca, Ill: Peacock Publishers Inc, 1994.
[10] Braulke M. A note on the nerlove model of agricultural supply response [J]. International Economic Review, 1982, 23(1): 241-44.
[11] Bravo-Ureta B. E., Reiger L. Dairy farm efficiency measurement using stochastic frontiers and neoclassical duality [J]. American Journal of Agricultural Economics, 1991, 73(2): 421-428.
[12] Brummer B., Glauben T., Thijssen G. Decomposition of productivity growth using distance functions: the case of dairy farms in three European countries [J]. American Journal of Agricultural Economics, 2002, 84: 628-644.
[13] C. Bastin, L. Laloux, A. Gillon, F. Miglior, H. Soyeurt, H. Hammami, C. Bertozzi, N. Gengler. Modeling milk urea of Walloon dairy cows in management perspectives [J].Journal of Dairy Science, 2009,92(7): 3529-3540.
[14] Cabrera V. E., Solís D., Corral J. D. Determinants of technical efficiency among dairy farms in Wisconsin [J]. Journal of Dairy Science, 2010,93(1): 387-393.
[15] Chang H. H., Mishra A. K. Does the Milk Income Loss Contract program improve the technical efficiency of US dairy farms [J]. Journal of Dairy Science, 2011,94(6): 2945-2951.
[16] Charnes A., Coopers W. W., Rhodes E. Measuring the efficiency of decision making units [J]. European Journal of Operational Research, 1978 (2): 429-444.
[17] Christensen L. R., Jorgensen D. W., Lau L. J. Transcendental logarithmic production frontiers [J]. Review of Economics Statistics, 1973 (55): 28-45.
[18] Clément Yélou, Bruno Larue, Kien C. Tran. Threshold effects in panel data stochastic frontier models of dairy production in Canada [J]. Economic Modelling, 2010,27(3): 641-647.
[19] Coelli T. J., Perelman S. A comparison of parametric and non-parametric distance functions: with application to European railways [J]. European Journal of Operational Research, 1999, 117(2): 326-339.
[20] Coelli T. J., Perelman S. Technical efficiency of European railways: a distance function approach [J]. Applied Economics, 2000, 32: 1967-1976.
[21] Cuesta R. A., Knox Lovell C. A., JoséL. Zofío. Environmental efficiency measurement with translog distance functions: A parametric approach [J]. Ecological Economics, 2009,68(8-9): 2232-2242.
[22] D. Roibas, A. Alvarez. Impact of genetic progress on the profits of dairy farmers [J]. Journal of Dairy Science, 2010,93(9): 4366-4373.
[23] D. Susanto, C. P. Rosson, D. P. Anderson, F. J. Adcock. Immigration policy, foreign agricultural labor, and exit intentions in the United States dairy industry [J]. Journal of Dairy Science, 2010,93(4): 1774-1781.
[24] Davis H. S. Productivity accounting [M]. Philadelphia: University of Pennsylvania Press, 1955.
[25] Easterly W., Levine R. It’s not factor accumulation: stylized facts and growth models [C]. Working Papers Central Bank of Chile, 2001.
[26] F. Shomo, M. Ahmed, K. Shideed, A. Aw-Hassan, O. Erkan. Sources of technical efficiency of sheep production systems in dry areas in Syria [J]. Small Ruminant Research, 2010,91(2-3): 160-169.
[27] Fare R., Grosskopf S., Norris M. et al. Productivity Growth, Technical progress andefficiency changes in industrialized countries [J]. American Economic Review, 1994, 84(1): 66-83.
[28] Farrell M.J.The measurement of productive efficiency [J]. Journal of the Royal Statistical Society, 1957, 120(3): 253-290.
[29] Fernando Lopes. Technical efficiency in portuguese dairy farms [C]. The 82nd Annual Conference of the Agricultural Economics Society, 2008, 1-21.
[30] Fisher F. M. A theoretical analysis of the impact of food surplus disposal on agricultural production in recipient countries [J]. Journal of Farm Economics, 1963, 45(4): 245-248.
[31] Fogarasi J., Latruffe L. Technical efficiency and productivity change of dairy farms: a comparison of France and Hungary [C]. European Association of Agricultural Economists, 2007, 4:23-25.
[32] Graham M., Fraser I. Scale efficiency in Australian dairy farms [C]. The 47th Annual AARES Conference,February, 2003, 1-17.
[33] Grosskopf S., Hayes K., Hirschberg J. Fiscal stress and the production of public safety: a distance function approach [J]. Journal of Public Economics, 1995, 57: 277-296.
[34] Haese M. D., Speelman S., Alary V., et al. Efficiency in milk production on Reunion Island: dealing with land scarcity [J]. Journal of Dairy Science, 2009,92(8): 3676-3683.
[35] Helena Hansson, Bo ?hlmér. The effect of operational managerial practices on economic, technical and allocative efficiency at Swedish dairy farms [J]. Livestock Science, 2008,118(1-2): 34-43.
[36] Heng-yun MA, Qing-lin HU, Wen LI, et al. Hog production in China: technological bias and factor demand [J]. Agricultural Sciences in China, 2011,10(3): 468-479.
[37] Jaforullah M., Devlin N. J. Technical efficiency in the New Zealand dairy industry: a frontier production function approach [J]. New Zealand Economic Papers, 1996, 30(1): 1-17.
[38] Jaforullah M., Whiteman J. Scale efficiency in the New Zealand dairy industry: a non-parametric approach [J]. The Australian Journal of Agricultural and Resource Economics, 1999, 43: 523-541.
[39] Jan P., Lips M., Roesch A. Total factor productivity change of Swiss dairy farms located in the mountainous area [C]. 5th Annual Symposium of the PhD Program in Sustainable Agriculture, Research Station Agroscope Reckenholz-T?nikon ART 2009, September 2009.
[40] Kendrick J. W. Productivity trends in the United States [M]. NBER Macroeconomics Annual, Princeton: Princeton University Press, 1961.
[41] Klenow P. J., Rodriguez-Clare A. The neoclassical revival in growth economics: has it gone too far [M]. NBER Macroeconomics Annual, Cambridge, MA, MIT Press, 1997, 73-103.
[42] Kompas T., Che T. N. Production and technical efficiency on Australian dairy farms [C]. International and Development Economics Working Papers, No:idec04-1, 2004.
[43] Kompas T., Che T. N. Productivity in the Australian dairy industry [C]. International and Development Economics Working Papers, No:idec03-8, 2003.
[44] Kompas T., Che T. N., Mcmeniman S., et al. Productivity in the Australian dairy industry [J]. Australian Agribusiness Review, 2001, 12: 1-12.
[45] Kumbhakar S. C., Lovell C. A. K. Stochastic frontier analysis [M]. Cambridge: Cambridge University Press, 2000.
[46] Kumbhakar S. C., Tsionas E. G. and Sipilainen T. Joint estimation of technology choice and technical efficiency: an application to organic and conventional dairy farming [J]. J Prod Anal, 2009, 31: 151-161.
[47] Lawson L. G., Bruun J., Coelli T., et al. Relationships of efficiency to reproductive disorders in Danish milk production: a stochastic frontier analysis [J]. Journal of dairy science, 2004, 87(1): 212-224.
[48] Leibenstein H. Allocative efficiency vs‘x-effieieney’[J]. American Economic Review, 1996, 56: 392-415.
[49] Lovell C. A. K. Applying efficiency measurement techniques to the measurement of productivity change [J]. Journal of Productivity Analysis, 1996 (7): 329-340.
[50] Meeusen W., Broeck J. and Den V. Efficiency estimation from Cobb-Douglas production functions with composed error [J]. International Economic Review, 1977, 18: 435-444.
[51] Mkhabela T. S. Measuring Technical efficiency in a panel of kwazulu-natal midlands dairy farms: using a sgm restricted cost function approach [C]. 11th Annual Conference Of The African Econometrics Society(Aes), JULY 2006.
[52] Moreira lopez V. H., Bravo-Ureta B. E. Technical efficiency and metatechnology ratios for dairy farms in three southern cone countries: a stochastic meta-frontier model [J]. Journal of Productivity Analysis, 2009 (33): 33-45.
[53] Moreira lopez V. H., Bravo-Ureta B. E., Arzubi A. et al. Multi-output technical efficiency for argentinean dairy farms using stochastic production and stochastic distance frontiers with unbalanced panel data [J]. Economía Agraria, 2006 (10): 97-106.
[54] Ndambi O. A., Hemme T. An economic comparison of typical dairy farming systems in South Africa, Morocco, Uganda and Cameroon [J]. Tropical Animal Health andProduction, 2009, 41(6): 979-994.
[55] Nerlovian M. Estimates of the elasticities of supply of selected agricultural commodities [J]. Journal of Farm Economics, 1956, 38(2): 496-509.
[56] Newman C., Matthews A. The productivity performance of Irish dairy farms 1984–2000: a multiple output distance function approach [J]. Journal of Productivity Analysis, 2006, 26(2): 191-205.
[57] Paul J. Burgess, Joe Morris. Agricultural technology and land use futures: The UK case [J]. Land Use Policy, 2009,26(1): S222-S229.
[58] Pierani P., Rizzi P. L. Technology and efficiency in a panel of Italian dairy farms: an SGM restricted cost function approach [J]. Agricultural Economics, 2003, 29: 195-209.
[59] Quiroga R. E., Bravo-Ureta B. E. Short and long-run adjustments in dairy production: a profit function analysis [J]. Applied Economics, 1992, 24(6): 607-616.
[60] Reinhard S. Econometric analysis of economic and environmental efficiency of Dutch dairy farms [D]. Ph.D Thesis, Wageningen Agricultural University, 1999.
[61] Schultz T. W. Impact and implication of foreign surplus disposal on underdeveloped economics [J]. Journal of Farm Economics, 1960, 76(2): 1019-1030.
[62] Scott Waldron, Colin Brown and John Longworth. A critique of high-value supply chains as a means of modernising agriculture in China: The case of the beef industry [J]. Food Policy, 2010,35(5): 479-487.
[63] Shephard R. W. Theory of cost and production functions [M]. Princeton: Princeton University Press, 1970.
[64] Solow R. M. Technical and the aggregate production function [J]. Review of Economic Statistics, 1957, 39(8): 312-320.
[65] Songqing Jin, Hengyun Ma, Jikun Huang, Ruifa Hu and Scott Rozelle. Productivity, efficiency and technical change: measuring the performance of China’s transforming agriculture [J]. Journal of Productivity Analysis, 2010,33(3): 191-207.
[66] Strathe A. B., Dijkstra J., France J., et al. A Bayesian approach to analyze energy balance data from lactating dairy cows [J]. Journal of Dairy Science, 2011,94(5): 2520-2531.
[67] Theodoridis M., Psychoudakis A. Efficiency measurement in Greek dairy farms: stochastic frontier vs. data envelopment analysis [J]. International Journal of Economic Sciences and Applied Research, 2008, 2: 53-66.
[68] Thiagarajah Ramilan, Frank Scrimgeour, Dan Marsh. Analysis of environmental and economic efficiency using a farm population micro-simulation model [J]. Mathematics and Computers in Simulation, 2011,81(7): 1344-1352.
[69] Tian W. M., Wan G. H. Technical efficiency and its determinants in China’s grain production [J]. Journal of Productivity Analysis, 2000 (13): 159-74.
[70] Viet-Ngu Hoang. Measuring and decomposing changes in agricultural productivity, nitrogen use efficiency and cumulative exergy efficiency: Application to OECD agriculture [J]. Ecological Modelling, 2011,222(1): 164-175.
[71] Wei Hong, Lijuan Cao, Na Hao. Trade Liberalization, domestic input and sustainability of agricultural TFP growth: A new Perspective Based on TFP growth structure [J]. Agriculture and Agricultural Science Procedia, 2010(1): 376-385.
[72] Zhuo Chen, Wallace E. Huffman, Scott Rozelle. Farm technology and technical efficiency: Evidence from four regions in China [J]. China Economic Review, 2009,20(2): 153-161.
[73]鲍学东,郑循刚.基于SFA的四川农业生产技术效率分析[J].科技管理研究, 2008(9): 80-82.
[74]卜卫兵,李纪生.我国原料奶生产的组织模式及效率分析[J].农业经济问题, 2007(6): 67-72.
[75]曹暕,孙顶强,谭向勇.农户奶牛生产技术效率及影响因素分析[J].中国农村经济, 2005(10): 42-48.
[76]曹暕.中国农户原料奶生产经济效率分析[J].中国农业经济评论, 2005,3(2): 126-150.
[77]程漱兰,姚莉,崔惠玲,等. WTO背景下的中国奶业发展前景[J].农业经济问题, 2002(03): 9-16.
[78]道日娜.乳品加工企业与奶农交易关系研究[J].华中师范大学学报(人文社会科学版), 2008(04): 57-62.
[79]邓翔,李建平.中国地区经济增长的动力分析[J].管理世界, 2004(11): 68-76.
[80]丁岩,翟印礼.辽吉两省玉米全要素生产率的比较研究——基于莫氏指数的研究[J].商业研究, 2008(12): 181-182.
[81]鄂丽娟,杨瑞秀,杨瑞来,等.农户奶牛养殖及经济效益测算[J].内蒙古农业大学学报(社会科学版), 2007(1): 107-108.
[82]傅晓霞,吴利学.技术效率、资本深化与地区差异——基于随机前沿模型的中国地区收敛分析[J].经济研究, 2006(10): 52-61.
[83]高峰.考虑到气候因素影响的农业全要素生产率测算[D].西南财经大学硕士学位论文, 2008.
[84]郭庆旺,贾俊雪.中国全要素生产率的估算:1979-2004 [J].经济研究, 2005(6): 51-60.
[85]贺燕丽.贯彻落实科学发展观,促进乳制品工业健康发展——解读《乳制品工业产业政策》[J].中国食品学报, 2008(04): 1-6.
[86]侯智惠,侯安宏,梅连杰.内蒙古奶业区域布局问题研究[J].中国农业资源与区划, 2010(02): 62-66.
[87]胡浩,应瑞瑶,刘佳.中国生猪产地移动的经济分析——从自然性布局向经济性布局的转变[J].中国农村经济, 2005(12): 45-52.
[88]胡瑞法,黄季焜,李立秋.中国农技推广体系现状堪忧——来自7省28县的典型调查[J].中国农技推广, 2004(03): 6-8.
[89]华鹤良.奶业产业化经营中影响农民决策行为因素的实证研究[D].中国农业大学硕士学位论文, 2004.
[90]蒋乃华.中国畜产品供给需求与贸易行为研究[D].中国农业大学博士后研究工作报告, 2002.
[91]金剑.生产率增长测算方法的系统研究[D].东北财经大学博士学位论文, 2008.
[92]靳庭良,郭建军.面板数据模型设定存在的问题及对策分析[J].数量经济技术经济研究, 2004(10): 131-135.
[93]亢霞,刘秀梅.我国粮食生产的技术效率分析——基于随机前沿分析方法[J].中国农村观察, 2005(04): 25-32.
[94]孔祥智,钟真.奶价大幅上涨情况下奶农缘何增收困难——呼和浩特市奶牛养殖效益分析[J].中国乳业, 2008(3): 30-35.
[95]李碧芳.基于SBM-DEA模型的中国大豆全要素生产率分析[J].河南农业科学, 2010(3): 116-119.
[96]李丁.奶业资源与市场背离问题分析[J].中央财经大学学报, 2003(06): 67-69.
[97]李谷成,冯中朝,范丽霞.农户家庭经营技术效率与全要素生产率增长分解——基于随机前沿生产函数与来自湖北省农户的微观证据[J].数量经济技术经济研究, 2007(8): 25-34.
[98]李谷成,冯中朝,李然.三种油料作物生产的全要素生产率估计、分解与行业比较——基于随机前沿生产函数的分析框架[J].中国油料作物学报, 2009(2): 263-268.
[99]李谷成.人力资本与中国区域农业全要素生产率增长——基于DEA视角的实证分析[J].财经研究, 2009(8): 115-128.
[100]李建平,刘冬梅.我国奶业发展面临的新问题与对策建议——对“奶农与乳品加工企业两头不见利”现象的思考[J].农业经济问题, 2005(12): 69-72.
[101]李尽法.河南省农业全要素生产率变动实证分析——基于Malmquist指数方法[J].农业技术经济, 2008(2): 96-102.
[102]李晶.奶业产业化经营中利益分配机制比较研究[D].内蒙古师范大学硕士学位论文, 2007.
[103]李静,孟令杰,吴福象.中国地区发展差异的再检验:要素积累抑或TFP [J].世界经济, 2006(01): 12-22.
[104]李胜利.当前奶业现状与国家政策——中国奶业未来5年面临的挑战及其发展预测与规划[J].北方牧业, 2009(12): 7.
[105]李胜利.中国奶牛养殖产业发展现状及趋势[J].中国畜牧杂志, 2008(10): 45-49.
[106]李树明,张俊飚,徐卫涛,等.我国出口型农产品的生产效率研究[J].生态经济, 2010(9): 95-99.
[107]李晓明.提高我国奶业竞争力的思考[J].内蒙古农业大学学报(社会科学版), 2004(01): 13-15.
[108]刘小玄,吴延兵.企业生产率增长及来源:创新还是需求拉动[J].经济研究, 2009,(7): 45-54.
[109]刘艺卓,乔光华.金融危机对中国奶业发展的影响[J].中国乳业, 2009(07):6-8.
[110]卢凌霄.中国蔬菜产地集中与主产地形成研究[D].南京农业大学博士学位论文, 2008.
[111]陆海霞,张丽君.中国奶业国内市场需求空间与竞争力研究[J].中国奶牛, 2007(12):4-6.
[112]陆云航,张德荣.我国省际收入差异的成因:要素积累还是生产率[J].当代财经, 2007(4):22-28.
[113]吕甜.基于TFP测算的上海农业经济增长因素的实证分析[D].上海财经大学硕士学位论文, 2009.
[114]马恒运,唐华仓, Allan Rae.中国牛奶生产的全要素生产率分析[J].中国农村经济, 2007(2): 40-48.
[115]马恒运.河南省牛奶生产的全要素生产率及财政支持政策研究[J].河南农业大学学报, 2009(1): 104-108.
[116]马君,孙先明,张蓓.中国奶业持续健康发展的策略[J].农机化研究, 2009(1): 246-248.
[117]彭秀芬.中国原料奶的生产技术效率分析[J].农业技术经济, 2008(6): 23-29.
[118]钱贵霞,郭建军.内蒙古奶业发展的现状、问题与对策[J].农业展望, 2007(9): 39-42.
[119]钱贵霞,郭晓川,邬建国,等.中国奶业危机产生的根源及对策分析[J].农业经济问题, 2010(3): 30-36.
[120]钱贵霞,解晶.中国原料奶供求矛盾关系的实证分析[J].农业现代化研究, 2010(03): 272-276.
[121]沈琼.价格波动对油菜籽生产影响的实证分析[J].河南农业大学学报, 2007(4): 462-465.
[122]石风光,何雄浪.全要素生产率、要素投入与中国地区经济差距的动态分布分析[J].南京社会科学, 2010(2): 19-31.
[123]石风光,李宗植.要素投入、全要素生产率与地区经济差距——基于中国省区数据的实证分析[J].数量经济技术经济研究, 2009(12): 24-30.
[124]石慧,王怀明,孟令杰.要素累积、全要素生产率与中国农业增长地区差异[J].农业技术经济, 2009(3): 17-26.
[125]司伟,王秀清.中国糖料的供给反应[J].中国农村观察, 2006(4): 2-11.
[126]宋春光,那娜.农村金融支持对农业技术效率影响的实证研究[J].学术交流, 2010(2): 92-98.
[127]孙骏.对外开放对福建农业全要素生产率增长的影响研究——基于DEA与VAR的实证分析[J].技术经济, 2010(10):57-63.
[128]田露,张越杰.吉林省农户养猪生产效率分析[J].吉林农业大学学报, 2008(5): 764-768.
[129]田素妍.中国化学肥料制造业生产率研究[D].南京农业大学博士学位论文, 2008.
[130]涂正革,肖耿.中国的工业生产力革命[J].经济研究, 2005(3): 4-15.
[131]万兴,范金,胡汉辉.江苏制造业TFP增长、技术进步及效率变动分析——基于SFA和DEA方法的比较[J].系统管理学报, 2007(5): 465-471.
[132]王德文,黄季焜.双轨制度下中国农户粮食供给反应分析[J].经济研究, 2001(12): 55-65.
[133]王德祥,徐德徽.北京奶牛业的利润率和效率分析:一个DEA方法的应用[J].农业技术经济, 1997(1): 33-36.
[134]王济民.我国的大豆经济:供给与需求的重点分析[D].中国农业科学院博士学位论文, 2000.
[135]王林枫.我国奶业主产区奶牛生产效益与牛奶品质的调研分析[D].中国农业科学院博士后研究工作报告, 2006.
[136]王树贵,曲金铎.奶牛养殖小区建设与奶业发展——再与刘国民先生等商榷[J].中国牧业通讯, 2006(05): 55-57.
[137]王树进.提高奶业竞争力的产业化路线与模式探讨[J].商业研究, 2003(15): 140-143.
[138]王威,刘丽萍.基于产业链模式的奶业利益分配机制研究[J].哈尔滨理工大学学报, 2010(3): 122-127.
[139]王秀清,程厚思.蔬菜供给反应分析[J].经济问题探索, 1998(10): 54-56.
[140]魏克佳.中国奶业追风赶云60年[J].中国奶牛, 2009(S1): 2-5.
[141]魏立华,许常亮.河北省奶业形势调研报告[J].中国乳业, 2009(11): 32-35.
[142]吴方卫.中国农业的增长源泉分析[J].中国软科学, 2000(01): 48-52.
[143]谢立新.区域产业竞争力[M].北京:社会科学文献出版社, 2004.
[144]薛春玲,张晓虎,陈翠,等.中国农业生产的技术效率测度模型及实证分析[J].农业科技管理, 2006(02):3-6.
[145]颜鹏飞,王兵.技术效率、技术进步与生产率增长:基于DEA的实证分析[J].经济研究, 2004,(12): 55-65.
[146]杨建青.关于内蒙古奶源发展情况的调查分析[J].农业经济问题, 2007(S1): 95-99.
[147]杨建青.中国原料奶生产组织模式及效率研究[D].中国农业科学院博士学位论文, 2009.
[148]姚莉,王仁华,崔惠玲,等. WTO框架下中国奶业发展前景研究[J].中国奶牛, 2002(03): 5-7.
[149]余建斌,李大胜.中国农业生产的技术效率及其影响因素分析[J].统计与决策, 2008(14): 83-86.
[150]袁庆禄,蒋中一.我国烤烟的供给反应分析[J].技术经济, 2010(5): 93-98.
[151]约韩·伊特韦尔,默里·米尔盖特,彼得·纽曼·新帕尔格雷夫.经济学辞典(第三卷) [M].北京:经济科学出版社, 1996.
[152]张娣杰,张金龙.发展液态奶提升我国奶业市场竞争力[J].中国农业大学学报(社会科学版), 2003(02): 37-41.
[153]张冬平,冯继红.我国小麦生产效率的DEA分析[J].农业技术经济, 2005(3): 48-54.
[154]张宏升,赵云平.农业产业集聚对提升竞争力的效应探析——基于呼和浩特市奶业产业集聚的分析[J].调研世界, 2007(07): 18-20.
[155]张军,吴桂英,张吉鹏.中国省际物质资本存量的估算[J].经济研究, 2004(10): 35-44.
[156]张莉侠,孟令杰.我国奶业生产波动及原因分析[J].农村经济, 2007(1): 44-46.
[157]张莉侠.中国乳制品业的效率与绩效研究[D].南京农业大学博士学位论文, 2008.
[158]张文兵.国内需求对产业国际竞争力的影响分析:以中国奶业为例[J].管理世界,2006(04): 146-147.
[159]张文兵.中国奶业国际竞争力:基于RCA和“钻石”模型的分析[J].农业经济问题, 2005(11): 36-40.
[160]张喜才,张利庠.农业产业发展与政府规制——中国奶业产业的案例研究[J].中国乳业, 2009(07): 2-5.
[161]张艳.中国烟草产业全要素生产率及其变动的实证研究[J].湖南科技学院学报, 2008(11): 129-132.
[162]张永根,李胜利,曹志军,等.奶牛散养户长期存在的必然性和未来出路的思考[J].中国畜牧杂志, 2009(02): 50-54.
[163]张永霞.中国农业生产率测算及实证研究[D].中国农业科学院博士学位论文, 2006.
[164]张越杰.中国东北地区玉米生产效率的实证研究——以吉林省为例[J].吉林农业大学学报, 2008(4): 632-639.
[165]张照新,王维友,徐欣.当前我国奶业发展的问题、原因、趋势与对策[J].调研世界, 2007(10): 18-21.
[166]张忠明.农户粮地经营规模效率研究[D].浙江大学博士学位论文, 2008.
[167]赵全厚.加强农业结构调整积极扶持奶农和奶业[J].农业经济问题, 2002(11): 10-15.
[168]赵志耘,刘晓路,吕冰洋.中国要素产出弹性估计[J].经济理论与经济管理, 2006(6): 5-11.
[169]郑循刚.基于组合评价的中国农业生产技术效率研究——基于2000-2007的面板数据[J].科技管理研究, 2010(07): 41-43.
[170]郑循刚.四川省农户农业生产全要素生产率增长分解——基于2005-2007年的面板数据分析[J].农村经济, 2010(6): 39-42.
[171]周宪锋,朱香荣,花俊国.基于供求弹性角度的原料奶生产影响因素的实证分析[J].中国农村经济, 2008(07): 73-80.
[172]周鑫宇,杨君香,黄文明,等.对我国规模奶牛养殖模式的思考[J].中国畜牧杂志, 2010(12): 35-41.
[173]周旭英,苏胜娣.我国奶业区域发展研究[J].中国食物与营养, 2007(09): 6-9.
[174]周一星,田帅.以“五普”数据为基础对我国分省城市化水平数据修补[J].统计研究, 2006(1): 62-65.
[175]朱玉春.我国奶业的生产波动与对策研究[J].中国农村经济, 1997(2): 65-69.
[176]祝孔顺.河南奶业产业化经营问题研究[D].河南农业大学硕士学位论文, 2007.
[177]宗桂琴,薛莉.我国奶业关联产业和支撑产业国际竞争力探析[J].中国奶牛,2007(08): 3-6.
[2] Aigner J., Lovell K., Schmidt P. Formulation and estimation of stochastic frontier production function models [J]. Journal of Econometric, 1977, 6: 21-37.
[3] Alvarez A., Arias C. Technical efficiency and farm size: a conditional analysis [M]. Agricultural Economics, 2004, 30: 241-250.
[4] Andrés J. Picazo-Tadeo, JoséA. Gómez-Limón, Ernest Reig-Martínez. Assessing farming eco-efficiency: a data envelopment analysis approach [J]. Journal of Environmental Management, 2011,92(4): 1154-1164.
[5] Armagan G., Nizam S. Productivity and efficiency scores of dairy farms: the case of Turkey [J]. Springer Science+ Business Media B. V. 2010.
[6] Atkinson S. E., Primont D. Stochastic estimation of firm technology, infficiency, and productivity growth using shadow cost and distance functions [J]. Journal of Econometrics, 2002 (108):203-225.
[7] Barnes P. Does multi-functionality affect technical efficiency? A non-parametric analysis of the Scottish dairy industry [J]. Journal of Environmental Management, 2006, 80(4): 287-294.
[8] Battese G. E., Coelli T. J. A model for technical inefficiency effects in a stochastic frontier production function for panel data [J]. Empirical Economics, 1995 (2): 325-332.
[9] Bohrnstedt G. W., Knoke D. Statistics for social data analysis [M]. Ithaca, Ill: Peacock Publishers Inc, 1994.
[10] Braulke M. A note on the nerlove model of agricultural supply response [J]. International Economic Review, 1982, 23(1): 241-44.
[11] Bravo-Ureta B. E., Reiger L. Dairy farm efficiency measurement using stochastic frontiers and neoclassical duality [J]. American Journal of Agricultural Economics, 1991, 73(2): 421-428.
[12] Brummer B., Glauben T., Thijssen G. Decomposition of productivity growth using distance functions: the case of dairy farms in three European countries [J]. American Journal of Agricultural Economics, 2002, 84: 628-644.
[13] C. Bastin, L. Laloux, A. Gillon, F. Miglior, H. Soyeurt, H. Hammami, C. Bertozzi, N. Gengler. Modeling milk urea of Walloon dairy cows in management perspectives [J].Journal of Dairy Science, 2009,92(7): 3529-3540.
[14] Cabrera V. E., Solís D., Corral J. D. Determinants of technical efficiency among dairy farms in Wisconsin [J]. Journal of Dairy Science, 2010,93(1): 387-393.
[15] Chang H. H., Mishra A. K. Does the Milk Income Loss Contract program improve the technical efficiency of US dairy farms [J]. Journal of Dairy Science, 2011,94(6): 2945-2951.
[16] Charnes A., Coopers W. W., Rhodes E. Measuring the efficiency of decision making units [J]. European Journal of Operational Research, 1978 (2): 429-444.
[17] Christensen L. R., Jorgensen D. W., Lau L. J. Transcendental logarithmic production frontiers [J]. Review of Economics Statistics, 1973 (55): 28-45.
[18] Clément Yélou, Bruno Larue, Kien C. Tran. Threshold effects in panel data stochastic frontier models of dairy production in Canada [J]. Economic Modelling, 2010,27(3): 641-647.
[19] Coelli T. J., Perelman S. A comparison of parametric and non-parametric distance functions: with application to European railways [J]. European Journal of Operational Research, 1999, 117(2): 326-339.
[20] Coelli T. J., Perelman S. Technical efficiency of European railways: a distance function approach [J]. Applied Economics, 2000, 32: 1967-1976.
[21] Cuesta R. A., Knox Lovell C. A., JoséL. Zofío. Environmental efficiency measurement with translog distance functions: A parametric approach [J]. Ecological Economics, 2009,68(8-9): 2232-2242.
[22] D. Roibas, A. Alvarez. Impact of genetic progress on the profits of dairy farmers [J]. Journal of Dairy Science, 2010,93(9): 4366-4373.
[23] D. Susanto, C. P. Rosson, D. P. Anderson, F. J. Adcock. Immigration policy, foreign agricultural labor, and exit intentions in the United States dairy industry [J]. Journal of Dairy Science, 2010,93(4): 1774-1781.
[24] Davis H. S. Productivity accounting [M]. Philadelphia: University of Pennsylvania Press, 1955.
[25] Easterly W., Levine R. It’s not factor accumulation: stylized facts and growth models [C]. Working Papers Central Bank of Chile, 2001.
[26] F. Shomo, M. Ahmed, K. Shideed, A. Aw-Hassan, O. Erkan. Sources of technical efficiency of sheep production systems in dry areas in Syria [J]. Small Ruminant Research, 2010,91(2-3): 160-169.
[27] Fare R., Grosskopf S., Norris M. et al. Productivity Growth, Technical progress andefficiency changes in industrialized countries [J]. American Economic Review, 1994, 84(1): 66-83.
[28] Farrell M.J.The measurement of productive efficiency [J]. Journal of the Royal Statistical Society, 1957, 120(3): 253-290.
[29] Fernando Lopes. Technical efficiency in portuguese dairy farms [C]. The 82nd Annual Conference of the Agricultural Economics Society, 2008, 1-21.
[30] Fisher F. M. A theoretical analysis of the impact of food surplus disposal on agricultural production in recipient countries [J]. Journal of Farm Economics, 1963, 45(4): 245-248.
[31] Fogarasi J., Latruffe L. Technical efficiency and productivity change of dairy farms: a comparison of France and Hungary [C]. European Association of Agricultural Economists, 2007, 4:23-25.
[32] Graham M., Fraser I. Scale efficiency in Australian dairy farms [C]. The 47th Annual AARES Conference,February, 2003, 1-17.
[33] Grosskopf S., Hayes K., Hirschberg J. Fiscal stress and the production of public safety: a distance function approach [J]. Journal of Public Economics, 1995, 57: 277-296.
[34] Haese M. D., Speelman S., Alary V., et al. Efficiency in milk production on Reunion Island: dealing with land scarcity [J]. Journal of Dairy Science, 2009,92(8): 3676-3683.
[35] Helena Hansson, Bo ?hlmér. The effect of operational managerial practices on economic, technical and allocative efficiency at Swedish dairy farms [J]. Livestock Science, 2008,118(1-2): 34-43.
[36] Heng-yun MA, Qing-lin HU, Wen LI, et al. Hog production in China: technological bias and factor demand [J]. Agricultural Sciences in China, 2011,10(3): 468-479.
[37] Jaforullah M., Devlin N. J. Technical efficiency in the New Zealand dairy industry: a frontier production function approach [J]. New Zealand Economic Papers, 1996, 30(1): 1-17.
[38] Jaforullah M., Whiteman J. Scale efficiency in the New Zealand dairy industry: a non-parametric approach [J]. The Australian Journal of Agricultural and Resource Economics, 1999, 43: 523-541.
[39] Jan P., Lips M., Roesch A. Total factor productivity change of Swiss dairy farms located in the mountainous area [C]. 5th Annual Symposium of the PhD Program in Sustainable Agriculture, Research Station Agroscope Reckenholz-T?nikon ART 2009, September 2009.
[40] Kendrick J. W. Productivity trends in the United States [M]. NBER Macroeconomics Annual, Princeton: Princeton University Press, 1961.
[41] Klenow P. J., Rodriguez-Clare A. The neoclassical revival in growth economics: has it gone too far [M]. NBER Macroeconomics Annual, Cambridge, MA, MIT Press, 1997, 73-103.
[42] Kompas T., Che T. N. Production and technical efficiency on Australian dairy farms [C]. International and Development Economics Working Papers, No:idec04-1, 2004.
[43] Kompas T., Che T. N. Productivity in the Australian dairy industry [C]. International and Development Economics Working Papers, No:idec03-8, 2003.
[44] Kompas T., Che T. N., Mcmeniman S., et al. Productivity in the Australian dairy industry [J]. Australian Agribusiness Review, 2001, 12: 1-12.
[45] Kumbhakar S. C., Lovell C. A. K. Stochastic frontier analysis [M]. Cambridge: Cambridge University Press, 2000.
[46] Kumbhakar S. C., Tsionas E. G. and Sipilainen T. Joint estimation of technology choice and technical efficiency: an application to organic and conventional dairy farming [J]. J Prod Anal, 2009, 31: 151-161.
[47] Lawson L. G., Bruun J., Coelli T., et al. Relationships of efficiency to reproductive disorders in Danish milk production: a stochastic frontier analysis [J]. Journal of dairy science, 2004, 87(1): 212-224.
[48] Leibenstein H. Allocative efficiency vs‘x-effieieney’[J]. American Economic Review, 1996, 56: 392-415.
[49] Lovell C. A. K. Applying efficiency measurement techniques to the measurement of productivity change [J]. Journal of Productivity Analysis, 1996 (7): 329-340.
[50] Meeusen W., Broeck J. and Den V. Efficiency estimation from Cobb-Douglas production functions with composed error [J]. International Economic Review, 1977, 18: 435-444.
[51] Mkhabela T. S. Measuring Technical efficiency in a panel of kwazulu-natal midlands dairy farms: using a sgm restricted cost function approach [C]. 11th Annual Conference Of The African Econometrics Society(Aes), JULY 2006.
[52] Moreira lopez V. H., Bravo-Ureta B. E. Technical efficiency and metatechnology ratios for dairy farms in three southern cone countries: a stochastic meta-frontier model [J]. Journal of Productivity Analysis, 2009 (33): 33-45.
[53] Moreira lopez V. H., Bravo-Ureta B. E., Arzubi A. et al. Multi-output technical efficiency for argentinean dairy farms using stochastic production and stochastic distance frontiers with unbalanced panel data [J]. Economía Agraria, 2006 (10): 97-106.
[54] Ndambi O. A., Hemme T. An economic comparison of typical dairy farming systems in South Africa, Morocco, Uganda and Cameroon [J]. Tropical Animal Health andProduction, 2009, 41(6): 979-994.
[55] Nerlovian M. Estimates of the elasticities of supply of selected agricultural commodities [J]. Journal of Farm Economics, 1956, 38(2): 496-509.
[56] Newman C., Matthews A. The productivity performance of Irish dairy farms 1984–2000: a multiple output distance function approach [J]. Journal of Productivity Analysis, 2006, 26(2): 191-205.
[57] Paul J. Burgess, Joe Morris. Agricultural technology and land use futures: The UK case [J]. Land Use Policy, 2009,26(1): S222-S229.
[58] Pierani P., Rizzi P. L. Technology and efficiency in a panel of Italian dairy farms: an SGM restricted cost function approach [J]. Agricultural Economics, 2003, 29: 195-209.
[59] Quiroga R. E., Bravo-Ureta B. E. Short and long-run adjustments in dairy production: a profit function analysis [J]. Applied Economics, 1992, 24(6): 607-616.
[60] Reinhard S. Econometric analysis of economic and environmental efficiency of Dutch dairy farms [D]. Ph.D Thesis, Wageningen Agricultural University, 1999.
[61] Schultz T. W. Impact and implication of foreign surplus disposal on underdeveloped economics [J]. Journal of Farm Economics, 1960, 76(2): 1019-1030.
[62] Scott Waldron, Colin Brown and John Longworth. A critique of high-value supply chains as a means of modernising agriculture in China: The case of the beef industry [J]. Food Policy, 2010,35(5): 479-487.
[63] Shephard R. W. Theory of cost and production functions [M]. Princeton: Princeton University Press, 1970.
[64] Solow R. M. Technical and the aggregate production function [J]. Review of Economic Statistics, 1957, 39(8): 312-320.
[65] Songqing Jin, Hengyun Ma, Jikun Huang, Ruifa Hu and Scott Rozelle. Productivity, efficiency and technical change: measuring the performance of China’s transforming agriculture [J]. Journal of Productivity Analysis, 2010,33(3): 191-207.
[66] Strathe A. B., Dijkstra J., France J., et al. A Bayesian approach to analyze energy balance data from lactating dairy cows [J]. Journal of Dairy Science, 2011,94(5): 2520-2531.
[67] Theodoridis M., Psychoudakis A. Efficiency measurement in Greek dairy farms: stochastic frontier vs. data envelopment analysis [J]. International Journal of Economic Sciences and Applied Research, 2008, 2: 53-66.
[68] Thiagarajah Ramilan, Frank Scrimgeour, Dan Marsh. Analysis of environmental and economic efficiency using a farm population micro-simulation model [J]. Mathematics and Computers in Simulation, 2011,81(7): 1344-1352.
[69] Tian W. M., Wan G. H. Technical efficiency and its determinants in China’s grain production [J]. Journal of Productivity Analysis, 2000 (13): 159-74.
[70] Viet-Ngu Hoang. Measuring and decomposing changes in agricultural productivity, nitrogen use efficiency and cumulative exergy efficiency: Application to OECD agriculture [J]. Ecological Modelling, 2011,222(1): 164-175.
[71] Wei Hong, Lijuan Cao, Na Hao. Trade Liberalization, domestic input and sustainability of agricultural TFP growth: A new Perspective Based on TFP growth structure [J]. Agriculture and Agricultural Science Procedia, 2010(1): 376-385.
[72] Zhuo Chen, Wallace E. Huffman, Scott Rozelle. Farm technology and technical efficiency: Evidence from four regions in China [J]. China Economic Review, 2009,20(2): 153-161.
[73]鲍学东,郑循刚.基于SFA的四川农业生产技术效率分析[J].科技管理研究, 2008(9): 80-82.
[74]卜卫兵,李纪生.我国原料奶生产的组织模式及效率分析[J].农业经济问题, 2007(6): 67-72.
[75]曹暕,孙顶强,谭向勇.农户奶牛生产技术效率及影响因素分析[J].中国农村经济, 2005(10): 42-48.
[76]曹暕.中国农户原料奶生产经济效率分析[J].中国农业经济评论, 2005,3(2): 126-150.
[77]程漱兰,姚莉,崔惠玲,等. WTO背景下的中国奶业发展前景[J].农业经济问题, 2002(03): 9-16.
[78]道日娜.乳品加工企业与奶农交易关系研究[J].华中师范大学学报(人文社会科学版), 2008(04): 57-62.
[79]邓翔,李建平.中国地区经济增长的动力分析[J].管理世界, 2004(11): 68-76.
[80]丁岩,翟印礼.辽吉两省玉米全要素生产率的比较研究——基于莫氏指数的研究[J].商业研究, 2008(12): 181-182.
[81]鄂丽娟,杨瑞秀,杨瑞来,等.农户奶牛养殖及经济效益测算[J].内蒙古农业大学学报(社会科学版), 2007(1): 107-108.
[82]傅晓霞,吴利学.技术效率、资本深化与地区差异——基于随机前沿模型的中国地区收敛分析[J].经济研究, 2006(10): 52-61.
[83]高峰.考虑到气候因素影响的农业全要素生产率测算[D].西南财经大学硕士学位论文, 2008.
[84]郭庆旺,贾俊雪.中国全要素生产率的估算:1979-2004 [J].经济研究, 2005(6): 51-60.
[85]贺燕丽.贯彻落实科学发展观,促进乳制品工业健康发展——解读《乳制品工业产业政策》[J].中国食品学报, 2008(04): 1-6.
[86]侯智惠,侯安宏,梅连杰.内蒙古奶业区域布局问题研究[J].中国农业资源与区划, 2010(02): 62-66.
[87]胡浩,应瑞瑶,刘佳.中国生猪产地移动的经济分析——从自然性布局向经济性布局的转变[J].中国农村经济, 2005(12): 45-52.
[88]胡瑞法,黄季焜,李立秋.中国农技推广体系现状堪忧——来自7省28县的典型调查[J].中国农技推广, 2004(03): 6-8.
[89]华鹤良.奶业产业化经营中影响农民决策行为因素的实证研究[D].中国农业大学硕士学位论文, 2004.
[90]蒋乃华.中国畜产品供给需求与贸易行为研究[D].中国农业大学博士后研究工作报告, 2002.
[91]金剑.生产率增长测算方法的系统研究[D].东北财经大学博士学位论文, 2008.
[92]靳庭良,郭建军.面板数据模型设定存在的问题及对策分析[J].数量经济技术经济研究, 2004(10): 131-135.
[93]亢霞,刘秀梅.我国粮食生产的技术效率分析——基于随机前沿分析方法[J].中国农村观察, 2005(04): 25-32.
[94]孔祥智,钟真.奶价大幅上涨情况下奶农缘何增收困难——呼和浩特市奶牛养殖效益分析[J].中国乳业, 2008(3): 30-35.
[95]李碧芳.基于SBM-DEA模型的中国大豆全要素生产率分析[J].河南农业科学, 2010(3): 116-119.
[96]李丁.奶业资源与市场背离问题分析[J].中央财经大学学报, 2003(06): 67-69.
[97]李谷成,冯中朝,范丽霞.农户家庭经营技术效率与全要素生产率增长分解——基于随机前沿生产函数与来自湖北省农户的微观证据[J].数量经济技术经济研究, 2007(8): 25-34.
[98]李谷成,冯中朝,李然.三种油料作物生产的全要素生产率估计、分解与行业比较——基于随机前沿生产函数的分析框架[J].中国油料作物学报, 2009(2): 263-268.
[99]李谷成.人力资本与中国区域农业全要素生产率增长——基于DEA视角的实证分析[J].财经研究, 2009(8): 115-128.
[100]李建平,刘冬梅.我国奶业发展面临的新问题与对策建议——对“奶农与乳品加工企业两头不见利”现象的思考[J].农业经济问题, 2005(12): 69-72.
[101]李尽法.河南省农业全要素生产率变动实证分析——基于Malmquist指数方法[J].农业技术经济, 2008(2): 96-102.
[102]李晶.奶业产业化经营中利益分配机制比较研究[D].内蒙古师范大学硕士学位论文, 2007.
[103]李静,孟令杰,吴福象.中国地区发展差异的再检验:要素积累抑或TFP [J].世界经济, 2006(01): 12-22.
[104]李胜利.当前奶业现状与国家政策——中国奶业未来5年面临的挑战及其发展预测与规划[J].北方牧业, 2009(12): 7.
[105]李胜利.中国奶牛养殖产业发展现状及趋势[J].中国畜牧杂志, 2008(10): 45-49.
[106]李树明,张俊飚,徐卫涛,等.我国出口型农产品的生产效率研究[J].生态经济, 2010(9): 95-99.
[107]李晓明.提高我国奶业竞争力的思考[J].内蒙古农业大学学报(社会科学版), 2004(01): 13-15.
[108]刘小玄,吴延兵.企业生产率增长及来源:创新还是需求拉动[J].经济研究, 2009,(7): 45-54.
[109]刘艺卓,乔光华.金融危机对中国奶业发展的影响[J].中国乳业, 2009(07):6-8.
[110]卢凌霄.中国蔬菜产地集中与主产地形成研究[D].南京农业大学博士学位论文, 2008.
[111]陆海霞,张丽君.中国奶业国内市场需求空间与竞争力研究[J].中国奶牛, 2007(12):4-6.
[112]陆云航,张德荣.我国省际收入差异的成因:要素积累还是生产率[J].当代财经, 2007(4):22-28.
[113]吕甜.基于TFP测算的上海农业经济增长因素的实证分析[D].上海财经大学硕士学位论文, 2009.
[114]马恒运,唐华仓, Allan Rae.中国牛奶生产的全要素生产率分析[J].中国农村经济, 2007(2): 40-48.
[115]马恒运.河南省牛奶生产的全要素生产率及财政支持政策研究[J].河南农业大学学报, 2009(1): 104-108.
[116]马君,孙先明,张蓓.中国奶业持续健康发展的策略[J].农机化研究, 2009(1): 246-248.
[117]彭秀芬.中国原料奶的生产技术效率分析[J].农业技术经济, 2008(6): 23-29.
[118]钱贵霞,郭建军.内蒙古奶业发展的现状、问题与对策[J].农业展望, 2007(9): 39-42.
[119]钱贵霞,郭晓川,邬建国,等.中国奶业危机产生的根源及对策分析[J].农业经济问题, 2010(3): 30-36.
[120]钱贵霞,解晶.中国原料奶供求矛盾关系的实证分析[J].农业现代化研究, 2010(03): 272-276.
[121]沈琼.价格波动对油菜籽生产影响的实证分析[J].河南农业大学学报, 2007(4): 462-465.
[122]石风光,何雄浪.全要素生产率、要素投入与中国地区经济差距的动态分布分析[J].南京社会科学, 2010(2): 19-31.
[123]石风光,李宗植.要素投入、全要素生产率与地区经济差距——基于中国省区数据的实证分析[J].数量经济技术经济研究, 2009(12): 24-30.
[124]石慧,王怀明,孟令杰.要素累积、全要素生产率与中国农业增长地区差异[J].农业技术经济, 2009(3): 17-26.
[125]司伟,王秀清.中国糖料的供给反应[J].中国农村观察, 2006(4): 2-11.
[126]宋春光,那娜.农村金融支持对农业技术效率影响的实证研究[J].学术交流, 2010(2): 92-98.
[127]孙骏.对外开放对福建农业全要素生产率增长的影响研究——基于DEA与VAR的实证分析[J].技术经济, 2010(10):57-63.
[128]田露,张越杰.吉林省农户养猪生产效率分析[J].吉林农业大学学报, 2008(5): 764-768.
[129]田素妍.中国化学肥料制造业生产率研究[D].南京农业大学博士学位论文, 2008.
[130]涂正革,肖耿.中国的工业生产力革命[J].经济研究, 2005(3): 4-15.
[131]万兴,范金,胡汉辉.江苏制造业TFP增长、技术进步及效率变动分析——基于SFA和DEA方法的比较[J].系统管理学报, 2007(5): 465-471.
[132]王德文,黄季焜.双轨制度下中国农户粮食供给反应分析[J].经济研究, 2001(12): 55-65.
[133]王德祥,徐德徽.北京奶牛业的利润率和效率分析:一个DEA方法的应用[J].农业技术经济, 1997(1): 33-36.
[134]王济民.我国的大豆经济:供给与需求的重点分析[D].中国农业科学院博士学位论文, 2000.
[135]王林枫.我国奶业主产区奶牛生产效益与牛奶品质的调研分析[D].中国农业科学院博士后研究工作报告, 2006.
[136]王树贵,曲金铎.奶牛养殖小区建设与奶业发展——再与刘国民先生等商榷[J].中国牧业通讯, 2006(05): 55-57.
[137]王树进.提高奶业竞争力的产业化路线与模式探讨[J].商业研究, 2003(15): 140-143.
[138]王威,刘丽萍.基于产业链模式的奶业利益分配机制研究[J].哈尔滨理工大学学报, 2010(3): 122-127.
[139]王秀清,程厚思.蔬菜供给反应分析[J].经济问题探索, 1998(10): 54-56.
[140]魏克佳.中国奶业追风赶云60年[J].中国奶牛, 2009(S1): 2-5.
[141]魏立华,许常亮.河北省奶业形势调研报告[J].中国乳业, 2009(11): 32-35.
[142]吴方卫.中国农业的增长源泉分析[J].中国软科学, 2000(01): 48-52.
[143]谢立新.区域产业竞争力[M].北京:社会科学文献出版社, 2004.
[144]薛春玲,张晓虎,陈翠,等.中国农业生产的技术效率测度模型及实证分析[J].农业科技管理, 2006(02):3-6.
[145]颜鹏飞,王兵.技术效率、技术进步与生产率增长:基于DEA的实证分析[J].经济研究, 2004,(12): 55-65.
[146]杨建青.关于内蒙古奶源发展情况的调查分析[J].农业经济问题, 2007(S1): 95-99.
[147]杨建青.中国原料奶生产组织模式及效率研究[D].中国农业科学院博士学位论文, 2009.
[148]姚莉,王仁华,崔惠玲,等. WTO框架下中国奶业发展前景研究[J].中国奶牛, 2002(03): 5-7.
[149]余建斌,李大胜.中国农业生产的技术效率及其影响因素分析[J].统计与决策, 2008(14): 83-86.
[150]袁庆禄,蒋中一.我国烤烟的供给反应分析[J].技术经济, 2010(5): 93-98.
[151]约韩·伊特韦尔,默里·米尔盖特,彼得·纽曼·新帕尔格雷夫.经济学辞典(第三卷) [M].北京:经济科学出版社, 1996.
[152]张娣杰,张金龙.发展液态奶提升我国奶业市场竞争力[J].中国农业大学学报(社会科学版), 2003(02): 37-41.
[153]张冬平,冯继红.我国小麦生产效率的DEA分析[J].农业技术经济, 2005(3): 48-54.
[154]张宏升,赵云平.农业产业集聚对提升竞争力的效应探析——基于呼和浩特市奶业产业集聚的分析[J].调研世界, 2007(07): 18-20.
[155]张军,吴桂英,张吉鹏.中国省际物质资本存量的估算[J].经济研究, 2004(10): 35-44.
[156]张莉侠,孟令杰.我国奶业生产波动及原因分析[J].农村经济, 2007(1): 44-46.
[157]张莉侠.中国乳制品业的效率与绩效研究[D].南京农业大学博士学位论文, 2008.
[158]张文兵.国内需求对产业国际竞争力的影响分析:以中国奶业为例[J].管理世界,2006(04): 146-147.
[159]张文兵.中国奶业国际竞争力:基于RCA和“钻石”模型的分析[J].农业经济问题, 2005(11): 36-40.
[160]张喜才,张利庠.农业产业发展与政府规制——中国奶业产业的案例研究[J].中国乳业, 2009(07): 2-5.
[161]张艳.中国烟草产业全要素生产率及其变动的实证研究[J].湖南科技学院学报, 2008(11): 129-132.
[162]张永根,李胜利,曹志军,等.奶牛散养户长期存在的必然性和未来出路的思考[J].中国畜牧杂志, 2009(02): 50-54.
[163]张永霞.中国农业生产率测算及实证研究[D].中国农业科学院博士学位论文, 2006.
[164]张越杰.中国东北地区玉米生产效率的实证研究——以吉林省为例[J].吉林农业大学学报, 2008(4): 632-639.
[165]张照新,王维友,徐欣.当前我国奶业发展的问题、原因、趋势与对策[J].调研世界, 2007(10): 18-21.
[166]张忠明.农户粮地经营规模效率研究[D].浙江大学博士学位论文, 2008.
[167]赵全厚.加强农业结构调整积极扶持奶农和奶业[J].农业经济问题, 2002(11): 10-15.
[168]赵志耘,刘晓路,吕冰洋.中国要素产出弹性估计[J].经济理论与经济管理, 2006(6): 5-11.
[169]郑循刚.基于组合评价的中国农业生产技术效率研究——基于2000-2007的面板数据[J].科技管理研究, 2010(07): 41-43.
[170]郑循刚.四川省农户农业生产全要素生产率增长分解——基于2005-2007年的面板数据分析[J].农村经济, 2010(6): 39-42.
[171]周宪锋,朱香荣,花俊国.基于供求弹性角度的原料奶生产影响因素的实证分析[J].中国农村经济, 2008(07): 73-80.
[172]周鑫宇,杨君香,黄文明,等.对我国规模奶牛养殖模式的思考[J].中国畜牧杂志, 2010(12): 35-41.
[173]周旭英,苏胜娣.我国奶业区域发展研究[J].中国食物与营养, 2007(09): 6-9.
[174]周一星,田帅.以“五普”数据为基础对我国分省城市化水平数据修补[J].统计研究, 2006(1): 62-65.
[175]朱玉春.我国奶业的生产波动与对策研究[J].中国农村经济, 1997(2): 65-69.
[176]祝孔顺.河南奶业产业化经营问题研究[D].河南农业大学硕士学位论文, 2007.
[177]宗桂琴,薛莉.我国奶业关联产业和支撑产业国际竞争力探析[J].中国奶牛,2007(08): 3-6.