[1] 曹俊文, 曾康. 2019. 低碳视角下长江经济带农业生态效率及影响因素研究[J]. 生态经济(8):115-119.
[2] 洪开荣, 陈诚, 丰超,等. 2016. 农业生态效率的时空差异及影响因素[J]. 华南农业大学学报(社会科学版) (2): 31-41.
[3] 侯孟阳, 姚顺波. 2019. 空间视角下中国农业生态效率的收敛性与分异特征[J]. 中国人口?资源与环境(4): 116-126.
[4] 赖斯芸, 杜鹏飞, 陈吉宁. 2004. 基于单元分析的非点源污染调查评估方法[J]. 清华大学学报(自然科学版) (9): 1184-1187.
[5] 李波, 张俊飚, 李海鹏,等. 2011. 中国农业碳排放时空特征及影响因素分解[J]. 中国人口?资源与环境(8): 80-86.
[6] 李敬, 陈澍, 万广华,等. 2014. 中国区域经济增长的空间关联及其解释:基于网络分析方法[J]. 经济研究(11): 4-16.
[7] 刘军. 2004. 社会网络分析导论[M]. 北京:社会科学文献出版社.王宝义, 张卫国. 2018. 中国农业生态效率的省际差异和影响因素:基于1996~2015年31个省份的面板数据分析[J]. 中国农村经济(1): 46-62.
[8] 曾福生, 刘俊辉. 2019. 区域异质性下中国农业生态效率评价与空间差异实证:基于组合DEA与空间自相关分析[J]. 生态经济(3): 107-114.
[9] 郑德凤, 郝帅, 孙才志,等. 2018. 中国大陆生态效率时空演化分析及其趋势预测[J]. 地理研究(5): 1034-1046.
[10] BAEK E G, BROCK W A. 1992. A general test for nonlinear Granger causality: Bivariate model[Z].Iowa State University and University of Wisconsin at Madison Working Paper.
[11] BROCK W A, BAEK E G. 1991. Some theory of statistical inference for nonlinear science[J]. The Review of Economic Studies, 58(4): 697-716.
[12] CHARNES A, COOPER W, LEWIN A Y, et al. 1994. Data envelopment analysis: Theory, methodology and application [M]. Norwell: Kluwer Academic Publishers.
[13] GRANGER C W J, NEWBOLD P. 1986. Forecasting economic time series (Second Edition) [M]. San Diego: Academic Press.
[14] HALKOS G E, TZEREMES N G. 2009. Exploring the existence of Kuznets curve in countries' environmental efficiency using DEA window analysis [J]. Ecological Economics, 68(7): 2168-2176.
[15] HAN H, DING T, NIE L, et al. 2020. Agricultural eco-efficiency loss under technology heterogeneity given regional differences in China [J]. Journal of Cleaner Production, 250(4): 19-51.
[16] HIEMSTRA C, JONES J D. 1994. Testing for linear and nonlinear Granger causality in the stock price-volume relation [J]. The Journal of Finance, 49(5): 1639-1664.
[17] HUPPES G, ISHIKAWA M. 2005. A framework for quantified eco-efficiency analysis[J]. Juornal of Industrial ecology, 9(4):25-41.
[18] LIU X, GUO P, GUO S. 2019. Assessing the eco-efficiency of a circular economy system in China's coal mining areas: Emergy and data envelopment analysis [J]. Journal of Cleaner Production, 206: 1101-1109.
[19] NOTARNICOLA B, SALA S, ANTON A, et al. 2017. The role of life cycle assessment in supporting sustainable agri-food systems: A review of the challenges [J]. Journal of Cleaner Production, 140: 399-409.
[20] OREA L, WALL A. 2017. A parametric approach to estimating eco-efficiency [J]. Journal of Agricultural Economics, 68(3): 901-907.
[21] PICAZO-TADEO A J, BELTRN-ESTEVE M, GMEZ-LIMN J A.2012. Assessing eco-efficiency with directional distance functions [J]. European Journal of Operational Research, 220(3): 798-809.
[22] PICAZO-TADEO A J, GMEZ-LIMN J A, REIG-MARTNEZ E. 2011.Assessing farming eco-efficiency: A data envelopment analysis approach [J]. Journal of Environmental Management, 92(4): 1154-1164.
[23] SCOTT J. 2013. Social network analysis [M].London: Sage Publication.URDIALES M P, LANSINK A O, WALL A. 2016. Eco-efficiency among dairy farmers: The importance of socio-economic characteristics and farmer attitudes [J]. Environmental and Resource Economics, 64(4): 559-574.
[24] ZHANG X, CHENG X, YUAN J, et al. 2011. Total-factor energy efficiency in developing countries [J]. Energy Policy, 39(2): 644-650. |