山东省农户秸秆资源化利用绩效评价——基于三阶段DEA模型

doi:10.18402/resci.2021.05.13

摘要/Abstract

摘要：

基于山东省932个农户2018年的秸秆资源化利用投入产出数据,利用三阶段DEA模型对农户秸秆资源化利用绩效进行评价。结果发现：①剔除外界环境和随机干扰的影响前,农户综合效率均值为0.5422,纯技术效率均值为0.7048,规模效率均值为0.7693;剔除外界环境和随机干扰的影响后,农户综合效率均值为0.5075,纯技术效率均值为0.9044,而规模效率均值为0.5611,规模效率下降是引起农户秸秆资源化利用综合效率下降的主要原因。②不同区域之间农户秸秆资源化利用绩效存在一定差异。剔除外界环境和随机干扰的影响前,各地区综合效率排序为德州市>菏泽市>潍坊市>聊城市>济宁市>临沂市;剔除外界环境和随机干扰的影响后,各地区综合效率排序变为菏泽市>德州市>潍坊市>聊城市>临沂市>济宁市。德州市和济宁市农户秸秆资源化利用绩效受外界环境和随机干扰影响较大。③SFA模型回归结果显示,政府的技术培训和资金补贴、专业经济合作组织的指导、农户对秸秆资源化利用方式和技术的认知等因素能显著降低农户的直接生产资料、劳动力和人力资本等投入中的浪费,由此提高农户秸秆资源化利用绩效。总体而言,山东省秸秆主产区农户秸秆资源化利用绩效相对较低,可以通过扩大秸秆利用规模、改善外界环境（如技术培训和资金补贴）等途径来提升绩效。

关键词: 农户, 秸秆资源化利用, 绩效评价, 三阶段DEA模型, 山东省

Abstract:

Based on the straw resource utilization input-output data of 932 farmers in Shandong Province in 2018, this study evaluated the performance of straw resource utilization using three-stage data envelopment analysis (DEA) model. The study found that: (1) Before excluding the influence of external environment and random interference, the mean value of farmers’ comprehensive efficiency was 0.5422, the mean value of pure technical efficiency was 0.7048, and the mean value of scale efficiency was 0.7693. After excluding the influence of external environment and random interference, the mean value of farmers’ comprehensive efficiency was 0.5075, the mean value of pure technical efficiency was 0.9044, while the mean value of scale efficiency was 0.5611. The decrease of scale efficiency is the main reason for the decrease of comprehensive efficiency of farmers’ straw resource utilization. (2) There are some differences in the performance of farmers’ straw resource utilization between different regions. Before excluding the influence of external environment and random interference, the ranking of comprehensive efficiency of each region was Dezhou>Heze>Weifang>Liaocheng>Jining>Linyi. After excluding the influence of external environment and random interference, the ranking of comprehensive efficiency became Heze>Dezhou>Weifang>Liaocheng>Linyi>Jining. The performance of farmers’ straw resource utilization in Dezhou and Jining is more influenced by external environment and random disturbances. (3) The regression results of the stochastic frontier approach (SFA) model show that government technical training and financial subsidies, guidance from professional economic cooperatives, and farmers’ knowledge of straw resource utilization methods and technologies can significantly reduce the waste of farmers’ inputs such as direct production materials, labor, and human capital, and improve farmers’ performance of straw resource utilization. Overall, the performance of farmers’ straw resource utilization in the main straw-producing areas of Shandong Province is relatively low, and it can be improved by expanding the scale of straw utilization and improving the external environment such as technical training and financial subsidies.

Key words: farmers, straw resource utilization, performance evaluation, three-stage DEA model, Shandong Province

李国志. 山东省农户秸秆资源化利用绩效评价——基于三阶段DEA模型[J]. 资源科学, 2021, 43(5): 996-1007.

LI Guozhi. Performance evaluation of farmers’ straw resource utilization in Shandong Province:Based on three-stage DEA model[J]. Resources Science, 2021, 43(5): 996-1007.

图/表 8

表1

表2

表3

表4

表5

表6

第二阶段模型估计结果"

变量	直接生产资料投入松弛		劳动力投入松弛		人力资本投入松弛
变量	系数	标准误	系数	标准误	系数	标准误
常数项	8.4403*	3.2548	4.2930**	2.8695	4.0236**	2.3308
户主年龄	0.2842	0.1634	0.2154	0.1890	-0.3215	0.1672
户主文化程度	-0.6372***	0.4208	-0.3335	0.1702	-1.235**	0.5821
秸秆资源化利用收入占家庭总收入比重	-0.3744*	0.2065	0.6228*	0.4426	0.2852	0.2002
人均农作物种植面积	-1.1525**	0.7506	0.5582*	0.4016	0.7836	0.3124
政府是否提供技术培训和资金补贴	-2.4006**	0.8645	-1.3628**	0.5294	-1.6028***	0.9965
周边交通状况	0.7285	0.5408	-0.8110**	0.5124	0.4962	0.2206
农户是否加入专业经济合作组织	-3.8655***	1.1246	-2.0664**	0.7729	-1.4894***	0.8386
是否了解秸秆相关产品的市场信息	-2.0306**	0.6643	1.2710	0.3608	1.1045*	0.4124
是否了解秸秆资源化利用的主要方式和技术	-2.5885***	1.2204	-1.6944**	0.9854	-3.2025***	1.4286
$σ 2$	1635.46***		1208.22***		985.63***
$γ$	0.9034***		0.8467***		0.8720***
Log likelihood	-489.36		-375.85		-406.77
LR 检验值	44.82***		60.38***		21.75***

表6

表7

表8

参考文献 36

[1]	司开玲. 秸秆焚烧与农村环境危机: 基于“代谢断裂”理论的思考[J]. 中国农业大学学报(社会科学版), 2018, 35(4): 61-68.
	[Si K L. Straw burning and rural environmental crisis: Based on the theory of “metabolic fracture”[J]. Journal of China Agricultural University Social Sciences, 2018, 35(4): 61-68.]
[2]	王士超, 闫志浩, 王瑾瑜, 等. 秸秆还田配施氮肥对稻田土壤活性碳氮动态变化的影响[J]. 中国农业科学, 2020, 53(4): 782-794.
	[Wang S C, Yan Z H, Wang J Y, et al. Nitrogen fertilizer and its combination with straw affect soil labile carbon and nitrogen fractions in paddy fields[J]. Scientia Agricultura Sinica, 2020, 53(4): 782-794.]
[3]	程曼, 解文艳, 杨振兴, 等. 黄土旱塬长期秸秆还田对土壤养分、酶活性及玉米产量的影响[J]. 中国生态农业学报(中英文), 2019, 27(10): 1528-1536.
	[Cheng M, Xie W Y, Yang Z X, et al. Effects of long-term straw return on corn yield, soil nutrient contents and enzyme activities in dryland of the Loess Plateau, China[J]. Chinese Journal of Eco-Agriculture, 2019, 27(10): 1528-1536.]
[4]	文中华, 刘喜雨, 孟军, 等. 生物炭和腐熟秸秆组配基质对水稻幼苗生长的影响[J]. 沈阳农业大学学报, 2020, 51(1): 10-17.
	[Wen Z H, Liu X Y, Meng J, et al. Research on biochar and rotten straw-based matrix on the growth of rice seedlings[J]. Journal of Shenyang Agricultural University, 2020, 51(1): 10-17.]
[5]	俞建良, 熊强, 刘晓峰, 等. 我国秸秆沼气行业发展模式探讨[J]. 中国沼气, 2019, 37(6): 74-79.
	[Yu J L, Xiong Q, Liu X F, et al. Discussion on the development model of straw biogas industry in China[J]. China Biogas, 2019, 37(6): 74-79.]
[6]	许越越, 赵明松, 苏弘扬. 基于MODIS数据的山东省秸秆焚烧遥感监测[J]. 科技创新与生产力, 2018, (7): 33-36.
	[Xu Y Y, Zhao M S, Su H Y. Remote sensing monitoring of straw burning in Shandong Province based on MODIS data[J]. Sci-tech Innovation and Productivity, 2018, (7): 33-36.]
[7]	Jiang D, Zhuang D F, Fu J Y, et al. Bioenergy potential from crop residues in China: Availability and distribution[J]. Renewable and Sustainable Energy Reviews, 2012, 16(3): 1377-1382. doi: 10.1016/j.rser.2011.12.012
[8]	Zhai N N, Mao C L, Feng Y Z, et al. Current status and future potential of energy derived from Chinese agricultural land: A review[J]. BioMed Research International, 2015, DOI: 10.1155/2015/824965. doi: 10.1155/2015/824965
[9]	Isabelle L M S, Terezinha F C, Narie R D S, et al. Electricity production from sugarcane straw recovered through Bale system: Assessment of retrofit projects[J]. BioEnergy Research, 2019, 12(1): 865-877. doi: 10.1007/s12155-019-10014-9
[10]	Dai J, Bean B, Brown B, et al. Harvest index and straw yield of five classes of wheat[J]. Biomass and Bioenergy, 2016, 85(2): 223-227. doi: 10.1016/j.biombioe.2015.12.023
[11]	Edelvy B A, Ralf K S, Osvaldo R R, et al. Life cycle assessment of the valorization of rice straw for energy purposes: Rice production in Cuba[J]. Journal of Agriculture and Environment for International Development, 2018, 112(2): 297-320.
[12]	孙建飞, 郑聚锋, 程琨, 等. 基于可收集的秸秆资源量估算及利用潜力分析[J]. 植物营养与肥料学报, 2018, 24(2): 404-413.
	[Sun J F, Zheng J F, Cheng K, et al. Estimate of collectable straw resources and competitive utilization potential[J]. Journal of Plant Nutrition and Fertilizers, 2018, 24(2): 404-413.]
[13]	丛宏斌, 姚宗路, 赵立欣, 等. 中国农作物秸秆资源分布及其产业体系与利用路径[J]. 农业工程学报, 2019, 35(22): 132-140.
	[Cong H B, Yao Z L, Zhao L X, et al. Distribution of crop straw resources and its industrial system and utilization path in China[J]. Transactions of the Chinese Society of Agricultural Engineering, 2019, 35(22): 132-140.]
[14]	霍丽丽, 赵立欣, 姚宗路, 等. 中国玉米秸秆草谷比及其资源时空分布特征[J]. 农业工程学报, 2020, 36(21): 227-234.
	[Huo L L, Zhao L X, Yao Z L, et al. Difference of the ratio of maize stovers to grain and spatiotemporal variation characteristics of maize stovers in China[J]. Transactions of the Chinese Society of Agricultural Engineering, 2020, 36(21): 227-234.]
[15]	Diep N Q, Fujimoto S, Minowa T, et al. Estimation of the potential of rice straw for ethanol production and the optimum facility size for different regions in Vietnam[J]. Applied Energy, 2012, 93(5): 205-211. doi: 10.1016/j.apenergy.2011.12.074
[16]	曹志宏, 黄艳丽, 郝晋珉. 中国作物秸秆资源利用潜力的多适宜性综合评价[J]. 环境科学研究, 2018, 31(1): 179-186.
	[Cao Z H, Huang Y L, Hao J M. Multi-suitability comprehensive evaluation of crop straw resource utilization in China[J]. Research of Environmental Sciences, 2018, 31(1): 179-186.]
[17]	李芬妮, 张俊飚, 何可. 非正式制度、环境规制对农户绿色生产行为的影响: 基于湖北1105份农户调查数据[J]. 资源科学, 2019, 41(7): 1227-1239.
	[Li F N, Zhang J B, He K. Impact of informal institutions and environmental regulations on farmers’ green production behavior: Based on survey data of 1105 households in Hubei Province[J]. Resources Science, 2019, 41(7): 1227-1239.]
[18]	尚燕, 颜廷武, 江鑫, 等. 公共信任对农户生产行为绿色化转变的影响: 以秸秆资源化利用为例[J]. 中国农业大学学报, 2020, 25(4): 181-191.
	[Shang Y, Yan T W, Jiang X, et al. Influence of public trust on the transformation of green production behavior of farmers: Taking straw resource utilization for example[J]. Journal of China Agricultural University, 2020, 25(4): 181-191.]
[19]	高立, 赵丛雨, 宋宇. 农地承包经营权稳定性对农户秸秆还田行为的影响[J]. 资源科学, 2019, 41(11): 1972-1981.
	[Gao L, Zhao C Y, Song Y. Effect of stability of land contract and land-use rights on straw retention for rural households[J]. Resources Science, 2019, 41(11): 1972-1981.]
[20]	曹慧, 赵凯. 耕地经营规模对农户亲环境行为的影响[J]. 资源科学, 2019, 41(4): 740-752.
	[Cao H, Zhao K. Farmland scale and farmers’ pro-environmental behavior: Verification of the inverted U hypojournal[J]. Resources Science, 2019, 41(4): 740-752.]
[21]	姚科艳, 陈利根, 刘珍珍. 农户禀赋、政策因素及作物类型对秸秆还田技术采纳决策的影响[J]. 农业技术经济, 2018, (12): 64-75.
	[Yao K Y, Chen L G, Liu Z Z. The influence of farmer’s endowment, policy factors and crop types on the adoption decision of straw returning technology[J]. Journal of Agrotechnical Economics, 2018, (12): 64-75.]
[22]	郭清卉, 李世平, 南灵. 环境素养视角下的农户亲环境行为[J]. 资源科学, 2020, 42(5): 856-869.
	[Guo Q H, Li S P, Nan L. Farming households’ pro-environmental behaviors from the perspective of environmental literacy[J]. Resources Science, 2020, 42(5): 856-869.]
[23]	姜维军, 颜廷武. 能力和机会双轮驱动下农户秸秆还田意愿与行为一致性研究: 以湖北省为例[J]. 华中农业大学学报(社会科学版), 2020, (1): 47-55.
	[Jiang W J, Yan T W. Study on the consistency of farmers’ straw returning willingness and behavior under the dual drive of ability and opportunity: A case study of Hubei Province[J]. Journal of Huazhong Agricultural University (Social Sciences Edition), 2020, (1): 47-55.]
[24]	盖豪, 颜廷武, 何可, 等. 基于农户视角的秸秆机械化还田服务绩效评价及其障碍因子诊断: 来自冀、鲁、皖、鄂四省的调查[J]. 长江流域资源与环境, 2018, 27(11): 2597-2608.
	[Gai H, Yan T W, He K, et al. A evaluation of mechanized straw returning service performance and its obstacle indicators based on farmers’ perspective: Based on the investigation of Hebei, Shandong, Anhui and Hubei Provinces in four provinces[J]. Resources and Environment in the Yangtze Basin, 2018, 27(11): 2597-2608.]
[25]	卫斌, 涂维亮. 荆州市农业废弃物资源化利用绩效测度及对策[J]. 长江大学学报(社会科学版), 2019, 42(6): 71-75.
	[Wei B, Tu W L. The performance measurement and countermeasures for the utilization of agricultural waste in Jingzhou[J]. Journal of Yangtze University (Social Sciences Edition), 2019, 42(6): 71-75.]
[26]	丁美. 农作物秸秆资源潜力与开发可持续性评价体系研究: 以江苏省为例[D]. 南京: 南京农业大学, 2011.
	[Ding M. Study on Sustainability Evaluation System for Crop Straw Resource Potential and Development: Jiangsu Province as an Example[D]. Nanjing: Nanjing Agricultural University, 2011.]
[27]	Dal-Mas M, Giarola S, Zamboni A, et al. Strategic design and investment capacity planning of the ethanol supply chain under price uncertainty[J]. Biomass and Bioenergy, 2011, 35(5): 2059-2071. doi: 10.1016/j.biombioe.2011.01.060
[28]	张科研. 江苏省农作物秸秆综合利用技术评价[D]. 南京: 南京农业大学, 2016.
	[Zhang K Y. Technical Evaluation on the Comprehensive Utilization of Straw in Jiangsu[D]. Nanjing Agricultural University, 2016.]
[29]	Cong P, Li Y Y, Wang J, et al. Increasing straw incorporation rates improves subsoil fertility and crop yield in the Huang-Huai-Hai Plain of China[J]. Archives of Agronomy and Soil Science, 2020, 66(14): 1976-1990. doi: 10.1080/03650340.2019.1704735
[30]	Roth M G, Mourtzinis S, Gaska J M, et al. Wheat grain and straw yield, grain quality, and disease benefits associated with increased management intensity[J]. Agronomy Journal, 2020, 113(1): 308-320. doi: 10.1002/agj2.v113.1
[31]	李鹏, 张俊飚, 丁玉梅, 等. 农业生产废弃物循环利用的产业联动绩效及影响因素的实证研究: 以废弃物基质化产业为例[J]. 中国农村经济, 2012, (11): 69-77.
	[Li P, Zhang J B, Ding Y M, et al. An empirical study on industrial linkage performance and impact factors of waste recycling in agricultural production: An example of waste matrix industry[J]. China Rural Economy, 2012, (11): 69-77.]
[32]	李鹏, 张俊飚. 农业生产废弃物循环利用绩效测度的实证研究: 基于三阶段DEA模型的农户基质化管理[J]. 中国环境科学, 2013, 33(4): 754-761.
	[Li P, Zhang J B. Empirical studies of agricultural production waste recycling efficiency: Based on peasant household substrate management with three-stage DEA model[J]. China Environmental Science, 2013, 33(4): 754-761.]
[33]	Fried H O, Lovell C A K, Schmidt S S, et al. Accounting for environment effects and statistical noise in data envelopment analysis[J]. Journal of Productivity Analysis, 2002, 17(1): 157-174. doi: 10.1023/A:1013548723393
[34]	Fuentes R, Fuster B, Lillo-Banuls A. A three-stage DEA model to evaluate learning-teaching technical efficiency: Key performance indicators and contextual variables[J]. Expert Systems With Applications, 2016, 48(4): 89-99. doi: 10.1016/j.eswa.2015.11.022
[35]	罗登跃. 三阶段DEA模型管理无效率估计注记[J]. 统计研究, 2012, 29(4): 104-107.
	[Luo D Y. A note on estimating managerial inefficiency if three-stage DEA model[J]. Statistical Research, 2012, 29(4): 104-107.]
[36]	陈巍巍, 张雷, 马铁虎, 等. 关于三阶段DEA模型的几点研究[J]. 系统工程, 2014, 32(9): 144-149.
	[Chen W W, Zhang L, Ma T H, et al. Research on three-stage DEA model[J]. Systems Engineering, 2014, 32(9): 144-149.]

秸秆种类	草谷比系数	秸秆种类	草谷比系数	秸秆种类	草谷比系数
小麦	1.37	高粱	1.72	油菜	2.51
稻谷	0.95	大豆	1.67	棉花	4.75
谷子	1.45	薯类	0.60	烟叶	1.60
玉米	1.58	花生	1.50	蔬菜及瓜果	0.10

地区	秸秆产量/万t	占比/%	地区	秸秆产量/万t	占比/%	地区	秸秆产量/万t	占比/%
菏泽市	1277	13.80	滨州市	612	6.61	东营市	226	2.45
德州市	1155	12.47	青岛市	586	6.32	淄博市	226	2.44
聊城市	870	9.40	济南市	490	5.29	日照市	171	1.85
潍坊市	813	8.78	泰安市	457	4.93	威海市	145	1.57
济宁市	786	8.49	烟台市	353	3.82
临沂市	773	8.35	枣庄市	318	3.43	全省	9258	100

变量类型	变量名称	变量赋值	最小值	最大值	均值	标准差
产出变量	秸秆资源化利用收入	实际收入/元	3000	180000	28456.35	4133.62
投入变量	直接生产资料投入	实际投入/元	800	85000	11864.40	2348.16
	劳动力投入	实际投入时间/（人·日）	8	1250	233.28	109.45
	人力资本投入	实际接受培训次数/次	1	6	3.112	1.371
环境变量	户主年龄	实际年龄/岁	25	72	45.21	13.24
	户主文化程度	小学及以下=1,初中=2,高中或中专=3,大专及以上=4	1	4	2.232	0.730
	秸秆资源化利用收入占家庭总收入比重	实际比重/%	10	95	35.36	28.77
	人均农作物种植面积	实际面积/亩	1.200	12.450	4.425	2.070
	政府是否提供技术培训和资金补贴	否=1,是=2	1	2	1.812	0.585
	周边交通状况	不方便=1,一般=2,方便=3	1	3	2.405	0.512
	农户是否加入专业经济合作组织	否=1,是=2	1	2	1.664	0.429
	是否了解秸秆相关产品的市场信息	否=1,是=2	1	2	1.340	0.405
	是否了解秸秆资源化利用的主要方式和技术	否=1,是=2	1	2	1.288	0.376

区域	综合效率	纯技术效率	规模效率
平均值	0.5422	0.7048	0.7693
菏泽市	0.5786	0.7245	0.7986
德州市	0.6033	0.7705	0.7830
聊城市	0.5008	0.6437	0.7780
潍坊市	0.5572	0.7254	0.7681
济宁市	0.4814	0.6661	0.7227
临沂市	0.4576	0.6472	0.7070

效率类型	效率值区间	[0, 0.2)	[0.2, 0.4)	[0.4, 0.6)	[0.6, 0.8)	[0.8, 1.0]
综合效率	农户数	84	168	391	224	65
综合效率	比例/%	9.01	18.03	41.95	24.03	6.97
纯技术效率	农户数	29	112	261	401	129
纯技术效率	比例/%	3.11	12.02	28.00	43.03	13.84
规模效率	农户数	18	84	168	438	224
规模效率	比例/%	1.93	9.01	18.03	47.00	24.03