
The impact of social supervision on household's sewage discharge behavior: Evidence from Jiangsu province
SU Min, FAN Peng-fei, ZHANG Lan, FENG Shu-yi
JOURNAL OF NATURAL RESOURCES ›› 2023, Vol. 38 ›› Issue (5) : 1349-1365.
The impact of social supervision on household's sewage discharge behavior: Evidence from Jiangsu province
As a means for multiple subjects to participate in rural environmental governance, social supervision can effectively overcome failures of government supervision and regulate farmers' behavior. This study put social supervision in rural social relations and deeply examined the mechanisms of social supervision on regulating households' domestic sewage discharge behavior (HDSDB). By adopting the Binary Probit Model and conducting an empirical analysis based on the sample of 2335 households from 13 prefecture-level cities in Jiangsu province, we found that: (1) Social supervision could reduce HDSDB, but this was mainly due to the river management teams' supervision. (2) Social relations moderated social supervision, mainly reflected in the supervision of village cadres being moderated by the cadre-farmer relations. Village cadres' supervision significantly decreased HDSDB only if the cadre-farmer relations were good. Otherwise, it significantly stimulated HDSDB. (3) It was robust that the river management teams' supervision significantly decreased HDSDB among different farmer groups according to the heterogeneity test. Moreover, for female, low literacy, low income, and elderly farmer groups, social supervision is moderated by farmer-farmer relations and river management team-farmer relations. However, social supervision is moderated by cadre-farmer relations and mutual supervision among rural households for males, high literacy, high income, and young groups.
social supervision / social relations / moderating effect / rural sewage governance performance / households' sewage discharge behavior {{custom_keyword}} /
Table 1 Sample households' domestic sewage discharge behavior表1 样本农户生活污水乱排情况 |
城市 | 农户生活污水 乱排比例/% | 城市 | 农户生活污水 乱排比例/% | 监督类型 | 农户生活污水 乱排比例/% | |
---|---|---|---|---|---|---|
南京市 | 15.248 | 泰州市 | 7.358 | 村民监督 | 有# | 25.668 |
无锡市 | 18.008 | 徐州市 | 50.278 | 无 | 39.634*** | |
常州市 | 25.909 | 连云港市 | 24.444 | 村干部监督 | 有# | 27.273 |
苏州市 | 17.192 | 淮安市 | 43.188 | 无 | 41.236*** | |
镇江市 | 48.696 | 盐城市 | 38.667 | 河道管护保洁队伍监督 | 有# | 22.572 |
南通市 | 34.899 | 宿迁市 | 44.803 | 无 | 37.026*** | |
扬州市 | 30.968 | 整体平均 | 31.399 |
注:#代表参照组,***、**、*分别代表在1%、5%、10%的统计水平上存在显著差异,数据来源于作者所在课题组的调研,下同。 |
Table 2 Definition of variables and descriptive statistics表2 变量说明及描述性统计分析 |
变量名称 | 变量含义和赋值 | 均值 | 标准差 | 预期影响 |
---|---|---|---|---|
农户乱排生活污水行为 | 您家平时是否将厨余或厕所污水等生活污水随意排放至村里的河、沟、池塘等公共水域?0=否,1=是 | 0.314 | 0.464 | \ |
社会监督/社会关系 | ||||
村民监督 | 村民邻里是否对您乱排生活污水进行监督?0=否,1=是 | 0.592 | 0.492 | - |
河道管护保洁队伍监督 | 河道管护保洁员是否对您乱排生活污水进行监督?0=否, 1=是 | 0.748 | 0.434 | - |
村干部监督 | 村干部是否对您乱排生活污水进行监督?0=否,1=是 | 0.706 | 0.456 | - |
村民关系 | 您跟其他村民邻里之间的关系是否和谐融洽?0=否,1=是 | 0.800 | 0.400 | - |
管群关系 | 您跟河道管护保洁员之间的关系是否和谐融洽?0=否,1=是 | 0.796 | 0.403 | - |
干群关系 | 您跟村干部之间的关系是否和谐融洽?0=否,1=是 | 0.583 | 0.493 | - |
农户个体及家庭特征 | ||||
性别 | 受访农户性别:0=女,1=男 | 0.520 | 0.500 | +/- |
年龄 | 受访农户年龄/岁 | 58.664 | 13.508 | + |
受教育年限 | 受访农户接受教育年限/年 | 6.266 | 4.418 | - |
村干部身份 | 受访农户家中是否有村干部?0=否,1=是 | 0.063 | 0.242 | - |
家庭总人口 | 受访农户家庭总人口数量/人 | 4.373 | 1.923 | + |
家庭总收入 | 受访农户家庭年平均总收入/万元 | 6.860 | 6.400 | - |
环境认知特征 | ||||
政策了解度 | 您对乱排生活污水的处罚和监督等政策的了解程度:1=非常不了解,2=比较不了解,3=一般,4=比较了解,5=非常了解 | 2.914 | 1.262 | - |
环保意识 | 您有义务和责任保护农村环境:1=非常不同意,2=比较不同意,3=一般,4=比较同意,5=非常同意 | 4.241 | 0.783 | - |
外部环境特征 | ||||
河道管护保洁队伍人数 | 河道管护保洁队伍的人数/人 | 3.111 | 5.089 | - |
污水管网接通到家 | 污水管网是否接通管道到您家?0=否,1=是 | 0.284 | 0.451 | - |
村庄特征 | ||||
综合示范村 | 是否在2019年农村人居环境整治综合示范村备案上?0=否,1=是 | 0.070 | 0.255 | - |
到乡镇距离 | 根据百度/高德地图定位,村委会到本村所在乡镇街道的距离/km | 5.032 | 3.909 | - |
注:样本户的性别、年龄、文化程度、人均年收入指标均值与根据《江苏统计年鉴2019》[37]数据计算出的结果大致相当,说明样本数据具有一定的代表性。 |
Table 3 Results of benchmark regression表3 基准回归的估计结果 |
变量名称 | 基准回归1 | 基准回归2 | 基准回归3 | 基准回归4 | 基准回归5 | 平均边际效应 (基于基准回归5) | 基准回归6 | 平均边际效应 (基于基准回归6) |
---|---|---|---|---|---|---|---|---|
村民监督 | -0.158* (0.009) | -0.170* (0.088) | -0.162* (0.090) | -0.085 (0.093) | -0.079 (0.092) | -2.281% (0.027) | -0.164 (0.185) | -2.808% (0.032) |
河道管护 保洁队伍 监督 | -0.389*** (0.082) | -0.361*** (0.082) | -0.350*** (0.081) | -0.304*** (0.083) | -0.306*** (0.083) | -8.855%*** (0.238) | -0.521*** (0.156) | -8.941%*** (0.027) |
村干部监督 | -0.027 (0.093) | -0.033 (0.094) | 0.013 (0.094) | 0.034 (0.098) | 0.043 (0.098) | 1.236% (0.028) | 0.351 (0.220) | 6.017% (0.038) |
性别 | — | 0.066 (0.063) | 0.063 (0.064) | 0.055 (0.066) | 0.057 (0.067) | 1.637% (0.019) | 0.038 (0.138) | 0.651% (0.024) |
年龄 | — | 0.001 (0.003) | 0.001 (0.003) | 0.002 (0.003) | 0.001 (0.003) | 0.038% (0.001) | 0.003 (0.006) | 0.056% (0.001) |
受教育年限 | — | -0.023*** (0.009) | -0.020** (0.009) | -0.019** (0.009) | -0.019** (0.009) | -0.561%** (0.003) | -0.009 (0.018) | -0.154% (0.003) |
村干部身份 | — | -0.058 (0.111) | -0.060 (0.111) | -0.023 (0.118) | -0.024 (0.119) | -0.685% (0.034) | -0.051 (0.258) | -0.873% (0.044) |
家庭总人口 | — | 0.021 (0.017) | 0.019 (0.017) | 0.009 (0.018) | 0.010 (0.018) | 0.288% (0.005) | -0.028 (0.034) | -0.466% (0.006) |
家庭总收入 | — | -0.111*** (0.037) | -0.101*** (0.037) | -0.058 (0.040) | -0.058 (0.040) | -0.017% (0.011) | -0.087 (0.077) | -1.497% (0.013) |
政策了解度 | — | — | -0.004 (0.034) | -0.015 (0.032) | -0.013 (0.033) | -0.381% (0.009) | -0.110* (0.060) | -1.892%* (0.010) |
环保意识 | — | — | -0.160*** (0.042) | -0.156*** (0.046) | -0.156*** (0.046) | -4.507%*** (0.013) | -0.287*** (0.107) | -4.931%*** (0.018) |
河道管护保洁队伍人数 | — | — | — | -0.017** (0.008) | -0.017** (0.008) | -0.488%** (0.002) | -0.002 (0.022) | -0.034% (0.004) |
污水管网接通到家 | — | — | — | -0.606*** (0.095) | -0.597*** (0.096) | -17.269%*** (0.027) | — | — |
综合示范村 | — | — | — | — | -0.267** (0.126) | -7.722%** (0.037) | -0.110 (0.167) | -1.880% (0.029) |
到乡镇距离 | — | — | — | — | -0.004 (0.012) | -0.112% (0.003) | -0.003 (0.017) | -0.044% (0.003) |
常数项 | -0.672*** (0.199) | -0.538* (0.282) | 0.073 (0.326) | 0.498 (0.440) | 0.511 (0.443) | — | 1.026 (0.986) | — |
观测值/户 | 2595 | 2580 | 2580 | 2353 | 2353 | 2353 | 785 | 785 |
对数伪似 然函数值 | -1364.375 | -1339.110 | -1330.810 | -1207.690 | -1205.476 | — | -247.990 | — |
Pseudo R2 | 0.087 | 0.098 | 0.103 | 0.127 | 0.128 | — | 0.093 | — |
注:为提高估计的准确性,对家庭总收入取对数。总共调研4010户农户,基准回归1所用样本为2595户(剔除缺失因变量值的21户样本,以及没有河道管护保洁队伍的1394户样本);基准回归2~基准回归3所用样本为2580户(进一步剔除家庭总收入为0,导致家庭总收入无法取对数的15户样本);基准回归4~基准回归5所用样本为2353户(更进一步剔除缺失污水管网接通到家变量值的227户样本);基准回归6所用样本为785户(再进一步剔除污水管网未接通到家的1568户样本);小括号里是村级聚类标准误;所有回归都控制了地级市虚拟变量,因篇幅限制省略其回归结果,若有需要请联系第一作者;下同。 |
Table 4 Results of moderating effects表4 调节效应回归的估计结果 |
变量名称 | 交互项回归1 (全样本) | 交互项回归2 (部分样本) |
---|---|---|
村民监督 | 0.080(0.214) | 0.407(0.460) |
河道管护保洁队伍监督 | -0.163(0.138) | -0.651**(0.294) |
村干部监督 | 0.309**(0.125) | 0.761***(0.270) |
村民关系 | 0.096(0.112) | 0.138(0.279) |
管群关系 | 0.266*(0.136) | 0.070(0.244) |
干群关系 | -0.203(0.130) | 0.154(0.298) |
村民监督 | 0.079(0.154) | -0.469(0.366) |
河道管护保洁队伍监督 | -0.309*(0.158) | 0.038(0.306) |
村干部监督 | -0.250*(0.148) | -0.565*(0.339) |
河道管护保洁队伍监督 | 0.053(0.165) | 0.283(0.327) |
村干部监督 | -0.323*(0.185) | -0.448(0.419) |
控制变量 | 已控制 | 已控制 |
常数项 | 0.137(0.477) | 0.518(1.014) |
观测值/户 | 2353 | 785 |
对数伪似然函数值 | -1185.966 | -243.444 |
Pseudo R2 | 0.142 | 0.110 |
Table 5 Marginal effects and marginal interaction effects of social supervision under different scenarios表5 不同调节情景下社会监督的边际效应及边际交互效应 |
全样本(N=2353) | |||
---|---|---|---|
村干部监督=0 | 村干部监督=1 | 边际交互效应 | |
村民监督=0 | 26.352***[0.028] | 31.038***[0.028] | (26.871-31.729)-(31.038-26.352)= -9.544* |
村民监督=1 | 31.729***[0.047] | 26.871***[0.016] | [0.056] |
河道管护保洁队伍监督=0 | 河道管护保洁队伍监督=1 | 边际交互效应 | |
管群关系=0 | 29.638***[0.034] | 25.877***[0.026] | (24.688-37.979)-(25.877-29.638)= -9.530** |
管群关系=1 | 37.979***[0.034] | 24.688***[0.016] | [0.048] |
村干部监督=0 | 村干部监督=1 | 边际交互效应 | |
干群关系=0 | 33.936***[0.037] | 37.274***[0.027] | (23.554-27.614)-(37.274-33.936)= -7.398* |
干群关系=1 | 27.614***[0.040] | 23.554***[0.018] | [0.046] |
部分样本(污水管网接通到家的农户样本N=785) | |||
村干部监督=0 | 村干部监督=1 | 边际交互效应 | |
干群关系=0 | 9.796**[0.041] | 18.854***[0.041] | (10.442-12.485)-(18.854-9.796)= -11.101* |
干群关系=1 | 12.485*[0.064] | 10.442***[0.017] | [0.068] |
注:第一列表示调节变量在不同情境下的取值情况;第二列和第三列反映了核心解释变量(受到调节的变量)在不同取值情况下,农户发生乱排行为的边际效应;第四列反映的是调节变量 |
Table 6 Heterogeneity analysis of benchmark regression表6 基准回归的分群估计结果 |
变量名称 | 基准回归分 群1(女性) | 基准回归分 群2(男性) | 基准回归分 群3(低文化) | 基准回归 分群4 (高文化) | 基准回归 分群5 (低收入) | 基准回归 分群6 (高收入) | 基准回归分群7(年轻) | 基准回归分群8(老年) |
---|---|---|---|---|---|---|---|---|
村民监督 | -0.308 (0.260) | 0.093 (0.231) | -0.153 (0.491) | -0.819* (0.454) | 0.039 (0.243) | -0.393 (0.287) | -0.160 (0.283) | -0.102 (0.249) |
河道管护 保洁队伍监督 | 0.050 (0.212) | -1.228*** (0.262) | -0.297* (0.183) | -1.285*** (0.479) | -0.550*** (0.210) | -0.598** (0.299) | -0.791*** (0.255) | -0.414* (0.226) |
村干部监督 | 0.635** (0.316) | 0.068 (0.263) | 0.230 (0.230) | 0.795 (0.589) | 0.051 (0.239) | 0.757** (0.361) | 0.424 (0.330) | 0.261 (0.278) |
控制变量 | 已控制 | 已控制 | 已控制 | 已控制 | 已控制 | 已控制 | 已控制 | 已控制 |
常数项 | 0.823 (1.339) | -2.340** (1.060) | 0.766 (1.074) | -3.517* (1.982) | 7.407*** (1.130) | -3.784*** (0.831) | -2.978** (0.944) | 1.515 (1.167) |
观测值/户 | 379 | 406 | 603 | 182 | 368 | 417 | 388 | 397 |
对数伪似然 函数值 | -116.215 | -114.887 | -196.886 | -30.720 | -133.486 | -97.645 | -97.717 | -138.748 |
Pseudo R2 | 0.105 | 0.199 | 0.091 | 0.456 | 0.120 | 0.171 | 0.169 | 0.100 |
注:部分样本(污水管网接通到家的农户样本,N=785)的分群回归结果与全样本(N=2353)的分群回归结果相似,受篇幅限制,此处仅汇报部分样本的分群回归估计结果。若需要全样本的分群回归估计结果,请联系第一作者;下同。 |
Table 7 Heterogeneity analysis of moderating effects表7 调节效应的分群估计结果 |
变量名称 | 交互项回归分群1 (女性) | 交互项回归分群2 (男性) | 交互项回归分群3 (低文化) | 交互项回归分群4 (高文化) | 交互项回归分群5 (低文化) | 交互项回归分群6 (高文化) | 交互项回归分群7 (年轻) | 交互项回归分群8 (老年) |
---|---|---|---|---|---|---|---|---|
村民监督 | 0.948 (0.832) | 0.440 (0. 685) | 0.556 (0.561) | 3.831*** (1.474) | 1.162 (0.719) | 0.396 (0.648) | -0.465 (0.818) | 0.974* (0.549) |
河道管护保洁队 伍监督 | 0.023 (0.371) | -5.396*** (0.426) | -0.341 (0.335) | -2.104* (1.180) | -0.776** (0.352) | -0.305 (0.502) | -0.842 (0.648) | -0.472 (0.360) |
村干部监督 | 1.128*** (0.419) | 0.967** (0.422) | 0.592** (0.292) | 4.663* (1.818) | 0.603 (0.409) | 1.442*** (0.461) | 1.141*** (0.358) | 0.447 (0.409) |
村民关系 | 0.862* (0.442) | -0.522 (0.557) | 0.375 (0.297) | -0.917 (1.184) | 0.243 (0.427) | -0.212 (0.341) | -0.462 (0.412) | 0.324 (0.447) |
管群关系 | -0.326 (0.316) | 0.573 (0.406) | 0.091 (0.295) | -1.275 (1.067) | -0.245 (0.401) | 0.397 (0.375) | 0.990* (0.571) | -0.550 (0.343) |
干群关系 | 0.260 (0.445) | 0.487 (0.477) | 0.061 (0.308) | 7.892*** (2.208) | 0.098 (0.446) | 0.844* (0.465) | 0.187 (0.420) | -0.056 (0.412) |
村民监督 | -1.189** (0.593) | 0.001 (0.624) | -0.734* (0.405) | -0.584 (1.139) | -1.037* (0.625) | -0.295 (0.385) | 0.504 (0.610) | -1.056* (0.573) |
河道管护保洁队伍监督 | 0.281 (0.434) | -0.272 (0.489) | 0.039 (0.361) | 0.776 (1.017) | 0.645 (0.480) | -0.675 (0.468) | -0.783 (0.614) | 0.858** (0.431) |
村干部监督 | -0.677 (0.554) | -1.137** (0.519) | -0.630* (0.360) | -6.874*** (1.996) | -0.858 (0.540) | -0.913 (0.576) | -0.782* (0.451) | -0.334 (0.487) |
河道管护保洁队伍监督 | -0.10 (0.459) | 4.723*** (0.474) | 0.152 (0.392) | 0.676 (1.585) | -0.180 (0.465) | 0.414 (0.521) | 1.105* (0.577) | -0.416 (0.455) |
村干部监督 | -0.306 (0.639) | -0.939 (0.662) | -0.276 (0.467) | -5.627** (2.417) | -0.335 (0.616) | -0.827 (0.693) | -0.824 (0.545) | -0.095 (0.584) |
控制变量 | 已控制 | 已控制 | 已控制 | 已控制 | 已控制 | 已控制 | 已控制 | 已控制 |
常数项 | -0.045 (1.468) | -3.259*** (1.248) | 0.062 (1.152) | -11.373 (3.585) | 7.254 (1.034) | -4.589 (0.998) | -3.370*** (0.969) | 1.166 (1.241) |
观测值/户 | 379 | 406 | 603 | 182 | 368 | 417 | 388 | 397 |
对数伪似然函数值 | -112.638 | -107.163 | -191.245 | -24.095 | -127.041 | -94.571 | -91.178 | -133.357 |
Pseudo R2 | 0.133 | 0.253 | 0.117 | 0.573 | 0.163 | 0.197 | 0.225 | 0.135 |
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21世纪以来,中国乡村社会经济发展与基础设施建设取得明显成效,但城乡发展不平衡、乡村发展不充分的问题仍较突出。特别是与乡村生活密切相关的人居环境仍为乡村发展的短板。2018年初,国家出台了《农村人居环境整治三年行动方案》,以着力改善农村人居环境,建设美丽宜居乡村,助力乡村振兴战略。本文解析了农村人居环境及其整治的概念与内涵,阐释了农村人居环境整治与乡村振兴的相互作用机理,剖析了农村人居环境整治的运行模式,梳理了整治成效的评价方法与结果,并展望了农村人居环境整治研究的重点领域。农村人居环境科学在过去十余年取得了快速发展,在基本理论、演化机理、质量评价、调控策略等方面有明显进展。但是,当前研究对于实践的指导性和支撑性仍存在明显不足,地方具体整治工作仍存在一些认识上或实践上的误区。面向乡村振兴战略需求,新时期的农村人居环境整治在认识和实践方面要形成“八项共识”。在研究层面,应强化乡村地理学与工程技术科学、城乡规划学、管理学、社会学等的交叉与融合,着力形成集理论研究、技术研发、机制剖析、成效评估、模式优化等于一体的系统性研究体系,可更好地支撑农村人居环境整治,实现乡村地域功能显化和价值提升,进而有效助力乡村振兴。
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王成, 代蕊莲, 陈静, 等. 乡村人居环境系统韧性的演变规律及其提升路径: 以国家城乡融合发展试验区重庆西部片区为例. 自然资源学报, 2022, 37(3): 645-661.
以国家城乡融合发展试验区——重庆西部片区为研究区,以2009年、2014年、2019年为研究时点,以2009—2019年为研究时段,按照思想缘起、理论基础、实证演绎、提升路径的研究思路,建立乡村人居环境系统韧性测度的指标体系,分析其演变规律。研究结果表明:2009—2019年,重庆西部片区的乡村人居环境系统韧性水平不断上升,呈现出“南高北低”的空间格局。各子系统韧性在时间上呈现出不同程度的增长趋势,在空间上差异明显:自然系统韧性与人类系统韧性分别呈现出“由南向北递减”和“东西部向中部递减”的空间格局;居住系统韧性与支撑系统韧性则分别呈现出由“低值点缀分布”逐渐过渡到较为均衡和“普遍均衡、高低值点缀”的空间格局;社会系统韧性表现为“西部增强、东部减弱”的空间格局特征。借助障碍度模型对重庆西部片区乡村人居环境系统韧性提升的障碍因子及不同区县面临的主导障碍进行诊断,根据结果将重庆西部片区划分为单一主导障碍型、双重障碍型与三层障碍型三种类型,据此设计乡村人居环境系统韧性提升的差异化路径,以期打破重庆西部片区乡村人居环境系统韧性提升的多重制约。
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This study takes Western Chongqing, a national urban-rural integration development pilot area, as the research area, and 2009-2019 as the research period. Based on the systematic analysis, according to the research ideas of ideological origin, theoretical foundation, empirical research and promotion path, this study constructs an index system to measure the rural human settlements system resilience, analyzes its evolution law, and then uses the obstacle degree model to identify the obstacle factors of rural human settlements system resilience. In order to break the multiple constraints of the resilience of rural human settlements in the western part of Chongqing, the paper designs a path to enhance the resilience. Results show that: From 2009 to 2019, the resilience level of rural human settlements in Western Chongqing shows a rising trend, which is characterized by the spatio-temporal differentiation of decreasing from south to north. The resilience of each subsystem shows different degrees of growth in time and significant differences in space. According to the results of obstacle factor analysis and leading obstacle diagnosis in the study area, the resilience improvement can be divided into three types: single dominant barrier type, double barrier type and triple barrier type. Based on this, the differentiation path of rural human settlements system resilience improvement is designed to promote the construction of livable countryside and boost the overall rural revitalization. It has important demonstration effect. {{custom_citation.content}}
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张童朝, 颜廷武, 张俊飚. 德政何以善治, 村域干群关系如何影响农民参与农业废弃物资源化: 来自四省1372份农户数据的验证. 南京农业大学学报: 社会科学版, 2020, 20(1): 150-160.
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杜焱强, 刘平养, 吴娜伟. 政府和社会资本合作会成为中国农村环境治理的新模式吗: 基于全国若干案例的现实检验. 中国农村经济, 2018, (12): 67-82.
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As an essential stakeholder of environmental resources, the public has become the third force which assists in promoting environmental governance, together with local governments and polluting enterprises. In this paper, we construct a mediation model and a 2SLS (Two Stage Least Square) model to illustrate the role of public participation based on inter-provincial panel data of China from 2011 to 2015. The results indicate that the advantages of handling informational asymmetry and enhancing social supervision are the two logical starting points of involving public participation in environmental governance. As the public has no executive power, they can participate in environmental governance in an indirect way by lobbying local governments’ environmental enforcement of polluting enterprises. In addition, their deterrent of polluting enterprises can also generate effects similar to local governments’ environmental enforcement, and such a deterrent will help promote environmental governance directly. At the present time in China, the effects of public participation in environmental governance are mainly reflected in the form of back-end governance, while the effects of front-end governance are not remarkable enough. This research is of great significance in perfecting China’s environmental governance system by means of arousing and expanding the public’s rights to participate in environmental governance.
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孙前路, 房可欣, 刘天平. 社会规范、 社会监督对农村人居环境整治参与意愿与行为的影响: 基于广义连续比模型的实证分析. 资源科学, 2020, 42(12): 2354-2369.
农户参与农村人居环境整治的意愿与行为是农村环境改善最为直接的动力,也是实现农村生态宜居和生态文明制度改革细则出台的重要依据。为细致探究农户参与农村人居环境整治的意愿与行为,本文基于社会规范和社会监督的视角,利用西藏707户调查数据,运用广义连续比模型,通过对样本数据分组,综合分析了农户人居环境整治参与意愿、行为及意愿与行为一致性的影响因素。结果显示:①农户具有参与农村人居环境整治意愿的占比略超过一半(51.77%),但参与意愿与行为一致性较差;②邻居参与积极性、保洁员监督、村庄人居环境改善能减少疾病传播等因素对农户参与意愿与行为均产生显著的积极影响;③农户的文化程度、村民监督及政府宣传有利于农户参与意愿向参与行为转化。本文的研究结论支持了农村人居环境整治中政府主导、农户参与的整治模式,对推进农村人居环境整治具有一定的政策启示,同时对政府出台农村环境管理政策亦有一定的借鉴意义。
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The willingness and behavior of farming households to participate in the improvement of rural living environment is the most direct driving force for rural environment improvement and an important basis for rural residents to realize the reform of improving rural livability and ecological civilization and the promulgation of detailed methods. To examine the willingness and behavior of farming household participation in rural residential environment improvement, this study comprehensively analyzed the willingness and behavior of farming households and factors that influence the consistency between behavior and intention based on the perspective of social norms and social supervision, using data from a survey of 707 farming households in Tibet and the generalized continuous ratio model. The results show that: (1) Willingness to participate in the improvement of rural living environment was observed in slightly more than half of the surveyed households (51.77%), but the consistency between willingness and behavior is poor; (2) Participation enthusiasm of neighbors, supervision of cleaning workers, and perception that the improvement of village living environment can reduce the spread of diseases have a significant positive impact on the willingness and behavior of farmers to participate; (3) Education level of farmers, peer supervision, and government publicity are conducive to the transformation of farmers’ willingness to participate into action. The conclusion of this study supports the rural living environment improvement model with the government taking the leading role and farmers participating, which has some policy implication for promoting the improvement of rural living environment and reference value for the government to issue rural management policies. {{custom_citation.content}}
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农村生活垃圾治理是全面改善农村人居环境的重要组成部分,农户既是垃圾的产生者也是治理成效的直接受益者。本文根据陕西农村地区的微观调查数据,利用双栏模型(DHM)考察环境关心对农户参与农村生活垃圾治理意愿(参与意愿及支付意愿)的影响;运用层次回归将制度信任对环境关心-农户参与治理意愿关系的调节效应纳入分析。结果表明:环境关心对农户参与意愿及支付意愿均存在显著正效应;制度信任不仅对农户参与意愿及支付意愿存在显著促进作用,而且还对环境关心-农户支付意愿之间的关系存在显著的正向调节效应;制度信任度高的农户,环境关心对其支付意愿的促进作用更强。此外,受教育年限及家庭人口数正向影响农户参与意愿,收入高的家庭参与垃圾治理的支付意愿相对更高。因此,提升农户环境关心意识、规范农户认可的法规制度以及创造良好的制度信任氛围,对于农村生活垃圾治理具有重要推动作用。
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为提高农户参与生活垃圾治理的积极性,提升农村人居环境整治成效,本文基于心理学视角,综合利用计划行为理论和大五人格理论,分析农户参与农村生活垃圾治理的行为机制,并运用结构方程模型、潜在类别分析和多群组结构方程模型,对河北省邯郸市1779户农户样本进行实证分析。结果表明:①态度、主观规范、知觉行为控制和行为意向对农户参与农村生活垃圾治理行为有显著影响。农户对正确投放生活垃圾的评价越积极、越愿意遵从家人和朋友的环保期望、在正确投放时感知到的困难度越低,其正确投放生活垃圾的意向就越高,最终正确的投放行为也越容易实现。②人格特质对农户参与农村生活垃圾治理行为的心理机制具有很强的调节作用,且该调节作用由稳定性人格特质元产生。随和性和责任性能增强主观规范对行为意向的正向影响,但也会削弱知觉行为控制对行为意向的正向影响;神经质能增强主观规范对行为意向的正向影响。据此,在农村生活垃圾治理过程中,建议政府在增加资金投入、优化基础设施空间布局的基础上,更加注重乡风文明建设,并充分考虑农户的人格特质,制定出更多个性化的环境治理方案,引导和激励农户的参与行为。
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Multiplicative interaction models are common in the quantitative political science literature. This is so for good reason. Institutional arguments frequently imply that the relationship between political inputs and outcomes varies depending on the institutional context. Models of strategic interaction typically produce conditional hypotheses as well. Although conditional hypotheses are ubiquitous in political science and multiplicative interaction models have been found to capture their intuition quite well, a survey of the top three political science journals from 1998 to 2002 suggests that the execution of these models is often flawed and inferential errors are common. We believe that considerable progress in our understanding of the political world can occur if scholars follow the simple checklist of dos and don'ts for using multiplicative interaction models presented in this article. Only 10% of the articles in our survey followed the checklist.
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This paper explains why computing the marginal effect of a change in two variables is more complicated in nonlinear models than in linear models. The command inteff computes the correct marginal effect of a change in two interacted variables for a logit or probit model, as well as the correct standard errors. The inteff command graphs the interaction effect and saves the results to allow further investigation.
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