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居民幸福感的城际差异及其影响因素探析——基于多尺度模型的研究
党云晓1,, 张文忠2,3,, 谌丽4, 湛东升2,3
1. 浙江财经大学土地与城乡发展研究院,杭州 310018
2. 中国科学院地理科学与资源研究所,区域可持续发展分析与模拟重点实验室,北京 100101
3. 中国科学院大学,北京 1000493
4. 北京联合大学应用文理学院,北京 100191

作者简介:党云晓(1987- ),女,河南济源人,博士,研究方向为居住环境与居民生活质量。E-mail:xiaoxiao187@126.com

张文忠(1966- ),男,内蒙古呼和浩特人,博士,研究员,研究方向为城市和区域发展。E-mail:zhangwz@igsnrr.ac.cn
摘要

居民幸福感是建设和谐社会与检验城镇化质量的重要内容。地理学视角的研究围绕幸福感空间差异展开,解读背景环境特征与其关系。国内已有研究缺乏基于个体与城市尺度的联合分析,且缺少城市特征对幸福感影响机制的综合考虑。以环渤海地区44个城市为例,基于大规模调研问卷,采用多尺度建模方法,分析居民幸福感的城际差异及影响因素。结果表明,居民幸福感在城市之间存在显著差异;经济最发达的城市居民幸福感最低;城市规模对居民幸福感有负面影响,收入可以缓解城市规模负面影响的程度;环境污染对居民幸福感有显著的负面影响,积极的环境评价对居民幸福感有正面影响;良好的社会治安与人文环境对居民幸福感影响为正。

关键词: 幸福感; 城际差异; 多尺度模型; 环渤海地区;
Inter-city difference and influencing factors of residents' subjective well-being: A study based on multilevel modelling
DANG Yunxiao1,, ZHANG Wenzhong2,3,, CHEN Li4, ZHAN Dongsheng2,3
1. College of Land and Urban-rural Development, Zhejiang University of Finance and Economics, Hangzhou 310018, China
2. Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
3. China University of Chinese Academy of Sciences, Beijing 100039, China
4. College of Applied Arts and Science, Beijing Union University, Beijing 100191, China
Abstract

During the last three decades, China has been marked by a remarkable economic growth, however, the greatly enriched material life did not promise Chinese an equal level of happiness. It has been proved that Chinese subjective well-being has been decreasing during the progress of high-speed urbanization. Scholars in Western world have conducted abundant research in influencing factors of residents' subjective well-being and evaluation of happy city. There is lack of studies aimed at Chinese residents, especially the systematic analysis of the influence by geographical background effect posed on the residents' subjective well-being. Taking all the prefecture-level cities in the Bohai Rim area as a case study, based on large sample survey questionnaires, objective statistics and census data, this paper analyzed the spatial distribution of subjective well-being at inter-city scale. Happiness function improved by multilevel modeling and GIS-based spatial analysis method are also applied to analyze the influencing factors of residents' subjective well-being. The conclusions are as follows: (1) There is significant disparity of residents' subjective well-being between cities. Most of the cities with more happy samples are in Liaoning province, while those with more unhappy samples are found in the majority of cities in Hebei province except Zhangjiakou and Chengde. (2) Urban scale and economic development are negatively related to residents' subjective well-being. People living in the biggest city are most unhappy with life, however, the high income can weaken the unhappiness. (3) Environment pollution has reduced the residents' subjective well-being, while positive evaluation of natural environment is helpful to improve residents' happiness. (4) Social security and human environment are positively related to the subjective well-being. The widening wealth inequality and urban diseases, such as pollution, traffic jam and housing shortage, should be responsible for the lowest degree of subjective well-being of residents living in the biggest cities. Even so, people are more likely to live in big cities. One possible reason is that the individual may be willing to trade off the subjective well-being for other things including high income, social status and accomplishments. Furthermore, individuals may prefer to take actions enabling to achieve the long-term desires and goals, although some of them could make them less happier at present.

Keyword: subjective well-being; spatial difference; multilevel modelling; Bohai rim area;
1 引言

幸福感是居民对其生活质量的整体认知与评价[1]。过去三十年,中国经历了高速的城镇化发展阶段,城市规模迅速扩张,经济发展水平快速提升,目前,中国城镇化率已超过50%。然而,居民的幸福感并没有在这个过程中提升,反而出现下降的趋势[2]。民众幸福感是检验城镇化质量的重要内容,也是建设和谐社会与实现“中国梦”的重要目标。探索如何提高居民幸福感具有重要的政策启示,因此,研究城市居民幸福感的影响因素有重要含义。

幸福感是国际前沿研究的热点话题,经济学、社会学、管理学等学科分别从各自的学科视角探讨了影响幸福感的客观因素。地理学对幸福感的研究侧重从空间视角揭示居民幸福水平的空间差异和区域不平衡性,回答背景环境特征与居民幸福感的关系。国外地理学对居民幸福感的研究已有一定积累,包括两个方面:一是在一定地理尺度单元下,采用客观数据[3]或者主观数据[4]对城市、地区或国家的整体幸福水平进行评价并比较。二是探讨不同尺度的地理背景因素对个体幸福感的影响。这些影响因素大致可以分为三类,首先是自然环境的舒适性和健康性,例如,Mackerron对自然环境与幸福感的关系进行研究发现,人们处在绿色或者自然环境中时往往比处在城市环境中更加幸福[5]。Symth的研究发现,环境健康性表现在人类生产和生活活动对环境的破坏,以牺牲环境为代价的人类活动降低了居住环境品质,甚至危及居民的身体健康,对居民的幸福感评价产生不利的影响[6]。其次是城市化水平,对这个因素的研究没有形成一致的结论。有些研究指出在经济发达、规模大、人口密度高的大都市区生活的居民幸福感更低[7,8]。有学者质疑,提出国家的经济发展有助于个体幸福感的提升[9]。Veenhoven认为,在不同尺度和时间序列上研究经济发展与幸福感的关系,往往会发现不一致的结论[10]。第三类影响因素是社会人文环境,该类因素引起的生活环境差异表现在城市对历史文化的传承、特色文化氛围、社会包容性和居民的文化素质上,引起居民对城市的人文环境、社会支持以及归属感的主观评价有所不同[11]。Aslam证明了欧洲国家的个体幸福感更依赖于个体所在区域的非经济属性特征与因素,例如社会信任度、社会凝聚力等[12]。此外,福利制度、公共设施投资等背景因素也被证明与幸福感有密切的联系[13,14]

国内学者的研究同样围绕城市幸福感评价和居民幸福感影响因素展开[15,16,17]。已有研究多数是基于个体层级的分析,对幸福感影响因素的研究集中于收入、城市规模、环境污染等因素。其中,城市规模与幸福感关系的研究中,有些学者主张“正U型”理论,认为居民幸福感先随城市规模扩大而下降,达到最不利城市规模后,幸福感随城市规模扩大而提升[18]。还有些学者主导“倒U型”理论,认为幸福感先随人口规模扩大而上升,达到20万~50万的最优规模时最高,此后幸福感随人口总量增大而下降,这一现象在发展中国家或地区尤为显著[19,20]。此外,也有研究认为居民幸福感与城市规模之间并不存在直接的线性或非线性关系,若将居民幸福感作为约束因子,则不同路径取得的最优城市规模大约在500万~780万人之间[21]。国内学者对环境污染与幸福感关系的研究结论与国外一致,环境污染会降低居民幸福感[22]

中国城市经历的高速城镇化极大地改变了原有城市。这种变化表现在各个方面,尤其是城市规模急速扩张、经济高速发展,而且伴随着城市环境恶化、原有的社会结构调整,以及缓慢变化的社会人文环境。从文献阅读可知,对中国城市居民幸福感的研究侧重于评价、比较不同城市的居民幸福感差距,以及分析单项城市特征对幸福感的影响,缺乏影响居民幸福感的城市因素的综合分析,尤其是缺少社会人文环境对居民幸福感的影响。此外,已有研究尺度通常基于城市或者个体单个层级,忽略考量城市因素对个体影响研究的数据结构的嵌套性,由此引起变量(特别是高层级变量)回归系数显著性的检验失效[23]。本文期望在以下两个内容对已有研究进行补充:一是综合量化城市规模与经济、自然环境、社会人文环境对居民幸福感的影响,特别是城市规模的影响;二是使用多尺度模型改进居民幸福感影响机制研究,同时从个体和城市两个尺度进行联合分析。除此以外,国内已有的研究对影响居民幸福感的背景因素往往使用客观指标,国外的研究已证明个体对客观环境的主观评价在更大程度上影响其幸福感,考虑到主观感受与客观现实之间不一定完全匹配,在选取城市层级的影响因素中,本文同时使用客观指标和主观指标。

本文以环渤海地区44个城市为例,基于大规模调研问卷,同时结合客观统计数据与人口普查数据,分析居民幸福感的城际差异,使用多尺度模型分析中国高速城镇化背景下,城市规模与经济、自然环境、社会人文等因素对居民幸福感的影响,重点检验快速扩张的城市规模对居民幸福感的影响。通过研究,本文期望实现以下目标:回答当前影响居民幸福感的主要城市因素,为提高居民幸福提供政策建议。

2 研究方法与数据来源
2.1 研究区概况

中国国土面积辽阔,境内自然景观、人文环境差别明显,可以预期到全国尺度居民幸福感的明显差别。然而由于研究时间和精力有限,本文选择环渤海地区的地级市为案例,主要是基于两个方面的考虑:① 环渤海地区是中国近30年来城市化发展最快的地区之一,可以说这个地区是中国城市化地区的一个缩影,研究该区域居民幸福感的城际差异及影响因素在全国范围内具有一定的代表性。② 环渤海地区城市类型丰富多样,既有北京这样的一线城市,也有二线、三线、四线城市,城市因自然本底条件、社会经济发展水平、人文环境和区域功能定位各异,有利于本文研究居民幸福感在城市之间差异的形成机制。此外,本文之所以选择空间上连片的城市化地区,主要是为了控制气候、风俗等因素的影响,重点观察城市规模与经济等因素对居民幸福感的影响。

2.2 数据来源

影响居民幸福感的城市因素大致分为城市化水平、自然环境舒适性和健康性、社会人文环境等。本文将影响居民幸福感城际差异的因素分为规模与经济指标、环境指标、社会人文指标三类。规模与经济指标选取城市GDP、总人口、人口密度、在岗职工平均工资四个变量,环境指标选取全年灰霾暴露天数、工业废水排放量、环境舒适性评价、环境健康性评价四个变量,社会人文指标选取社会治安评价、失业率、人文环境舒适度评价三个变量。客观变量主要来自城市统计年鉴,主观变量来自问卷调研。本研究使用的主观数据来源:① 2014年10-11月在环渤海三省(河北、山东、辽宁)一市(天津)地区实施的问卷调研,按照直辖市300份、省会和副省级城市250份、其他城市根据人口规模大小各200或150份的标准发放问卷,共发放问卷7500份,回收有效问卷6965份。② 2013年7-8月在北京主城六区及五个远郊居住区执行的问卷调研,共发放问卷7000份,回收有效问卷5733份。两次调研的问卷设置一致。为了与其他43个城市的问卷调研样本量达到数量相当的目的,采用SPSS中的数据抽取方法,从北京市的调研问卷中随机抽取209份(环渤海43个城市回收的问卷中,删除无效问卷以及没有填写本文考察的核心指标的问卷,每个城市剩余的参与模型运算的样本分布为82份~208份不等,因此本文从北京的所有有效问卷中随机抽取209份。对209份问卷的单独分析,以及并入整个环渤海的样本的整体分析,均显示人口结构合理。),并入环渤海的整体调研问卷中。通过对调查主体的性别、年龄、城市分布等特征进行分析,表明样本符合控制要求,合格问卷的数量和分布结构满足抽样设计和研究要求。

参考国外幸福感的数据采集经验[24],问卷中直接询问居民,“目前这种生活状态您觉得——非常幸福/幸福/一般/不幸福/很不幸福”。问卷调研还同时搜集了个体的属性信息,例如年龄、收入、户籍属性等。对个体属性特征及城市特征的统计如表1所示。

表1 环渤海地区城市特征及问卷调研样本属性统计 Tab.1 Statistics of city attributes and research samples in Bohai Rim Area
2.3 研究方法

居民幸福感主要受两类因素的影响,个体层面的居民属性特征和地理空间层面的背景因素。虽然本文主要研究背景因素对居民幸福感的影响,但个体属性特征的影响也不能忽视,需要控制个体属性的影响。因此,本文的数据涉及个体和城市两个层级,需要同时从个体和城市两个尺度进行分析。要处理单层以上的数据结构,需要使用多尺度的分析模型,因此本文选取多尺度线性模型作为基础模型。此外,问卷中对幸福感的测度结果为有序分类的李克特量表氏变量,如果转化为普通的连续变量,不仅会导致信息丢失,而且容易引起换算失调。考虑到本研究的主要目的是检验变量对幸福感是否有显著的影响,即关注个体幸福与否,因此这里对因变量的处理采取二分类变量赋值法,其中对选项为非常幸福及幸福赋予1,其他选项赋予0。这样的赋值将问题简化为概率计算,最适用于这种情况的模型是二元分类响应变量的概率模型[25]。综上,本文使用的模型设定如下:

Res p jk ~Binomial ( 1 , π jk ) (1)

probit π jk = β 0 Con s jk + i = 1 i β i x ijk + p = 1 p β p x pk + v k (2)

v k ~N 0 , Ω v : Ω v = σ v 2 (3)

式中:二元分类响应变量 Res p jk 表示在城市的居民的生活幸福感,居民选择幸福的概率分布服从;表示所有预测变量为0时居民选择幸福的估计概率;表示城市层级的残差,服从均值为0;方差为的正态分布; β i x ijk 为第个个体层级变量的固定效应,用于检验个体属性特征效应; β p x pk 为第个城市层级变量的固定效应,用于检验城市特征效应。需要说明的是,在多尺度二元分类响应变量的概率模型中,个体层级服从方差为1的概率分布[26],因此,城市层级的方差分解占比VPC应该为/( σ v 2 + 1 ),该数值也被称为组内相关系数ρ或者方差分解系数,用于衡量组间差异对因变量的解释能力[23]

本文模型均采用MLwinN 2.32软件进行估计,估计算法采用马尔科夫链蒙特卡洛模拟的贝叶斯估计方法(MCMC)。对MCMC的设定为抽取10000个模型估计结果,舍去前5000个结果,最终的模型参数汇总均基于这之后的5000个结果。本文采用DIC(Deviance Information Criterion)这一指标比较不同模型的拟合效果。DIC作为一个综合指标,既考虑到不同模型对数据的拟合程度又能考虑到模型的复杂程度。DIC值越小表明模型对数据的拟合程度越高,一般来说,如果DIC值差别大于10则表明两个模型见有显著的差异[27]

3 环渤海地区城市居民幸福感差异及影响因素分析
3.1 居民幸福感的城际差异

构建多尺度模型的空模型(不引入任何个体与城市层级的变量),计算所有样本分别在城市与个体层级的幸福感差异。空模型的方差估计结果显示,居民幸福感在城市与个体层级的方差分别为0.101和1,其中城市层级方差占比(VPC)为9.2%,说明城市之间的幸福感差异可以解释所有样本幸福感差异的9.2%。一般认为,如果高层级的方差占比高于5.9%,说明高层级的差异不可以忽略,需要采用多尺度模型的分析方法[28]

图1显示了每个城市调研样本中选择幸福和非常幸福的样本占比,以此反映城市的居民幸福感总水平。辽阳、东营、锦州是居民幸福感水平最高的城市,保定、天津、北京是居民幸福感水平最低的城市。整体分布上,辽宁省城市的居民幸福感水平较高,河北省居民的幸福感水平普遍偏低。

图1 环渤海地区城市居民幸福水平空间差异 Fig. 1 Spatial disparity of residents' subjective well-being in Bohai Rim Area

3.2 居民幸福感城际差异的影响因素分析

3.2.1 规模与经济指标 根据已有研究中对个体属性特征的分析,将样本的年龄、性别、收入、户籍、婚姻状况、就业状况等个体层级变量作为控制变量引入模型,由于本文重点关注城市层级变量对居民幸福感的影响,这里对个体变量不作解释。对城市层级变量之间的相关性进行检验,考虑到本文选择的反应城市规模与经济的四个变量之间存在显著且较强的相关性,因此将每个变量依次引入以避免共线性问题,反应城市自然环境与社会人文环境的模型设定同理。表2显示了城市规模与经济指标对居民幸福感的影响,模型回归结果表明,与居住在GDP大于2000亿元城市的居民相比,居住在其他GDP相对小城市的居民其幸福感更高,其中,GDP为1000亿~2000亿元城市的居民幸福感最高。可见,城市经济发展水平对居民幸福有非线性的影响,最高的经济发展水平并没有对应最高的居民幸福感。城市总人口数对居民幸福感的影响呈线性,居住在人口总量小于100万人城市的居民幸福感最高,而居住在人口总量大于500万人城市的居民幸福感最低,可见,城市人口规模对居民幸福感的影响为负。经济发展水平最高的城市与人口规模最大的城市其居民幸福感最低,这解释了图1中,北京与天津这样的超大城市居民的幸福感比较低的原因。城市人口密度对居民幸福感的影响为负,但是并没有通过显著性检验。

值得注意的是,个体属性变量中,家庭月总收入对居民幸福感有显著的正向作用,收入越高居民的幸福感越高。但是从城市的职工平均工资对居民幸福感的影响来看,城市工资水平越高,居民的幸福感反而越低。这与“伊斯特林悖论”类似[29],不过本文的研究尺度不是国家而是城市,即在一个城市内,富人的幸福水平整体高于穷人,但如果进行城市之间的比较,收入水平高的城市居民其幸福感反而低于收入水平低的城市居民,可能的原因是在平均工资高的城市,相对收入差距更大,由此造成的收入不平等降低了居民的幸福感[30]

3.2.2 自然环境指标 表3显示了城市自然环境指标对居民幸福感影响的模型估计结果。客观指标中,灰霾暴露天数对幸福感有非常显著的负面影响,城市年灰霾暴露天数越多,居民的生活越不幸福。工业废水排放量对居民幸福感的影响为负,但是并没有通过显著性检验。可见,客观的环境污染不利于居民幸福感的提升。这解释了图1中,河北省以工业为主的城市(例如保定、衡水)居民幸福感偏低的原因。主观指标中,城市自然环境舒适度与环境健康性的满意度评价均对居民幸福感有显著的正向影响,表明居民对所在城市的自然环境满意度越高时,也更倾向于对生活状态作出更积极的综合评价。

表2 城市规模与经济指标的多尺度模型回归结果 Tab.2 Multilevel model results of city size and economic development
表3 自然环境指标的多尺度模型回归结果 Tab.3 Multilevel model results of natural environment

比较引入四个变量的城市层级方差,两个引入主观指标的城市层级方差(环境舒适度模型0.083、环境健康性模型0.077)明显小于引入客观指标的城市层级方差(灰霾暴露模型0.096、工业废水模型0.106)。由于城市层级的方差表示控制模型引入的变量后,城市层级的居民幸福感差异水平,因此,城市层级方差越小,表明引入的城市层级变量所解释的居民幸福感差异越多,即主观的环境指标相比客观指标更有助于解释城市之间的居民幸福感差异。

3.2.3 社会人文环境指标 表4显示了社会人文环境指标对居民幸福感影响的模型估计结果。主观指标中,居民对社会治安的评价与幸福感有显著的正向关系,说明居民对社会治安状况越满意其幸福感也越高。居民对社会人文环境的满意度越高其幸福感也更高。这解释了图1中,一些社会治安和社会人文环境评价较低的城市(例如保定、泰安、衡水)居民幸福感偏低的原因。反映社会人文环境的客观指标失业率对居民幸福感的影响没有通过显著性检验。良好的社会环境对城市高品质的生活环境起到正面的作用,有利于居民对城市社会、经济发展形成积极向上的评价,也会提升居民的幸福感。

表4 社会人文环境指标的多尺度模型回归结果 Tab.4 Multilevel model results of human environment
表5 城市人口规模敏感性检验的多尺度模型回归结果 Tab.5 Multilevel model results of sensitivity test of population size

3.2.4 城市规模影响的敏感性分析 上述结果表明,城市规模对居民幸福感有显著的负面影响,本节将通过改变变量设定检验城市规模影响的敏感性。模型设定时,城市人口规模作为主要解释变量引入,个体层级变量作为控制变量引入,自然环境与社会人文环境作为城市层级控制变量引入。上文已提到,每类城市层级指标中所选择的变量分别存在显著的相关性,为避免共线性,反应城市自然环境与社会人文环境的变量各取一个表征该类城市特征。此处选取变量的依据是:在单独检验时该变量对居民幸福感的影响通过显著性检验(自然环境指标包括灰霾暴露、环境舒适度评价、环境健康性评价,社会人文环境指标包括社会治安评价、社会人文环境评价);该变量在同类变量中对居民幸福感差异的解释最强,即城市层级方差最小(若该变量在同类变量中对居民幸福感差异的解释最强,意味着该模型的拟合优度最高,即DIC优于其他模型。对比模型I至模型XI发现,引入环境健康性评价和社会人文环境评价的模型DIC比其他模型更小。)

表5中,模型XII引入反映城市规模、环境、社会人文情况的指标,同时控制除家庭收入以外的其他个体层级变量,模型XIII在此基础上引入家庭收入。首先,比较模型II与模型XIII可以发现,即使控制了城市的环境与社会人文指标,城市人口规模依然对居民幸福感有显著的负面影响,然而影响有所减弱。例如,人口规模大于500万人的城市系数从-0.373减弱为-0.250,人口规模为200万~500万人的城市系数从-0.255减弱为-0.176,人口最多的城市的负面影响减弱程度最大。

其次,比较模型XII与模型XIII可以看出,控制收入并没有改变城市人口规模与居民幸福感之间的直接关系,仅仅是减弱了人口规模负面影响的程度。例如,人口规模大于500万人的城市系数从-0.259减弱为-0.250。可见,虽然生活在人口最多的城市的居民其幸福感相对较低,但是收入高可以缓解这类城市带来的部分负面影响。

4 结论与讨论
4.1 结论

基于大规模调研问卷数据,采用多尺度建模方法,分析居民幸福感的城际差异及其影响因素,主要得到以下结论:环渤海地区居民幸福感在城市之间存在显著差异,辽宁省城市居民幸福感较高,河北省城市居民幸福感偏低;城市经济发展水平对居民幸福的影响呈非线性,经济发展水平最高的城市其居民幸福感最低;城市人口规模对居民幸福感的负面影响呈线性,居住在人口总量大于500万人城市的居民幸福感最低;城市职工平均工资对居民幸福感的影响为负,证明了城际尺度的伊斯特林悖论;城市客观的环境污染对居民幸福感有显著的负面影响,积极的环境舒适度和环境健康性评价对居民幸福感有显著的正面影响;社会治安与人文环境满意度对居民幸福感影响为正。城市规模影响的敏感性分析表明,城市人口规模对居民幸福感有比较稳健的负面影响,而控制个体的家庭收入减弱了人口规模负面影响的程度。

4.2 讨论

居住在经济更发达且城市化水平更高的大城市,对居民而言,既有益处也有弊端。本文的研究结果与西方发达国家的同类研究结果一致,在规模最大、经济最发达的大城市居住的居民其幸福感最低[8]。然而,中国人口流动依然呈现出向大城市集中的特征。这是因为个体所追求的效用并不等同于幸福感,个体可能为了某种效用,例如丰富的消费品、快速的资本积累、社会地位、个人成就等,而愿意生活在幸福感比较低的大城市,个体为了获取这种效用而牺牲当前的幸福感[31]。当然,这些效用也可能作用于个体幸福感,但是作用较弱,例如,本文的研究结果证明,收入能够缓解大城市的部分负面影响。

在大城市生活的居民之所以幸福感最低,可能的原因有两个,一是人口激增带来的交通拥堵、环境污染、住房紧张等“大城市病”,降低了城市的居住品质;二是大城市持续拉大的财富差距加深了社会不公平,甚至于导致阶层隔离而威胁社会稳定,这种财富差距在一定程度上“剥夺”了个体的幸福感。然而,本文未能回答大城市居民不幸福的根本原因,未来应当加深对此的研究,这也将有助于制定更加有效的提高居民幸福感的政策。虽然本文证明了大城市居民的幸福感更低,然而关于如何提高居民幸福感,政策指向应当瞄准如何扬大城市生活之长而避大城市生活之短,即采取措施增加大城市为居民带来的财富与人力资本累积等效用,同时降低在大城市生活的弊端,通过这些手段来提高居民幸福感,而不仅仅是约束城市规模和经济发展水平。

本文还发现,与客观指标相比,居民对实体环境的主观评价更有助于解释城市之间的居民幸福感差异。然而,本文并没有回答实体环境如何作用于个体认知,进而作用于幸福感,这将是未来研究的深化方向。

此外,由于本文选取的案例城市在空间上连成一片,因此城市的气候、风俗等区别并不明显,而这对居民幸福感也可能有重要的影响。如果从全国视角来看,必然需要综合考虑更多背景环境的影响,未来的研究需要进一步对此完善。

The authors have declared that no competing interests exist.

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We consider the economic and non-economic determinants of well-being across Europe and ask what level of geographical aggregation (for example, individual, regional or national) matters for individual well-being and whether the drivers of well-being differ within and between these different levels. Our results show a more heterogenous set of drivers for individual well-being across regions in Europe than previously described. Not only are individual-level effects significant, but so too are regional factors. In particular, absolute regional factors dominate the effect of an individual's position relative to their region for certain non-economic variables. The significance of these non-economic factors changes depending on the sample of countries considered, but in each case the regional effects dominate for those variables that are significant.
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Social scientists in the comparative policy tradition have long argued that welfare systems in modern capitalist societies can be broken down into ideal types. The idea of different worlds of welfare capitalism has an enduring appeal and growing practical policy relevance as governments seek to enhance population wellbeing. In this paper, we explore the worlds of welfare theory from the perspective of happiness. Drawing on data from theWorld Values Survey, we examine how welfare regimes may contribute to wellbeing and we consider the significance of our findings for the development of social policy. By using multilevel models, it is possible to separate out effects due to observed and unobserved, as well as both individual-level and country-level, welfare state characteristics and we can make inferences to the distribution of social wellbeing across welfare typologies. We find that respondents living in liberal and conservative countries experience at least twice the odds of unhappiness of those living in social democracies, after controlling for individual- and country-level explanatory variables. The observed differences between the worlds of welfare were found to be highly statistically significant.
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The Beijing government has made massive investments in rail transit construction since the 2000s. While existing studies provide marginal values for rail access in the real estate market, little is known about homeowners0964 happiness evaluation of such public investment. Using large-scale micro survey data, this paper estimates, in a difference-in-difference framework, the effects on homeowners0964 happiness about public commuting and other residential realms of a transport improvement that altered the residence09“station distance for some households, whilst leaving others unaffected. The estimation accounts for the endogeneity between the residential location choice and transport choice by using non-market (fang gai) housing with pre-determined residential location. It is found that better rail access not only provides sizeable happiness about public commuting to Beijing homeowners, but also affects their happiness in other residential realms. This finding adds to the evidence that public investment has an important role to play in influencing homeowners0964 living experience.
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本文对幸福感的客观影响因素相关研究进行回顾和总结,在分析世界民众主观幸福感概况的基础上,分析中国民众主观幸福感的情况及其在世界的位置,并进行解释。总体上,调查范围内的世界各国民众处于比较幸福的状态,且多数国家民众主观幸福感在上升,幸福感分布具有一定区域差异并与经济水平等存在一定的关系。中国民众主观幸福感处于世界中等偏上水平,衡量的影响因素中人均收入和政府治理水平处于低水平,就业率在世界中处于比较高的水平。1990年到2007年的调查中中国民众幸福感有所下降,本文以相对剥夺理论解释中国人均收入在低生活水平条件下显著增长但是幸福感却下降的现象,此外,失业率增高,政府治理水平放慢也影响中国民众幸福感的提升。未来中国应提升民众收入的同时注重社会公平、促进就业和提升政府治理质量来促进民众的幸福感的提升。
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Although Durkheim, Simmel, and other early social theorists posited causal links between urban life and individual despair or distrust, most contemporary analyses of subjective well-being attribute variations primarily to individual characteristics. However, China-檚 recent warp-speed urbanization requires a more dynamic and multi-level analysis that simultaneously models individual and geographic attributes. Using a representative survey conducted in 2011 of adults living in urban China, we find that, while age, marital status, and household wealth have an impact on life satisfaction, the characteristics of the surrounding county or city district, the size of the city, as well as the route by which an individual became an urban resident, often have an independent impact. Our results indicate that after controlling for individual socio-demographic characteristics, health status, and household wealth, the new urbanites (rural-to-urban migrants and in situ urbanized rural residents) who settle in cities with urban populations between 200,000 and 500,000 are more satisfied with their lives than those who settle in either larger or smaller cities. We argue that in China, where urban centers vary greatly in size, research on individual life satisfaction should factor in the characteristics of the urban location and the means by which individuals become urban residents. Our work suggests a new research and policy direction for small cities undergoing urbanization and their future trends.
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构建了以人口计的城市规模对居民幸福感的影响机制模型,采用问卷调查数据与官方统计年鉴数据汇总而成的2011年截面数据,对具有代表性的130个样本城市的居民幸福感与城市规模的关系进行了定量分析,进而计算出了幸福框架下的最优城市规模。结果显示:将每一个城市的数据都排列出来,城市规模与居民幸福感之间并不存在直接的线性关系或倒U型关系;若将城市规模按大小分为5个组别,并加入人均收入、政府财政支出、图书拥有量、教育机会和交通状况这5个反映生活质量的中间变量,则能够帮助建立相应路径中城市规模与居民主观幸福感两者之间的倒U型关系;在中国目前的条件下,将居民幸福感作为约束因子,不同路径取得的最优城市规模大约在500万-780万人之间。
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This paper presents a structural equation model of happiness, as influenced by inter alia perceived risk due to (i) intensity of exposure to polluted air, and (ii) hazard of pollutants. In addition, objective risk measured as proximity to the pollution source, is considered. The main finding is that both types of perceived risk negatively and significantly influence people's happiness, although in absolute terms, the total perceived risk effect is less than the (positive) effect of ability, measured by income and education. Other important determinants of happiness are family size, age, proximity to the pollution source, work environment and current health condition. Perceived risk due to intensity of exposure is influenced by environmental knowledge and proximity to the pollution source; perceived risk of hazard by ability, environmental knowledge, family size, family health experience and proximity to the pollution source. Environmental knowledge is found to be a function of age, ability and work environment. On the basis of the findings, we conclude that reducing air pollution is an important policy measure to ameliorate happiness. As environmental knowledge is an important determinant of perceived risk, reduction policies should be accompanied by disclosure of the state of air quality.
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