呼吸的成本:房价空间分异视角下城市居民对雾霾污染治理的支付意愿测度
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摘要
雾霾污染的日益加剧给我国经济发展带来诸多负面影响的同时,也使得居民生活的行为决策发生了一定的改变。本文基于成都市19个区县的住宅市场及大气监测数据,以二手住房成交价作为行为决策后果的代理变量,通过将空气质量因素引入特征价格法中,并在考虑了房价空间自相关的基础上,综合运用空间误差模型和空间滞后模型考察了城市居民对雾霾污染改善所愿意作出的边际支付水平。研究结果表明,雾霾污染对居民购买和租赁房屋的价格均有着显著的负面影响。雾霾污染程度下降会引起居民购房和租房的边际支付意愿上升。在控制了反向因果的内生性问题后,上述结论依然稳健。进一步利用空间分位数回归发现,不同消费水平的居民对雾霾污染的支付意愿存在异质性,中高端住宅的消费者相对而言更愿意对环境的改善进行支付。最后,通过准自然实验并采用空间双重差分法还揭示出,媒介宣传教育所激发的居民环境关心意识对隐含在房价中的雾霾治理支付意愿具有积极的引导作用。因此,相关政府部门可根据由雾霾污染改善所带来的住房潜在"升值空间"来初步进行污染治理的收益-成本分析,并通过提高居民环保意识、采用多元化的筹资方式来加强环境治理。
The increasing haze pollution has brought many negative effects to China's economic development,and it has also caused certain changes in the living behavioral decisions of residents. Based on the residential market and atmospheric monitoring data of 19 districts and counties in Chengdu,the second-hand housing transaction price was used as a proxy variable for behavioral decision-making. On the basis of the introduction of air quality factors into the Hedonic feature system and considering the spatial correlation of housing prices,this paper used the spatial error model and the spatial lag model to investigate the level of marginal payment that urban residents were willing to make for the improvement of haze pollution. The results showed that the haze pollution had a significant negative impact on the prices of residents buying and renting houses,and the price of renting houses was more sensitive. The reduction in haze pollution will improve the residents' willingness to payment for purchasing and renting houses. By using spatial quantile regression further,this paper also found that residents of different consumption levels had heterogeneity in their willingness to payment for haze pollution,and consumers in middle and high-end residential houses were more willing to pay for environmental improvement. Finally,through a quasi-experiment and difference-in-difference method,it was also revealed that the awareness of environmental concerns of residents stimulated by media's propaganda and education had a positive guiding effect on the willingness to payment for haze pollution which was implied in housing prices. Therefore,the relevant government departments can carry out the basic revenue-cost analysis of pollution control based on the potential left of housing caused by the improvement of haze pollution,and strengthen environmental governance by improving residents' environmental awareness and adopting diversified financing methods.
The increasing haze pollution has brought many negative effects to China's economic development,and it has also caused certain changes in the living behavioral decisions of residents. Based on the residential market and atmospheric monitoring data of 19 districts and counties in Chengdu,the second-hand housing transaction price was used as a proxy variable for behavioral decision-making. On the basis of the introduction of air quality factors into the Hedonic feature system and considering the spatial correlation of housing prices,this paper used the spatial error model and the spatial lag model to investigate the level of marginal payment that urban residents were willing to make for the improvement of haze pollution. The results showed that the haze pollution had a significant negative impact on the prices of residents buying and renting houses,and the price of renting houses was more sensitive. The reduction in haze pollution will improve the residents' willingness to payment for purchasing and renting houses. By using spatial quantile regression further,this paper also found that residents of different consumption levels had heterogeneity in their willingness to payment for haze pollution,and consumers in middle and high-end residential houses were more willing to pay for environmental improvement. Finally,through a quasi-experiment and difference-in-difference method,it was also revealed that the awareness of environmental concerns of residents stimulated by media's propaganda and education had a positive guiding effect on the willingness to payment for haze pollution which was implied in housing prices. Therefore,the relevant government departments can carry out the basic revenue-cost analysis of pollution control based on the potential left of housing caused by the improvement of haze pollution,and strengthen environmental governance by improving residents' environmental awareness and adopting diversified financing methods.
引文
[1]陈硕,陈婷.空气质量与公共健康:以火电厂二氧化硫排放为例[J].经济研究,2014,(8):158-169.
[2]陈永伟,陈立中.为清洁空气定价:来自中国青岛的经验证据[J].世界经济,2012,(4):140-160.
[3]范巧,Hudson D.一种新的包含可变时间效应的内生时空权重矩阵构建方法[J].数量经济技术经济研究,2018,(1):131-148.
[4]林伯强,蒋竺均.中国二氧化碳的环境库兹涅茨曲线预测及影响因素分析[J].管理世界,2009,(4):27-36.
[5]卢春天,石靖,陈玲.教育对中国城乡居民环境关心的影响——基于媒介使用的多重中介分析[J].社会发展研究,2018,(1):122-137.
[6]李永友.房价上涨的需求驱动和涟漪效应——兼论我国房价问题的应对策略[J].经济学(季刊),2014,13(2):443-464.
[7]苗艳青,陈文晶.空气污染和健康需求:Grossman模型的应用[J].世界经济,2010,(6):140-160.
[8]王兵,聂欣.经济发展的健康成本:污水排放与农村中老年健康[J].金融研究,2016,(3):59-73.
[9]席鹏辉,梁若冰.城市空气质量与环境移民——基于模糊断点模型的经验研究[J].经济科学,2015,37,(4):30-43.
[10]杨继东,章逸然.空气污染的定价:基于幸福感数据的分析[J].世界经济,2014,(12):162-188.
[11]虞义华.空间计量经济学理论及其在中国的实践应用[M].北京:经济科学出版社,2015.
[12]张博,黄璇.中国空气质量的价格评估[J].经济与管理研究,2017,38(10):94-103.
[13]郑君君,刘璨,李诚志.环境污染对中国居民幸福感的影响——基于CGSS的实证分析[J].武汉大学学报(哲学社会科学版),2015,68(4):66-73.
[14]赵晓丽,范春阳,王予希.基于修正人力资本法的北京市空气污染物健康损失评价[J].中国人口:资源与环境,2014,24(3):169-176.
[15]Baltagi,B. H. and Y. Deng. EC3SLS Estimator for a Simultaneous System of Spatial Autoregressive Equations with Random Effects[J]. Econometric Reviews,2015,34(6-10),659-694.
[16]Bayer,P.,N. Keohane,and C. Timmins. Migration and Hedonic Valuation:The Case of Air Quality[J].Journal of Environmental Economics and Management,2009,58(1):1-14.
[17]Brander,L. M. and M. J. Koetse. The Value of Urban Open Space:Meta-Analyses of Contingent Valuation and Hedonic Pricing Results[J]. Journal of Environmental Management,2011,92(10):2763-2773.
[18]Broome,R. A.,N. Fann,T. J. N. Cristina,C. Fulcher,H. Duc,and G. G. Morgan. The Health Benefits of Reducing Air Pollution in Sydney,Australia[J]. Environmental Research,2015,143:19-25.
[19]Chay,K. Y. and M. Greenstone. Does Air Quality Matter? Evidence from the Housing Market[J]. Journal of Political Economy,2005,113(2):376-424.
[20]Chernozhukov,V. and C. Hansen. Instrumental Variable Quantile Regression:A Robust Inference Approach[J]. Journal of Econometrics,2008,142(1):379-398.
[21]Cu1ado,J. and F. P. De Gracia. Environment and Happiness:New Evidence for Spain[J]. Social Indicators Research,2013,112(3):549-567.
[22]Ferreira,S.,A. Akay,F. Brereton,J. Cu1ado,P. Martinsson,M. Moro,and T. F. Ningal. Life Satisfaction and Air Quality in Europe[J]. Ecological Economics,2013,88:1-10.
[23]Grossman,M. On the Concept of Health Capital and the Demand for Health[J]. Journal of Political Economy,1972,80(2):223-255.
[24]Inglehart,R. Modernization and Postmodernization:Cultural,Economic,and Political Change in 43Societies[M]. USA:Princeton University Press,1997.
[25]Jones,R. E. and R. E. Dunlap. The Social Bases of Environmental Concern:Have They Changed over Time?[J]. Rural Sociology,1992,57(1):28-47.
[26]Kelejian,H. H. and I. R. Prucha. Estimation of simultaneous systems of spatially interrelated cross sectional equations[J]. Journal of Econometrics,2004,118(1):27-50.
[27]Kneese,A. V. and B. T. Bower. Environmental Quality Analysis:Theory&Method in the Social Sciences[M]. USA:Routledge,2011.
[28]Koubi,V.,G. Spilker,L. Schaffer,and T. B9hmelt. The Role of Environmental Perceptions in Migration Decision-Making:Evidence from both Migrants and Non-migrants in Five Developing Countries[J]. Population&Environment,2016,38(2):1-30.
[29]Kuminoff,N.,C. F. Parmeter,and J. C. Pope. Which Hedonic Models Can We Trust to Recover the Marginal Willingness to Pay for Environmental Amenities?[J]. Journal of Environmental Economics and Management,2010,60(3):145-160.
[30]Levinson,A. Valuing Public Goods Using Happiness Data:The Case of Air Quality[J]. Journal of Public Economics,2012,96(9-10):869-880.
[31]Li,Z.,H. Folmer,and J. Xue. To What Extent does Air Pollution Affect Happiness? The Case of the Jinchuan Mining Area,China[J]. Ecological Economics,2014,99(23):88-99.
[32]Luechinger,S. Valuing Air Quality Using the Life Satisfaction Approach[J]. Economic Journal,2009,119(536):482-515.
[33]Morelli,X.,C. Rieux,J. Cyrys,B. Forsberg,and R. Slama. Air Pollution,Health and Social Deprivation:A Fine-scale Risk Assessment[J]. Environmental Research,2016,147:59-70.
[34]Pleasant,A.,M. M. Scanlon,and M. Pereira-Leon. Literature Review:Environmental Design and Research on the Human Health Effects of Open Spaces in Urban Areas[J]. Human Ecology Review,2013,20(1):36-49.
[35]Rosen,S. Hedonic Prices and Implicit Markets:Product Differentiation in Pure Competition[J]. Journal of Political Economy,1974,82(1):34-55.
[36]Samuelson,P. A. Diagrammatic Exposition of a Theory of Public Expenditure[J]. Review of Economics&Statistics,1955,37(4):350-356.
[37]Sinha,P. and M. Cropper. The Value of Climate Amenities:Evidence from US Migration Decisions[R]. 2013.
[38]Smith,V. K. and J. C. Huang. Can Markets Value Air Quality? A Meta-analysis of Hedonic Property Value Models[J]. Journal of Political Economy,1995,103(1):209-227.
[39]Su,L. and Z. Yang. Instrumental Variable Quantile Estimation of Spatial Autoregressive Models[R]. 2007.
[40]Suki,N. M. Green Awareness Effects on Consumers'Purchasing Decision:Some Insights from Malaysia[J]. International Journal of Asia-Pacific Studies,2013,9(2):49-63.
[41]Urban,J. and M. Scasny. Exploring Domestic Energy-Saving:The Role of Environmental Concern and Background Variables[J]. Energy Policy,2012,47:69-80.
(1)参见《欧盟商会称成都空气质量糟糕》,2016-4-14,搜狐网:http://www.sohu.com/a/69308435_320137。
(1)若采用以往文献通常使用的单套住房数据进行研究,则容易受到当年交易楼盘位置的限制,如本文样本中,青羊区和锦江区的二手房交易量要明显高于其他各区县,样本量分布的严重不均往往会导致估计结果产生偏差。此外,基于单套住房层面的估计也会给本文空间权重矩阵带来超出能力范围的庞大运算量。故综合考虑,本文最终使用的是社区层面的平均住房交易数据。
(2)AQI综合考虑了六种雾霾污染物的污染水平,包括:二氧化硫(SO2)、二氧化氮(NO2)、一氧化氮(NO)、臭氧(O3)、可吸入颗粒物(PM10)和细颗粒物(PM2.5)。相比于过往文献大多采用的API,AQI纳入了更多的监测指标特别是PM2.5,且分级标准也相对更严,所得到的评价结果会更为准确及客观。
(1)不同于张博和黄璇(2017),本文选择成都市这一特定地区展开研究,可以有效避免如地区间的土地城镇化为房屋提供持续稳定的供给等干扰情况,且在近些年成都楼市去库存的背景下,社区住房的供给量基本持平,因此可认为供需均衡和市场出清的条件均能得到满足,HPM具备较强的适用性。
(1)与雾霾污染变量的处理类似,本文基于成都市气象局公布的各区县降水量数据,同样采用反距离权重插值法测算了住宅社区层面的降水量大小。
(1)限于篇幅,本文此处仅汇报了房屋售价的联立方程组估计结果。
(1)本文时空权重矩阵的计算公式可表达为:W=W'Θ',其中W'为经过标准化的空间权重矩阵,采用邻接距离进行设定;Θ’为时间权重矩阵,依据准自然实验发生前后房屋售价Global Moran’s I指数的行列比值计算而得。限于篇幅,推导过程未予列示,具体可参见范巧和Hudson(2018)。
(1)由于本文所采用的为两期混合截面数据,故无法进行平行趋势检验。但本文所选取的时间范围为事件的前后各一年,一定程度上可以尽可能地实现外界环境其他条件的接近性。
[2]陈永伟,陈立中.为清洁空气定价:来自中国青岛的经验证据[J].世界经济,2012,(4):140-160.
[3]范巧,Hudson D.一种新的包含可变时间效应的内生时空权重矩阵构建方法[J].数量经济技术经济研究,2018,(1):131-148.
[4]林伯强,蒋竺均.中国二氧化碳的环境库兹涅茨曲线预测及影响因素分析[J].管理世界,2009,(4):27-36.
[5]卢春天,石靖,陈玲.教育对中国城乡居民环境关心的影响——基于媒介使用的多重中介分析[J].社会发展研究,2018,(1):122-137.
[6]李永友.房价上涨的需求驱动和涟漪效应——兼论我国房价问题的应对策略[J].经济学(季刊),2014,13(2):443-464.
[7]苗艳青,陈文晶.空气污染和健康需求:Grossman模型的应用[J].世界经济,2010,(6):140-160.
[8]王兵,聂欣.经济发展的健康成本:污水排放与农村中老年健康[J].金融研究,2016,(3):59-73.
[9]席鹏辉,梁若冰.城市空气质量与环境移民——基于模糊断点模型的经验研究[J].经济科学,2015,37,(4):30-43.
[10]杨继东,章逸然.空气污染的定价:基于幸福感数据的分析[J].世界经济,2014,(12):162-188.
[11]虞义华.空间计量经济学理论及其在中国的实践应用[M].北京:经济科学出版社,2015.
[12]张博,黄璇.中国空气质量的价格评估[J].经济与管理研究,2017,38(10):94-103.
[13]郑君君,刘璨,李诚志.环境污染对中国居民幸福感的影响——基于CGSS的实证分析[J].武汉大学学报(哲学社会科学版),2015,68(4):66-73.
[14]赵晓丽,范春阳,王予希.基于修正人力资本法的北京市空气污染物健康损失评价[J].中国人口:资源与环境,2014,24(3):169-176.
[15]Baltagi,B. H. and Y. Deng. EC3SLS Estimator for a Simultaneous System of Spatial Autoregressive Equations with Random Effects[J]. Econometric Reviews,2015,34(6-10),659-694.
[16]Bayer,P.,N. Keohane,and C. Timmins. Migration and Hedonic Valuation:The Case of Air Quality[J].Journal of Environmental Economics and Management,2009,58(1):1-14.
[17]Brander,L. M. and M. J. Koetse. The Value of Urban Open Space:Meta-Analyses of Contingent Valuation and Hedonic Pricing Results[J]. Journal of Environmental Management,2011,92(10):2763-2773.
[18]Broome,R. A.,N. Fann,T. J. N. Cristina,C. Fulcher,H. Duc,and G. G. Morgan. The Health Benefits of Reducing Air Pollution in Sydney,Australia[J]. Environmental Research,2015,143:19-25.
[19]Chay,K. Y. and M. Greenstone. Does Air Quality Matter? Evidence from the Housing Market[J]. Journal of Political Economy,2005,113(2):376-424.
[20]Chernozhukov,V. and C. Hansen. Instrumental Variable Quantile Regression:A Robust Inference Approach[J]. Journal of Econometrics,2008,142(1):379-398.
[21]Cu1ado,J. and F. P. De Gracia. Environment and Happiness:New Evidence for Spain[J]. Social Indicators Research,2013,112(3):549-567.
[22]Ferreira,S.,A. Akay,F. Brereton,J. Cu1ado,P. Martinsson,M. Moro,and T. F. Ningal. Life Satisfaction and Air Quality in Europe[J]. Ecological Economics,2013,88:1-10.
[23]Grossman,M. On the Concept of Health Capital and the Demand for Health[J]. Journal of Political Economy,1972,80(2):223-255.
[24]Inglehart,R. Modernization and Postmodernization:Cultural,Economic,and Political Change in 43Societies[M]. USA:Princeton University Press,1997.
[25]Jones,R. E. and R. E. Dunlap. The Social Bases of Environmental Concern:Have They Changed over Time?[J]. Rural Sociology,1992,57(1):28-47.
[26]Kelejian,H. H. and I. R. Prucha. Estimation of simultaneous systems of spatially interrelated cross sectional equations[J]. Journal of Econometrics,2004,118(1):27-50.
[27]Kneese,A. V. and B. T. Bower. Environmental Quality Analysis:Theory&Method in the Social Sciences[M]. USA:Routledge,2011.
[28]Koubi,V.,G. Spilker,L. Schaffer,and T. B9hmelt. The Role of Environmental Perceptions in Migration Decision-Making:Evidence from both Migrants and Non-migrants in Five Developing Countries[J]. Population&Environment,2016,38(2):1-30.
[29]Kuminoff,N.,C. F. Parmeter,and J. C. Pope. Which Hedonic Models Can We Trust to Recover the Marginal Willingness to Pay for Environmental Amenities?[J]. Journal of Environmental Economics and Management,2010,60(3):145-160.
[30]Levinson,A. Valuing Public Goods Using Happiness Data:The Case of Air Quality[J]. Journal of Public Economics,2012,96(9-10):869-880.
[31]Li,Z.,H. Folmer,and J. Xue. To What Extent does Air Pollution Affect Happiness? The Case of the Jinchuan Mining Area,China[J]. Ecological Economics,2014,99(23):88-99.
[32]Luechinger,S. Valuing Air Quality Using the Life Satisfaction Approach[J]. Economic Journal,2009,119(536):482-515.
[33]Morelli,X.,C. Rieux,J. Cyrys,B. Forsberg,and R. Slama. Air Pollution,Health and Social Deprivation:A Fine-scale Risk Assessment[J]. Environmental Research,2016,147:59-70.
[34]Pleasant,A.,M. M. Scanlon,and M. Pereira-Leon. Literature Review:Environmental Design and Research on the Human Health Effects of Open Spaces in Urban Areas[J]. Human Ecology Review,2013,20(1):36-49.
[35]Rosen,S. Hedonic Prices and Implicit Markets:Product Differentiation in Pure Competition[J]. Journal of Political Economy,1974,82(1):34-55.
[36]Samuelson,P. A. Diagrammatic Exposition of a Theory of Public Expenditure[J]. Review of Economics&Statistics,1955,37(4):350-356.
[37]Sinha,P. and M. Cropper. The Value of Climate Amenities:Evidence from US Migration Decisions[R]. 2013.
[38]Smith,V. K. and J. C. Huang. Can Markets Value Air Quality? A Meta-analysis of Hedonic Property Value Models[J]. Journal of Political Economy,1995,103(1):209-227.
[39]Su,L. and Z. Yang. Instrumental Variable Quantile Estimation of Spatial Autoregressive Models[R]. 2007.
[40]Suki,N. M. Green Awareness Effects on Consumers'Purchasing Decision:Some Insights from Malaysia[J]. International Journal of Asia-Pacific Studies,2013,9(2):49-63.
[41]Urban,J. and M. Scasny. Exploring Domestic Energy-Saving:The Role of Environmental Concern and Background Variables[J]. Energy Policy,2012,47:69-80.
(1)参见《欧盟商会称成都空气质量糟糕》,2016-4-14,搜狐网:http://www.sohu.com/a/69308435_320137。
(1)若采用以往文献通常使用的单套住房数据进行研究,则容易受到当年交易楼盘位置的限制,如本文样本中,青羊区和锦江区的二手房交易量要明显高于其他各区县,样本量分布的严重不均往往会导致估计结果产生偏差。此外,基于单套住房层面的估计也会给本文空间权重矩阵带来超出能力范围的庞大运算量。故综合考虑,本文最终使用的是社区层面的平均住房交易数据。
(2)AQI综合考虑了六种雾霾污染物的污染水平,包括:二氧化硫(SO2)、二氧化氮(NO2)、一氧化氮(NO)、臭氧(O3)、可吸入颗粒物(PM10)和细颗粒物(PM2.5)。相比于过往文献大多采用的API,AQI纳入了更多的监测指标特别是PM2.5,且分级标准也相对更严,所得到的评价结果会更为准确及客观。
(1)不同于张博和黄璇(2017),本文选择成都市这一特定地区展开研究,可以有效避免如地区间的土地城镇化为房屋提供持续稳定的供给等干扰情况,且在近些年成都楼市去库存的背景下,社区住房的供给量基本持平,因此可认为供需均衡和市场出清的条件均能得到满足,HPM具备较强的适用性。
(1)与雾霾污染变量的处理类似,本文基于成都市气象局公布的各区县降水量数据,同样采用反距离权重插值法测算了住宅社区层面的降水量大小。
(1)限于篇幅,本文此处仅汇报了房屋售价的联立方程组估计结果。
(1)本文时空权重矩阵的计算公式可表达为:W=W'Θ',其中W'为经过标准化的空间权重矩阵,采用邻接距离进行设定;Θ’为时间权重矩阵,依据准自然实验发生前后房屋售价Global Moran’s I指数的行列比值计算而得。限于篇幅,推导过程未予列示,具体可参见范巧和Hudson(2018)。
(1)由于本文所采用的为两期混合截面数据,故无法进行平行趋势检验。但本文所选取的时间范围为事件的前后各一年,一定程度上可以尽可能地实现外界环境其他条件的接近性。