人口城市化滞后对生态效率的影响外文文献

The impact of population urbanization lag on eco effi ciency A panel quantile approach Yang Zhou a Ying Konga b Hankun Wangc Fangyong Luod aShenzhen Environmental Science and New Energy Technology Engineering Laboratory Tsinghua Berkeley Shenzhen Institute Shenzhen 518055 China bDepartment of Economics York University 4700 Keele Street Toronto Canada M3J 1P3 cInstitute for Hospital Management Tsinghua University Shenzhen 518000 China dSchool of Commerce and Economics Southwest University Chongqing 400715 China a r t i c l e i n f o Article history Received 31 July 2019 Received in revised form 27 September 2019 Accepted 29 September 2019 Available online 3 October 2019 Handling editor Almeida Keywords Population urbanization lag Urbanization Eco effi ciency Panel quantile regression a b s t r a c t China s urban built up areas have developed fast along with land urbanization growing rapidly How ever the population of urban agglomeration has not increased simultaneously and urbanization speed of population is much smaller compared to land expansion This study exploits super slack based measure to evaluate eco effi ciency for 47 cities in the Bohai Rim from year 2005e2015 A population urbanization lag index is synthesized and the ordinary least squares and generalized methods of moments estimation approaches are adopted to explore the relationship between eco effi ciency and urbanization with special concentration on the population urbanization lag Furthermore a panel quantile approach is conducted to interpret the impact of urbanization and population urbanization lag on eco effi ciency in different quantiles This study shows that per capita GDP and foreign direct investment have positive effects on eco effi ciency while industry structure urbanization and population urbanization lag have negative infl uences on eco effi ciency 2019 Elsevier Ltd All rights reserved 1 Introduction Since the reform and opening up China s economy has experi enced 40 years of rapid growth but this has coincided with a rapid decline in China s environmental quality China s Environment Performance Index score is 50 74 points ranking 120 out of 180 economies in the world EPI 2018 revealing the negative effect of rapid economic growth on the environment As a major center of China s regional economic development Bohai Rim has abundant natural resources and is well connected by land and sea to trade channels connecting Korea Japan and other regions in China Dadabaev and Timur 2017 This region is home to many in dustries including the steel petroleum and chemical industry with extensive energy development that is characterized as high resource input high environmental cost and low economic output These industries have contributed to a signifi cant environmental burden and severe ecological problems serving as a bottleneck for social and economic sustainable development Thus it is urgent for authorities to boost ecological development in the Bohai Rim Urbanization in China has obtained tremendous achievements Yang et al 2019 and is much higher in its speed and scale than those of other countries during the same period Longwu Liang 2019 From 1978 to 2018 the number of permanent residents in urban areas have increased from 170 million to 830 million The population urbanization rate has risen from 17 92 to 59 58 with an increase of 41 66 China National Bureau of Statistics Ur banization is an undoubtedly important driving force for China s economic development Liang and Yang 2019 but it has spawned a series of environmental pollution issues such as excessive amount of carbon emissions Ali et al 2019 PM2 5 concentrations Du et al 2019 and wastewater pollution Nget al 2014 and so forth which cause a series of ecological crises placing great pressures on China s resources and environment Moreover China s land urbanization has been growing rapidly but the population of urban agglomer ation has not increased simultaneously and population urbaniza tion speed is much smaller compared to land expansion Tian and Wang 2019 So China faces the unbalanced development of land urbanization and population urbanization which leads to a string of challenges such as low land utilization rate traffi c congestion Corresponding author Shenzhen Environmental Science and New Energy TechnologyEngineeringLaboratory Tsinghua BerkeleyShenzhenInstitute Shenzhen 518055 PR China E mail address kongying Y Kong Contents lists available at ScienceDirect Journal of Cleaner Production journal homepage https doi org 10 1016 j jclepro 2019 118664 0959 6526 2019 Elsevier Ltd All rights reserved Journal of Cleaner Production 244 2020 118664 haze weather and so on In order to solve the above problems Chinese government has proposed new urbanization construction strategy and green economy strategy to ensure environmental and economic sustainability Song et al 2018 It is of great signifi cance to integrate the principles of ecological civilization into the whole process of urbanization and economic development The innovations of this paper are mainly refl ected in the following three aspects Firstly population urbanization lag index is synthesized based on city level data to ensure the accuracy and reliability of empirical analysis Secondly this study is one of the few existing papers linking population urbanization lag and eco effi ciency and innovatively talks about the impact of population urbanization lag on eco effi ciency Thirdly a panel quantile regression model is conducted to explore the relationship between eco effi ciency and population urbanization lag at the arbitrary quantile of the eco effi ciency level providing scientifi c empirical support to the new urbanization construction strategy and green economy strategy Thispaper is organized as follows Second 2 provides a literature review Section 3 talks about methods and data Section 4 provides research results and discussions Section 5 draws conclusions and proposes corresponding policy recommendations 2 Literature review The term eco effi ciency was fi rst proposed by German scholars Schalitegger and Strum 1990 and promoted by the World Busi ness Council for Sustainable Development WBCSD Eco effi ciency refers to the value of products and services based on unit envi ronmental pressure or cost Seppala et al 2005 and refl ects the ability of an enterprise an industry or an economy to acquire products and services with lower environmental costs and natural consumption Eco effi ciency links environmental factors to eco nomic production suggesting the intrinsic coupling of economic development and environmental protection as well as the impor tance of sustainable development and green economy at all stages of economic production Many methods have been developed to evaluate eco effi ciency for diversifi ed research objects including single ratio indicator system and models The single ratio method uses the ratio of economic output to environmental pollution to measure eco effi ciency Vogtl ander et al 2002 The single ratio method is easy to calculate and suitable for discrete and independent targets but most integrate all environmental impacts into a single envi ronmental index which is diffi cult to accomplish in reality The indicator system method measures the eco effi ciency of a target through evaluations of a set of related indicators This approach incorporatessociety economic environment andotherdi mensions making it more appropriate for the analysis of more complex researchobjects Many studies haveused the index system method to measure the eco effi ciency of industries Yang and Yang 2019 Wackernagel et al 1999 However this method is somewhat subjective since the weights for variables in the system must be set objectively Quariguasi Frota Neto et al 2009 Compared with these two methods the model method ignores advanced as sumptions Moutinho et al 2018 and avoids the need to assign weights for multi input and multi output problems Data envel opment analysis DEA Charnes et al 1978 is one of the most common model method and many papers have applied DEA to measure input output effi ciency within environmental constraints Yu et al 2018 G omez et al 2018 Data envelopment ana lysis DEA explores tools such as convex analysis and linear pro gramming to measure the relative effi ciency of multi input and multi output problems DEA mainly includes classic constant returns to scale CCR model Charnes et al 1978 and the variable returns to scale BCC model Cooper 1984 Through radial mea surement the value of effi ciency can be improved by an increase or decrease in input or output ratio of DMUs But these methods have to follow the same proportion of DMU input or output improve ment which cannot maximize the improvement of effi ciency values Tone 2001 proposed a non radial Slacks Based Measure SBM method to evaluate the effi ciency of DMUs Compared to the original radial DEA SBM model includes the slack variable in the measurement In terms of driving forces infl uencing eco effi ciency studies have shown that economy industrial structure government regu lation technologicalprogress managementlevel resource endowment market openness and population are all play signifi cant roles in eco effi ciency Yu et al 2019 Zhu et al 2019 Li et al 2013 showed that fi scal decentralization and technological advancement generally have positive effects on eco effi ciency Zhang et al 2016 showed per capita GDP industrial structure innovation government regulation and population density can signifi cantly improve eco effi ciency while energy intensity signif icantly reduces eco effi ciency using tobit regressions Based on the data of the western Taiwan straits Zhu et al 2019 found that energy intensity and technology expenditure had negative impacts on eco effi ciency while economic development and population density had positive effects Urbanization has boost China s eco nomic development Liang and Yang 2019 but spawned a series of environmental pollution issues Yanget al 2019 Ali et al 2019 Du et al 2019 Ng et al 2014 Zhao et al 2018 found there is an N shaped curve relationship between land use eco effi ciency and urbanization However there is few papers concentrating on the impact mechanism of urbanization on eco effi ciency Based on the existing literature this study believes that ur banization can affect eco effi ciency from three dimensions eco nomic growth Br ckner 2012 Moomaw and Shatter 1996 energy consumption Zheng and Walsh 2019 and environmental pollution He et al 2017 Jaeger et al 2010 Li et al 2017 Longwu Liang 2019 Scholars have studied the impact of urbanization rate on per capita GDP based on panel data at the national or city level Zheng and Walsh 2019 confi rmed there exists a U shaped relationship between urbanization and economic growth While urbanization promotes economic growth it raises the problem of extensive energy consumption Sodri and Garniwa 2016 pointed out urbanization accelerates energy consumption in transportation sector and promoted carbon emissions investigating data of 266 cities in China from year 2000e2010 Yang et al 2017 examined the heterogeneity of the effects of urbanization on energy con sumption and found urbanization causes a signifi cant increase in energy consumption while considering diversifi ed levels of ur banization Some scholars have demonstrated there is nonlinearly relationship between urbanization and environment pollution Fan et al 2019 used the experiences of Vietnam to explain that ur banization and economic development give rise to environmental degradation and concludes urbanization leads the urban popula tion to exceed its optimal scale and poses a serious threat to the ecological environment Henderson 2003 Song et al 2018 had proved that urbanization can bring economic growth while also produce industrial wastes Longwu Liang 2019 showed an inver ted U shaped relationship between urbanization and carbon emissions usinga paneldatafor 141 countriesfrom year 1961e2011 Therefore clarifying the impact of urbanization and urbanization lag on eco effi ciency has important practical signifi cance for realizing the effective balance among economy energy consumption and environment Most of the existing studies on urbanization only focus on population urbanization or land urbanization but this is not comprehensive The current urbanization in China is highlighted by Y Zhou et al Journal of Cleaner Production 244 2020 1186642 the uncoordinated development of population urbanization and land urbanization Lichtenberg and Ding 2009 The land urbani zation is obviously faster than population urbanization and this phenomenon is referred to as population urbanization lag Tian and Wang 2019 Population urbanization lag creates problems such as idle urban land or crowded central urban areas and relates to unreasonable resource consumption which has an indispensable impact on eco effi ciency However existing studies rarely involve the impact of population urbanization lag on economic output This study focuses on the impact of urbanization and population urbanization lag on eco effi ciency Using super slacked based measure this study measures the ecological conditions for 47 cities in Bohai Rim By constructing population urbanization lag index this study talks about the role of population urbanization lag in the evolution of eco effi ciency To ensure the conclusions are robust ness this study exploits ordinary least squares OLS and General ized Methods of Moments GMM to discuss the impact of urbanization populationurbanizationlagon eco effi ciency Furthermore panel quantile regressions are adopted to analyze the relationship between eco effi ciency and population urbaniza tion lag at the arbitrary quantile of the eco effi ciency level 3 Methods and data 3 1 Super slack based measure with undesirable outputs This study employs a non radial Slacks Based Measure SBM considering the undesired output Tone 2003 to evaluate eco effi ciency Assume there are n DMUs each with m kinds of in puts defi ned as xi i 1 2 m q1kinds of expected output defi ned as yr r 1 2 q1 and q2kinds of unexpected output defi ned as yt t 1 2 q2 then x yd yudare elements in the corresponding input matrix desired output matrices and unde sired output matrices EE is the object function to measure eco effi ciency using SBM approach The formulas for SBM model with undesired outputs are as follows minEE 1 1 m Pm i 1 s i xi0 1 1 q1 q2 Pq1 r 1 sdr yd r0 Pq2 t 1 sud t yud t0 1 Subject to Xl s i x0 Ydl sd yd 0 Yudl sud yud 0 l s sd sud 0 X x1 x2 xn 2Rm n Yd h yd 1 y d 2 y d n i 2Rq1 n Yud h yud 1 yud 2 yud n i 2Rq2 n Where sdrefers to the lack of desirable outputs s and sudare related to the extravagant amount of inputs and bad outputs The subscript o corresponds to the DMU that is being measured The range for EE is from 0 to 1 For value less than 1 there exists po tential improvements for the DMU To further distinguish the effective DMUs Tone 2002 put forward the super effi ciency SBM model considering undesirable outputs Based on the super SBM model this paper includes undesirable outputs into super SBM model Given effi cient DMUk xk yk d ykud and a production possibility set f x y x Pn j 1 jskxijlj y Pn j 1 jskyrjljg x y is the projected value of the evaluated DMUk in the SBM super effi ciency model and is the point closest to the leading edge made by other DMUs minEEsup 1 m Pm i 1 xi xik 1 q1 q2 Pq1 r 1 yd r yd rk Pq2 t 1 yud t yud tk 2 Subject to X n j 1 jsk xijlj xi X n j 1 jsk yd rjlj yd r X n j 1 jsk ytjlj yud t x xkand yd yd k and yud yud k l s yd r y ud r 0 i 1 2 m r 1 2 q j 1 2 n jsk Where EEsup is the super effi ciency and its largest value is able to be more than 1 Including the merits of SBM with undesirable outputs models super SBM with undesirable outputs models can effectively evaluate the effi cient DMUs Therefore we exploit this approach to measure eco effi ciency in our paper For n DMUs at p periods this study treats the amount of n p DMUs together in evaluation 3 2 Variable selections and data source 3 2 1 Data for eco effi ciency Table 1 shows the indicator system used in super SBM model to evaluate eco effi ciency This indicator system is based on the literature summarized in Table A1 Labor resources and capital investment are considered as inputs and uses industrial built up areas electricityconsumption andwaterconsumptionare considered as resource input indicators and the perpetual in ventory method was used to compute the capital stock The for mula is Kt Kt 1 1 d It where K is the capital stock I is the investment in the current year dis the depreciation rate and i and t represent the cities and years respectively As done by Zhang et al 2004 this study selected 2005 as the starting value and defi ned the annual depreciation rate as 9 6 In terms of output this study used GDP defl ator to convert the nominal GDP of each province year by year to obtain actual GDP based on the nominal GDP inyear 2005 GDP is treated as the expected output and industrial three wastes and carbon emissions are as the undesired output The carbon emission is calculated based on the method provided in Xie et al 2017 3 2 2 Data for panel quantile regression Table 2 describes the variables in the model section The per Y Zhou et al Journal of Cleaner Production 244 2020 1186643 capita GDP PGDP was exploited to stand for economic develop ment This study assumes the higher per capita GDP is the higher eco effi ciency is Industry structure IS refers to the proportion of second industry in this study and secondary industry mainly in cludes industries with higher energy consumption and higher pollution emissions than the more environmentally friendly ter tiary industry So it assumes that the higher industry structure is the lower eco effi ciency is Foreign direct investment FDI has controversial arguments on eco effi ciency based on previous dis cussions C Zhou et al 2018 Urbanization is represented by ur bani