Research on the Impact of China’s Foreign Trade Technology Spillover on Green Total Factor Productivity of Countries Along the“Belt and Road”:Based on the Institutional Quality Threshold Effect

China’s growing trade with countries along the“Belt and Road”Initiative is accompanied by a focus on green development.Based on the panel data from 2007 to 2018,this paper establishes a threshold regression model to empirically analyze the institutional quality threshold effect of China’s foreign trade technology spillover on the GTFP of countries along the“Belt and Road.”The results show that China’s foreign trade technology spillover has a significant institutional quality double threshold effect on the green total factor productivity of the countries along the“Belt and Road.”As the institutional quality of the countries along the“Belt and Road”crosses a specific threshold value,the impact of China’s foreign trade technology spillover on the green total factor productivity of the countries along the“Belt and Road”has a significant positive promoting effect,and corresponding suggestions are put forward.

The impact of market coordination on urban green total factor productivity:An analysis of the mediating effect of factor misallocation

Promoting market coordination and enhancing the efficiency of green growth is a necessity for China’s effective economic development.Using panel data from 2007 to 2020,this paper conducts a comprehensive study on 226 cities at the prefecture-level and above,combining theoretical analysis and empirical tests to systematically explore the impact of market cohesion on urban green total factor productivity(GTPF)and the mediating role of factor mismatch.Findings demonstrate that market coordination maximizes urban GTPF.At the mechanism level,factor mismatch plays a mediating role,and market coordination can enhance GTPF by addressing capital and labor mismatch.In terms of heterogeneity analysis,market coordination significantly promotes GTPF positively in the east-central region and negatively in the western region.In terms of technological progress and technical efficiency,the eastern region shows a larger significance than the central and western regions combined.In view of the above,the concept of market coordination development has been implemented to promote GTFP in cities.

Does innovative city pilot policy promote urban green growth in China?An analysis of green total factor productivity,2005-2020

The innovative city pilot policy(ICPP)is an essential manifestation of China’s construction of an innovative and green-driven development country.We incorporated urban green total factor productivity(GTFP)growth into the evaluation of ICPP.Based on the panel data of 223 cities in China from 2005 to 2020,we used the difference-in-differences model to empirically assess the influence and mechanism of the ICPP on urban GTFP growth.The main results show that(i)The ICPP has maintained an effectively fluctuating promotion on urban GTFP growth,mainly manifested in the urban green technological progress improvement.(ii)The ICPP has urban heterogeneity in promoting GTFP growth in pilot cities,mainly affecting key cities such as provincial capitals.(iii)The interaction between the agglomeration of producer services and the ICPP inhibits GTFP growth in pilot cities.

Empirical Analysis of the Impact of Green Finance and Technological Progress on Total Factor Productivity in China’s Industrial Sector

The enhancement of industrial green total factor productivity is pivotal for achieving high-quality and sustainable economic development.This study assesses China’s performance using the SBM-GML model,employing province-level panel data spanning from 2004 to 2020.Furthermore,we examine the influence of green finance and technological progress on industrial green total factor productivity using a spatial econometric model.The findings uncover that the relationship between the level of green financial development and industrial green total factor productivity follows a U-shaped curve.Initially,low levels of green financial development exert a suppressive effect on industrial green total factor productivity,proving ineffective in the short term.However,with the progression of green finance development,a positive and significant long-term impact on industrial green total factor productivity emerges.Moreover,technological progress demonstrates a noteworthy promotional effect on industrial green total factor productivity.The analysis delves deeper into revealing that industrial structure and environmental regulation intensity exhibit a significant negative relationship with industrial green total factor productivity.In contrast,both energy structure and education level showcase a substantial positive relationship with industrial green total factor productivity.

Dynamic analysis of spatial convergence of green total factor productivity in China's primary provinces along its Belt and Road Initiative

This paper focuses on China's primary provinces along its Belt and Road Initiative,measures and analyses the provincial green total factor productivity (GTFP) development by GML index based on SBM directional distance function,discusses the temporal evolution characteristics of spatial convergence of the provincial GTFP under multiple spatial weight matrices,and estimates the net effect of China's Belt and Road Initiative on the development gap of provincial GTFP by regression discontinuity.The research shows that the provincial GTFP is generally good while the internal gap is relatively large.There is spatial absolute βconvergence and condition βconvergence in provincial GTFP,and the convergence speed has been signifcantly accelerated since the construction of China's Belt and Road Initiative.The current low economy level and infrastructure allocation efficiency of primary provinces restrict the GTFP development,while government expenditure has promoted the GTFP development,trade between provinces and countries along China's Belt and Road Initiative is negative to GTFP.China's Belt and Road Initiative has significantly narrowed the gap of provincial GTFP development with the net effect of-0.016.

Technological innovation paths toward green industry in China

With the environmental carrying capacity reaching its limits and the decreasing margin benefits of traditional production factors, the green transformation and green development through technological innovations has been a major direction for the future development of Chinese industries. However, the characteristics and heterogeneities of various types of industries call for different approaches regarding technological innovations. How to choose the most effective mode of technological innovation according to the characteristics of a certain industry has been a key issue. This paper measures the green total factor productivity of 32 industrial trades using the Slacks Based Measure(SBM)-DDF method. The effects of three innovation modes in the green transformation of industrial industry, including the independent innovation(Ⅱ), the technology introduction(TI), and the government support(GS), are empirically analyzed based on industry heterogeneity. Results indicate that the green total factor productivities of different industries show significant differences if taking into account the energy input and the undesirable output of pollutant emissions. The green total factor productivities of traditional high input,high pollution, and high energy consumption industrial trades were significantly lower than those with obvious green features. The year of 2009 is a leap year for the industrial green transformation in China. For resource-intensive industries, the II and the GS are the important ways to achieve green transformation. For labor-intensive industries, the TI is the best path to achieve green transformation, while for technology-intensive industries, the II is the primary driving force for the promotion of green developments. In addition, the innovation-compensating effect of the current Chinese environmental regulations to the resource-intensive industries has been revealed. Improving the overall scale and the industrial concentration of the industries is also beneficial for the green transformation of the industries.

基于DEA-Tobit模型的生猪产业绿色发展效率研究

近年来,生猪产业绿色化取得长足进展。为了解生猪产业绿色发展效率变化情况及相关影响因素,研究首先通过DEA模型对生猪产业绿色发展效率进行测算,研判样本期内生猪产业绿色发展效率变化情况;再利用面板Tobit模型分析生猪产业绿色发展效率的影响因素。结果表明:从时间维度观察,生猪产业绿色发展效率在研究期间展现出波动上升的趋势,而在2019年之后,这一趋势则趋于稳定并持续上升。若从空间角度审视,内蒙古、黑龙江等9个省份在生猪产业绿色发展效率方面的提升最为显著。进一步分析动态效率,我们发现规模效率在推动生猪产业绿色发展效率提升中起到了关键作用。此外,资源禀赋、经济发展水平、环境规制、开放程度、交通通达度和规模化水平等要素,均对生猪产业绿色发展效率产生了显著的正向影响,为其提升提供了强大的驱动力。资源禀赋、经济发展水平、环境规制、开放程度、交通通达度和规模化水平均可显著正向提升生猪产业绿色发展效率。因此,应从释放区域资源禀赋、差异化落实环境规制和推动规模化养殖等方面提高生猪产业绿色发展效率。

Industrial Green Spatial Pattern Evolution of Yangtze River Economic Belt in China

We use the directional slacks-based measure of efficiency and inverse distance weighting method to analyze the spatial pattern evolution of the industrial green total factor productivity of 108 cities in the Yangtze River Economic Belt in 2003–2013.Results show that both the subprime mortgage crisis and ‘the new normal' had significant negative effects on productivity growth,leading to the different spatial patterns between 2003–2008 and 2009–2013.Before 2008,green poles had gathered around some capital cities and formed a tripartite pattern,which was a typical core-periphery pattern.Due to a combination of the polarization and the diffusion effects,capital cities became the growth poles and ‘core' regions,while surrounding areas became the ‘periphery'.This was mainly caused by the innate advantage of capital cities and ‘the rise of central China' strategy.After 2008,the tripartite pattern changed to a multi-poles pattern where green poles continuously and densely spread in the midstream and downstream areas.This is due to the regional difference in the leading effect of green poles.The leading effect of green poles in midstream and downstream areas has changed from polarization to diffusion,while the polarization effect still leads in the upstream area.

目标价格政策对棉花绿色全要素生产率影响分析——基于12个棉花主产省面板数据的Malmquist-Tobit模型

全要素生产率是衡量棉花经济增长的重要指标,而绿色全要素生产率则决定棉花产业的可持续发展。运用中国12个棉花主产省的棉花投入产出数据,测算棉花绿色全要素生产率的Malmquist指数并对其进行分解,采用Tobit模型估计棉花目标价格政策核心变量及区域经济发展水平、棉花每公顷收益、棉花产业聚集程度和区域环境投资力度等控制变量对棉花绿色全要素生产率的影响。研究表明:我国棉花绿色全要素生产率为1.02,安徽地区绿色全要素生产率最高为1.92,湖南地区棉花全要素生产率最低为0.91。目标价格政策对棉花绿色全要素生产率无显著影响,而区域经济发展水平、棉花每公顷收益、棉花产业聚集程度和区域环境投资力度则对棉花绿色全要素生产率有显著正向影响。

数字经济、绿色创新与企业绿色全要素生产率

文章从绿色创新视角切入,以2011—2022年中国沪深A股重污染行业上市公司为样本,实证考察了城市数字经济对重污染企业绿色全要素生产率的影响效应和内在机制。研究发现:数字经济对重污染企业绿色全要素生产率具有显著的提升作用,且对国有性质和中小城市的重污染企业的促进作用更强;绿色创新是数字经济驱动重污染企业绿色生产的重要传导机制,但仅绿色发明专利申请量有中介效应,增加绿色实用新型专利不是数字经济提升重污染企业绿色全要素生产率的有效途径;数字经济对重污染企业绿色全要素生产率的推动作用表现出边际效应递增的非线性特征,且两者之间的关系存在绿色创新的门槛约束,随着绿色发明专利和绿色实用新型专利申请量的增加,数字经济对重污染企业绿色全要素生产率的促进作用分别表现出效应增强和效应减弱的非线性特征。

农地流转提升了农业绿色全要素生产率吗?

在2006-2021年中国30个省份的面板数据基础上,本文通过SBM-GML超效率模型测算中国各省份农业绿色全要素生产率。采用双向固定效应模型和工具变量模型等方法,实证分析农地流转和农业绿色TFP之间的内在联系,并分析其影响路径机制。研究发现,中国农业绿色全要素生产率能够持续增长的主要原因在于技术进步。而农地流转能够推动农业绿色全要素生产率增长则是得益于技术效率改进。从异质性分析来看,农地流转对农业绿色全要素生产率增长的促进作用最显著的是东部地区和非粮食主产区,但在西部地区却正好相反。因此,中国应当加快推进农地流转工作进展,促进农业生产和经营管理模式变革,加快研发、推广和应用农业绿色生产技术,构建区域协作互助机制促进地区交流,进而促进农业绿色全要素生产率的提高。

数字乡村建设、资源要素错配与农业绿色全要素生产率

数字乡村建设与农业绿色发展深度融合是推动农业高质量发展的新动力引擎。本文选取2011-2021年中国31个省级面板数据,构建数字乡村建设和农业绿色全要素生产率的评价体系,多维度分析数字乡村建设对农业绿色全要素生产率的影响及作用机制。研究发现,数字乡村建设既可以直接促进农业绿色全要素生产率提升,也可以通过带动绿色技术进步而促进农业绿色全要素生产率提升,还可以通过降低土地资源错配、资本资源错配、劳动力资源错配程度而间接促进农业绿色全要素生产率。数字乡村建设对农业绿色全要素生产率的影响异质性明显,东部地区、南方、粮食主产区的数字乡村建设的正向推动作用较强。

科技服务业试点对城市绿色全要素生产率的影响研究

科技服务业试点对于推动绿色全要素生产率的提高具有重要作用。通过利用2005—2021年292个地级市的面板数据,使用双重差分法、中介模型研究科技服务业试点对中国绿色全要素生产率的影响。研究发现,科技服务业试点能提升中国绿色全要素生产率;人均消费支出在科技服务业试点与绿色全要素生产率之间发挥中介作用;科技服务业试点可以通过促进产业结构高级化间接提升绿色全要素生产率。因此,应进一步发挥人均消费支出对绿色全要素生产率的促进作用,促进企业加快技术创新,科技服务业试点政策要支持新兴产业快速发展。

碳交易如何影响绿色低碳发展?——基于多期DID与连续DID的经验研究

碳交易如何影响以绿色全要素生产率为核心指标的绿色低碳发展,需进行实证检验。基于2005—2019年中国省际面板数据,运用多期DID模型评估碳交易对绿色低碳发展的影响及其作用机制。结果表明:碳交易促进了试点地区绿色低碳发展,在经过安慰剂、PSM-DID、剔除用能权交易试点样本等一系列稳健性检验后,结论仍成立;碳交易实施对能源结构优化、产业结构升级与技术进步具有正向影响,绿色能源消费占比增加、高技术产业结构提升与技术进步是碳交易提高试点地区绿色低碳发展水平的主要机制。构建连续DID模型,研究碳交易规模对绿色低碳发展的影响,发现碳交易规模扩大对绿色低碳发展水平具有正向影响。研究结论为碳交易助力绿色低碳发展提供了经验支持,也为区域碳市场及全国统一碳市场的进一步扩容提供了有价值的启示。

“双碳”目标下黄河流域旅游绿色生产率时空分异特征及影响因素——以陕西段为例

陕西作为黄河流域旅游资源赋存高密度区,其绿色发展对黄河流域高标准高质量地实现“双碳”目标起着重要作用。收集2010—2021年相关数据,采用非期望产出的SBM模型、ML指数及Tobit回归模型等方法对陕西旅游绿色生产率(TGTFP)的时空分异特征及影响因素进行了分析。研究表明:(1)在时序发展上,2010—2021年内陕西旅游能源消耗与碳排放总量呈上升态势,其静态TGTFP唯有2017年实现有效,动态ML指数在2010—2013年和2014—2019年内实现有效,但其他年份均表现为无效,在发展过程中均呈左高右低的山峰型。(2)在空间分异上,TGTFP呈现“关中最强,陕北高于陕南”的分异特征,三大区域内部市域发展渐趋均衡,而三大区域间分化显著导致了陕西总差异扩大。(3)影响因素上,政府干预、环境规制及城镇化水平等外部因素对陕西旅游绿色生产率具有显著的推动作用,但仍有强烈的内部阻力来自旅游总收入、旅游能源消费及碳排放。

中国蛋鸡饲养绿色全要素生产率实证研究

为提高蛋鸡生产效率的同时减少污染排放,在考虑负向产出以及规模异质性和地区异质性的前提下,对蛋鸡养殖绿色全要素生产率(LHBG)进行测度。构建3层次SBM-MML指数,并将其分解为规模结构效率、技术效率以及管理效率。结果表明,2004-2018年平均LHBG为0.9967;大中小规模LHBG分别为0.9949、1.0013、0.9938;东中西部地区LHBG分别为0.9930、0.9980、1.0040。我国蛋鸡饲养绿色全要素生产率总体下降0.33%;规模上中规模最高、大规模其次、小规模最低;区域上西部最高,中部其次,东部最低;其分解效率表现为规模结构效率和技术效率提高,管理效率下降。

数字普惠金融、企业全要素生产率与绿色创新

绿色创新是企业提升绩效获得持续发展的重要动力,数字普惠金融和企业全要素生产率对企业绿色创新具有重要影响。以2011—2021年A股上市公司为样本,运用面板回归模型检验数字普惠金融对企业绿色创新的影响。研究发现:数字普惠金融对企业绿色创新具有显著促进作用,特别是相对于非国有企业、低污染行业和东部地区企业而言,数字普惠金融对国有企业、高污染行业和中西部地区企业的绿色创新促进力度更大;此外,企业全要素生产率(TFP)是数字普惠金融对企业绿色创新影响的中介,发展数字普惠金融可以提高企业TFP,从而推动企业绿色创新;环境监管在数字普惠金融与企业绿色创新之间发挥着积极的调节作用,提升环境监管水平将进一步增强数字普惠金融对企业绿色创新的促进作用。

金融科技能提升城市包容性绿色全要素生产率吗?

包容性绿色全要素生产率强调绿色发展、社会公平与经济增长协调并进,是判断城市经济发展质量的重要依据。本文以2011—2019年中国284个地级及以上城市的数据为样本,实证检验了金融科技对城市包容性绿色全要素生产率的影响及作用机制。研究发现,金融科技对城市包容性绿色全要素生产率具有明显的促进作用,主要表现在技术进步指数显著提升,这一结论在经过一系列内生性处理和稳健性检验后依然成立。机制分析显示,金融科技能够通过促进绿色创新、增加环保投资以及激发创业活力提升城市包容性绿色全要素生产率。异质性分析表明,金融科技对包容性绿色全要素生产率的提升作用在人力资本水平、金融发展水平和基础设施水平较高的城市中更为明显。本文的研究为加快实现经济绿色发展和包容性增长的“双重红利”提供了重要的经验证据。

产业结构优化升级、绿色税收与绿色全要素生产率——基于门槛效应与调节效应的分析

基于中国2003—2019年30个省份的面板数据,实证检验产业结构优化升级、绿色税收与绿色全要素生产率(GTFP)的互动关系。研究发现:(1)产业结构高级化能有效促进全国及各区域GTFP的提升;而产业结构合理化对GTFP的影响存在区域差异,产业结构合理化对长江经济带区域GTFP有显著的抑制作用,但是对非长江经济带区域的GTFP效果不显著。(2)在绿色税收的约束下,产业结构合理化对GTFP的影响存在单重门槛效应,而产业结构高级化对GTFP的影响存在双重门槛效应。(3)绿色税收可以负向调节产业结构合理化对GTFP的影响。

中国工业绿色低碳转型指数的时空演变分析

工业绿色低碳转型是实现“双碳”目标和经济高质量发展的重要支撑。文章基于2002-2020年中国30个省份的面板数据,利用超效率EBM模型和GML指数对工业绿色低碳转型指数进行测度并探究其时空演变特征。研究发现:从时序上看,全国工业绿色低碳转型指数变化有明显的阶段性特征,呈先上升、后下降、再上升的趋势;从空间上看,工业绿色低碳转型指数的空间集聚特征显著,地理相邻对工业绿色低碳转型有显著的正向影响。进一步,文章采用了空间β收敛模型对工业绿色低碳转型指数的收敛趋势进行评价,实证结果显示,中国工业绿色低碳转型指数空间绝对β收敛和空间条件β收敛显著。