Do smart city policies improve energy efficiency?Evidence from China

To address air pollution and offer a convenient and comfortable living environment,the Chinese government launched a smart city pilot(SCP)project in 2012,accompanied by a comprehensive set of environmental and energy-related laws and regulations.Although academic interest in smart cities has surged,there remains a notable gap in empirical research exploring the economic,environmental,and energy effects of such initiatives.Taking 232 prefecture-level cities from 2003 to 2017 as research subjects,this study measures energy effi‐ciency by using energy consumption per unit of GDP and adopts a difference-in-differences(DID)analysis to investigate the impact of SCPs on energy efficiency.The empirical results indicate that SCPs improved energy efficiency by promoting urban technological innovation capabilities and green total factor productivity,and this effect was more pronounced in cities that were more dependent on traditional fossil fuel energy sources and had more developed fiscal and financial levels.Studying the impact of smart city construction on energy utilization efficiency in developing countries,such as China,is not only significantly enlightening for China’s green and low-carbon transition but also provides reference opinions for constructing smart cities and the path to enhancing energy efficiency in other developing countries.The findings provide valuable insights into the global development of smart cities,urban sustainability,and high-quality economic growth.

Influencing Factors of Total Factor Energy Efficiency in Bohai Rim Region Based on DEA-Tobit Model

Bohai Rim region is an important economic development area and a large carbon emission area in China.It is of great significance to explore the total factor energy efficiency and its influencing factors for the low carbon transformation and high-quality development of the Bohai Rim region.Based on the total factor energy efficiency framework,the DDF-DEA model was used to calculate the total factor energy efficiency,and the internal and external differences of the total factor energy efficiency were further analyzed.The internal and external influencing factors were determined by ML index method and classical endogenous growth theory,and then the Tobit panel model was used to empirically analyze the action mechanism of all influencing factors of total factor energy efficiency in the Bohai Rim region.The results show that the pure technical efficiency,scale efficiency and technological progress among the internal influencing factors contribute to the improvement of energy efficiency in the Bohai Rim region.Industrial structure,industrial internal structure and ownership structure inhibit the improvement of energy efficiency.Energy consumption structure and energy endowment also have a negative impact on energy efficiency.Therefore,measures such as promoting technological progress,adjusting economic structure and optimizing energy structure will effectively improve total factor energy efficiency in the Bohai Rim region.

Dynamic change of agricultural energy efficiency and its influencing factors in China

In order to practice the concept of‘lucid waters and lush mountains are invaluable assets’and promote the green development of agriculture,it is necessary to improve the efficiency of agricultural energy utilization.Based on the panel data of 28 provinces from 1995 to 2018,this paper calculated China’s agricultural energy input from two categories of direct energy and indirect energy,and used EBM(Epsilon-based Measure)mixed distance function model to measure the energy efficiency of agriculture in China.The nuclear density function and spatial autocorrelation were used to analyze the dynamic evolution of agricultural energy efficiency,and the dynamic panel model was used to analyze the influencing factors of agricultural energy efficiency.The results showed that:①From 1995 to 2018,the total agricultural energy input had increased year by year in China,with an average annual growth rate of 2%.Energy input structure changed from indirect energy-based to direct energy-based.Agricultural energy efficiency showed an evolutionary trend of‘rising-stagnating-rising rapidly’in China.The agricultural energy efficiency was generally low in China,and there was a large space for improvement in agricultural energy efficiency.②From 1995 to 2018,the average annual growth rate of agricultural energy efficiency in the eastern,central and western regions was 2.7%,1.9%and 1.4%respectively.In 2018,the agricultural energy efficiency in the eastern,central and western regions was 0.81,0.71 and 0.59 respectively.The gap between regions was expanding rapidly,and the agricultural energy efficiency in the central and western regions needed to be improved.③From 1995 to 2018,the agricultural energy efficiency of each province was polarized and the absolute gap was widened.There was obvious improvement in agricultural energy efficiency in Guangdong,Shandong,Jiangxi,Jiangsu,Liaoning and Tianjin,while the agricultural energy efficiency of Xinjiang,Guizhou,Zhejiang,Shanghai,and Inner Mongolia deteriorated.④From 1995 to 2018,there was no global spatial correlation of China’s agricultural energy efficiency.However,local‘high-high’concentration gradually appeared in the eastern region since 2010.⑤The first lag of energy efficiency had a significant positive impact on agricultural energy efficiency,and agricultural energy efficiency improvement had a time lag.The level of human capital,per capita net income of farmers and the level of urbanizaton had a significant positive impact on agricultural energy efficiency.The disaster rate,the level of development of secondary and tertiary industries,and the level of opening up had a significant negative impact on agricultural energy efficiency.In the implementation of the strategy of rural revitalization,we should focus on the central and western regions,take the cultivation of professional farmers as the key,focus on improving agricultural production conditions,enhance the level of cooperation between regions,exert the leading role of the secondary and tertiary industries,and enhance the ability of agricultural disaster prevention and mitigation.

Energy Factor and Mathematical Modeling for Power DC/DC Converters

Mathematical modelling for power DC/DC converters is a historical problem accompanying DC/DC conversion technology since 1940’s. The traditional mathematical modelling is not available for complex structure converters since the differential equation order increases very high. We have to search other way to establish mathematical modelling for power DC/DC converters.We have theoretically defined a new concept-Energy Factor （EF） in this paper and researched the relations between EF and the mathematical modelling for power DC/DC converters. EF is a new concept in power DC/DC conversion technology, which thoroughly differs from the traditional concepts such as power factor （PF）, power transfer efficiency （η）, total harmonic distortion （THD） and ripple factor （RF）. EF and the subsequential EFV (and EFVD) can illustrate the system stability, reference response and interference recovery. This investigation is very helpful for system design and DC/DC converters characteristics foreseeing. Two DC/DC converters: Buck converter and Super-Lift Luo-Converter as the samples are analysed in this paper to demonstrate the applications of EF, EFV (and EFVD), PE, SE, VE （and VED）, time constant τ and damping time constant τd.

Urban Energy Efficiency from Cities in China and Policy Implications

Using 1995-2006 panel data for 210 cities,this article firstly measures total factor energy efficiency for Chinese cities with constant return to scale data envelopment analysis model,and then describes the features of regional differences.The results show that the changing trend displays four "reversed U" shapes.A turning point of widening gap occurred among cities in 2000 and there was a certain convergence among four regions.Urban energy efficiency level is unstable.Cities with low efficiency and high energy input will be the focus of energy-saving and reducing emissions.According to Tobit model,resource endowment,temperature,industrial structure,technology level and variety of policy factors should be treated differently in different situations.

城镇化、技术创新影响全要素能源利用效率的中介效应研究——来自黄河“几”字弯的实证

采用全局参比Malmquist模型测算黄河“几”字弯都市圈城市2006—2021年的全要素能源利用效率,分析GML指数变化与全要素能源利用值的变化,利用三阶段中介效应模型分析城镇化、技术创新对黄河“几”字弯都市圈城市全要素能源利用效率的影响效应。研究表明:黄河“几”字弯大部分城市的全要素能源利用效率值呈现增长态势,且资源型城市高于非资源型城市,省会城市低于非省会城市;产业结构高级化是城镇化促进全要素能源利用效率的部分中介;经济增长是技术创新促进全要素能源利用效率的完全中介;降低环境污染是技术创新促进全要素能源利用效率的部分中介。黄河“几”字弯都市圈各城市应构建现代经济能源体系,加速产业升级与城市转型,建设低碳零碳负碳工程,推动技术创新与经济增长、绿色发展齐头并进。

新能源在高质量发展中的全要素生产率贡献研究

新能源作为具有高科技、高效能、高质量特征的新质生产力,催生能源领域的新产业、新模式、新动能,带动全要素生产率提升。在测度中国全要素生产率、全要素能源效率和绿色全要素新能源效率及其变化率基础上,分析新能源技术效率对全要素生产率变化的贡献。研究表明,提升新能源效率不仅有利于增强新能源对传统能源的竞争优势,助推能源结构绿色市场化转型,而且有利于提高全要素生产率,因此有必要以持续创新加快新能源技术进步和技术效率提升,以更高的新能源效率促进能源结构绿色转型,助力经济高质量发展。

我国财政支农支出效率测度及评价

为充分发挥财政的职能作用和强化财政支农资金管理,选取2013—2021年我国31个省(区、市)相关数据,基于三阶段DEA模型和Malmquist指数模型,分别从静态和动态两方面对财政支农支出效率及其全要素生产率进行分析。结果表明,剔除外部环境和随机干扰后,2013—2021年我国财政支农支出综合技术效率均值为0.852,仅黑龙江省和山东省处于DEA有效状态。我国财政支农支出全要素生产率以年均1.8%的速度下降。相关部门应合理调整财政支农投入,加强区域间合作,拓宽财政支农投入渠道,提高财政支农支出效率。

家用空调器产品监督检验中常见不合格项目解析

制冷量、制冷消耗功率、全年能源消耗效率(APF)和制冷季节能源消耗效率(SEER)、接地措施、连续骚扰(端子电压)这五个项目是家用空气调节器产品在监督检验中常见的不合格项目,本文通过列举具体案例,从标准要求和实测数据等方面,重点分析了导致不合格产生的客观及主观原因,并给出了相应的整改方案,为企业提升认识、完善设计、加强质控、规范制造提供了有效的改进建议,助力企业生产出符合国家标准要求的合格产品。

农机购置补贴对农业绿色全要素生产率的影响研究

农业机械化会产生经济增长效应和环境污染效应,进而导致农机购置补贴带来的农业绿色全要素生产率(GTFP)增长慢于农业全要素生产率(TFP)增长。采用2008—2021年31个省份数据的分析发现:农机购置补贴提高了农业总产值和碳排放量并降低了碳排放强度(经济增长效应大于环境污染效应),从而显著促进了农业GTFP提升,但该正向影响小于农机购置补贴对农业TFP的正向影响;农机购置补贴主要通过技术进步渠道促进农业GTFP和农业TFP提升(技术效率改善渠道的作用不显著),且对农业绿色技术进步的促进作用小于对农业技术进步的促进作用;在农村人力资本水平较高地区、平原面积占比较高地区和环境规制较强地区,农机购置补贴对农业GTFP和农业TFP的提升作用更为显著,且在环境规制较强地区对农业GTFP的提升作用大于对农业TFP的提升作用。因此,应增强支农政策的绿色偏向,提高农村人力资本水平和环境规制强度,并通过完善配套政策和加强基础设施建设有效提高农业技术效率,进而实现更快的农业GTFP增长。

绿色金融改革创新的节能效应研究

设立绿色金融改革创新试验区是中国开启绿色金融区域探索的典型实践,也是促进节能降耗、减污降碳和绿色发展的重要手段。本文以绿色金融改革创新试验区实践为绿色金融政策的切入点,采用双重差分方法考察绿色金融改革创新政策的节能效应、作用机制和异质效应。研究结果表明,绿色金融改革创新政策的推行有助于降低试验区的能源强度,并提升试验区的绿色全要素能源效率,从而产生节能效应。机制检验结果表明,绿色金融改革创新政策能够通过推动产业结构升级和绿色技术创新来促进节能效应的产生。异质性分析结果显示,绿色金融改革创新政策有助于改善非资源型城市和中西部城市能源强度和绿色全要素能源效率,从而产生节能效应。本文的研究结论能够为促进绿色金融政策的制定和推广、挖掘节能效应的驱动力提供经验证据。

中国区域农业生产用能、农业经济增长及农业能源碳排放关系研究——基于绿色全要素生产率视角

采用超效率SBM-GML模型对1990—2020年中国31个省份的农业绿色全要素生产率及其变化指数进行测算,通过农业产值增长率和绿色全要素生产率效率值将不同省份划分成四个区域,运用面板固定效应模型探究农业生产用能对农业经济增长的影响和区域异质性,应用面板门槛模型对农业经济增长与农业能源碳排放的关系进行分析。研究表明:(1)1990—2020年中国的绿色全要素生产率呈现缓慢上升趋势,其中技术进步是主要推动力,而技术效率指数增速为负。(2)全国及各区域农业生产用能与农业产出的相关系数均为正值,即生产用能的投入能够明显增加农业产出,但是产出增加的实现程度存在区域异质性。(3)我国农业经济增长和农业能源碳排放之间存在单一门槛效应,在门槛值前,二者正向关系较强;跨过门槛值后,二者正向关系减弱,呈现协调发展态势。据此,提出积极鼓励农业技术进步、全面提高农业技术效率、因地制宜优化农业生产用能结构、差异化选择农业绿色发展道路等政策建议。

煤炭开采企业绿色全要素能源效率研究

煤炭开采行业是高碳能源的生产行业,提升煤炭开采企业的绿色全要素能源效率对促进我国“双碳”目标的实现具有重要作用。基于影子价格模型,对企业的二氧化碳边际减排成本进行测算,进而构建DEA-Malmquist指数模型计算煤炭开采企业绿色全要素能源效率。实证结果表明:样本企业绿色全要素能源效率水平参差不齐,但均呈现不同程度的上升趋势;相对于综合技术效率,技术进步对企业绿色全要素能源效率水平上升做出了更多贡献。基于上述结果,从企业内部、外部2个视角对影响企业绿色全要素能源效率的因素进行分析,通过专利分析企业自主研发能力及技术选择、分析外部政策环境,提出完善碳交易市场形成有效监管、适当扩张企业规模提高规模效率、加强自主研发走内涵式发展道路等对策建议。

数字要素配置、绿色全要素能源效率约束与城市韧性

选取2011—2021年中国244个地级以上城市的面板数据,引申压力—状态—响应模型,运用面板向量自回归模型和动态平衡面板模型对数字要素配置、绿色全要素能源效率约束与城市韧性三者之间的互动关系进行实证分析。结果表明:第一,数字要素配置水平对城市韧性存在正向影响而绿色全要素能源效率对城市韧性存在负向影响,城市韧性对数字配置水平存在正向影响,城市韧性对绿色全要素能源效率存在负向影响。第二,数字要素横向配置调节效应分析表明,数字要素制度供给水平、数字要素产业发展水平和数字要素技术发展水平起负向调节作用;数字要素纵向配置调节效应分析表明,数字要素配置水平起负向调节作用。基于研究结论,提出吸收数字经济发展及绿色节能创新发展过程中产生的新技术、新制度以创新韧性城市建设理念,并制定差异化、动态化的政策措施。

数字技术创新、能源偏向型技术进步与城市全要素能源效率

数字技术创新通过改变资本和能源要素的配置,对能源偏向型技术进步产生影响,并且这种偏向型技术进步可能进一步影响全要素能源效率。本文采用2006—2021年中国275个地级及以上城市数据,利用双向固定效应模型实证检验数字技术创新对能源偏向型技术进步的影响效应及机制,并拓展分析能源偏向型技术进步的能源效率提升效应。研究发现:样本期内,我国城市的数字技术创新水平呈现逐年上升趋势;我国城市技术进步主要偏向资本,但偏向资本的程度在减弱,且我国城市能源和资本之间总体呈现替代关系。数字技术创新能够促进能源偏向型技术进步。数字技术创新能够通过促进能源消费绝对规模增加和相对规模增加,从而促进能源偏向型技术进步。数字技术创新对能源偏向型技术进步的影响在中部和西部地区显著,而在东部和东北部地区不显著。除数字产品服务业外,数字技术创新其他维度均能显著促进能源偏向型技术进步。拓展分析发现,当资本和能源为替代关系时,能源偏向型技术进步对全要素能源效率提升存在不利影响。

科技成果转化效率如何影响农村产业融合发展?

农村产业融合发展是转变农业发展方式、拓宽农民增收渠道和推动农业强国建设的重要举措。但不容忽视的是,科技与产业脱节仍是当前制约农村产业融合发展的迫切问题。基于2011—2020年中国30个省份的面板数据,利用固定效应模型,实证检验了科技成果转化效率对农村产业融合发展的影响及内在机制。研究结果表明,科技成果转化效率的提高有助于促进农村产业融合发展,这一结论在控制内生性和进行稳健性分析后依然成立。作用机制方面,科技成果转化效率主要通过提高农业全要素生产率和促进农村劳动力转移两条路径对农村产业融合发展产生影响。进一步分析的结果显示,科技成果转化效率对农村产业融合发展的作用效果受到科技成果转化政策与地区资源禀赋的约束,且农村人力资本在其中发挥了门槛作用。研究结论不仅为理解科技成果转化效率如何影响农村产业融合发展提供了理论依据,也从科技成果转化效率的角度为促进农村产业融合发展提出了政策启示。

农业全要素生产率空间格局演化、驱动因素及提升策略——以扬州市为例

农业全要素生产率效率是衡量农业经济增长、农业生态环境保护与资源节约统筹发展的重要指标。文章基于扬州2008—2017年扬州的面板数据;采用超效率SBM模型就其农业全要素生产率展开了实证分析并在此基础上对其影响因素进行了剖析。结果表明:研究期间扬州市各乡镇农业全要素生产率空间上凸显个体差异性特征;影响因素分析发现不同区域对各要素的响应程度存在很大的差异性。

山东省农业用水效率评价及促进对策研究

为了科学评价山东省农业用水效率,采用DEA-BCC-I模型测算山东省农业用水效率,采用Malmquist指数对山东省2011—2021年16个地级市用水效率的动态演变机理进行了研究。研究结果表明:2021年山东省农业用水综合效率值为0.822,总体水平相对较高;农业用水效率由高到低的区域排序为:鲁中>鲁东>鲁西南>鲁西北;2011—2021年间山东省农业用水全要素生产率呈上升趋势,但用水综合效率呈下降趋势;技术进步是山东省用水全要素生产率提高的主要推动力;建议采取技术创新,促进各地区均衡发展,提高投入要素的匹配度,合理控制投入规模,并对水资源价格进行调控,以提高山东省农业用水效率。

环境规制对城市全要素能源效率的影响及其机制研究

提升能源效率已成为中国绿色转型发展的必然选择。本文采用非期望产出的Dynamic Network SBM模型测算了2006-2021年中国261个地级市的全要素能源效率,并采用地级市面板数据和上市公司面板数据实证检验了环境规制对全要素能源效率的影响效应及其作用机制。研究结果显示:样本期内中国城市全要素能源效率总体呈略微下降趋势,距离有效前沿面还有69.75%的提升空间;环境规制与城市全要素能源效率之间存在显著的“U”型关系;机制分析表明环境规制对技术创新具有先下降后上升的影响,对企业融资成本具有先上升后下降的影响;环境规制对不同资源禀赋的城市具有显著的异质性影响。进一步研究发现,环境规制对全要素能源效率具有较强的空间溢出效应。以上研究结论对于不同城市如何因地制宜实施不同的环境规制强度以及提升我国城市全要素能源利用效率具有重要的现实意义。

户籍制度约束视角下城乡流动性限制对农业全要素生产率的影响研究

在城乡大规模人口流动背景下,通过构建农业与非农业部门的两部门模型,探讨户籍制度限制下劳动力配置扭曲对农业全要素生产率的影响及其作用机制。运用地级市层面的数据,结合DEA-Malmquist生产率指数分析方法测算农业全要素生产率,并以人口流动网络的视角构建一个城乡流动性限制指数,最终通过实证研究分析城乡流动性限制对农业全要素生产率的影响。结果表明,城乡流动性限制会抑制农业全要素生产率,而该抑制作用是通过农业技术进步与资源配置效率的降低得以实现。地区异质性分析结果表明,中西部地级市的城乡流动性约束对农业全要素生产率抑制效果显著,而这两者在东部地级市中则并无显著关系。因此,持续推进户籍制度改革,优化城乡要素流动,是实现农业高质量发展的有效途径。