Molecular Dynamics, Physical Properties, Diffusion Coefficients and Activation Energy of the Lithium Oxide (Li-O) and Sodium Oxide (Na-O) Electrolyte (Cathode)

This work is a simulation model with the LAMMPS calculation code of an electrode based on alkali metal oxides (lithium, sodium and potassium) using the Lennard Jones potential. For a multiplicity of 8*8*8, we studied a gap-free model using molecular dynamics. Physical quantities such as volume and pressure of the Na-O and Li-O systems exhibit similar behaviors around the thermodynamic ensembles NPT and NVE. However, for the Na2O system, at a minimum temperature value, we observe a range of total energy values;in contrast, for the Li2O system, a minimum energy corresponds to a range of temperatures. Finally, for physicochemical properties, we studied the diffusion coefficient and activation energy of lithium and potassium oxides around their melting temperatures. The order of magnitude of the diffusion coefficients is given by the relation Dli-O >DNa-O for the multiplicity 8*8*8, while for the activation energy, the order is well reversed EaNa-O > EaLi-O.

Small Sample Estimation in Dynamic Panel Data Models: A Simulation Study

We used simulated data to investigate both the small and large sample properties of the within-groups (WG) estimator and the first difference generalized method of moments (FD-GMM) estimator of a dynamic panel data (DPD) model. The magnitude of WG and FD-GMM estimates are almost the same for square panels. WG estimator performs best for long panels such as those with time dimension as large as 50. The advantage of FD-GMM estimator however, is observed on panels that are long and wide, say with time dimension at least 25 and cross-section dimension size of at least 30. For small-sized panels, the two methods failed since their optimality was established in the context of asymptotic theory. We developed parametric bootstrap versions of WG and FD-GMM estimators. Simulation study indicates the advantages of the bootstrap methods under small sample cases on the assumption that variances of the individual effects and the disturbances are of similar magnitude. The boostrapped WG and FD-GMM estimators are optimal for small samples.

The influence of heterogeneous environmental regulation on the green development of the mining industry: empirical analysis based on the system GMM and dynamic panel data model

The intensity of environmental regulation (ERI) affects the short-term effect of the level of green mining (GML),and which structure determines the long-term mechanism.Based on the panel data from 2001 to 2015,with the dynamic panel model and system GMM estimation method were employed to test the influence of heterogeneous environmental regulation on green mining and its transmission mechanism.The results show that,there is a 'U' type nonlinear relationship between the ERI and GML.The direct effect of command-control-based (CAC) and the market incentive-based (MBI) environmental regulation on green development of mining shows the characteristics of inhibition and promotion.There is a 'U' type of indirectly moderating effect between technological innovation and the energy consumption structure on the GML.The technological innovation promotes the green development of the mining industry only after pass the inflection point of MBI,while the CAC plays a significant guiding role in upgrading of the energy consumption structure.There is an inhibition and promotion effect of MBI on the GML in the southeast coastal area,and the CAC is not significantly.Meanwhile,both of the ERI shows no positive effects in the central and western inland region.

Quasi Maximum Likelihood for MESS Varying Coefficient Panel Data Models with Fixed Effects

The study of spatial econometrics has developed rapidly and has found wide applications in many different scientific fields,such as demog­raphy,epidemiology,regional economics,and psychology.With the deepening of research,some scholars find that there are some model specifications in spatial econometrics,such as spatial autoregressive(SAR)model and matrix exponential spatial specification(MESS),which cannot be nested within each other.Compared with the common SAR models,the MESS models have computational advantages because it eliminates the need for logarithmic determinant calculation in maxi­mum likelihood estimation and Bayesian estimation.Meanwhile,MESS models have theoretical advantages.However,the theoretical research and application of MESS models have not been promoted vigorously.Therefore,the study of MESS model theory has practical significance.This paper studies the quasi maximum likelihood estimation for ma­trix exponential spatial specification(MESS)varying coefficient panel data models with fixed effects.It is shown that the estimators of model parameters and function coefficients satisfy the consistency and asymp­totic normality to make a further supplement for the theoretical study of MESS model.

Semi-Varying Coefficient Panel Data Model with Technical Indicators Predicts Stock Returns in Financial Market

Accurately predicting stock returns is a conundrum in financial market.Solving this conundrum can bring huge economic benefits for investors and also attract the attention of all circles of people.In this paper the authors combine semi-varying coefficient model with technical analysis and statistical learning,and propose semi-varying coefficient panel data model with individual effects to explore the dynamic relations between the stock returns from five companies:CVX,DFS,EMN,LYB,and MET and five technical indicators:CCI,EMV,MOM,ln ATR,ln RSI as well as closing price(ln CP),combine semi-parametric fixed effects estimator,semi-parametric random effects estimator with the testing procedure to distinguish fixed effects(FE) from random effects(RE),and finally apply the estimated dynamic relations and the testing set to predict stock returns in December 2020 for the five companies.The proposed method can accommodate the varying relationship and the interactive relationship between the different technical indicators,and further enhance the prediction accuracy to stock returns.

基于PanelData的金砖国家对美高技术产品出口竞争力及影响因素分析

以巴西、俄罗斯、印度、中国、南非组成的金砖国家(BRICS),作为新兴经济代表,纷纷重视高技术产品的出口竞争。2010年金砖国家高技术产品出口总值达5008亿美元,占世界高技术产品出口的22.76%,而金砖国家在美国市场高技术产品的出口竞争成为新的焦点。本文旨在比较金砖国家对美高技术产品出口竞争力影响因素,挖掘金砖国家高技术产品出口的竞争优势,并借鉴金砖国家的成功经验,为中国提出对策建议,以增强中国对美高技术产品出口竞争力。

Panel-Data下Granger因果检验的理论和应用发展综述

Panel-Data下Granger因果检验的相关理论是最近几年才发展起来的,现有的研究提出了关于Panel-Data下Granger因果检验的四个基本假设:同质无因果关系假设(HNCH)、同质因果关系假设(HCH)、异质因果关系假设(HECH)以及异质无因果关系假设(HENCH),根据检验参数的特点给出三种类型的检验模型:固定系数模型、随机系数模型和混合固定随机系数模型。目前,还只有固定系数模型的相关理论较为完善,另外两种模型的检验还都存在一定的难度。因此,只有从理论研究和实际应用两个方面对该理论进行阐述,并对现有的理论进行简要的评述,才可指出其存在的不足及可能的改进方向。

我国旅游经济增长对星级饭店规模的弹性系数分析——基于Panel-Data模型

文章选取2001～2010年全国31个省域的数据,基于panel-data模型,采用空间面板回归和聚类分析方法,研究中国省域星级饭店规模与旅游经济增长的关系。按照旅游经济增长对星级饭店规模的弹性系数,将全国分为四类地区。研究发现:各类区域星级饭店对旅游经济的影响程度有很大差异,且存在一定的空间相关性。对于部分星级饭店规模已趋于饱和的省域,应注重星级酒店的市场营销,发展经济型酒店和家庭旅馆;而对于弹性系数较大的区域,则应加强发展星级酒店,扩大星级酒店的规模,提高接待水平。

ESTIMATION IN A SEMI-VARYING COEFFICIENT MODEL FOR PANEL DATA WITH FIXED EFFECTS

This paper considers a semi-varying coefficient model for panel data with fixed effects,proposes the profile-likelihood-based estimators for the parametric and nonparametric components,and establishes convergence rates and asymptotic normality properties for both estimators.Simulation results show that the proposed estimators behave well in finite sample cases.

An analysis of Chinese urban residents＇ consumer demand employing a dynamic semi-parametric panel data model

Using data for China for the years 1991 to 2005 by province and employing the semi- parametric panel data model estimation method developed by Horowitz （2004） and Henderson et al. （2006） and Hubler＇s non-parametric generalized method of moments （GMM） estimation （2005）, this article constructs a dynamic semi-parametric panel data model and describes the dynamic changing trajectory of the effect on consumption of income disparity among urban residents. Our findings show that there is a significant ＂ratchet effect＂ in the consumption of urban residents; that income disparity among urban residents has a clear negative influence on consumption; and that the trajectory of this influence shows a roughly bimodal curve.

A Multidimensional Analysis of the Relationship between Corporate Social Responsibility and Firm’s Financial Performance—Based on the Data of 78 Listed Companies in 10 years in Henan Province, China

At present, the research on the relationship of corporate social responsibility and economic performance mostly adopts the method of large-scale sampling, but does not distinguish the sample industries and regions, so the relevant research needs to be further analyzed. Based on the 2008-2017 data of 78 listed enterprises in Henan province, the relationship between corporate social responsibility and economic performance in 7 industries is measured by 8 indexes through Arellano-Bond dynamic panel data model. The research shows that the social responsibility of listed enterprises in Henan Province has a lagging impact on the economic performance of enterprises, which has a negative impact on the short-term and a positive impact on the long-term. The common point is that the responsibility of the investor has a positive impact on the economic performance of the enterprise, and other aspects vary greatly due to industry categories. In general, the degree of corporate social responsibility of listed enterprises in Henan Province is relatively low.

基于辅助回归的面板数据固定效应变系数模型的估计

本文针对面板数据固定效应变系数模型引入辅助回归来解释个体效应与协变量之间的关系,以此来处理固定效应,将模型转化为部分线性变系数模型.为了获得系数函数的估计,采用正交投影的方法消除固定效应,进一步基于局部线性估计对系数函数进行估计.在一些正则条件下,给出了系数函数估计的渐近性质.随后,模拟研究了所提出的估计方法的有限样本性质.模拟结果表明无论个体效应是随机的还是固定的,本文方法优于已有的方法.最后,对艾滋病人的CD4数据进行了实证分析.

低碳技术创新、区域经济发展对汽车业碳排放的影响机制研究

为了探究低碳技术创新、经济发展对汽车业碳排放的影响,基于我国新能源汽车较为普及的7个省市2013—2020年的数据,采用静态面板模型和动态面板模型,细致分析低碳技术创新、区域经济发展对汽车业碳排放量的影响,并通过分样本回归检验低碳技术创新、经济发展对燃油车碳排放和新能源车碳排放的异质性影响。研究表明:低碳技术创新对汽车业碳排放量有显著负向影响,区域经济发展对汽车业碳排放量有显著正向影响;汽车业碳排放具有延续性特征,受前期排放量的影响较大;低碳技术水平的进步可以更有效地促进燃油车的碳减排,而经济发展水平的提高则会更显著影响新能源汽车的碳减排。

中国开放型经济时空格局演化与影响因素

开放型经济时空格局的研究有利于制定不同类型省份开放型经济发展路径,促进区域间的协调发展.从贸易开放、投资开放和战略耦合3个维度构建开放型经济评价体系,分别采用熵权TOPSIS法、探索性时空数据分析、动态空间面板模型对2001—2021年中国省域开放型经济发展水平、时空格局演化以及影响因素进行分析.结果表明:中国开放型经济发展整体水平提升,但不同地区省份的变化迥异.“东高中西低”的梯度格局被打破,东西协同的“T字型”架构初步建立并稳步提升.开放型经济空间异质性逐渐弱化,空间自相关性更加显著.LISA时间路径相对长度在空间上呈现由沿海沿边向内陆地区递减趋势,LISA时间路径弯曲度呈现从沿边地区到其邻接省份再到沿海和内陆地区依次递减趋势.制度环境、自然资源禀赋、国家优惠政策、基础设施水平、邻接省份效应等因素驱动了开放型经济发展.

趋势固定效应函数系数面板模型的估计与应用研究

传统固定效应变系数面板模型因在捕捉截面个体的异质性方面具有显著优势而被广泛应用于经济分析中,但其劣势在于忽略了不同截面个体之间的共同性。为弥补上述不足,本文构建了趋势固定效应函数系数面板模型,从理论上分析新模型相对于传统固定效应变系数面板模型的优越性,在此基础上针对该模型提出参数的两步估计法,并推导估计量的渐近性质。一系列蒙特卡罗模拟结果表明,本文构建的模型比传统模型具有明显优势,且提出的估计方法具有良好的有限样本性质。将模型和估计方法应用于外商直接投资(FDI)对地区经济增长影响的研究,结果表明FDI对经济增长的影响随着地区初始经济发展水平的变化而变化,即FDI对经济增长具有非线性动态偏效应。

中国省域国际知名度对入境旅游业的影响——基于文化大数据的分析

文化吸引力是影响旅游目的地选择的关键因素,但以国家为分析单位的文化距离理论难以解释一国内部入境旅游发展差距现象。本研究提出了分析层次更加多元的文化影响力视角,并且以中国为例考察省域国际知名度对入境旅游发展的影响。利用涵盖多种国际语言的书籍大数据构建省域国际知名度指标,并将其与省级入境旅游发展相关数据进行匹配,构建了区域入境旅游发展动态面板模型。研究发现,中国各省的国际知名度在改革开放四十年间的差距较为明显。在控制了经济发展水平、对外开放程度、交通设施、旅游资源、酒店供应等因素后,省域国际知名度对入境旅游业具有显著的促进作用。本研究提供了一个关于入境旅游目的地选择决策的新文化解释,强调地域文化影响力对入境旅游发展的重要作用,这对于地方政府优化关于入境旅游业的政策设计和营销计划具有参考意义。

空间视角下黄河流域绿色信贷发展的碳减排效应研究

选取2011—2021年黄河流域9省(区)的99个地级市为研究样本,运用双向固定效应的空间杜宾模型考察绿色信贷支持碳减排的空间溢出效应,并结合动态面板数据模型对各绿色金融工具之间的“挤入效应”和“挤出效应”进行分析。研究发现,黄河流域各省(区)之间碳排放存在着显著的空间相关性,其绿色信贷发展具有显著的“本地—邻地”碳减排效应,同时各绿色金融工具之间存在“挤入效应”。基于此提出相应建议,切实推动黄河流域整体绿色信贷发展水平稳步提高,建立区域绿色信贷促进碳减排的协同机制,从而引导各绿色金融工具合力发挥碳减排效应。

集聚与地区经济增长:基于中国地级城市数据的再检验

本文基于我国地级以上城市的数据采用动态面板数据模型对集聚与经济增长之间的关系进行了实证检验。集聚对于人均GDP的增长和生产率的增长都具有显著的正向促进作用,但当地区经济发展水平达到一定高度后,集聚的增长效应则转变为负方向。这意味着,在经济发展的初级阶段,经济活动的集聚的确有利于经济增长,但当经济发展水平突破一定的门槛后,集聚的负面效应将逐步显现。这一结论对于当前集聚趋势下我国区域协调发展政策的制定具有重要的指导意义。

中国环境污染与经济增长:基于空间动态面板数据模型的实证分析

产业结构转型和区域间的产业转移进一步增强了中国各地区间的经济联动性,一个地区的产业规模和发展模式不仅影响本地区的环境质量,也会对其他地区尤其是周边地区的环境质量产生影响,这种地域间环境质量的空间相关性已不容忽视。为此,基于环境库兹涅茨曲线(Environment Kuznets Curve,EKC)假定,引入空间相关因素,运用空间动态面板模型分析中国环境污染与经济增长的关系。研究结果表明,中国基本满足EKC的假定,并且环境污染存在显著的空间相关性;基于地理权重的估计模型明显优于经济权重模型,即造成中国环境污染溢出的主要原因是地理因素而非经济因素。

异质性环境规制对矿业绿色发展的影响

绿色已成为新时代矿业发展的主基调,经济增长方式转变和供给侧结构性改革对矿业提出了新要求,环境规制强度影响矿业绿色水平的短期效应,环境规制结构决定矿业绿色发展的长效机制。基于2001—2015年我国省级面板数据,采用EBM模型定义的方向性距离出数(EBM-DDF)方法构建GML指数来衡量矿业绿色水平。采用动态面板模型和系统GMM估计方法,检验环境规制对矿业绿色发展的直接和间接效应及其传导机制,并重点考察不同类型、不同地区环境规制对矿业绿色发展的异质效应,探索构建矿业绿色发展的长效机制。研究发现:(1)环境规制强度与矿业绿色水平之间存在"U"型非线性关系,命令控制型和市场激励型环境规制对矿业绿色发展表现出先抑制后促进的直接效应。(2)技术创新和能源消费结构对矿业绿色水平具有"U"形间接调节效应,技术创新仅在市场激励型环境规制越过拐点后促进矿业绿色发展,能源消费结构对命令控制型环境规制的倒逼作用显著。经济发展水平学矿业绿色水平之间存在"U"形关系,只有经济发展到一定水平后,提高环境规制强度才有利于改善地区环境质量。(3)东南沿海地区的市场激励型环境规制对矿业绿色水平存先抑制后促进的作用,而命令控制型环境规制的影响不显著;中西部内陆地区由于经济发展水平相对滞后,环境规制并不能促进矿业绿色发展。因此,政府要合理选择环境规制类型,因地制宜地设定环境规制强度,增强绿色技术创新能力,推动能源消费结构升级,加快推进绿色矿山建设和绿色矿业发展,实现矿业转型升级和绿色发展。