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.

Bootstrap inference of the skew-normal two-way classification random effects model with interaction

In this paper,we consider the statistical inference problems for the fixed effect and variance component functions in the two-way classification random effects model with skewnormal errors.Firstly,the exact test statistic for the fixed effect is constructed.Secondly,using the Bootstrap approach and generalized approach,the one-sided hypothesis testing and interval estimation problems for the single variance component,the sum and ratio of variance components are discussed respectively.Further,the Monte Carlo simulation results indicate that the exact test statistic performs well in the one-sided hypothesis testing problem for the fixed effect.And the Bootstrap approach is better than the generalized approach in the one-sided hypothesis testing problems for variance component functions in most cases.Finally,the above approaches are applied to the real data examples of the consumer price index and value-added index of three industries to verify their rationality and effectiveness.

Panel data models with cross-sectional dependence: a selective review

In this review, we highlight some recent methodological and theoretical develop- ments in estimation and testing of large panel data models with cross-sectional dependence. The paper begins with a discussion of issues of cross-sectional dependence, and introduces the concepts of weak and strong cross-sectional dependence. Then, the main attention is primarily paid to spatial and factor approaches for modeling cross-sectional dependence for both linear and nonlinear （nonparametric and semiparametric） panel data models. Finally, we conclude with some speculations on future research directions.

Evaluation of Economic, Social Effects of Renewable Energy Technologies

What is sustainability? Does it only concern the environment or even socio-economic policies? It is only a question of ethics or a redefinition of industrial policy oriented towards the use of renewable energy, it can bring benefits both atmospheric and social employment. The need for the development of renewable sources can be in tune with the correct management of the territory in consideration of the fact that these sources involve the widespread implementation of small and medium-sized plants. A model of economic development based on renewable sources should respect the peculiarities and characteristics of the territories involved. It should also think of the territory as a “value” to be strengthened and used in a sustainable and integrated way and no longer as a passive platform on which to install plants. Solar thermal and photovoltaic, biomass, geothermal, hydrological, wind power are some of the sources the various countries must constantly invest. This publication is based on these concepts starting from an analysis of the employment data of the OECD “Organisation for Economic Co-operation and Development countries”, comparing them successively with the results of renewable energy productivity. The analysis was performed by analyzing a sample of 22 countries over a period of 20 years, after which the regression curve for the variables with the OLS method was created. This econometric method has allowed us to analyze the impact that renewable technologies have on the parameters of social welfare and in particular on unemployment.

非参数固定效应Panel Data模型的分位数回归推断

利用分位数回归方法,讨论了非参数固定效应Panel Data模型的估计和检验问题,得到了参数估计的渐近正态性及收敛速度。同时,建立一个秩得分(rank score)统计量来检验模型的固定效应,并证明了这个统计量渐近服从标准正态分布。

变系数Panel Data模型的建立与估计

研究了一类变系数Panel Data模型的建立与估计问题,并介绍了两个重要的变系数Panel Data模型.

基于空间Panel data固定效应模型的人口增长影响分析

运用空间面板数据分析方法考查了城镇化水平和人均GDP对人口增长的问题。首先介绍了面板数据在分析中的优越性,并阐述了面板数据模型的空间相关性检验。在此基础上,通过选用省级2003—2012年的Panel观测数据,对变量的面板数据进行平稳性检验,考查了变量的空间相关性。最后结合空间面板数据,运用固定效应法,估计了中国各省城镇化水平、人均GDP对人口增长的影响。经过实证检验,表明各省人口增长存在空间相关性,并概括了主要研究结论。

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.

Bootstrap LM Tests for Spatial Dependence in Panel Data Models with Fixed Effects

This paper applies bootstrap methods to LM tests(including LM-lag test and LM-error test) for spatial dependence in panel data models with fixed effects, and removes fixed effects based on orthogonal transformation method proposed by Lee and Yu(2010). The consistencies of LM tests and their bootstrap versions are proved, and then some asymptotic refinements of bootstrap LM tests are obtained. It shows that the convergence rate of bootstrap LM tests is O((N T)-2) and that of fast double bootstrap LM tests is O((NT)-5/2). Extensive Monte Carlo experiments suggest that,compared to aysmptotic LM tests, the size of bootstrap LM tests gets closer to the nominal level of signifiance, and the power of bootstrap LM tests is higher, especially in the cases with small spatial correlation. Moreover, when the error is not normal or with heteroskedastic, asymptotic LM tests suffer from severe size distortion, but the size of bootstrap LM tests is close to the nominal significance level.Bootstrap LM tests are superior to aysmptotic LM tests in terms of size and power.

Modelling energy efficiency in China:a fixed-effects panel stochastic frontier approach

This paper combines energy demand modelling with stochastic frontier analysis to investigate the changing trends,variations and determinants of energy efficiency for 27 Chinese provinces over the period 1995 to 2014.An aggregate‘frontier’energy demand function and an efficiency function are estimated simultaneously.We obtained several findings.First,the energy intensity is not a particularly good indicator of energy efficiency.Second,the energy efficiency levels for all the provinces improved during the sample period,but the current efficiency levels are still low,implying great potential for energy saving.In addition,the energy efficiency gap among the provinces seems to have widened over the past 20 years,as the variance has increased by almost three times.Finally,technological progress driven by new investment and the development of market mechanisms are two important drivers of energy efficiency improvement.

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.

西部地区城镇居民文化消费的影响机制

基于2010—2020年西部地区数据,运用固定效应面板模型对城镇居民文化消费的内在影响机制进行实证分析。结果表明:科技创新和文化产业集聚对西部地区城镇居民文化消费影响均有促进作用;区域异质性和产业异质性方面,科技创新和文化产业集聚对西南地区城镇居民文化消费的促进效用均高于西北地区,且对文化服务业的消费市场影响最显著。为了优化西部文化消费结构,应探索文化产业的科技创新型发展路径,提升文化消费市场潜力。

数字基础设施建设对共同富裕的影响研究

我国正值数字化转型和推进共同富裕的交叠期,数字基础设施建设成为缓解“数字鸿沟”、促进共同富裕的新契机。本文在阐释数字基础设施建设和共同富裕二者理论关系的基础上,以2011~2020年290个地级及以上城市为样本进行了实证检验。研究发现,数字基础设施建设对共同富裕存在积极影响。进一步分析显示,移动通信基站、互联网宽带基础设施、5G基站、超大型和大型数据中心、智能计算中心对共同富裕的正向作用程度依次递减。机制分析表明,数字基础设施建设通过提升资本配置效率、促进劳动力流动助推共同富裕,其影响效应在非中心城市和城市群内部城市更明显。研究为新一轮数字基础设施建设优化布局,促进地区间要素流动,助力全体人民共同富裕具有借鉴意义。

公路基础设施对经济与环境协调发展的影响——来自成渝地区双城经济圈的证据

了解公路基础设施对城市经济和环境协调发展的影响可以为城市规划和交通建设提供理论参考。本文基于2010—2020年成渝地区双城经济圈内16个城市的面板数据,通过耦合协调模型测度经济与环境的协调发展水平,采用面板固定效应模型和面板门槛模型,研究公路基础设施对经济与环境协调发展水平的影响。结果表明:2010—2020年成渝地区双城经济圈16个城市的经济与环境协调发展水平整体呈上升趋势,重庆和成都远高于其他城市,其余协调发展水平较好的城市主要集中于“双核”周围;公路密度与城市经济和环境的协调发展水平呈正相关,人口密度为负相关,而私营经济的发展和市场化程度、科技创新能力以及教育水平等都呈正相关;长期来看,公路密度的增加对城市经济环境协调发展的促进作用依然显著,且呈现边际效用递增的趋势;当公路密度小于2.043时,对经济与环境协调发展的影响系数为0.118,而公路密度超过2.043时,影响系数则增加到0.144,说明公路密度对城市经济环境协调发展的促进作用呈现出逐渐递增的非线性特征。当地应长期重视公路基础设施的建设,积极响应国家路网建设,差异化制定投资发展规划,推动交通、经济和环境的可持续发展。

数字金融水平对新型城镇化的影响——基于省域面板数据

基于中国2011—2021年省域面板数据,构建统计指标体系测度新型城镇化水平,利用面板固定效应模型分析数字金融水平赋能新型城镇化发展的影响效应。结果表明:数字金融覆盖广度、使用深度和数字化程度对新型城镇化具有显著的促进作用;不同地区数字金融水平对新型城镇化均有显著的促进作用;区别在于影响程度不同,其中,中部地区促进作用最大,东部地区影响效果最小。应根据地区差异性制定当地适宜的发展政策,构建多层次数字金融服务体系,促进新型城镇化发展。

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.

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。

绿色投资的“碳减排”效应研究

近年来,“双碳”目标下绿色投资与碳排放的关系,备受学界和政府有关部门的关注。本文运用静态面板固定效应模型,采用部分省(区、市)相关数据对我国绿色投资的“碳减排”效应进行分析,得出两点主要结论:一是绿色投资与碳排放存在倒“U”型关系,绿色投资初期对碳排放具有促进作用,而高水平绿色投资对碳排放有抑制作用,即绿色投资具有“碳减排”效应。二是地区经济规模和城镇人口规模均与碳排放呈正相关。建议继续加大绿色投资、制定环保激励政策、加强政策协调、提高技术创新能力与建立合作机制等。

数字经济助推我国文旅融合的作用机理研究

数字经济是推动我国经济高质量发展的新动力,文化产业、旅游产业的发展提高了人们生活的幸福感和归属感,但是数字经济对文旅融合的影响和作用机制尚未明确。文章在构建文化产业、旅游产业和数字经济指标体系的基础上,采用纵横向拉开档次法,计算出它们的综合发展水平,采用双向固定效应模型、面板分位数回归和面板平滑转换模型,研究数字经济影响文旅融合的作用机理,结果显示:(1)数字经济能促进文旅融合的发展,在处理内生性问题后结论依然成立,且随着文旅融合水平的提高,数字经济对文旅融合影响幅度递减。(2)以人力资本作为门槛变量时,数字经济对文旅融合存在显著的非线性影响,影响方式为“倒U型”,且区域创新存在显著的中介效应。(3)划分区域和数字经济一级指标后得出,数字基础设施对东部、中部和西部的文旅融合均存在显著的促进作用,数字产业化对东部和西部的文旅融合存在显著的促进作用,而产业数字化对东部的文旅融合存在显著的抑制作用。研究表明,数字经济促进文旅融合主要体现在数字基础设施和数字产业化上。

农机社会化服务对农地“趋粮化”的门槛效应研究

稳定农地粮食种植面积是确保粮食安全的重要途径,农机社会服务与农地“趋粮化”直接相关,因此有必要对农机社会化服务对农地“趋粮化”的影响效应进行深入研究。基于2007—2022年中国省级面板数据,运用固定效应模型和面板门槛模型,实证分析农机社会化服务对农地“趋粮化”的非线性影响。研究发现:农机社会化服务对农地“趋粮化”的影响存在基于收入水平下的双门槛效应,当农村居民收入水平低于6276.25元时,农机社会化服务对农地“趋粮化”的影响显著为负;当农村居民收入水平介于6276.25元和10619.40元之间时,农机社会化服务对农地“趋粮化”的影响作用提升;而当农村居民收入水平高于10619.40元时,农机社会化服务对农地“趋粮化”的影响程度最大。因此,为了稳定农地粮食种植比例,应该积极完善农业政策,大力推动农机社会化服务水平,提高农民收入以及对不同地区实施差异化补贴政策。