产业结构变迁对房价的时空动态效应研究 ——基于人口老龄化背景的实证分析

产业结构调整与房地产市场理性发展是我国当前面临的重要任务,人口老龄化程度的加深会对二者产生影响.本文利用2004年~2016年省际面板数据,采用空间动态面板模型分析人口老龄化背景下产业结构变迁对房价波动的时空效应.研究表明,在基于地理、经济和人口三个维度构建的空间权重矩阵下,我国房价均具有显著的空间相关特性,但在不同市场中表现出异质性;产业结构高级化能显著助推房价上涨,产业结构合理化对房价具有正向影响且效应可持续五期;进一步分析表明,人口老龄化和产业结构变迁对房价的影响在不同市场、不同区域间均存在显著差异;人口老龄化对房价的影响完全通过与产业结构高级化相互作用的间接途径实现.     

中国区域食品价格差异收敛性检验——基于微观价格数据的空间计量与动态效应分析

构建有别于以往文献的区域价格β收敛空间计量分析框架,实证研究了1994年以来中国食品价格差异收敛性及其动态变化特征。研究发现:1994年以来,中国食品价格收敛速度表现出了先减弱后增强的U型动态变化特征,而非此前文献所揭示的逐步增强,这是由改革红利的"螺旋效应"所致,且最近几年中国食品价格收敛性在走弱,应引起特别注意。对此,进一步的分析表明,主要原因可能包括三期叠加的宏观经济形势、有所抬头的新型贸易壁垒、食品消费结构升级以及国内宾大效应。     

Single-Variable Threshold Effects in Ordered Response Models With an Application to Estimating the Income-Happiness Gradient

This short article extends well-known threshold models to the ordered response setting. We consider the case where the sample is endogenously split to estimate regime-dependent coefficients for one variable of interest, while keeping the other coefficients and auxiliary parameters constant across the threshold. We use Monte Carlo methods to examine the behavior of the model. In addition, we derive the formulae for the partial effects associated with the model. We apply our threshold model to the relationship between income and self-reported happiness using data drawn from the U.S. General Social Survey. While the findings suggest the presence of a threshold in the income-happiness gradient at approximately U.S. $76,000, no evidence is found in support of a satiation point. Supplementary materials for this article are available online.     

Random Effects,Fixed Effects and Hausman's Test for the Generalized Mixed Regressive Spatial Autoregressive Panel Data Model

This article suggests random and fixed effects spatial two-stage least squares estimators for the generalized mixed regressive spatial autoregressive panel data model. This extends the generalized spatial panel model of Baltagi et al. (2013 Baltagi, B. H., Egger, P., Pfaffermayr, M. (2013). A generalized spatial panel data model with random effects. Econometric Reviews 32:650–685.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) by the inclusion of a spatial lag term. The estimation method utilizes the Generalized Moments method suggested by Kapoor et al. (2007 Kapoor, M., Kelejian, H. H., Prucha, I. R. (2007). Panel data models with spatially correlated error components. Journal of Econometrics 127(1):97–130.[Crossref], [Web of Science ®] , [Google Scholar]) for a spatial autoregressive panel data model. We derive the asymptotic distributions of these estimators and suggest a Hausman test a la Mutl and Pfaffermayr (2011 Mutl, J., Pfaffermayr, M. (2011). The Hausman test in a Cliff and Ord panel model. Econometrics Journal 14:48–76.[Crossref], [Web of Science ®] , [Google Scholar]) based on the difference between these estimators. Monte Carlo experiments are performed to investigate the performance of these estimators as well as the corresponding Hausman test.     

Common Correlated Effects Estimation of Dynamic Panels with Cross-Sectional Dependence

We derive inconsistency expressions for dynamic panel data estimators under error cross-sectional dependence generated by an unobserved common factor in both the fixed effect and the incidental trends case. We show that for a temporally dependent factor, the standard within groups (WG) estimator is inconsistent even as both N and T tend to infinity. Next we investigate the properties of the common correlated effects pooled (CCEP) estimator of Pesaran (2006) which eliminates the error cross-sectional dependence using cross-sectional averages of the data. In contrast to the static case, the CCEP estimator is only consistent when next to N also T tends to infinity. It is shown that for the most relevant parameter settings, the inconsistency of the CCEP estimator is larger than that of the infeasible WG estimator, which includes the common factors as regressors. Restricting the CCEP estimator results in a somewhat smaller inconsistency. The small sample properties of the various estimators are analyzed using Monte Carlo experiments. The simulation results suggest that the CCEP estimator can be used to estimate dynamic panel data models provided T is not too small. The size of N is of less importance.     

基于超效率DEA的京津冀知识溢出效应研究

知识溢出是探索科技创新和区域经济发展的重要途径之一。利用超效率DEA模型对京津冀区域空间知识溢出效应做评价分析,选取全社会固定资产投资、实际利用外资直接投资和R&D经费内部支出为资本投入指标,R&D人员全时当量为劳动投入指标,人均地区生产总值为经济产出指标,专利授权数为科技产出指标,计算了北京、天津及河北省11个地市的2014至2016年知识溢出效应值,并从综合效率、投入冗余和产出不足三方面对评价结果进行分析,为推动河北省的科技创新提供了理论和实践依据。     

新时代中华优秀传统文化进教材的理性审思

中华优秀传统文化是中华民族的精神命脉。推动中华优秀传统文化融入教材,对于建设培根铸魂、启智增慧的新时代中国特色高质量教材体系,培养具有高度文化自信的社会主义建设者与接班人具有重要意义。中华传统文化教材建设百年来经历了从“沉寂”到“复兴”的曲折发展历程,反映出中华优秀传统文化顽强的生命力。在中国特色社会主义新时代,中华优秀传统文化“进教材”既是一种注重文化传承与精神引领的知识建构,也是一种凝聚文化教育合力的协同发展。新时代中华优秀传统文化教材建设,应以习近平新时代中国特色社会主义思想为指导,坚持创造性转化与创新性发展的基本方向,探索教材基于新时代语境的现代化诠释、基于全球化语境的本土化编写的发展向度,塑造中华民族优秀文化形象,开发数字教材资源,让中华优秀传统文化渗透、融入教材。新时代中华优秀传统文化教材建设也应强化规范意识,积极规避“人文关怀式微”的价值危机、“学科视野窄化”的认识误区、“教材泛德育化”的理念偏差以及“教育逻辑缺失”的路向偏移等失范问题,增强责任之心,勇于担当作为,落实立德树人根本任务,在固本与创新中肩负起推动中华优秀传统文化传承和发展的历史使命。     

西部农村学校同伴效应对青少年近视的影响

我国青少年近视率居高不下,农村地区也不例外,已严重威胁我国未来人力资本水平。基于2018-2019年在西部2省9县农村地区163所学校四至九年级的实地调查数据,使用工具变量法分析了同伴效应对青少年近视的影响。研究发现班级中近视同伴比例越高,青少年的视力水平更差、近视的可能性更大。同时发现同伴效应在近视的青少年中影响更大,但该影响在戴眼镜的近视青少年中有所降低。同伴效应对女生、初中生以及住校生的视力影响更大。作用机制检验发现,同伴近视并未通过间接影响个体对于近视的态度来增大近视可能性,可能主要通过直接改变个体用眼行为产生影响。因为同伴效应的存在,近视防控亟需引起全社会的重视,让近视防控产生社会乘数效应。同时,近视防控工作需要针对不同的青少年给予差异化的关怀与帮助,积极倡导正确的用眼行为。     

新型农村合作医疗挤出了商业健康保险吗？——基于CHARLS数据的实证分析

基于中国健康与养老追踪调查（CHARLS）2013年和2018年数据,利用面板固定效应模型、双重差分倾向得分匹配法（PSM-DID模型）和面板门槛回归模型,本研究考察了新型农村合作医疗保险与商业健康保险之间的关系。研究结果表明,新型农村合作医疗保险的参加非但没有挤出农村居民购买商业健康保险,反而在总体上促进了商业健康保险的发展,并且这种促进作用随着居民收入水平的提高越来越显著。因此,商业保险公司应针对不同收入水平居民设计和基本医疗保险相衔接的商业健康保险产品,满足人们多样化的医疗保障需求。     

Quantile regression for panel data models with fixed effects under random censoring

Abstract

The locally weighted censored quantile regression approach is proposed for panel data models with fixed effects, which allows for random censoring. The resulting estimators are obtained by employing the fixed effects quantile regression method. The weights are selected either parametrically, semi-parametrically or non-parametrically. The large panel data asymptotics are used in an attempt to cope with the incidental parameter problem. The consistency and limiting distribution of the proposed estimator are also derived. The finite sample performance of the proposed estimators are examined via Monte Carlo simulations.