环境分权、地方政府竞争对绿色技术创新影响的“本地—邻地”效应

随着绿色发展成为五大发展理念之一,各地政府推进绿色技术创新成为降低环境污染和提高增长质量的主要途径。为了考察地方政府环境分权和竞争对绿色技术创新影响的“本地—邻地”效应,本文利用非期望产出EBM模型测度绿色技术创新程度,并将绿色技术创新指数引入动态空间杜宾模型。最后,结合2003-2017年中国省级面板数据进行实证分析。研究发现：(1)绿色技术创新具有显著的路径依赖、空间集聚以及邻近地区的策略竞争效应;(2)环境分权对本地和邻地绿色技术创新的影响呈“U型”变动特征,且现阶段并未跨越分权驱动创新的临界点;(3)环境分权与地方政府竞争的交互效应整体为负,环境行政分权、环境监察分权和环境监测分权等不同类型环境分权采取的策略并不相同;(4)区域环境分权产生的绿色技术创新激励效应存在异质性,中西部地区环境分权对绿色技术创新的激励效果更强。     

我国养老机构空间布局特征及其优化

基于ArcGIS软件,运用空间分析法,从公平性和均衡性视角,对全国31个省市（不包括港澳台地区）养老机构的空间布局特征展开研究,探究我国养老机构整体发展历程与演化特点,并利用改进的两步移动搜索法对各县域养老机构的空间可达性进行测算。结果表明：我国养老机构的发展历程可划分为萌芽期（1949—1977年）、增长期（1978—1998年）、规范期（1999—2008年）和建设期（2009—2020年）四个阶段,各阶段具有不同的分布特征;养老机构总体区域分布差异较大,主要集中在东部和中部地区,而西部地区较为分散,供给水平尚未达到预期目标值;我国养老机构空间分布出现多个聚集核心,布局总体呈“品字形”分布,密度由聚集中心向周边地区逐渐递减;按规模划分有效服务半径评价养老机构的空间可达性更为有效,我国东南部地区的可达性明显优于西北部地区,西北部多数为可达性低值区,养老机构资源配置有待进一步完善。     

农产品贸易对农业碳排放的影响——兼议数字乡村发展的门槛效应

基于1999—2019年中国省际面板数据,运用普通面板模型、空间面板模型与面板门槛模型实证分析了农产品贸易对农业碳排放的影响及其空间溢出效应与数字乡村发展门槛效应。研究发现：（1）农产品贸易对农业碳排放具有显著的抑制作用,并且相较于东部地区、粮食主产区以及贸易顺差区间,这种抑制作用在中西部地区、非粮食主产区以及贸易逆差区间更为显著; （2）在三种空间权重矩阵设定下,农产品贸易对本地区和“毗邻地区”农业碳排放均具有显著抑制作用,存在空间溢出效应,且相较于农产品出口贸易,农产品进口贸易抑制农业碳排放的空间溢出效应更为显著;（3）农产品贸易影响农业碳排放的过程中存在数字乡村发展双重门槛,即随着跨越数字乡村发展两道“门槛”,农产品贸易对农业碳排放的抑制作用呈现出边际递增的特征。由此,提出推动农产品贸易深度开放、构建农产品贸易交流协调机制以及增强数字乡村建设力度等政策建议。     

数字经济与城市群协同发展：基于夜间灯光数据的研究

准确认识数字经济与城市群协同发展的关系,有利于拓展数字经济影响的评估视角,也为发挥数字经济和区域一体化的融合倍增效应提供有益思路。研究发现,数字经济时代城市群辐射带动区域协同发展的步伐正在加快,数据要素跨域流通打破了城市群内部和城市群之间的市场分割,助推城市群边界的有效扩大。数字经济促进城市群协同发展主要通过两个作用机制,一是推动创新主体跨城市跨区域进行合作创新,促进城市协同创新网络发育壮大;二是提升城市空间集中度,增强邻近空间范围内的城市要素集聚能力。数字经济的网络性、跳跃性及外部性特征放大了中心城市对外围城市的辐射带动作用和空间溢出效应,因此构建与数字经济相匹配的区域一体化协调机制和要素统筹配置机制正当其时。     

收费公路运营效率测度及时空分异研究

收费公路行业内部债务治理与外部减税降费均要求收费公路运营降本增效。为了探析收费公路运营效率水平及其空间分布格局,使用SBM模型测度了2014—2020年29个省份收费公路运营效率,进而采用泰尔指数和Moran's I指数分析了其时空分异特征。研究认为:收费公路运营存在着效率较低且在时间维度上没有明显增长的趋势,在空间上存在发展不平衡问题,收费公路运营效率的区域差异主要来源于区域内部差异,区域内差异的贡献率平均达到81.578%; 收费公路运营效率具有空间正相关性,呈现出显著的“高-高”集聚和“低-低”集聚的空间特征,运营效率较高的省份对相邻省份具有正向溢出效应。研究表明,各省针对相邻省份或最近省份的运营效率现状,结合自身的比较优势探索产业升级或者物流发展模式,充分发挥相邻省份的经济发展和产业集聚对本省收费公路运营的辐射带动作用,推动建立起收费公路跨区域合作运营机制。     

Measuring credibility of compensatory preference statements when trade-offs are interval determined

This paper studies how an overall fuzzy preference relation can be constructed in the compensatory context of the simple additive difference model, when imprecision on the trade-offs has to be taken into account. Three credibility indices of preferences are analysed and illustrated by a numerical example. Arguments are presented supporting the use of the third index, for which an interesting transitivity property (which was an open problem) is proved.     

Sampling from spatial databases

This paper deals with techniques for obtaining random point samples from spatial databases. We seek random points from a continuous domain (usually ²) which satisfy a spatial predicate that is represented in the database as a collection of polygons. Several applications of spatial sampling (e.g. environmental monitoring, agronomy, forestry, etc) are described. Sampling problems are characterized in terms of two key parameters: coverage (selectivity), and expected stabbing number (overlap). We discuss two fundamental approaches to sampling with spatial predicates, depending on whether we sample first or evaluate the predicate first. The approaches are described in the context of both quadtrees and R-trees, detailing the sample first, acceptance/rejection tree, and partial area tree algorithms. A sequential algorithm, the one-pass spatial reservoir algorithm is also described. The relative performance of the various sampling algorithms is compared and choice of preferred algorithms is suggested. We conclude with a short discussion of possible extensions.     

常系数齐次线性微分方程组与其相应的差分方程组之间的联系

给出了求解常系数线性齐次微分方程组和常系数线性齐次差分方程组的一个方法,指出了这两种方程组之间存在的一个有趣关系．     

A Population Approach to Analysis of Variance Models

Several authors have contributed to what can now be considered a rather complete theory for analysis of variance in cases with orthogonal factors. By using this theory on an assumed basic reference population, the orthogonality concept gives a natural definition of independence between factors in the population. By looking upon the treated units in designed experiments as a formal sample from a future population about which we want to make inference, a natural parametrization of expectations and variances connected to such experiments arises. This approach seems to throw light upon several controversial questions in the theory of mixed models. Also, it gives a framework for discussing the choice of conditioning in models     

Finite mixture models with concomitant information: assessing diagnostic criteria for diabetes

The World Health Organization (WHO) diagnostic criteria for diabetes mellitus were determined in part by evidence that in some populations the plasma glucose level 2 h after an oral glucose load is a mixture of two distinct distributions. We present a finite mixture model that allows the two component densities to be generalized linear models and the mixture probability to be a logistic regression model. The model allows us to estimate the prevalence of diabetes and sensitivity and specificity of the diagnostic criteria as a function of covariates and to estimate them in the absence of an external standard. Sensitivity is the probability that a test indicates disease conditionally on disease being present. Specificity is the probability that a test indicates no disease conditionally on no disease being present. We obtained maximum likelihood estimates via the EM algorithm and derived the standard errors from the information matrix and by the bootstrap. In the application to data from the diabetes in Egypt project a two-component mixture model fits well and the two components are interpreted as normal and diabetes. The means and variances are similar to results found in other populations. The minimum misclassification cutpoints decrease with age, are lower in urban areas and are higher in rural areas than the 200 mg dl^-1 cutpoint recommended by the WHO. These differences are modest and our results generally support the WHO criterion. Our methods allow the direct inclusion of concomitant data whereas past analyses were based on partitioning the data.