检索结果-内蒙古大学图书馆

Asia-Pacific Power and Energy Engineering Conference (APPEEC)

作者： Su, Fanglin Song, Bangying Guangxi Normal Univ Sch Econ & Management Guilin 541004 Peoples R China

ISBN: (纸本)9781424448135

Learning from the experience of the C-D function form's double logarithm, and using five explanatory variables, the authors tentatively build models by themselves and introduce spatial effect into the introduction of the research about Chinese provincial low-carbon economy. First, according to Moran's index of coal consumption behavior we determine the existence of spatial autocorrelation, secondly, we determine the best choice about the spatial lag models and spatial error models through the five spatial weight matrix, and then analysis conclusions are made (achieved) through the most superior model: spatial effect exists among the provincial coal consumption behavior. The estimated value of spillover effect parameter is up to 0.1286, and gradually becomes smaller with the distance;There exist endogenous economic relations among the dependent variable of coal consumption quantity and the independent variables of industrial structure, population growth, resources talent, income level and industry economy growth, among which the industrial structure and the population growth are the two most important factors affecting the coal energy consumption behavior, while the higher industrial economic growth is not necessarily accompanied by higher coal consumption. It implies the enhancement of coal efficiency. Finally we make conclusion and put forward related policy recommendations.

关键词： Chinese provinces low-carbon economy spatial weight matrix spatial lag model spatial error model

来源：评论

学校读者我要写书评

暂无评论

An Application of spatially Autoregressive models to the Study of US County Mortality Rates

引用

POPULATION SPACE AND PLACE 2010年第6期16卷 465-481页

作者： Sparks, Patrice Johnelle Sparks, Corey S. Univ Texas San Antonio Dept Demog & Org Studies San Antonio TX 78249 USA

County mortality rates in the US tend to be associated with social and economic resources of counties and the unequal distribution of these resources across space. The processes that generate these social and economic inequalities are often tied to geographical location. In this paper, we present an application of spatially autoregressive models of US county mortality rates that control for the social and economic conditions that often influence mortality rates and the effects of spatial structure of counties in the US. We suggest that arguments are missing from the social science and demographic literatures to offer possible explanations for the spatial patterning of county mortality rates and ecological correlates of these rates at the county level. We find that, after controlling for spatial structure in the data, several key social variables become insignificant in the analysis. We suggest that spatial statistical models are valuable tools in the social and behavioural sciences but that the use of these methods needs to be well grounded in considerations about the spatial process inherent to the outcome studied, and the applications of these methods should not be used solely for post hoc statistical correction. Copyright (C) 2009 John Wiley & Sons, Ltd.

关键词： spatial regression local autocorrelation spatial error model spatial lag model county mortality rates US

来源：评论

学校读者我要写书评

暂无评论

Hedonic approaches based on spatial econometrics and spatial statistics: application to evaluation of project benefits

引用

JOURNAL OF GEOGRAPHICAL SYSTEMS 2009年第4期11卷 357-380页

作者： Tsutsumi, Morito Seya, Hajime Univ Tsukuba Dept Policy & Planning Sci Tsukuba Ibaraki Japan PASCO Corp Meguro Ku Tokyo Japan

This study discusses the theoretical foundation of the application of spatial hedonic approaches-the hedonic approach employing spatial econometrics or/and spatial statistics-to benefits evaluation. The study highlights the limitations of the spatial econometrics approach since it uses a spatial weight matrix that is not employed by the spatial statistics approach. Further, the study presents empirical analyses by applying the spatial Autoregressive error model (SAEM), which is based on the spatial econometrics approach, and the spatial Process model (SPM), which is based on the spatial statistics approach. SPMs are conducted based on both isotropy and anisotropy and applied to different mesh sizes. The empirical analysis reveals that the estimated benefits are quite different, especially between isotropic and anisotropic SPM and between isotropic SPM and SAEM;the estimated benefits are similar for SAEM and anisotropic SPM. The study demonstrates that the mesh size does not affect the estimated amount of benefits. Finally, the study provides a confidence interval for the estimated benefits and raises an issue with regard to benefit evaluation.

关键词： Benefits evaluation spatial hedonic approach spatial error model spatial process model Anisotropy

来源：评论

学校读者我要写书评

暂无评论

An Urban Study of Crime and Health Using an Exploratory spatial Data Analysis Approach

An Urban Study of Crime and Health Using an Exploratory Spat...

引用

International Conference on Computational Science and Its Applications (ICCSA 2009)

作者： Tan, Su-Yin Haining, Robert Univ Waterloo Dept Geog & Environm Management Fac Environm 200 Univ Ave W Waterloo ON N2L 3G1 Canada Univ Cambridge Dept Geog Cambridge CB2 3EN England

ISBN: (纸本)9783642024535

Research into the impacts of crime on health is relevant to adopting effective social policy and encouraging partnerships between local health and crime prevention agencies. Although it is not difficult to support the notion of crime as a threat to public health, the difficulty lies in quantifying the impact. Confounding effects of other influential variables (i.e. income, employment, housing) further complicate any analysis into the causal relationships between crime and health. An exploratory spatial data analysis approach was adopted in this study to examine the spatial relationships between crime, health, and quality of life indicators in Super Output Areas (SOAs) in Sheffield (UK). Quantitative methods of spatial data exploration and visualisation, and spatial autocorrelation analysis were used, based on aggregated secondary data drawn from census and crime databases. Statistical models of crime and health were specified, while taking into account the presence of spatial effects by applying spatial regression techniques.

关键词： Health Crime Deprivation spatial Autocorrelation spatial Regression spatial error model Moran's 1 LISA Sheffield UK

来源：评论

学校读者我要写书评

暂无评论

Evaluating natural resource amenities in a human life expectancy production function

引用

FOREST POLICY AND ECONOMICS 2009年第4期11卷 253-259页

作者： Poudyal, Neelam C. Hodges, Donald G. Bowker, J. M. Cordell, H. K. Univ Tennessee Nat Resource Policy Ctr Dept Forestry Fisheries & Wildlife Knoxville TN 37996 USA Univ Georgia Daniel B Warnell Sch Forestry & Nat Resources Athens GA 30602 USA USDA Forest Serv So Res Stn Athens GA 30602 USA

This study examined the effect of natural resource amenities on human life expectancy. Extending the existing model of the life expectancy production function, and correcting for spatial dependence, we evaluated the determinants of life expectancy using county level data. Results indicate that after controlling for socio-demographic and economic factors, medical facilities and risk factors, counties with natural amenities such as high proportion of land in forests, farmland, rangeland and water bodies, as well as mild climate such as longer sunlight hours during winter and cooler year around temperature exhibited longer life expectancies at birth. In addition, counties containing state parks and outdoor recreation facilities, and those located near federal wilderness parks were associated with the longer expectancies at birth. Findings from this study have several implications for natural resource economics and management, public health, and human development. An important message of our findings is that the traditional approach of public health should be extended beyond just controlling diseases or treating patients to a more comprehensive approach that also acknowledges the preservation and utilization of natural resources, environmental amenities. and outdoor recreation opportunities in maintaining public health, quality of life, and overall human development. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Life expectancy Natural resource amenities spatial error model Production function Public health

来源：评论

学校读者我要写书评

暂无评论

Spanish Internal Migration: Is there Anything New to Say?

引用

spatial ECONOMIC ANALYSIS 2009年第1期4卷 103-120页

作者： Mulhern, Alan Watson, John G. Kingston Univ Sch Econ Kingston Upon Thames KT1 2EE Surrey England

Spanish internal migration has long been resistant to traditional economic explanations. However, this paper examines the data for the period 1999-2006 after considerable changes in the Spanish economy. Moreover, it examines migration at the disaggregated level of Spanish provinces rather than regions, the usual unit of measurement. Using a spatial error model as well as a spatial autoregression model it finds the differentials in wages and unemployment between provinces to be significant explanatory variables. House prices are also important in accounting for the dynamics of internal migration.

关键词： Internal migration Spain spatial error model

来源：评论

学校读者我要写书评

暂无评论

An Evaluation of spatial Autocorrelation and Heterogeneity in the Residuals of Six Regression models

引用

FOREST SCIENCE 2009年第6期55卷 533-548页

作者： Zhang, Lianjun Ma, Zhihai Guo, Luo SUNY Coll Environm Sci & Forestry Dept Forest & Nat Resources Management Syracuse NY 13210 USA MinZu Univ China Coll Life & Environm Sci Beijing 100081 Peoples R China

spatial effects include spatial autocorrelation and heterogeneity. Ignoring spatial effects in a modeling process causes misleading significance tests and suboptimal model prediction. In this study, we used three forest plots with different spatial patterns of tree locations (i.e, clustered, random, and re-gular patterns) to investigate the spatial distributions and heterogeneity in the model residuals from six regression models with the ordinary least squares (OLS) as the benchmark Our results revealed that when significant spatial autocorrelations and variations existed in the relationship between tree height and diameter, as in the softwood plot (clustered) and hardwood plot (random). OLS was not appropriate for modeling the relationship between tree variables. spatial regression models (i.e., spatial lag and spatial error models) were effective for accounting for spatial autocorrelation in the model residuals. but they were insufficient to deal with the problem of spatial heterogeneity. It was evident that the model residuals in both spatial lag and spatial error models had a similar pattern and magnitudes of spatial heterogeneity at spatial scales different from those of the OLS model. In contrast, the linear mixed model and geographically weighted regression incorporated the spatial dependence and variation into modeling processes, and consequently, fitted the data better and predicted the response variable more accurately. The model residuals from both the linear mixed model and geographically weighted regression had desirable spatial distributions, meaning fewer clusters of similar or dissimilar model residuals over space. FOR. SCI. 55(6).533-548

关键词： model residuals ordinary least-squares spatial lag model spatial error model linear mixed model geographically weighted regression

来源：评论

学校读者我要写书评

暂无评论

Particulate air pollution and chronic ischemic heart disease in the eastern United States: a county level ecological study using satellite aerosol data

引用

ENVIRONMENTAL HEALTH 2009年第1期8卷 26-26页

作者： Hu, Zhiyong Rao, K. Ranga Univ W Florida Dept Environm Studies Pensacola FL 32514 USA Univ W Florida Ctr Environm Diagnost & Bioremediat Pensacola FL 32514 USA

Background: There are several known factors that cause ischemic heart disease. However, the part played by air pollution still remains something of a mystery. Recent attention has focused on the chronic effect of particulate matter on heart disease. Satellite-derived aerosol optical depth (AOD) was found to be correlated with PM2.5 in the eastern US. The objective of this study was to examine if there is an association between aerosol air pollution as indicated by AOD and chronic ischemic heart disease (CIHD) in the eastern US. Methods: An ecological geographic study method was employed. Race and age standardized mortality rate (SMR) of CIHD was computed for each of the 2306 counties for the time period 2003-2004. A mean AOD raster grid for the same period was derived from Moderate Resolution Imaging Spectrometer (MODIS) aerosol data and the average AOD was calculated for each county. A bivariate Moran's I scatter plot, a map of local indicator of spatial association (LISA) clusters, and three regression models (ordinary least square, spatial lag, and spatial error) were used to analyze the relationship between AOD and CIHD SMR. Results: The global Moran's I value is 0.2673 (p = 0.001), indicating an overall positive spatial correlation of CIHD SMR and AOD. The entire study area is dominated by spatial clusters of AOD against SMR (high AOD and high SMR in the east, and low AOD and low SMR in the west) (permutations = 999, p = 0.05). Of the three regression models, the spatial error model achieved the best fit (R-2 = 0.28). The effect of AOD is positive and significant (beta = 0.7774, p = 0.01). Conclusion: Aerosol particle pollution has adverse effect on CIHD mortality risk in the eastern US. High risk of CIHD mortality was found in areas with elevated levels of outdoor aerosol air pollution as indicated by satellite derived AOD. The evidence of the association would support targeting of policy interventions on such areas to reduce air pollution levels. Remote sensi

关键词： Aerosol Optical Depth Geographically Weighted Regression spatial error model spatial Outlier Chronic Ischemic Heart Disease

来源：评论

学校读者我要写书评

暂无评论

Measuring the impact of large-scale transportation projects on land price using spatial statistical models

引用

PAPERS IN REGIONAL SCIENCE 2008年第3期87卷 385-402页

作者： Tsutsumi, Morito Seya, Hajime Univ Tsukuba Grad Sch Syst & Informat Engn Tsukuba Ibaraki 3058573 Japan PASCO Corp Meguro Ku Tokyo 1530043 Japan

Large-scale transportation projects such as the construction of a commuter railway accessible to metropolises have a significant regional impact. This study attempts to measure this impact using spatial statistical models and land price data. First, dynamic changes in the land price are analysed and the so-called announcement effect is presented using the spatial interpolation techniques. Second, various types of land price models are constructed by employing the existing methods of spatial econometrics and geostatistics;their estimates and project benefits are compared and discussed, particularly from the viewpoint of policy implications.

关键词： Land price spatial error model spatial process model spatial hedonic approach benefit evaluation

来源：评论

学校读者我要写书评

暂无评论

spatial dependency of V-cholera prevalence on open space refuse dumps in Kumasi, Ghana: a spatial statistical modelling

引用

INTERNATIONAL JOURNAL OF HEALTH GEOGRAPHICS 2008年第1期7卷 62-62页

作者： Osei, Frank B. Duker, Alfred A. KNUST Dept Geomat Engn Kumasi Ghana

Background: Cholera has persisted in Ghana since its introduction in the early 70's. From 1999 to 2005, the Ghana Ministry of Health officially reported a total of 26,924 cases and 620 deaths to the WHO. Etiological studies suggest that the natural habitat of V. cholera is the aquatic environment. Its ability to survive within and outside the aquatic environment makes cholera a complex health problem to manage. Once the disease is introduced in a population, several environmental factors may lead to prolonged transmission and secondary cases. An important environmental factor that predisposes individuals to cholera infection is sanitation. In this study, we exploit the importance of two main spatial measures of sanitation in cholera transmission in an urban city, Kumasi. These are proximity and density of refuse dumps within a community. Results: A spatial statistical modelling carried out to determine the spatial dependency of cholera prevalence on refuse dumps show that, there is a direct spatial relationship between cholera prevalence and density of refuse dumps, and an inverse spatial relationship between cholera prevalence and distance to refuse dumps. A spatial scan statistics also identified four significant spatial clusters of cholera;a primary cluster with greater than expected cholera prevalence, and three secondary clusters with lower than expected cholera prevalence. A GIS based buffer analysis also showed that the minimum distance within which refuse dumps should not be sited within community centres is 500 m. Conclusion: The results suggest that proximity and density of open space refuse dumps play a contributory role in cholera infection in Kumasi.

关键词： Cholera Ordinary Little Square model spatial error model Cholera Outbreak Refuse Dump

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：