检索结果-内蒙古大学图书馆

TESTING FOR spatial AUTOCORRELATION: THE REGRESSORS THAT MAKE THE POWER DISAPPEAR

ECONOMETRIC REVIEWS 2012年第2期31卷 215-240页

作者： Martellosio, Federico Univ Reading Sch Econ Reading RG6 6AW Berks England

We show that for any sample size, any size of the test, and any weights matrix outside a small class of exceptions, there exists a positive measure set of regression spaces such that the power of the Cliff-Ord test vanishes as the autocorrelation increases in a spatial error model. This result extends to the tests that define the Gaussian power envelope of all invariant tests for residual spatial autocorrelation. In most cases, the regression spaces such that the problem occurs depend on the size of the test, but there also exist regression spaces such that the power vanishes regardless of the size. A characterization of such particularly hostile regression spaces is provided.

关键词： Cliff-Ord test Point optimal tests Power spatial error model spatial lag model spatial unit root

来源：评论

学校读者我要写书评

暂无评论

Approximated likelihood and root estimators for spatial interaction in spatial autoregressive models

引用

REGIONAL SCIENCE AND URBAN ECONOMICS 2012年第3期42卷 446-458页

作者： Jin, Fei Lee, Lung-fei Ohio State Univ Dept Econ Columbus OH 43210 USA

In this paper, we first generalize an approximate measure of spatial dependence, the APLE statistic (Li et al., 2007), to a spatial Durbin (SD) model. This generalized APLE takes into account exogenous variables directly and can be used to detect spatial dependence originating from either a spatial autoregressive (SAR), spatial error (SE) or SD process. However, that measure is not consistent. Secondly, by examining carefully the first order condition of the concentrated log likelihood of the SD (or SAR) model, whose first order approximation generates the APLE, we construct a moment equation quadratic in the autoregressive parameter that generalizes an original estimation approach in Ord (1975) and yields a closed-form consistent root estimator of the autoregressive parameter. With a specific moment equation constructed from an initial consistent estimator, the root estimator can be as efficient as the MLE under normality. Furthermore, when there is unknown heteroskedasticity in the disturbances, we derive a modified APLE and a root estimator which can be robust to unknown heteroskedasticity. The root estimators are computationally much simpler than the quasi-maximum likelihood estimators. (C) 2011 Elsevier B.V. All rights reserved.

关键词： spatial autoregressive model spatial error model spatial Durbin model APLE GMM

来源：评论

学校读者我要写书评

暂无评论

The effects of spatial autoregressive dependencies on inference in ordinary least squares: a geometric approach

引用

JOURNAL OF GEOGRAPHICAL SYSTEMS 2012年第1期14卷 91-124页

作者： Smith, Tony E. Lee, Ka Lok Univ Penn Dept Elect & Syst Engn Philadelphia PA 19104 USA Univ Penn Wharton Sch Philadelphia PA 19104 USA

There is a common belief that the presence of residual spatial autocorrelation in ordinary least squares (OLS) regression leads to inflated significance levels in beta coefficients and, in particular, inflated levels relative to the more efficient spatial error model (SEM). However, our simulations show that this is not always the case. Hence, the purpose of this paper is to examine this question from a geometric viewpoint. The key idea is to characterize the OLS test statistic in terms of angle cosines and examine the geometric implications of this characterization. Our first result is to show that if the explanatory variables in the regression exhibit no spatial autocorrelation, then the distribution of test statistics for individual beta coefficients in OLS is independent of any spatial autocorrelation in the error term. Hence, inferences about betas exhibit all the optimality properties of the classic uncorrelated error case. However, a second more important series of results show that if spatial autocorrelation is present in both the dependent and explanatory variables, then the conventional wisdom is correct. In particular, even when an explanatory variable is statistically independent of the dependent variable, such joint spatial dependencies tend to produce "spurious correlation'' that results in over-rejection of the null hypothesis. The underlying geometric nature of this problem is clarified by illustrative examples. The paper concludes with a brief discussion of some possible remedies for this problem.

关键词： spatial dependence spatial autocorrelation spatial error model OLS regression Geometric approach

来源：评论

学校读者我要写书评

暂无评论

Empirical Analysis on Green Innovation of Chinese Paper Manufacturing

Empirical Analysis on Green Innovation of Chinese Paper Manu...

引用

International Conference on Business, Economics, and Financial Sciences, Management (BEFM 2011)

作者： Liu, Haiying Zou, Zhiyong Shandong Polytech Univ Sch Business Jinan Shandong Peoples R China

ISBN: (纸本)9783642279652

In this paper. Moran index of spatial statistics, the spatial lag and spatial error model of spatial econometric economics, combined with Griliches&Jaffe knowledge production function(Knowledge Production Function. KPF). were used in spatial econometric analysis on China's provincial paper manufacturing R&D and innovation knowledge spillovers. The results show that there are significant global and local spatial autocorrelation in paper industry green innovation model: also find that China's 31 provincial contribution of green innovation in paper manufacturing sector was mainly achieved by enterprises R&D investment, while the combination of university and enterprise did not show significant effect on green innovation spillovers. The results show effect of knowledge spillovers are exist, but not significant. In the end, according to the conclusions, we draw some advices.

关键词： spatial econometric analysis knowledge production function green innovation spillovers spatial lag model spatial error model

来源：评论

学校读者我要写书评

暂无评论

Estimation of three-dimensional panel data sur spatial econometric model

Estimation of three-dimensional panel data sur spatial econo...

引用

2011 International Conference on Transportation, Mechanical, and Electrical Engineering, TMEE 2011

作者： Wu, Mei Long, Zhihe School of Economics and Commerce South China University of Technology Guangzhou 510640 China

ISBN: (纸本)9781457717017

By combining SUR panel data model theory with spatial econometric analysis, we propose a three-dimensional panel data SUR spatial econometric model in which both of spatial correlation between individual and time-related are considered. We study the three-dimensional panel data SUR spatial econometric model estimation methods, and separately examine the 3SLS estimation steps of the three-dimensional panel data spatial lag SUR model and three-dimensional panel data spatial error SUR model. The aim of this paper is to provide a programming basis for the empirical study. © 2011 IEEE.

关键词： spatial error model spatial Lag model SUR Three-dimensional Panel Data

来源：评论

学校读者我要写书评

暂无评论

modeling and Prediction of Tree Height Diameter Relationships Using spatial Autoregressive models

引用

FOREST SCIENCE 2011年第3期57卷 252-264页

作者： Lu, Junfeng Zhang, Lianjun SUNY ESF Dept Forest & Nat Resource Management Syracuse NY 13210 USA

Three spatial autoregressive models were applied to model the tree height diameter relationship, including spatial lag model (SLM), spatial error model (SEM), and spatial Durbin model (SDM), with ordinary least squares (OLS) as a benchmark. Five spatial weight matrices were used to evaluate the impacts of different weighting schemes on model fitting. It was evident that different schemes of spatial weight matrix strongly affected the model fitting and parameter estimation in these spatial autoregressive models. We found that the variogram or geostatistical weight matrix was superior to other spatial weight matrices such as contiguity, inverse distances, and local G(i)* statistics. Further, the spatial autoregressive models were used to predict tree heights at unsampled locations. The results showed that the three spatial autoregressive models overperformed the OLS model not only in model fitting and reducing spatial dependence, but also in model predictions. In general, SDM and SEM performed significantly better than SLM, whereas SDM was slightly better than SEM in each aspect of model fitting and prediction. However, if the complexity of the model structure is a concern, SEM with a geostatistical weight matrix is a reasonable choice over SDM because SEM offers the model coefficient estimates close to those of the OLS model, which makes the interpretation and understanding of the model much easier. FOR. SCI 57(3):252-264.

关键词： spatial lag model spatial error model spatial Durbin model spatial autocorrelation spatial weight matrix

来源：评论

学校读者我要写书评

暂无评论

spatial Regression Analysis in Hemorrhagic Fever with Renal Syndrome(HFRS) in China

Spatial Regression Analysis in Hemorrhagic Fever with Renal ...

引用

2011 IEEE International Conference on spatial Data Mining and Geographical Knowledge Services(ICSDM 2011)

作者： Xin Feng~(#1),Shihong Du~(#2),Hong Shu~(*3) # Institute of Remote Sensing and GIS,Peking University Beijing 100871,China * State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing Wuhan 430079,China

With spatial regression analysis,the cause of the hemorrhagic fever with renal syndrome(HFRS) is detected in China in *** results showed that:the incidence of HFRS is influenced by six factors:latitude,longitude of regional centers, the proportion of settlement place,the proportion of grassland, average elevation,and the average precipitation in October and *** these factors,the incidence is correlated significantly and negatively with the proportion of settlement place,while is associated significantly and positively with latitude and longitude of regional centres.

关键词： epidemiology spatial statistics spatial regression hemorrhagic fever with renal syndrome spatial lag model spatial error model

来源：评论

学校读者我要写书评

暂无评论

Estimating front-wave velocity of infectious diseases: a simple, efficient method applied to bluetongue

引用

VETERINARY RESEARCH 2011年第1期42卷 60-60页

作者： Pioz, Maryline Guis, Helene Calavas, Didier Durand, Benoit Abrial, David Ducrot, Christian INRA Ctr Clermont Ferrand Theix Unite Epidemiol Anim St Genes Champanelle France CIRAD UMR Controle Malad F-34398 Montpellier France French Agcy Food Environm & Occupat Hlth Safety Lyon France French Agcy Food Environm & Occupat Hlth Safety Maisons Alfort France

Understanding the spatial dynamics of an infectious disease is critical when attempting to predict where and how fast the disease will spread. We illustrate an approach using a trend-surface analysis (TSA) model combined with a spatial error simultaneous autoregressive model (SAR(err) model) to estimate the speed of diffusion of bluetongue (BT), an infectious disease of ruminants caused by bluetongue virus (BTV) and transmitted by Culicoides. In a first step to gain further insight into the spatial transmission characteristics of BTV serotype 8, we used 2007-2008 clinical case reports in France and TSA modelling to identify the major directions and speed of disease diffusion. We accounted for spatial autocorrelation by combining TSA with a SAR(err) model, which led to a trend SAR(err) model. Overall, BT spread from north-eastern to south-western France. The average trend SAR(err)-estimated velocity across the country was 5.6 km/day. However, velocities differed between areas and time periods, varying between 2.1 and 9.3 km/day. For more than 83% of the contaminated municipalities, the trend SAR(err)-estimated velocity was less than 7 km/day. Our study was a first step in describing the diffusion process for BT in France. To our knowledge, it is the first to show that BT spread in France was primarily local and consistent with the active flight of Culicoides and local movements of farm animals. models such as the trend SAR(err) models are powerful tools to provide information on direction and speed of disease diffusion when the only data available are date and location of cases.

关键词： spatial Autocorrelation spatial Weight Matrix spatial error model Wild Ungulate Clinical Case Report

来源：评论

学校读者我要写书评

暂无评论

Spatio-temporal Effects Analysis of Grain Yield on Country Level in Shandong Province

Spatio-temporal Effects Analysis of Grain Yield on Country L...

引用

2011 International Conference on New Technology of Agricultural Engineering(ICAE 2011)

作者： Yang Yujian,Tong Xueqin S&T Information and Engineering Research Center Shandong Agricultural Science Academy Jinan,250100,P.R.China

Grain security deals with grain alone differs from food security,grain security is related to the development of the national economy is a major strategic issues,the warning limits and spatial autocorrelation characteristics and of per capita grain possession about 91 country units were analyzed in Shandong province in 2000 and in ***,spatial error model of the total grain yield was established about 91 country *** showed that the spatial status of per capita grain possession of 63 country units in 2007 increased comparing with that of 2000,percent 69.2%of 91 units presented the increasing *** center of per capita grain possession located in lingxian,Yucheng country,in the north of Shandong province whether in 2000 or in *** results also indicated there is the no warning status of per capita grain possession about 80 countries units,11 county units with warning *** 2000 to 2007,the spatial autocorrelation characteristics of per capita grain possession was significantly presented and the spatial difference of per capita grain possession suffered a decrease and the spatial pattern was more *** SEM study results indicated development of the total grain yield need agricultural informationization and mechanization,policy orientation,social economy driving forces for total grain yield increased important influence.

关键词： Grain yield spatial autocorrelation spatial error model Country level

来源：评论

学校读者我要写书评

暂无评论

The spatial Pattern Analysis of Economic Growth of JingJinJi Metropolitan Region

The Spatial Pattern Analysis of Economic Growth of JingJinJi...

引用

18th International Conference on Geoinformatics

作者： Lian, Jian Li, Xiaojuan Gong, Huili Wang, Yanbing Sun, Yonghua Capital Normal Univ Key Lab Informat Acquisit & Applicat 3D Minist Educ Coll Resource Environm & Tourism Beijing Peoples R China

ISBN: (纸本)9781424473021

The regional economic disparity is always a research hot spot to domestic and foreign scholars. In this paper, the Beijing-Tianjin-Hebei metropolitan region was taken as research object;methods of exploratory spatial data analysis and spatial autocorrelation model provide new insights to explore spatial dependence relation of JingJinJi Metropolitan Region over the 2001-2006 periods. Through spatial trend and character analysis, the Trend Info TuPu of GDP and population in this region was created. Furthermore, the certificated spatial data analysis method was introduced to construct the fit spatial relation model for the economic growth process, including spatial error model (SRM), spatial lag model (SLM), to further confirmed the spatial relation effect in the regional economic growth.

关键词： economic growth spatial pattern analysis spatial trend analysis spatial error model spatial lag model

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：