Journal ArticleDOI
Spatial Externalities, Spatial Multipliers, And Spatial Econometrics
TLDR
In this paper, a taxonomy of spatial econometric model specifications that incorporate spatial externalities in various ways is presented, where the point of departure is a reduced form in which local or globa...Abstract:
This article outlines a taxonomy of spatial econometric model specifications that incorporate spatial externalities in various ways. The point of departure is a reduced form in which local or globa...read more
Citations
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Journal ArticleDOI
Spatial and Temporal Measurement of the Interaction between the County Economy and Rural Transformation in Xinjiang, China
TL;DR: Zhang et al. as discussed by the authors used the spatial econometric model to study the spatiotemporal synergy and interaction between Xinjiang's county economy and rural transformation from 2007 to 2017.
Book ChapterDOI
Semiparametric Spatial Autoregressive Geoadditive Models
TL;DR: In this article, the authors describe these methodological contributions and present some applications of these methodologies in the fields of regional science and economic geography in order to deal with some important methodological issues, such as spatial dependence, spatial heterogeneity and nonlinearities.
Accounting for spatial autocorrelation in modeling the distribution of water quality variables
Abstract: OF THESIS ACCOUNTING FOR SPATIAL AUTOCORRELATION IN MODELING THE DISTRIBUTION OF WATER QUALITY VARIABLES Several studies in hydrology have reported differences in outcomes between models in which spatial autocorrelation (SAC) is accounted for and those in which SAC is not. However, the capacity to predict the magnitude of such differences is still ambiguous. In this thesis, I hypothesized that SAC, inherently possessed by a response variable, influences spatial modeling outcomes. I selected ten watersheds in the USA and analyzed them to determine whether water quality variables with higher Moran’s I values undergo greater increases in the coefficient of determination (R2) and greater decreases in residual SAC (rSAC) after spatial modeling. I compared non-spatial ordinary least squares to two spatial regression approaches, namely, spatial lag and error models. The predictors were the principal components of topographic, land cover, and soil group variables. The results revealed that water quality variables with higher inherent SAC showed more substantial increases in R2 and decreases in rSAC after performing spatial regressions. In this study, I found a generally linear relationship between the spatial model outcomes (R2 and rSAC) and the degree of SAC in each water quality variable. I suggest that the inherent level of SAC in response variables can predict improvements in models before spatial regression is performed. The benefits of this study go beyond modeling selection and performance, it has the potential to uncover hydrologic connectivity patterns that can serve as insights to water quality managers and policy makers.
Posted Content
Agglomeration effects on regional unemployment in europe
TL;DR: In this article, the authors propose to disentangle agglomeration effects due to high concentration of population and those due to firm's clusters or high presence of employees, by controlling for a wide set of variables, basically related to sectorial and dimensional shocks and human capital, in order to highlight the total "size" effect in the labour market.
References
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Book
Statistics for spatial data
Noel A Cressie,Noel A Cressie +1 more
TL;DR: In this paper, the authors present a survey of statistics for spatial data in the field of geostatistics, including spatial point patterns and point patterns modeling objects, using Lattice Data and spatial models on lattices.
Book
Spatial Econometrics: Methods and Models
TL;DR: In this article, a typology of Spatial Econometric Models is presented, and the maximum likelihood approach to estimate and test Spatial Process Models is proposed, as well as alternative approaches to Inference in Spatial process models.
Journal ArticleDOI
5. Statistics for Spatial Data
Mike Rees,N. Cressie +1 more
TL;DR: Cressie et al. as discussed by the authors presented the Statistics for Spatial Data (SDS) for the first time in 1991, and used it for the purpose of statistical analysis of spatial data.
Journal ArticleDOI
Identification of Endogenous Social Effects: The Reflection Problem
TL;DR: The authors examined the reflection problem that arises when a researcher observing the distribution of behaviour in a population tries to infer whether the average behaviour in some group influences the behaviour of the individuals that comprise the group.
Book
Spatial Processes Models and Applications
Andrew Cliff,J. Keith Ord +1 more
TL;DR: The authors describe various ways the degree of spatial autocorrelation in a set of variate values can be assessed and to which the pattern formed by the location of objects treatable as points can be examined.