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Read e-book online Advances in Spatial Econometrics: Methodology, Tools and PDF

By Luc Anselin, Raymond Florax, Sergio J. Rey

ISBN-10: 3642078389

ISBN-13: 9783642078385

ISBN-10: 3662056178

ISBN-13: 9783662056172

Advances in Spatial Science

This sequence of books is devoted to reporting on fresh advances in spatial technology. It comprises clinical experiences concentrating on spatial phenomena, utilizing theoretical frameworks, analytical equipment, and empirical systems particularly designed for spatial research. The sequence brings jointly leading edge spatial examine employing ideas, views, and strategies with a relevance to either uncomplicated technological know-how and coverage making. the purpose is to provide advances in spatial technology to an educated readership in universities, examine organizations, and policy-making associations during the world.

The kind of fabric thought of for e-book within the sequence includes:

- Monographs of theoretical and utilized study in spatial science;

- state of the art volumes in components of uncomplicated research;

- stories of leading edge theories and techniques in spatial science;

- Tightly edited experiences shape in particular organised study seminars.

Manuscripts has to be ready based on the ideas for authors and editors that could be acquired from Springer-Verlag. Manuscripts thought of for the sequence could be reviewed via self sustaining specialists to make sure their originality, clinical point, and overseas coverage relevance.

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Additional resources for Advances in Spatial Econometrics: Methodology, Tools and Applications

Example text

In addition, we argue that one of the distinctive advantages of meta-analysis, in particular of multivariate meta-regression, is the possibility to investigate the variability of an "effect size" while controlling for intervening factors. The comparison across studies evokes specific caveats in meta-analysis as compared to response surface analysis. First, the selection of studies included in the meta-analysis is biased if there is a systematic variation between the sampling decision and the magnitude of the effect and/or its associated variance.

More precisely, they apply a technique known as meta-analysis to obtain general conclusions from the evidence presented in the literature. The meta-analysis boils down to a regression of the experimentally derived rejection probabilities (of the null hypothesis of no spatial correlation) on various characteristics of the simulation design, such as the sample size, error distribution, spatial weights characteristics, strength of the induced correlation, and the presence of other misspecifications.

The framework encompasses no less than 35 special cases, illustrated for a two equation system. Rey and Boarnet point to three important issues to consider in the estimation of such models: feedback simultaneity, spatial autoregressive lag simultaneity and spatial crossregressive lag simultaneity. They next move to a close scrutiny of estimation issues and consider the properties of four estimators in a series of Monte Carlo simulation experiments. Specifically, ordinary least squares, spatial two stage least squares and two versions of the Kelejian-Robinson-Prucha instrumental variables estimators are compared in terms of bias and root mean squared error (RMSE).

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Advances in Spatial Econometrics: Methodology, Tools and Applications by Luc Anselin, Raymond Florax, Sergio J. Rey

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