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

By Luc Anselin, Raymond Florax, Sergio J. Rey

Advances in Spatial Science

This sequence of books is devoted to reporting on fresh advances in spatial technology. It includes clinical reports concentrating on spatial phenomena, applying theoretical frameworks, analytical equipment, and empirical techniques in particular designed for spatial research. The sequence brings jointly cutting edge spatial examine employing ideas, views, and strategies with a relevance to either simple technological know-how and coverage making. the purpose is to provide advances in spatial technological know-how to an educated readership in universities, examine businesses, and policy-making associations through the world.

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

- Monographs of theoretical and utilized examine in spatial science;

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

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

- Tightly edited experiences shape specifically organised study seminars.

Manuscripts has to be ready in keeping with the tips for authors and editors which may be got from Springer-Verlag. Manuscripts thought of for the sequence could be reviewed by way of self reliant specialists to make sure their originality, medical point, and overseas coverage relevance.

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Extra info for Advances in Spatial Econometrics: Methodology, Tools and Applications

Sample text

2 Meta-Analysis of Simulation Studies 31 sample behavior of Moran's I for regression residuals in a Monte Carlo setting, and by now some 30 simulation studies exist. Anselin and Rey (1991) present a qualitative survey of the early simulation studies of spatial effects in linear regression models. As a complement to a literature survey, a quantitative analysis of simulation results of different studies provides additional insights. A quantitative multivariate approach across studies has three distinct advantages.

In "The performance of diagnostics for spatial dependence in regression models: a meta-analytical approach," Raymond Florax and Thomas de Graaff set out to assess and summarize the literature that uses experimental Monte Carlo simulation techniques to document the small sample properties of tests for spatial correlation in the residuals of a linear regression model. They present a taxonomy of the various tests, and review the experimental literature as it came about over the last twentyfive years.

Specifically, Fingleton introduces an augmented spatial lag Verdoorn law, an augmented spatial error Verdoorn law, and a reduced unrestricted spatial effects Verdoorn law. These models incorporate the role of spatial effects through spatially lagged terms for the dependent variable, the error term, or the explanatory variables. Fingleton goes on to discuss in some detail the implications of these specifications for equilibrium and steady state, which follow from different ways to model the connection between productivity growth and the level of productivity.

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