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Spatial Econometrics [electronic resource] :Statistical Foundations and Applications to Regional Convergence / by Giuseppe Arbia.

by Arbia, Giuseppe [author.]; SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Advances in Spatial Science: Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2006.Description: XVII, 207 p. 19 illus. online resource.ISBN: 9783540323051.Subject(s): Economics | Geographical information systems | Economics -- Statistics | Econometrics | Economics/Management Science | Regional Science | Econometrics | Statistics for Business/Economics/Mathematical Finance/Insurance | Geographical Information Systems/CartographyDDC classification: 338.9 Online resources: Click here to access online
Contents:
Motivation -- Random Fields and Spatial Models -- Likelihood Function for Spatial Samples -- The Linear Regression Model with Spatial Data -- Italian and European ?-convergence Models Revisited -- Looking Ahead: A Review of More Advanced Topics in Spatial Econometrics.
In: Springer eBooksSummary: The new economic geography and the debate on regional economic convergence have drawn increasingly the interest of economists in the empirical analysis of regional and spatial data. However, even if the methodology for the econometric treatment of spatial data is well developed, there does not exist a book without strong pre-requisites that is easily accessible to economists. This book bridges the gap between economic theory and spatial econometric techniques. It is easy accessible to people with only basic statistical background and no prior knowledge of spatial econometric methods. It provides a comprehensive treatment of the topic by motivating the reader with examples and real data analysis. The volume provides a rigorous treatment, founded on stochastic fields theory, of the basic spatial linear model, and discusses the violations of the classical regression assumptions that occur when dealing with spatial data.
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Motivation -- Random Fields and Spatial Models -- Likelihood Function for Spatial Samples -- The Linear Regression Model with Spatial Data -- Italian and European ?-convergence Models Revisited -- Looking Ahead: A Review of More Advanced Topics in Spatial Econometrics.

The new economic geography and the debate on regional economic convergence have drawn increasingly the interest of economists in the empirical analysis of regional and spatial data. However, even if the methodology for the econometric treatment of spatial data is well developed, there does not exist a book without strong pre-requisites that is easily accessible to economists. This book bridges the gap between economic theory and spatial econometric techniques. It is easy accessible to people with only basic statistical background and no prior knowledge of spatial econometric methods. It provides a comprehensive treatment of the topic by motivating the reader with examples and real data analysis. The volume provides a rigorous treatment, founded on stochastic fields theory, of the basic spatial linear model, and discusses the violations of the classical regression assumptions that occur when dealing with spatial data.

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