Spatial econometrics : statistical foundations and applications to regional convergence /

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Bibliographic Details
Author / Creator:Arbia, Giuseppe.
Imprint:Berlin ; New York : Springer, 2006.
Description:1 online resource (xvii, 207 p.) : ill., maps.
Language:English
Series:Advances in spatial science
Advances in spatial science.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/8879562
Hidden Bibliographic Details
ISBN:9783540323051
3540323058
9786610613137
6610613133
354032304X (Cloth)
9783540323044 (Cloth)
Notes:Includes bibliographical references (p. [167]-189) and indexes.
Description based on print version record.
Other form:Print version: Arbia, Giuseppe. Spatial econometrics. Berlin ; New York : Springer, 2006 354032304X 9783540323044
Description
Summary:In recent years the so-called new economic geography and the issue of regional economic convergence have increasingly drawn the interest of economists to the empirical analysis of regional and spatial data. However, even if the methodology for econometric treatment of spatial data is well developed, there does not exist a textbook theoretically grounded, well motivated and easily accessible to eco- mists who are not specialists. Spatial econometric techniques receive little or no attention in the major econometric textbooks. Very occasionally the standard econometric textbooks devote a few paragraphs to the subject, but most of them simply ignore the subject. On the other hand spatial econometric books (such as Anselin, 1988 or Anselin, Florax and Rey, 2004) provide comprehensive and - haustive treatments of the topic, but are not always easily accessible for people whose main degree is not in quantitative economics or statistics. This book aims at bridging the gap between economic theory and spatial stat- tical methods. It starts by strongly motivating the reader towards the problem with examples based on real data, then provides a rigorous treatment, founded on s- chastic fields theory, of the basic spatial linear model, and finally discusses the simpler cases of violation of the classical regression assumptions that occur when dealing with spatial data.
Physical Description:1 online resource (xvii, 207 p.) : ill., maps.
Bibliography:Includes bibliographical references (p. [167]-189) and indexes.
ISBN:9783540323051
3540323058
9786610613137
6610613133
354032304X
9783540323044