[ebook]statistics- springer- statistical foundations of spatial Econometrics.pdf

To Francesco and Enrica
Preface
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 econo-
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) prehensive and ex-
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 statis-
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 sto-
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. I am convinced that, once the reader is introduced to the
probabilistic and statistical arguments on which the basic linear model is
grounded, he will be able to understand quite straightforwardly also the more so-
phisticated models and techniques that are present in the spatial econometric lit-
erature. A review of some more advanced topics excluded from the range of inter-
est of this book, is confined to a final chapter which provides the references for
further, more in-depth going, studies.
The project of a self-contained statistically