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.

Statistical approach to spatial econometrics Easily accessible to people with low statistical background Didactic approach motivating the readers with examples and real data analysis Includes supplementary material: sn.pub/extras

Autorentext

Giuseppe Arbia is a full professor of Economic Statistics at the Faculty of Economics, Catholic University of Rome (Italy) and lecturer at the University of Italian Switzerland in Lugano (Switzerland). His research focuses on spatial statistics and spatial econometrics, and he has published nine books and more than 200 articles in leading journals on these topics. He has been a chairman of the Spatial Econometrics Association since 2006 and a member of the Directory Board of the Italian Statistical Society in the period 2016-2020. He is also an active member of several other international scientific societies. From 2020, he is an editor-in-chief of the Journal of Spatial Econometrics, published by Springer-Verlag. Since 2008 he is the Director of the "Spatial Econometrics Advanced Institute", and since 2016 the leading editor of the book series "Spatial Statistics and Spatial Econometrics", Elsevier. He has been a visiting professor in several universities in the five continents of the world.

Inhalt
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.