Giuseppe Arbia Knihy

The book explores spatial econometrics by introducing fundamental concepts and methodologies for analyzing regional data, focusing on the SARAR framework. It details estimation techniques like Maximum Likelihood, GMM, and 2SLS. The text further delves into spatial microeconometrics, examining individual-level data to understand location decisions and economic behaviors through spatial autoregressive models. Additionally, it discusses spatial interaction models based on origin-destination data, while intentionally excluding dynamic spatial data analysis for clarity.

The book addresses the growing interest in regional economic convergence and spatial data analysis among economists. It fills a gap in existing literature by providing a theoretically grounded yet accessible introduction to spatial econometric techniques, which are often overlooked in mainstream econometric textbooks. By using real data examples, it motivates readers and offers a rigorous exploration of the basic spatial linear model, while also addressing common violations of classical regression assumptions in spatial contexts.

The book delves into the complexities of analyzing areal data, highlighting the significance of spatial correlograms, a concept adapted from time series analysis. It discusses the relationships between first-order and second-order neighbors in spatial contexts, illustrating how dependencies can extend beyond immediate areas. Various figures provide visual representations of voting patterns and demographic statistics, emphasizing the intricate connections between geographic regions and their socio-political characteristics. The exploration of these themes offers valuable insights into spatial analysis methodologies.

Focusing on economic inequality, the book examines its measurement and connection to growth and development through various perspectives, including ethical and political. It provides statistical methods for assessing income inequality and offers international comparisons. By analyzing three decades of theoretical and empirical evidence, it explores the intricate relationship between inequality and economic growth. Additionally, it discusses potential political measures aimed at reducing disparities while promoting economic advancement.

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.